Costs of adaptation to the effects of climate change in AVOID:

Costs of adaptation to the effects of climate change in the world’s large port cities

AVOID:

Avoiding dangerous climate change

AVOID is a DECC/Defra funded research programme led by the Met Office in a consortium with the Walker

Institute, Tyndall Centre and Grantham Institute

Author(s): M.M Linham, C.H. Green, R.J. Nicholls

Institute: University of Southampton and Middlesex University

Reviewer: R.J. Nicholls

Institute: University of Southampton

Date: 01/07/2010

-

AVOID is an LWEC accredited activity

Key outcomes / non-technical summary

A globally applicable methodology for estimating flood losses was developed which will allow improved broad assessments of potential losses from climate change to take place. A database describing unit costs of coastal adaptation measures was also compiled. This updates previous global vulnerability assessments and in the future will also allow more accurate estimations of the costs of adapting to climate change to be made. Finally, a database describing applied standards of protection in large port cities was also established. This database highlights significant variation in protection levels worldwide. The level of protection applied is clearly influenced by numerous factors. This makes predicting probable levels of protection problematic.

This study has moved beyond the exposure analysis undertaken by Nicholls et al.

(2008) and shows that even when coastal defences are considered, significant assets and population can still be at risk of coastal flooding.

The study highlighted that low standards of coastal protection are applied in a number of the cities studied. Of particular concern are New Orleans, New York,

Miami, Kolkata, Mumbai, Ho Chi Minh City and Guangzhou where high exposed populations also exist.

The study highlighted a lack of information for evaluating the costs of adapting to climate change. This lack of data desperately needs to be addressed.

Further information on key outcomes can be found in the executive summary.

This report should be referenced as

Linham M., Green C., Nicholls R., 2010:

Costs of adaptation to the effects of climate change in the world’s large port cities.

Work stream 2, Report 14 of the AVOID programme (AV/WS2/D1/R14). Available online at www.avoid.uk.net

AVOID WS2 Deliverable 1 Report 14: COSTS OF

ADAPTATION TO THE EFFECTS OF CLIMATE CHANGE

IN THE WORLD’S LARGE PORT CITIES

This report represents the fourteenth output to be delivered under Deliverable 1 of

Workstream 2.

Matthew M. Linham 1 , Colin H. Green 2 , Robert J. Nicholls 3

1

School of Civil Engineering and the Environment, University of Southampton, UK

2

Flood Hazard Research Centre, Middlesex University, UK

3

School of Civil Engineering and the Environment, University of Southampton, UK and Tyndall Centre for

Climate Change Research

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities

ACKNOWLEDGEMENTS

The authors wish to acknowledge the assistance provided by Munich Re through access to their archive and the supply of information from their NatCat database.

Specifically thanks go to Dr. Wolfgang Kron for his help, advice and hospitality. The authors would also like to thank Andrew Mather of eThekwini Municipality in Durban for his work to provide extensive information for the cities of Durban and Maputo.

The feedback and discussion offered by Prof. Ian Townend, Dr. Dominic Hames and

Dr. Steven Wade of HR Wallingford is gratefully acknowledged. The assistance of

Ms. Susan Hanson and Dr. Sally Brown throughout the project is appreciatively recognised. Thanks also go to Prof. Richard Tol for his input into the project. Finally, the authors would like to thank the numerous individuals contacted throughout the course of this study who provided invaluable information on specific cities and countries. i


TABLE OF CONTENTS

LIST OF FIGURES....................................................................................................iv

LIST OF TABLES........................................................................................................vi

ABBREVIATIONS.................................................................................................... viii

EXECUTIVE SUMMARY...........................................................................................ix

1.0 BACKGROUND........................................................................................ 1

1.1 Study Objectives........................................................................................ 2

1.2 Applications of this Research..................................................................... 3

1.3 Structure of the Report ............................................................................. 5

2.0 DEPTH-DAMAGE CURVES ..................................................................... 7

2.1 Background................................................................................................ 7

2.2 Coastal Flooding........................................................................................ 8

2.2.1 Characteristics ............................................................. 8

2.2.2 Approach adopted ..................................................... 10

2.3 Methodology ............................................................................................ 11

2.3.1 The Value of Assets ................................................... 13

2.3.2 Exposure to Flooding ................................................. 25

2.3.3 Susceptibility to Flood Damage .................................. 28

2.4 Cross Validation....................................................................................... 41

2.5 Limitations ............................................................................................... 42

2.6 Future Research ...................................................................................... 43

2.7 Summary ................................................................................................. 44

3.0 COSTS OF ADAPTATION...................................................................... 48

3.1 Background.............................................................................................. 48

3.1.1 IPCC CZMS (1990) .................................................... 48

3.1.2 Hoozemans et al. (1993) ............................................ 49

3.1.3 The Present Study ..................................................... 49

3.2 Methodology ............................................................................................ 50

3.2.1 Data Acquisition ......................................................... 50

3.2.2 Normalisation of Costs ............................................... 51

3.3 Results..................................................................................................... 52

3.3.1 Critical Evaluation of Previous Costing Studies .......... 52

3.3.2 Coastal Defence Unit Costs ....................................... 53

3.3.3 Associated Uncertainties ........................................... 65

3.4 Limitations ............................................................................................... 67

3.5 Discussion ............................................................................................... 68

3.5.1 Future Research ........................................................ 71

3.6 Summary ................................................................................................. 72

4.0 APPLIED STANDARDS OF PROTECTION ........................................... 73

4.1 Background.............................................................................................. 73

4.2 Methodology ............................................................................................ 75

4.3 Results..................................................................................................... 76

4.4 Limitations ............................................................................................... 91

4.5 Discussion ............................................................................................... 93

4.5.1 Coastal Adaptation Measures Applied ....................... 93

4.5.2 Performance of Demand for Safety Functions ........... 95 ii


4.5.3 Factors Influencing Applied Standards of Protection .. 95

4.5.4 Future Research ........................................................ 97

4.6 Summary ................................................................................................. 98

5.0 DISCUSSION AND CONCLUDING THOUGHTS ................................. 100

APPENDIX I: Coastal defence cost estimates. Case study of the Netherlands,

New Orleans and Vietnam........................................................102

APPENDIX II: Coastal Adaptation to Climate Change: Measures and Costs. A

Cape Town Case Study........................................................... 157

APPENDIX III: Additional Information on Consequential Losses ..................... 183

APPENDIX IV: Depth-damage curves; additional information.......................... 189

APPENDIX V: The Future of Losses .............................................................. 196

APPENDIX VI: Email survey............................................................................ 197

APPENDIX VII: Matrix summarising the main data contained within the accompanying Excel database................................................ 198

APPENDIX VIII: Coastal adaptation neglected by IPCC CZMS (1990) and

Hoozemans et al. (1993)......................................................... 208

APPENDIX IX: Persons Contacted.................................................................. 209

6.0 REFERENCES ..................................................................................... 211

Further Reading.................................................................................... 224

iii


LIST OF FIGURES

Fig. 1.1 The locations of the 136 port cities analysed in this study.................. 2

Fig. 2.1 Varying purposes for evaluating flood losses...................................... 7

Fig. 2.2 Chain of characteristics which influence the degree of flood damage................................................................................................ 12

Fig. 2.3 Method for estimating potential losses from flooding.......................... 13

Fig. 2.4 National estimates of the breakdown of fixed assets as a percentage of the total value of fixed assets.......................................................... 14

Fig. 2.5 Proportions of fixed investment in dwellings for a selection of countries in Europe.............................................................................. 18

Fig. 2.6 Proportions of fixed investment in other buildings for a selection of countries in Europe.............................................................................. 19

Fig. 2.7 Fixed asset formation as a proportion of GDP in a selection of countries where rates vary significantly............................................... 21

Fig. 2.8 Regional growth of fixed assets in China............................................ 22

Fig. 2.9 Time series of net fixed assets to GDP for China................................ 23

Fig. 2.10 Regional variations in the ratio of net fixed assets to GDP from

Chinese provincial data....................................................................... 24

Fig. 2.11 Ratio of fixed assets to GDP and fixed asset formation to GDP for the USA............................................................................................... 25

Fig. 2.12 Proportions of dwellings in multi-storey buildings................................ 26

Fig. 2.13 Comparative urban densities............................................................... 27

Fig. 2.14 Proportional damages to residential structures of varying constructions – Australia..................................................................... 30

Fig. 2.15 Structural losses in dwellings – Bangladesh....................................... 32

Fig. 2.16 Comparison of structural losses for type 3 dwellings.......................... 33

Fig. 2.17 UK average house – components of structural loss............................ 34

Fig. 2.18 Non-domestic structural damages from UK data................................. 35

Fig. 2.19 Content loss and income effects in domestic buildings; UK Terraced

1919-1944........................................................................................... 37

Fig. 2.20 Dwellings: content losses and income effects..................................... 38

Fig. 2.21 Dwellings: contents loss, comparative proportional curves................. 39

Fig. 2.22 UK non-domestic contents losses....................................................... 40

Fig. 2.23 Summary of the methodology recommended for estimation of losses from coastal flooding for domestic structures...................................... 46

Fig. 2.24 Summary of the methodology recommended for estimation of losses from coastal flooding for non- domestic structures.............................. 47

Fig. 3.1 Comparison of nourishment costs estimated by IPCC CZMS (1990) and known nourishment costs............................................................. 59

Fig. 3.2 Comparison of actual nourishment costs with those estimated by

DIVA.................................................................................................... 62

Fig. 3.3 Comparison of the actual costs of raising sea dikes with those estimated by IPCC CZMS (1990)........................................................ 63 iv


Fig. 3.4 Comparison of actual unit cost per km length of dikes against estimates from Hoozemans et al. (1993)............................................. 64

Fig. 4.1 Recent storm damage on the western coast of France during winter storm Xynthia....................................................................................... 74

Fig. 4.2 Procedure for finding SoP using defence height data......................... 76

Fig. 4.3 The airport at Rio de Janeiro located in the downtown area of the city....................................................................................................... 81

Fig. 4.4 Comparison of country wealth measured in terms of GDP/capita and applied standards of protection........................................................... 82

Fig. 4.5 Comparison of city GDP and applied standards of protection............. 84

Fig. 4.6 Exposed population (from Nicholls et al., 2008) plotted against applied SoPs....................................................................................... 85

Fig. 4.7 Comparison of applied SoPs with demand for safety as calculated by DIVA................................................................................................ 86

Fig. 4.8 Regression of average applied SoP against demand for safety.......... 89

Fig. 4.9 Differing levels of safety offered by structural and planning approaches to flood defence in the presence of a flood event in excess of design standard................................................................... 94 v


LIST OF TABLES

Tab. 1.1 Top 10 costliest coastal disasters since 1980 ranked in terms of losses in 2010 US dollars..................................................................... 3

Tab. 1.2 The top 10 most deadly coastal disasters since 1980.......................... 4

Tab. 2.1 Flood characteristics and the relevant modes of damage.................... 10

Tab. 2.2 Flood types and the corresponding characteristics of flooding which cause losses......................................................................................... 11

Tab. 2.3 Proportional value of different assets presented as a percentage of total fixed asset value for countries where data is available................ 16

Tab. 2.4 Ratios of fixed assets to GDP.............................................................. 17

Tab. 2.5 Floor to footprint densities for Shanghai............................................... 27

Tab. 2.6 Recommended assumptions for proportion of net assets at risk by population density................................................................................ 28

Tab. 2.7 Recommended depth-damage curve for estimating structural losses in lightweight, timber-framed dwellings................................................ 31

Tab. 2.8 Descriptors of housing type adopted by Islam..................................... 32

Tab. 2.9 Recommended depth-damage curve for estimating structural losses in lightweight, mixed construction dwellings......................................... 32

Tab. 2.10 Recommended depth-damage curve for estimating structural losses in masonry dwellings............................................................................ 34

Tab. 2.11 Recommended depth-damage curve for estimating structural losses in non-domestic buildings..................................................................... 36

Tab. 2.12 Recommended depth-damage curve for estimating contents losses in domestic buildings............................................................................ 39

Tab. 2.13 Recommended depth-damage curve for estimating contents losses in non-domestic buildings..................................................................... 41

Tab. 2.14 Historical losses from natural disasters................................................ 42

Tab. 2.15 USA proportional value of assets as a percentage of total fixed asset value..................................................................................................... 45

Tab. 3.1 Summary of Dutch ‘all in’ unit costs from IPCC CZMS (1990)............. 48

Tab. 3.2 Summary of Dutch ‘all in’ unit costs from Hoozemans et al.

(1993)................................................................................................... 49

Tab. 3.3 Coastal adaptation measures which are important globally in addition to those costed by IPCC CZMS (1990) and Hoozemans et al.

(1993)................................................................................................... 52

Tab. 3.4 Unit costs of coastal defence measures normalised to 2009 US

Dollars.................................................................................................. 54

Tab. 3.5 DIVA estimated national nourishment costs and volumes for 2010..... 61

Tab. 4.1 Port cities studied known to be at risk of coastal flooding or erosion under present conditions...................................................................... 77

Tab. 4.2 Port cities studied found to be at minimal risk of coastal flooding or erosion under present conditions and associated exposed populations........................................................................................... 78

Tab. 4.3 Applied standards of protection in port cities........................................ 78 vi


Tab. 4.4 Additional cities which can be termed ‘risk tolerant’; applied SoP is significantly over-predicted by the demand for safety function............. 88

Tab. 4.5 Comparison between DIVA demand for safety and the economic optimisation method............................................................................. 89

Tab. 4.6 Absolute height of coastal defences above various datums................ 91 vii


ABBREVIATIONS

CBD

CGE

CIF

DCLG

DIVA

EFAS

FUND

GBP

GDP

GNI

GVA

ILO

LiDAR

MLLW

MSL

PPI

RMB

SLR

SoP

UNECE

USACE

USD

Central Business District

Computable General Equilibrium

Cost, Insurance and Freight

Department for Communities and Local Government

Dynamic Interactive Vulnerability Assessment

European Flood Alert System

Framework for Uncertainty, Negotiation and Distribution

Pound Sterling (Great British Pound)

Gross Domestic Product

Gross National Income

Gross Value Added

International Labour Organisation

Light Detection and Ranging

Mean Lower Low Water

Mean Sea Level

Producer Price Index

Renminbi (¥)

Sea Level Rise

Standard of Protection

United Nations Economic Commission for Europe

United Stets Army Corps of Engineers

US Dollars viii


EXECUTIVE SUMMARY

This report investigates the costs of adaptation to the effects of climate change in

136 port cities with populations over 1 million in 66 countries worldwide. Three areas are investigated; the susceptibility of assets to flood damage worldwide, the costs of constructing adaptive measures and the level of protection against coastal flooding applied in these cities.

The main outcomes are as follows:

•

A globally applicable methodology for assessing coastal flood damage with varying depth has been produced. This global methodology provides guidance on the scaling up of existing analyses to a global scale and will allow broad assessments of potential losses from climate change. This is an important outcome which will allow indicative loss estimates to be made which will support decisions on the level of protection to offer port cities.

•

Actual unit costs for coastal adaptation measures in a number of countries have been assembled. This is the first known database to be gathered and will provide a useful resource in costing future adaptation to climate change.

This database will provide a starting place for addition of further cost information in the future.

•

The collation of the unit cost database has allowed costs to be compared against previous and widely used cost estimates from IPCC CZMS (1990) and Hoozemans et al. (1993). Although actual nourishment costs typically agree with previous estimates, outliers do exist which suggests not all cost factors have been accounted for. Limited cost information was available for dikes although crude analysis suggests that previous estimates are overpredictions; this now needs to be investigated in more detail. Cost estimates for other measures are also available but have not been estimated in previous studies.

•

A database describing applied standards of protection (SoP) in approximately

50 port cities was established. The corresponding defence types utilised were also recorded. SoP is seen to vary considerably both globally and in some cases, within cities. The decision to apply a given SoP is clearly influenced by a diversity of factors beyond the ability to pay for such measures.

•

A number of cities have been previously found to have high exposed populations (Nicholls et al., 2008). In this study it was found that a number of these cities were afforded very low levels of protection. Such cities include

New Orleans, New York, Miami, Kolkata, Mumbai, Ho Chi Minh City and

Guangzhou. Information on the applied SoP was not available for many cities; as such many more highly exposed populations may also be protected to low levels. This finding is particularly worrying as large numbers of people are consequently at risk of coastal flooding.

•

Previous investigations have been forced to use econometric functions to estimate SoP in the absence of direct information. Applied SoPs were compared against DIVA’s demand for safety function in this study. DIVA was ix

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities found to typically over-estimate SoP but was typically correct to within a factor of 10.

•

If the true costs of adapting to climate change are to be assessed in future, significant data limitations must first be addressed. Secondly, the full range of coastal adaptation measures available must be considered and costed if the true cost of adaptation is to be known.

In summary, this report indicates that the costs of adapting to climate change are likely to be significant, in agreement with IPCC CZMS (1990) and Hoozemans et al.

(1993). Existing standards of protection are hugely variable worldwide and the decision to employ given levels of protection is evidently influenced by a large range of factors. This investigation goes beyond the exposure analysis undertaken by

Nicholls et al. (2008) and indicates that even when coastal defences are considered, significant asset values and population are still at risk of coastal flooding. x


1.0 BACKGROUND

In the late 20th century the world witnessed an unprecedented economic and social transformation in the form of coastal urbanisation (Rivera-Arriage, 1999). Port cities are an important aspect of this trend and have become vitally important both in terms of the global economy and as concentrations of population and asset value (Nicholls et al., 2008; Hanson et al., 2010). Investigating the capacity of large port cities to adapt to climate change and the associated costs of adaptation is therefore an important issue, especially given the increasing certainty of sea level rise (SLR) predictions globally.

Port cities are of particular international importance because of their role as transhipment points and consequently as the location of industries relying upon bulk imports or exports. In turn, port cities are frequently centres of population and supporting services and industries.

The volume of seaborne trade has more than doubled in the past 30 years causing port cities to become an integral link in the global economy (Nathwani et al., 2009). The economic significance of port cities has grown noticeably, particularly in developing countries, in line with globalisation and the rapid development of newly industrialised countries (Nicholls et al.,

2008). Thirteen of the twenty most populated cities in the world in 2005 were port cities

(Nicholls et al., 2008) and other studies estimate that approximately two thirds of the world’s population lives within 150 km of the coast (Alcamo et al., 2003), making the study of these cities especially important from a human perspective.

The importance of port cities is conferred by the asset values contained within them in the form of buildings, transport infrastructure, utility infrastructure and other long-lived assets

(Nicholls et al., 2008). Climate change impacts on these cities are likely to be particularly disruptive because in addition to direct damages, these cities also have a role in supplying goods to other industries within these countries. Such impacts can be very costly and far reaching.

The importance of port cities globally is expected to continue into the future. However, the positioning of port cities at the land-sea interface makes them inherently susceptible to the potential effects of climate change, specifically SLR and increased storm intensity. In addition, many port cities are predisposed to accelerated subsidence due to their location on geologically young, often deltaic sediments (Nicholls, 1995; Nicholls et al., 2008). Fast growing coastal populations, an increasing volume of seaborne trade and a changing climate will inevitably increase the risk to port cities (Nicholls et al., 2008). The protection of these cities is expected to be a major cost of accelerated SLR (Turner et al., 1990).

Whilst debating which natural hazard presents the greatest threat globally is not particularly helpful since disasters happen locally, Munich Re’s statistics (Munich Re, 2009) show the meteorological events associated with flooding, on average, rate alongside earthquakes.

Thus, coastal zones couple a high value at risk with a high degree of exposure to natural hazards.

Nicholls et al. (2008) produced rankings of the 136 port cities with populations over 1 million in 2005 based on physical exposure and socio-economic vulnerability to climate extremes, the effects of relative SLR due to global climate change and local subsidence. Rankings were produced for two types of exposure; (1) population and (2) assets. The study underlined the vulnerability of several of the rapidly developing cities to future SLR and highlighted the importance of socio-economic changes as a driver of overall increase in both population and asset exposure. Climate change and subsidence were also shown to potentially exacerbate this effect.

1


Whilst Nicholls et al. (2008) studied exposure to flooding, it is important to recognise that exposure does not automatically translate into impact. The linkage between exposure and the risk of impact depends upon flood protection measures (Nicholls et al., 2008) which were explicitly ignored due to the limited availability of accurate and comprehensive data on flood protection in many cities.

1.1 Study Objectives

This study builds on the work of Nicholls et al. (2008) and Hanson et al. (2010) with the aim of developing a clearer understanding of the damages that might occur and the feasibility and costs associated with planned adaptation to SLR. The study focuses on the 136 port cities with populations over 1 million in 2005, shown in Figure 1.1. More broadly, we are interested in damages and adaptation around the world’s coasts so other areas have been investigated if appropriate.

¯

0 3,250 6,500 13,000

Kilometers

Figure 1.1: The locations of the 136 port cities analysed in this study

In order to accomplish this research, the following objectives have been set:

1. Determine how flood damage varies with depth in different cities across the world.

While nation-specific depth-damage curves exist, these assessments require a generic ‘global’ depth-damage function which simultaneously accounts for local circumstances. The aim is to develop a robust and empirically-embedded ‘global’

2.

3. depth-damage methodology.

Review earlier estimates (IPCC CZMS, 1990; Hoozemans et al., 1993) of coastal defence costs for the full range of hard and soft engineering options. Develop a database of new indicative costs for these measures which account for the associated uncertainty which has previously been ignored.

Acquire data on risk perception in the 136 port cities under study to determine if coastal flooding and erosion are issues of concern. Acquire data on the standard of protection offered by existing artificial and natural defences in these cities.

Compare applied standards against ‘demand for safety’ functions. Where possible it will also be attempted to determine other measures which cities are able to implement including flood warning systems, build resilience, land use planning, etc.

2


1.2 Applications of this Research

This study is an extension of the work of Nicholls et al. (2008) and Hanson et al. (2010).

Both studies focussed on the same 136 port cities investigated in this study. The work of

Nicholls et al. (2008) focussed on population and asset exposure to climate extremes such as extreme water and wind levels. By considering the exposure metric a ‘worst case scenario’ analysis of exposed assets and populations in these cities was possible. The work of Hanson et al. (2010) investigated how climate mitigation is likely to affect exposed populations and assets in future.

The research objectives addressed in this investigation should all contribute valuable knowledge on the exposure of port cities to climate extremes, the damages that are likely to occur and the potential costs of adapting to a changing climate. This is especially important when viewed in the context of coastal disasters which can be costly both in terms of damages and lives lost. Table 1.1 shows the top 10 most costly coastal disasters since 1980 in 2010 US dollars while Table 1.2 illustrates the deadliest disasters since 1980.

Table 1.1: Top 10 costliest coastal disasters since 1980 ranked in terms of losses in 2010

US dollars (Source: Munich Re NatCat Database)

Date

Aug.

2005

Sept.

2008

Aug.

1992

Sept.

2004

Oct.

2005

Aug.

2004

Sept.

2005

Sept.

1998

Sept.

1989

Sept

1991

Event

Hurricane

Katrina

Hurricane

Ike

Hurricane

Andrew

Hurricane

Ivan

Hurricane

Wilma

Hurricane

Charley

Hurricane

Rita

Hurricane

Georges

Hurricane

Hugo

Typhoon

Mireille

Port Cities

Affected

Severely

Affected Areas

New Orleans

Houston

Miami n/a

Miami

Havana

Louisiana,

Alabama

Texas, Louisiana,

Cuba

South Florida,

Louisiana,

Bahamas

Caribbean Is.,

Alabama, Florida,

Louisiana, Texas

Cuba, Florida,

Bahamas

Florida, Cuba,

Caribbean Is.,

N&S Carolina

New Orleans Louisiana, Texas,

Santo

Domingo,

Havana,

New Orleans n/a

Hiroshima

Dominican

Republic, Cuba,

Florida, Louisiana,

Mississippi,

Alabama

S. Carolina,

Guadeloupe,

Montserrat

Japan

Overall Losses (millions

USD)

Original

Values

Normalised to

2010 Levels

125000 142000

38000 39300

26500

23000

22000

18000

16000

13000

9600

10000

41800

26800

25000

21000

18200

17400

17400

16400

Table 1.2: The top 10 most deadly coastal disasters since 1980 (Source: Munich Re NatCat database)

3


Date

Dec. 2004

May 2008 Cyclone Nargis

Apr. 1991 Tropical Cyclone

May 1985 Tropical Cyclone

Oct. 1999 Tropical Cyclone

June 1998 Tropical Cyclone

Nov. 1998 Hurricane Mitch

Nov. 1991 Cyclone Thelma

Sept. 1998

Nov. 2007

Event

Asian Tsunami

Hurricane

Georges

Cyclone Sidr

4

Port Cities

Affected

Visakhapatnam

Madras

Cochin

Rangoon

Chittagong

Chittagong n/a n/a n/a

Santo Domingo,

Havana,

New Orleans

Dhaka

Severely Affected

Areas

Sri Lanka, Indonesia,

Thailand, India,

Myanmar

Bangladesh

Bangladesh

India, Bangladesh

India

Honduras, Nicaragua,

Florida

Philippines

Dominican Republic,

Cuba, Florida,

Louisiana, Mississippi,

Alabama

Bangladesh, India

Total

Deaths

220,000

140,000

139,000

11,050

10,000

10,000

9,976

6,000

4,000

3,360

Although not all losses can be attributed to coastal flooding, (the deep depressions causing storm surges are also associated with high velocity winds) it is clear that coastal hazards are potentially catastrophic.

The production of a global depth-damage function should make it possible to assess the likely value of damage caused by flooding at any location across the world. As such, the function is likely to prove useful in predicting flood losses and their likely impacts on the economy and in evaluating the losses in economic, distributional or socio-economic terms. If an appropriate methodology can be determined, it will provide a valuable tool for assessing loss potentials from flood events globally.

Unit costs of coastal defence measures are investigated to help develop a better understanding of the impact of future socio-economic development pathways on risks from climate change. Understanding how the costs of protection change with wealth will help us to understand how existing defences could change with socio-economic and climate changes in the future.

The findings of this report can also be used to update the coastal defence unit costs originally proposed by IPCC CZMS (1990) and Hoozemans et al. (1993) and to assess their applicability in present day coastal engineering. Despite being produced more than 15 years ago, these studies still provide a major input into most global vulnerability assessments to this day, likely in part due to the absence of more recent studies. It is therefore hoped that this analysis and any subsequent improvements will improve future global vulnerability assessments.

The existence of a global unit cost database will provide an important source of up to date, standardised and comparable primary information which can be referred to when assessing the costs of adapting to SLR globally. Addressing the issue of uncertainty in cost estimates will provide important information on the likely range within which costs should lie and the

4

Note tsunamis have been excluded from Table 1.1 but the Asian Tsunami is included here for reference

4

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities potential reasons for this variation – issues which have been neglected in previous studies

(IPCC CZMS, 1990; Hoozemans et al., 1993).

This analysis should also improve our understanding of adaptation responses to coastal hazards and will help illustrate how defence levels applied change with social, economic and cultural factors. By improving our understanding in this area, we should gain a better appreciation of how applied defence levels will change as a result of other factors in the future.

This study will also provide a valuable contribution toward our understanding of the structural, institutional and behavioural barriers to cost-effective adaptation. One goal of this research is to draw together a database describing existing flood defences in the 136 cities.

By determining the applied SoP in each of these cities it should be possible to progress from exposure analysis such as that conducted by Nicholls et al. (2008) toward risk analysis for these locations. This should give a more complete picture of the population and assets at risk in each city.

The compilation of a database describing adaptive measures for coastal flooding and information on the level of protection offered to port cities should provide a valuable source of information for future investigations and decision making. It will also provide a baseline for assessing how coastal defences will evolve under scenarios of climate and other change.

It is hoped that in the same way the work of Nicholls et al. (2008) led to further investigations into coastal vulnerability (c.f. Nathwani et al., 2009), this work will hopefully also stimulate interest in the costs of adapting to climate change along the world’s coast thus motivating further investigations.

1.3 Structure of the Report

This report is presented in three sections to address each of the objectives stated in Section

1.1.

Starting with Section 2, an analysis of how flood damage varies with depth is presented followed by the presentation of a global depth damage methodology.

Section 3 addresses unit costs of coastal defences and attempts to draw together a new indicative database detailing the costs of adapting to coastal change.

Section 4 investigates the levels of protection applied in the port cities under study and the coastal adaptation options implemented. Applied SoPs are also contrasted with suggested levels of protection from econometric functions.

Finally, Section 5 provides concluding thoughts and overarching comments.

This report also contains two companion papers which are included in Appendices I and II.

The first is produced by Hillen et al. (2010) and is a case study investigating coastal defence unit costs in the Netherlands, New Orleans and Vietnam. The main findings of this report have been assimilated into the body of this report and have been analysed accordingly. The full report however provides additional information carefully outlining the background and history of coastal defences in these three regions, provides some further cost information and contains a detailed look at economically optimal levels of protection.

Appendix II contains a report by Geldenhuys (2010) which covers adaptation measures applied in Cape Town, South Africa to cope with climate change. Again, the main relevant findings have been assimilated into the main body of this report. The full report contains

5

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities additional information on the specific situation with regards vulnerability to coastal flooding in

Cape Town. Although the city is high enough not to be subjected to inundation following defence breaches, it is vulnerable to coastal erosion during storms. Discussion of a recent large storm and consequent damages illustrates the importance of coastal defence to the city now and into the future.

6


2.0 DEPTH-DAMAGE CURVES

2.1 Background

At present, depth-damage curves exist for specific locations but in order to generalise results and make broad assessments of the potential for flood losses as a result of climate change, a ‘global’ depth-damage function is required. Although a suite of depth-damage curves focussing on specific locations exists (Dale, 2009; Islam, 1997; Yan, 2005; Meyer &

Messner, 2005; Penning-Rowsell et al., 2003a, 2003b), there is little guidance on how to scale up these analyses to a global scale. This project provides a synthesis of previous national studies and investigates how they can be implemented as part of a global analysis.

The ultimate aim here is to produce a methodology for estimating how flood damage varies with depth around the world through the use of a methodology which can be applied in conjunction with pre-existing depth-damage curves to produce a ‘global depth-damage function’. At present, nation-specific curves are available but the development of a widely applicable methodology will allow global damages to be assessed whilst also accounting for local circumstances.

There are several reasons for evaluating flood losses and distinctions need to be drawn between them. Three overlapping concepts are shown in Figure 2.1.

Post event assessment

E.g. ECLAC

Predicting losses

Assessment of losses

Whole life costing: discounting:

IWRM

Cost-benefit analysis

Best means of recovery

Reallocation of expenditure: balance of consumption and reinvestment

Figure 2.1: Varying purposes for evaluating flood losses

1. Evaluating the impacts upon social, economic and environmental systems in order to determine the best means of recovery

2. Making an economic assessment of the options for reducing the risk of future disasters

3. Evaluating the losses to the economy from a disaster such as a flood

Point one concerns how available resources should be re-allocated so as to return swiftly to pre-flood conditions. For instance, this may involve assessing whether a government should seek to reduce consumption in order to promote re-investment. Equally, such analyses can examine how households, communities or organisations reallocate resources so as to recover (Chatterjee, 2007; Jahan, 2000; Toya & Skidmore, 2004; Webb et al., 2002).

7


Point two assesses the various costs of the different forms of interventions but an economic assessment claims also to be able to identify the best intervention strategy of those identified. Conversely, it necessarily excludes a number of possible societal objectives which might be considered relevant by a society in deciding how to intervene; it necessarily excludes those objectives which economics has deemed to be not a concern of economics

(Robbins, 1935).

This report is solely intended to address the third concept; it is an economic assessment of the likely losses from extreme coastal flooding events. The purpose is to enable the estimation of flood losses resulting from an event which has not yet happened. The rationale for assessing the extent of flood losses is to determine how these losses impact the economy or to evaluate those losses in economic, distributional or socio-economic terms.

At its simplest, the economy is essentially a system of transforming input into goods and services which contribute to human well-being at the individual level and welfare at the community level. A flood is capable of impacting the economic inputs, transformation processes and outputs with losses in one component feeding through into losses in subsequent components. Through most of history the most critical impact of flooding has been upon food although, this emphasis is now changing. Whilst agricultural losses are still important in low income countries, globally they are now relatively unimportant and droughts almost certainly represent a greater risk to food production than floods.

This investigation focuses exclusively on determining the impact of flooding on the transformation of natural endowment into goods and services. Despite the fact that the impacts of flooding have been shown to be significant in affecting health (Parker et al., 1987) and interpersonal relations (Red River Basin Board, 2000) at both the individual household level (Allee et al., 1980) and upon communities (Erikson, 1976), so far the capacity to account for differences both between households and communities, and between different types of flood event has proved very limited (RPA/FHRC, 2004). There is a suspicion that differences in personality or life-experience play a significant role. This renders the prediction of the relative impacts of flooding on well-being and welfare highly problematic at present and consequently, this research has not attempted to address it.

As an economic assessment, this investigation uses money as a numeraire to express the relative magnitude of the impact of a flood in different locations. ‘Money’ is a problematic concept in economics (Shubik, 2001; von Mises, 1981) and has a number of different meanings or uses. In particular, money as a numeraire has to be differentiated from ‘money capital’, a resource. In this document, the term money will be used when it is being used as a numeraire and money capital when referring to money as a resource.

2.2 Coastal Flooding

2.2.1 Characteristics

Extreme coastal floods are the result of deep atmospheric depressions of different types: the most intense events being variously referred to as typhoons, cyclones or hurricanes. It is also worth noting, intense storms such as hurricanes are unlikely to form in many areas because conditions such as sea surface temperature and relative humidity which favour the formation of these storms are not present (Warrick et al., 2000). Whilst flooding is essentially the consequence of the tidal surge induced by the low pressure, such intense depressions are necessarily accompanied by high wind speeds and intense rainfall. Hence, those depressions are a multi-hit event resulting in:

1. Flooding caused by the tidal surge;

2. Wind damage;

8


3. Local pluvial flooding;

4. Heavy rainfall on the catchment which results in river flooding.

5. Potential landslides induced by rainfall where coasts are backed by steep hills

Consequently, there is a difference between the damage caused by extreme depressions and damage from the coastal flooding which results from them. In assessing the benefits of an intervention strategy designed to reduce the risk of coastal flooding, it will generally be incorrect to assume that the other forms of loss will be reduced by that strategy.

Flood events have a number of characteristics including depth, duration, velocity and load.

These are addressed below under the following subheadings:

Depth

Flood depth is a function of both the water level and the ground level; errors in either result in erroneous estimates of flood depth. As depths of flooding increase, the error in estimating the flood loss decreases: the vertical error in LiDAR data, for example, washes out when flooding is >3 m deep and more important when flooding is <0.25 m in depth. Coastal flooding is associated with significant depths of flooding which will vary greatly between occurrences.

Duration

Very long flood durations (over one week) are associated with increased physical damages

(Green et al., 2006). In addition, the consequential losses associated with the inability to perform particular activities or deliver goods and services are also increased. In the case of coastal flooding, events are typically short duration although there can be exceptions such as following Hurricane Katrina in the USA, where land levels were below sea level and flooding persisted for an extended period. In the majority of cases however, ebbing tides tend to drain surge waters with them.

Velocity

High velocity flows increase damage to buildings in a number of ways:

•

Flows can entrain debris such as vehicles, trees and rocks causing damage upon collision with buildings

•

Obstructions create standing waves and associated scour which can undermine foundations

•

Pressure differentials may occur between interior and exterior of buildings

The combination of depth and velocity can result in partial or complete structural failure of a building, the required combination depending upon the structural form of the buildings

(Kelman, 2002). Only the last causal mechanism can currently be modelled. For coastal flooding, the problem is significant only in the event of breaches of natural or artificial defences.

Load

In the most extreme cases these are mud flows; essentially the movement of liquidified soil.

Mud flows are capable of destroying entire urban areas. However, such instances are usually the result either of volcanic eruptions causing instanteous snow melt and consequent soil erosion (e.g. Armero, 1985) or on alluvial fans (e.g. Venezuela, 1999).

Some rivers carry a very high load of sediment but this load varies greatly between rivers, as does the nature of that sediment. Sewage, oil and other petrochemicals are all commonly released in floods, along with agricultural chemicals such as fertilisers and pesticides.

9


Because of the very large volumes of water involved, dilution of pollutants will normally be such in coastal floods that the only load of significance are the salts of the waters. A number of materials are subject to quite aggressive attack in the combination of water and salts.

Pebbles and sand thrown by waves can be an issue along the coastline itself. The process of local flooding is also likely to cause liberation of petrol, oil and other pollutants from normal storage areas.

2.2.2 Approach adopted

As shown above, floods have many characteristics of which only a small number are typically associated with coastal flooding. As this investigation is primarily concerned with the assessment of coastal locations some of these characteristics can be ignored; this is beneficial with regards to simplifying the process of developing a global depth-damage function and also with regards to the non-availability of information on some aspects of flooding associated with other flood types.

The characteristics of flooding can impact upon buildings, land uses and the activities carried out in these locations through a number of different physical, chemical or biological processes as shown in Table 2.1. The most obvious causes of damage are velocity of flow and the load of silt and pollutants carried by the flood. Attention has focused upon the depth of flooding because it is only comparatively recently that hydrological-hydraulic computer models have developed the capacity to derive realistic estimates of velocities.

Table 2.1: Flood characteristics and the relevant modes of damage

Depth

Duration

Velocity

Load

Physical

●

●

●

Mode of Damage

Chemical

●

●

●

Biological

●

●

As discussed in Section 2.2.1, only the depth of coastal flooding is particularly important in terms of deriving losses. This is shown in Table 2.2 along with the damage mechanisms associated with other flood types.

Table 2.2: Flood types and the corresponding characteristics of flooding which cause losses

Groundwater

Pluvial

Flash

Depth

○

6

Flood Characteristic

Duration Velocity

●

○

5

●

Load

●

5

Very dependent upon form of catchment, especially steepness

6

Very dependent upon shape of catchment and therefore degree to which flood flows are concentrated

10


Alluvial fan

Lowland river

Coastal

●

●

●

●

● ●

○

7

Consequential losses refer to the different forms of indirect losses as a result of flooding.

The losses from a flood are not restricted to physical damages but the effects on the socio economic system ripple outwards; these consequential losses are the socio-economic system’s response to the perturbation caused by the flood. Despite their potential importance, neither the appropriate models nor the data with which to calibrate those models are available and as such, it has not been possible to include estimations of consequential losses in this study. The difficulties in determining these losses are explored in more detail in

Appendix III.

2.3 Methodology

Flood losses should be explicable as a consequence of what people are doing and in what form of building they are undertaking that activity. The determinants of flood losses are the laws of physics, chemistry and biology. These laws determine how the characteristics of a given flood, such as depth or duration, result in damaging effects upon some material or assemblage of materials. In order to produce a predictive relationship, the chain in Figure

2.2 must be considered.

Figure 2.2: Chain of characteristics which influence the degree of flood damage

When attempting to calculate the value of physical losses from flooding it is important to note that this value cannot be larger than the value of the assets. In turn, only a proportion of

7

Dependent upon sediment load of river

11

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities those assets are exposed to flooding; in densely populated urban areas, a significant proportion of buildings are multi-storey and hence a large portion of the assets are above any conceivable flood level. Following on from this, only a given proportion of the assets exposed are susceptible to the effects of flooding. In order to account for this, actual losses must be expressed as a function of depth-damage curves.

The driver in loss assessment has always been and always will be the availability of data: what can be done depends upon what data is available. Data is the ability to make meaningful categorisation and hence a crucial aspect of data is the degree to which it is possible to differentiate into meaningful categorisations. Numbers are simply a form of categorisation and one which aspires to being a continuum. In practice, numbers are often fuzzy categories and the degree to which different numbers are significantly different can be unclear. Here, as in all other cases, it is better to be roughly right rather than precisely wrong.

In addressing differences in assets at risk and the differing consequences of these losses in the wider economy, we are restricted to that data which is available at least at national level across the countries at risk. Since the areas at risk are likely to be a biased sample of the relevant country as a whole, data at regional and preferably city area is preferable. In addition to population, the most widely available data is on GDP/GNI, collated using an international standard, and more usefully on the components of GDP/GNI, notably asset formation, GVA and household income. Data on household expenditure on food is also available for many countries from the ILO. Other data is patchily available.

The focus in this report is upon economic losses and this has a number of differences from a simple financial assessment. Firstly, a nation is treated as if it is a single person, secondly, either changes in a stock or in the flows which are produced by or which produce that stock are valued but not both. Which of the two approaches is adopted in a particular instance depends upon which is more feasible. That relationship between stock and flow values implies the third difference: the value of an older product is not taken as equivalent to the value of a replacement.

The remainder of this section sets out and justifies the determination of a ‘global’ methodology applying depth-damage functions across multiple nations up to global scales.

The structure of this methodology is as set out in Figure 2.3.

12


Estimated from per capita net asset formation

Crude assumption of average number of floors from population density

Proportional depth-damage curves

Figure 2.3: Method for estimating potential losses from flooding

2.3.1 The Value of Assets

The first step in determining flood losses is to estimate the value of assets. As already stated, there can be no more losses than there are assets to be lost. The current value of those assets can be expressed as a function of the annual investment in new assets. The current value is determined by accounting for depreciation and investment in existing assets.

Currently few countries have managed to estimate the value of their physical assets although there are some exceptions as shown in Figures 2.4a to 2.4g.

UK

A

13


Netherlands

B

Germany

C

-

Figures 2.4A – C: National estimates of the breakdown of fixed assets as a percentage of the total value of fixed assets

Korea

D

14


Australia

E

Japan

F

Intangible Fixed Assets

Figures 2.4D – F: National estimates of the breakdown of fixed assets as a percentage of the total value of fixed assets

15


USA

G

Govt. Residential

Consumer Durable Goods

Figure 2.4G: National estimates of the breakdown of fixed assets as a percentage of the total value of fixed assets

This data has been derived using the perpetual inventory method (Lutzel, 1977; Meinen et al., 1998). Whilst this method depends upon a chain of assumptions (Schmalwasser &

Schidlowski, nd; van den Bergen et al., 2009), it has been concluded that the accuracy of these estimates is approximately 10% in the UK (Omundsen et al., 2009). For the purposes of this study, this accuracy is quite acceptable and represents a higher degree of accuracy than has been possible for other parameters. This accuracy is however dependent on the accuracy of the raw data which varies from country to country.

Although the countries fixed asset classifications differ, it can be seen that the largest components of the assets are made up of dwellings and non-domestic buildings with contents forming a relatively minor component. Japan, in what is a very small sample, is anomalous and the proportion for ‘other structures’ may reflect public works undertaken as part as counter-deflationary programmes and the long life assigned to such works.

Whilst a search was undertaken for fixed asset data for other middle income countries and low income countries, none was found for the countries searched in the English language literature. The breakdown of proportions of different assets is shown in Table 2.3 this is undertaken in countries where data is available and categories similar enough to enable comparison.

Table 2.3: Proportional value of different assets presented as a percentage of total fixed asset value for countries where data is available

USA UK Japan Germany

Non-domestic buildings & structures 42 36 61 36

Dwellings

Equipment

36

14

Domestic durables 9

40

17

20

14

47

16

16


From this very small sample of countries, all of them high income, the best approximation that can be made as to the breakdown of fixed assets is to adopt the figures for the USA since these are the only ones which include domestic durables.

As noted earlier, for a few high income countries, estimates of the current value of fixed assets are available. These are summarised in Table 2.4.

Table 2.4: Ratios of fixed assets to GDP (from the relevant offices of national statistics).

GDP/capita values are taken from the DIVA database and scaled to the stated years

Country

UK

USA 41500

Netherlands 34933

Germany

China

43800

817

Japan

GDP per capita ($) Ratio of fixed assets to GDP per capita

29933 2.1 (2008)

58267

3.0 (2008)

3.3 (2004)

4.9 (2006) – modern replacement cost

0.6 (2005)

2.4 (2005)

Where information on the current value of fixed assets is unavailable, it may be possible to determine the value of assets using available figures for net asset formation. For most countries, the breakdown of net asset formation into different forms of investment is not available. However, EUROSTAT provides detailed breakdowns for the construction element of net asset formation in European countries. It also gives the total asset formations for the

USA and Japan although detailed information is not available as to breakdown of that asset formation. Figures 2.5 and 2.6 show how the proportions of total asset formation ascribed to the additions to the stock of dwellings and other construction vary. Only a selection of the countries for which data is available is shown but these examples illustrate the full range of investment in housing and other construction shown by the EUROSTAT database and also show how these statistics vary between and within countries over time. As a result of this variation, it does not seem possible to apply a uniform rate to all countries.

17


100%

90%

80%

70%

60%

50%

40%

30%

20%

Ireland

Luxembourg (Grand-Duché)

Malta

Portugal

Romania

Former Yugoslav Republic of

Macedonia, the

Turkey

Norway

10%

0%

2000 2001 2002 2003 2004

Year

2005 2006 2007 2008

Figure 2.5: Proportions of fixed investment in dwellings for a selection of countries in Europe

Other countries contained in the dataset but excluded from the figure fall within the range shown

18


100%

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

2000 2001 2002 2003 2004 2005 2006 2007 2008

Germany

Spain

Lithuania

Luxembourg (Grand-Duché)

Hungary

Malta

Turkey

Norway

Figure 2.6: Proportions of fixed investment in other buildings for a selection of countries in Europe

Other countries contained in the dataset but excluded from the figure fall within the range shown

19


In other countries some data is available through the standard statistics on national accounts published by the United Nations (European Commission et al., 2009). This provides the net annual investment in fixed assets. However, if intending to use this data, the problem then becomes how to derive a means of estimating current fixed assets using only data on net annual fixed asset formation . In addition, the data shows wide variations in the proportion of GDP ascribed to net asset formation as shown in

Figure 2.7. Montserrat was included here because of the effect of volcanic eruption

(1995-98). The island has also previously been hit by a series of other natural disasters

(notably Hurricane Hugo in 1989). Not surprisingly, each disaster was followed by major net asset formation.

20


300%

280%

260%

240%

220%

200%

180%

160%

140%

120%

100%

80%

Somalia

Vietnam

Indonesia

India

USA

UK

China

Germany

Netherlands

Singapore

Montserrat

Japan

60%

40%

20%

0%

1970 1980 1990

Year

2000 2010

Figure 2.7: Fixed asset formation as a proportion of GDP in a selection of countries where rates vary significantly (from International Monetary Fund, 2009).

Countries are offset by 20% so that patterns can be discerned

Both the very large differences between the proportions of GDP that are invested in fixed asset formation and the variations over time in this rate are noticeable. The latter may be explicable by external events such as disasters but the former implies that no uniform

21

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities rate could be applied to all countries although more detailed statistical analysis might reveal standard rates that might be applied to identifiable groups of countries.

A further complicating factor in the determination of asset values from national statistics is that GDP generally shows variations within countries, this is especially the case in larger countries. Therefore there is a risk of systemic variation with coastal zones having a higher GDP per capita than inland regions and also in the rate at which fixed assets are being created, as shown in Figure 2.8. In particular, the case of China shows that 47% of all fixed capital investment is taking place in coastal provinces and cities with the average investment being 137% of the national average. The conclusion therefore is to use regional GDP data where this available.

12000

10000

8000

6000

4000

2000

0

1952 1960 1970 1978 1985

Year

1990 1995 2000 2004

Beijing

Tianjin

Hebei

Shanxi

Inner Mongolia

Liaoning

Jilin

Heilongjiang

Shanghai

Jiangsu

Zhejiang

Anhui

Fujian

Jiangxi

Shandong

Henan

Hubei

Hunan

Guangdong

Guangxi

Hainan

Figure 2.8: Regional growth of fixed assets in China (from Jun et al., 2007)

Given the sparsity of data, a number of techniques were explored to derive a ratio of net fixed assets to GDP. The aim was to derive a means of estimating the value of fixed assets per capita on the basis of data on GDP per capita.

Calibration of this approach was only possible in China and the USA where concurrent estimates of the value of fixed assets (from Jun et al., 2007 and BEA, 2010 respectively) and a time series of GDP were available. In this analysis, there is an element of autocorrelation since the figures for GDP include the net asset formation in that year.

Equally, it might logically be expected that GDP per capita is related to fixed assets per capita at least in regard to the productive assets (i.e. excluding consumption assets).

The logical causal relationship is between fixed assets per capita and GDP per capita, probably with some time lag; for example, an investment in schools would not be expected to show in higher GDP per capita until the first cohort educated in those schools moved to productive work.

22


Figure 2.9 shows the annual ratio of net fixed assets in China against the Bureau of

Statistics’ report of GDP for that year. Rather than the expectation that increases in GDP would be associated with disproportionate increases in the ratio of fixed assets to GDP, the trend appears at best constant, averaging about 0.8. The falling ratio for China was unexpected but logically follows from a very high growth which even with a high proportion of that GDP being composed of net fixed asset accumulation, must consequently grow faster than the net asset base.

1.4

1.2

1

0.8

0.6

0.4

0.2

0

1970 1978 1985 1990 1995 2000 2004

Year

Figure 2.9: Time series of net fixed assets to GDP for China (from Jun et al., 2007)

In addition to this longitudinal analysis, a cross-sectional analysis was also undertaken for the provinces of China of the ratio of fixed assets to GDP against GDP (Figure 2.10).

Any statistical trend there is being determined by Beijing as an outlier and very large variations are observable between provinces with a GDP per capita of 20,000 RMB or less.

23


1.40

1.20

1.00

0.80

0.60

0.40

0.20

R 2 = 0.11

0.00

0 10,000 20,000 30,000

GDP/capita (¥)

40,000 50,000 60,000

Figure 2.10: Regional variations in the ratio of net fixed assets to GDP from Chinese provincial data (from Jun et al., 2007)

A similar analysis was undertaking using data from the USA (BEA, 2010). Analysis of that data from 1929 onwards shows no progressive change over time; as shown by

Figure 2.11, the ratio seems instead to reflect major economic upheavals such as depressions, when the ratio rises and booms when it falls. The rate of net asset formation shows a similar but obverse pattern.

24

AVOID WS2/D1/R14

0.20

Costs of Adaptation to Climate Change in Large Port Cities

5.00

4.00

0.15

3.00

0.10

2.00

0.05

Ratio of Fixed Asset

Formation : GDP

Ratio of Fixed Assets :

GDP

1.00

0.00

1920 1940 1960

Year

1980 2000

0.00

Figure 2.11: Ratio of fixed assets to GDP and fixed asset formation to GDP for the USA

(from BEA, 2010)

Thus, neither of the analyses of China nor of the USA revealed a clear association between GDP per capita and net fixed asset per capita which could then be reasonably generalised to other countries. Therefore, on the basis of the very limited evidence that has been obtained, it is believed that the best approximation that can be made is to adopt ratios of net fixed assets to GDP as shown below. These ratios should provide a good contemporary ‘snapshot’ although future research may want to investigate how these ratios may change in future.

•

3:1 for developed economies

•

1:1 for developing economies

An important caveat that should be noted is that the National Accounts, such as GDP, are no more than a form of double-entry booking and have been shown to have a number of major defects as an economic measure (Daly & Cobb, 1990). However, this source must be utilised as it is the only one available.

2.3.2 Exposure to Flooding

Of the physical assets to be found in an area, only a given proportion will be exposed to the risk of flooding. Those assets below 5-7 metres above mean sea level may be considered ‘at risk’. Thus, in areas where there are a high proportion of high rise apartments, a significant proportion of the stock of dwellings will be above any foreseeable risk of flooding. In very densely developed areas, a large proportion of all properties will simply be above any foreseeable flood level; in Hong Kong for example, a significant proportion of factories are in multi-storey buildings. However, in these densely developed areas, spaces below ground level are often put to use, most obviously in underground car parking (possibly the land use type with highest loss per unit area) but also for shopping and leisure facilities such as cinemas.

Since data as to vertical distribution of fixed assets is not available, there is a requirement to find some proxy for this vertical distribution.

25


One potential source of information is EUROSTAT which provides data for much of

Europe on the proportions of dwellings which are in ‘high rise’ buildings, defined as a building of more than 4 stories. These statistics are presented in Figure 2.12. On this basis, it can be seen that in many countries only a proportion of housing stock can be at risk. The mean number of stories in building designated as ‘high rise’ is not given.

50

40

30

20

10

0

Figure 2.12: Proportions of dwellings in multi-storey buildings (from Federcasa, 2006)

The EUROSTAT data can be used to calculate a theoretical maximum value of assets at risk of flooding. For example, in the Czech Republic where 34% of dwellings are ‘high rise’, a maximum of 75% of housing assets can be at risk of flooding (assuming no dwelling above the ground floor is at risk). For the countries included, the proportions at risk for different countries then vary between 71% and 98%. Data has not been found for other countries.

In order to accurately assess the assets at risk of flooding, it would be useful to know the ratio of floor area to building footprint in order to gain an understanding of the number of likely storeys. However, no comprehensive data has been found. Pan et al. (2008) report the use of high resolution satellite imagery to assess the floor area ratio over the

Shanghai metropolitan region, although this methodology is inhibited by cost. The results of Pan et al. (2008) are shown in Table 2.5.

Table 2.5: Floor to footprint densities for Shanghai (from Pan et al., 2008)

26


Total floor area

(ha)

CBD Lujiazui areas

428.4

Xujiahui areas

417.1

New residential areas 541.1

Huangpuqu areas

496.5

The Inner Circle

13664.5

Old residential areas

62.8

Villa areas

29.7

Shikumen areas

8.9

Total footprint area (ha)

15.4

34.2

53.0

59.9

2374.3

23.8

11.8

6.9

Total site area

(ha)

130.9

214.6

261.8

168.0

9450.6

53.3

40.7

16.2

Ratio floor to footprint

27.8

12.2

10.2

8.3

5.8

2.6

2.5

1.3

However, Shanghai has the characteristically high population density of Asian, South

American and African cities; urban population densities in other parts of the world are considerably lower. This could cause problems in the application of the findings of Pan et al. (2008) to other cities; based upon the arguments of early twentieth century geographers some relationship would be expected to exist between density and development intensity in terms of high rise construction although the large differences in population densities worldwide may mean it is incorrect to generalise the floor area to footprint ratio found in Shanghai to other cities.

The typical global trends in population density are illustrated in Figure 2.13. This data characteristically indicates the occurrence of ultra-high density cities in Asia and South

America; Kwun Tong in Hong Kong has a population density of over 54,000/km 2 and some residential areas may have a density over 100,000/km

America and Australasia.

2 (Hui 2000). Middle density cities are typically found in Europe and ultra-low densities in many urban areas of North

35,000

30,000

25,000

20,000

15,000

10,000

5,000

0

Figure 2.13: Comparative urban densities (from City Mayors, 2010)

In addition, there are two different ways of achieving high densities: take up most the available land with buildings or build high. Historically, the former approach was

27

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities generally adopted and very high densities were achieved in this way in cities such as

Cairo. Such densities are also associated with poverty: slum areas of European cities achieved phenomenally high densities in the nineteenth century in relatively low rise buildings.

Unfortunately, there are very few other studies available on floor space density

(Alhadaddad et al., 2004; Lu et al., 2002; Mitomi et al., nd; Yamazaki et al., 2004) and those that do exist do not provide sufficient detail to draw clear conclusions as to floor area density in the areas studied. Hence, whilst the possibility was considered of deriving some general approximation of floor space density to population density, it could not be pursued because there was an insufficient sample of studies.

In the absence of a reliable relationship, it is therefore proposed that it be assumed only

50% of the assets in any area are at potential risk of flood loss. For the purposes of sensitivity analysis, the approximations shown in Table 2.6 are suggested based on the available data for Shanghai (Pan et al., 2008).

Table 2.6: Recommended assumptions for proportion of net assets at risk by population density

Ratio of assets at risk to net assets

<1000/km

2

1:1

Urban Population Density

1000-8000/km

2

8000-15,000/km

2

1:2 1:4

>15,000/km

2

1:6

2.3.3 Susceptibility to Flood Damage

Depth-damage curves are one method of assessing the susceptibility of assets to flooding. These curves have been derived in different ways in different countries. In those countries where there is readily available data on the values of the assets at risk, depth-damage curves have been developed as a function of the proportion of the total value of a building which will be lost at different depths (Davis, 1985). In other countries where data is not available on the property values at risk, depth-damage curves instead describe loss per building or loss per unit at different depths. The second is the case in the UK which arguably has the most detailed and best documented depth-damage data

(Penning-Rowsell & Chatterton, 1977; Parker et al., 1987; Penning-Rowsell et al., 1995,

2003a, 2003b). In this study, given that gross aggregates of the value of assets at risk is all that is available, proportional depth-damage curves have had to be used.

Using net fixed asset data derived from national accounts poses a limitation in this investigation. In general, proportions of the different types of asset (e.g. dwellings, nondomestic buildings, equipment, etc.) are not presented. Consequently, it is not generally known what proportion of the assets fall into each land use/building category. Hence, whilst many different combinations of activity and built form may have differing susceptibilities to flood loss, there is no data with which to work. The best that can be done is to adopt the following:

Residential buildings:

•

Structural or fabric depth-damage curve

•

Contents depth-damage curve

Non-residential buildings:

•

Structural or fabric depth-damage curve

•

Contents depth-damage curve

28


The approximations as to the proportions of net fixed assets falling into each of these four classes are taken as equivalent to those in the USA, described in Table 2.3.

Since buildings form the largest proportion of fixed assets, it is important to focus attention upon estimating the susceptibility of buildings to flood damage.

Residential: Structural Losses

For dwellings, there are significant differences in the constructional form of dwellings in different countries; a result of culture, the availability of materials and climate. In turn, these differences affect susceptibility to flood damage.

Highly susceptible structures may include lightweight timber frame structures, with suspended floors, especially if dwellings have basements. Such dwellings are especially susceptible if floors are made of ordinary chipboard and internal partitions are stud walls which simply sit upon the ground floor. In comparatively shallow depths of flooding, the entire ground floor structure is effectively destroyed. In the presence of even moderate velocity, buildings may simply float off their foundations. Such dwelling types are frequently found in North America and Australia.

Less susceptible structures may include those with mass concrete walls and concrete floors. In hot climates the desire to avoid warm surfaces means floors are often left bare and hence contents losses are also reduced. Such dwellings are increasingly found in

South America and China. The drive towards energy efficiency is likely to promote the wider adoption of such built forms in future due to a reduced requirement for heating and cooling.

These differences in susceptibility are best illustrated using data from a single country, derived in the same way. Dale (2009) took a standard house plan and calculated structural or fabric damages for different forms of typical construction. The results are shown in Figure 2.14. It can be seen that structures of brick construction experience lower losses than those with a brick veneer. Differences between construction methods are even more marked in data from Japan (River Planning Division, 1990) and in

Bangladesh (Islam, 1997).

29


40%

30%

20%

10%

80%

70%

60%

50%

Brick Veneer Slab

Floor

Brick Veneer Timber

Floor

Double Brick Slab

Floor

Double Brick Timber

Floor

Double Brick

Average

Brick Veneer

Average

0%

0 0.5 1 1.5 2 2.5 3

Water Depth (metres)

Figure 2.14: Proportional damages to residential structures of varying constructions –

Australia (Dale, 2009)

As a proxy for typical forms of dwelling construction, UNECE statistics on housing construction material consumption were examined. Although there are some major exclusions in the dataset: notably, India, China, Japan and Korea, marked differences were observed in the relative balance of materials used. However, there appears to be no rule which can be derived statistically for associating a particular constructional form to a country. As an approximation therefore, the following allocation rule has been adopted. The basis for this approximation is largely personal observation.

1. Lightweight timber framed construction: North America, Australasia

2. Lightweight mixed construction: low income countries

3. Masonry construction: the rest of the world

Lightweight timber framed construction

The two best candidates for use in this category generally are the curves for the USA and the new curves for Australia shown in Figure 2.14. In this case, the Australian curves are recommended for application. This decision is based on the fact that these curves (Dale, 2009) show significantly higher losses at shallow depths than the US curves (USACE, 2004) and provide detailed discussion on the building construction adopted. The form of the recommended curve is shown in Table 2.7.

30


Table 2.7: Recommended depth-damage curve for estimating structural losses in lightweight, timber-framed dwellings (from Dale, 2009)

Depth (m) Loss as a percentage of net asset value

-0.25 0.9

0.00

0.25

1.6

16.9

0.50

1.00

1.50

2.00

2.50

3.00

44.5

61.8

62.9

63.3

69.4

69.4

Lightweight mixed construction

For the second category, three considerations were regarded in the selection of curves:

1. Sufficient detail, including the sample size was required to be available in order to determine the basis upon which the curves were derived

2. All curves based upon fitting of a statistical function to data were rejected: the conceptual reason for doing so is that there is no theoretical reason for expecting one functional form over another. The practical reason is that these curves are generally outliers when compared to curves derived in other ways

3. The curve was required to be expressed as a proportion of the value of asset at risk or could be converted to that form

In addition to these requirements, an additional problem existed in that there are very few curves to choose from and most of those were excluded by one of the three considerations given above. The best available data was assessed to be Islam’s (1997) depth-damage curves for Bangladesh as shown in Figure 2.15.

40.0%

30.0%

20.0% h1 h2 h3 h4 average

10.0%

0.0%

0 0.5 1 1.5

Depth of Flooding (m)

2 2.5

31


Figure 2.15: Structural losses in dwellings – Bangladesh (Islam, 1997)

The descriptors h1 to h4 represent different types of housing construction; these are detailed in Table 2.8:

Table 2.8: Descriptors of housing type adopted by Islam (1997) for Bangladesh

Construction h1 h2 h3 h4

Description

Brick floor, brick walls, plaster

Brick floor, cast iron walls on timber frames

Earth floor, cast iron walls on timber, cast iron roof

Earth floor, thatched walls, bamboo walls, thatched roof

The form of Islam’s (1997) curve recommended for application for estimating structural losses in lightweight mixed constructions is shown in Table 2.9.

Table 2.9: Recommended depth-damage curve for estimating structural losses in lightweight, mixed construction dwellings (from Islam, 1997)


0.25 3.4

0.50 5.0

1.00

1.50

2.00

2.50

7.7

10.6

13.4

15.1

Masonry construction

For the third class, the same three determinants of curve selection were applied as in the lightweight mixed construction category:

1.

2.

3.

Sufficient detail available

Rejection of statistical function based curves

Rejection of curves that could not be expressed as proportional losses

Several candidate curves exist for this construction type. Of these, the UK data does not differentiate between constructional forms but appears to assume suspended timber flooring throughout and German data is only available as a graphic (Meyer & Messner,

2005). Although a set of depth-damage curves by Barredo et al. (2008) are cited as being derived in a report by Huinziga, this report is apparently not publically accessible.

Two curves for the Netherlands were additionally available (Yan, 2005) – the curve used by Genovese (2006) for Prague appearing to be identical to one of the Dutch curves.

The Taihu Basin, China curves (Research Institute of Water Economics, 2001) were also considered to represent solid masonry construction with a solid floor.

These curves are overlain in Figure 2.16 where in each case the loss at any given depth is expressed as a proportion of the loss experienced at 3 metres. From this, it can be

32

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities seen that losses at shallow depths are considerably higher for the UK data set than from those obtained in the Netherlands or China. Indeed, the curves for the UK closely approach those for Australia and the USA. Unfortunately, the breakdown for the components of the loss are not available for countries other than the UK and it is consequently not possible to explore whether there is a systematic problem with the UK data or if the data from other countries omits damage categories included in the UK data.

1.0

0.8

0.6

0.4

Rijkswaterstaat

HVK

UK

Taihu Basin, China

Australia

Prague

USA

0.2

0.0

0 0.5 1 1.5 2 2.5 3

Figure 2.16: Comparison of structural losses for type 3 dwellings

The components of structural loss for UK houses are shown in Figure 2.17 to illustrate the significance of different damages.

33


14000

12000

10000

8000

6000

PLUMBING & ELECTRICAL

INTERNAL DECORATIONS

JOINERY

FLOORS

PLASTERWORK

EXT. MAIN BUILDING

GARDENS/FENCES/SHEDS

PATHS & PAVED AREAS

4000

2000

0

-0.3 0 0.05 0.1 0.2 0.3


0.6 0.9 1.2

Figure 2.17: UK average house – components of structural loss (from Penning-Rowsell et al., 2003a, 2003b)

Since the use of the Dutch curves is reported to have over-predicted the losses from the flooding on the Meuse (Lamonthe et al., 2005), the Dutch curve is proposed for use in this class. The values for this curve are supplied in Table 2.10.

Table 2.10: Recommended depth-damage curve for estimating structural losses in masonry dwellings (from Yan, 2005)


0.00 0.0

0.25

0.50

1.0

2.0

1.00

1.50

2.00

2.50

3.00

5.0

8.0

11.0

22.0

35.0

Non-Residential: Structural Losses

For other building uses, there appears to be a greater convergence of built form between countries. There is a general adoption of either steel or concrete framed construction,

34

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities lightweight cladding and concrete floods and roof or mass masonry walls, concrete floors and roof. One driver towards convergence is the adoption of earthquake resistant construction.

Non-domestic buildings are also well-known for the variance in flood losses, so much so that a number of attempts to statistically derive depth-damage curves have concluded that no statistically significant results can be obtained (e.g. Gissing, 2002; Saelthun, nd).

For these reasons, a single depth-damage curve for structural damage to non-domestic buildings has been adopted in this study. The curves recommended here were derived by taking the depth-damage curves for UK non-domestic buildings and deriving a weighted average using data on the total area of each type of property in the UK, as published by DCLG. The result is shown in Figure 2.18.

100%

80%

Retail

Offices

Factories

Warehouses

Average

60%

40%

20%

-1.0 -0.5

0%

0.0 0.5 1.0 1.5


2.0 2.5 3.0

Figure 2.18: Non-domestic structural damages from UK data (Penning-Rowsell et al.,

2003a, 2003b)

Unfortunately, there is insufficient evidence, both in the UK depth-damage data and from other sources, to explain differences between different properties.

The UK curves are derived from sample surveys but it is not clear what the samples were intended to be representative of or whether properties at risk of flooding are a representative sample of buildings of that type for the country as a whole.

The UK data is selected for use here because it has been developed over the last 30 years and continually refined in the face of practice and because both the methodology and detail are well documented. The recommended depth-damage curve for application to structural losses in non-domestic buildings is shown in Table 2.11.

35


Table 2.11: Recommended depth-damage curve for estimating structural losses in nondomestic buildings (from Penning-Rowsell et al., 2003a, 2003b)


-1.00 0.4

-0.75

-0.50

0.6

0.8

-0.25

0.00

0.25

0.50

2.8

4.0

18.3

39.1

1.00

1.50

2.00

2.50

3.00

50.4

59.7

64.6

66.5

68.1

Residential: Contents Losses

For domestic contents, the total value of the contents should be explicable in terms of the coupled relationship between household income and the proportion of which is spent upon food. At low income levels, a high proportion of household income is spent upon food and hence little money is left over to buy those things that might then be damaged or destroyed in a flood. Equally, it might be hypothesised that the essential items purchased when incomes are low are less susceptible to flood damage than the luxury items purchased by those on high incomes. Items owned by those on low incomes are likely to be restricted to cooking equipment and simple furniture; these are less susceptible to damage than items such as radios, televisions and computers or furniture incorporating stuffing or springs. Therefore it may be hypothesised that a flood affecting a poor household will result in proportionately lower losses than one affecting a high income household. This hypothesis is borne out in the UK data (Figure 2.19).

36

AVOID WS2/D1/R14

100%

80%

60%


Social Class AB

Social Class DE

40%

20%

0%

0 0.5 1 1.5


2 2.5

Figure 2.19: Content loss and income effects in domestic buildings; UK Terraced 1919

1944 (from Penning-Rowsell et al., 2003a, 2003b)

Similarly, data for Bangladesh also indicates that contents losses fall as a proportion of total loss in cruder building types which are associated with lower incomes (Islam, 1997).

Differences may also exist in the shape of the proportional depth-damage curve between households. Such differences in the shapes of the proportional depth-damage curves should logically be explicable in terms of differences in:

1. The heights at which items are stored;

2. The average susceptibility to flood damage of those items; and

3. The average height of the population

The latter factor will influence aspects such as the height of worktops; in kitchens, worktop heights might be supposed to create a discontinuity as storage ends at that height and then recommences some height above worktop height. Equally, few items will be located at heights above those which it is convenient to reach.

The original hypothesis was that with increasing income, the proportional depth damage curve should be shifted upwards and to the left, reflecting the higher value of floor coverings in higher income households as shown in Figure 2.20. Some important caveats need to be introduced here though; (1) social class is not solely dependent on income; and (2) all UK depth-damage curves were derived in the same way, hence similarities in the shape of the curves between different household groups may be a methodological artefact rather than necessarily showing a true similarity.

37


35000

30000

25000

20000

15000

10000

5000

0

0

Social Class AB

Social Class C1

Social Class C2

Social Class DE

0.5 1 1.5 depth

Depth of flooding (m)

2 2.5

Figure 2.20: Dwellings: content losses and income effects

Despite the possibility it may be a methodological artefact, the kink shown on Figure 2.20 has face plausibility in that it is inconvenient to reach down to floor level and so storage often is found to start some height above floor level. In addition, the Australian depthdamage curves (Dale, 2009), which are also judged to be of high quality, show a similar kink. This question could be explored by an analysis of the vertical distribution of the value of inventory items but has not been undertaken to my knowledge.

For the contents of dwellings, there are a number of considerations. Although, there is logic in adopting a different income dependent curve for different income countries, again there is a limited range of data sets which are of appropriate standard. The available datasets are compared in Figure 2.21 in which the results of each are standardised to a value of 1.0 at a depth of 3 metres in order that the shapes of the different curves can be compared.

38


1.0

0.8

0.6

0.4

0.2

USA

Japan

Japan (Dutta, pers. comm.)

Australia

Taihu Basin, China

Germany (Knogge, pers. comm.)

Germany (Knogge, pers. comm.)

Rijkswaterstaat

HKV

-0.5

0.0

0 0.5 1 1.5 2


2.5 3

Figure 2.21: Dwellings: contents loss, comparative proportional curves normalised against loss at 3 m depth

It can be seen that both statistical fit curves that Knogge (pers. comm.) derived from

Germany data are below the other curves whilst the two curves from the Netherlands

(Yan, 2005) lie well above the other curves. Those curves from the Netherlands are also reported to have seriously over-predicted losses in the Meuse flood (Lamonthe et al.,

2005).

Islam’s data for Bangladesh supports the case for adopting a loss function which is income dependent: with higher proportional losses for those with lower incomes. But there is insufficient data with which to apply this approach globally. As such, it was decided to utilise the UK values shown in Table 2.12.

Table 2.12: Recommended depth-damage curve for estimating contents losses in domestic buildings (from Penning-Rowsell et al., 2003a, 2003b)


0.00 0

0.25

0.50

1.50

2.50

31

34

38

38

Non-Residential: Contents Losses

For non-domestic buildings, the proportions of net fixed assets which comprise the contents of the buildings is surprisingly low as shown previously in Figures 2.4a to 2.4g.

39


The depth-damage curve for contents losses in non-residential buildings was constructed in the same way as that for structural losses in non-residential buildings through the use of a weighted average as discussed earlier. That the curve for offices shown in Figure

2.22 flattens out is not surprising given that office work is conducted sitting down and fixtures and equipment are consequently located for convenience when sitting. What might be considered more carefully is whether the height at which the curve flattens out is lower than might have been expected. Given the increasing reliance upon multistacked warehouses, the linear curve for warehousing is reasonable.

100%

80%

60%

40%

20%

Weighted loss

Shops

Offices

Factories

Warehouses

-1.0

0%

0.0 1.0


2.0 3.0

Figure 2.22: UK non-domestic contents losses (Penning-Rowsell et al., 2003a, 2003b)

The form of the recommended curve to be applied for estimating contents losses from flooding in non-domestic buildings is shown in Table 2.13.

Table 2.13: Recommended depth-damage curve for estimating contents losses in nondomestic buildings

40



-1.00 0.3

-0.75

-0.50

0.4

0.4

-0.25

0.00

0.25

0.5

0.6

17.0

0.50

1.00

1.50

2.00

2.50

3.00

37.4

55.0

63.2

68.9

73.3

76.8

2.4 Cross Validation

As a means of testing the adequacy of these models, the results can be compared to actual losses experienced in recent coastal flood events. This is a cross-validation exercise; significant differences between values may mean a problem with either the recorded losses in the actual event or with the method of predicting flood losses.

In practice, extreme coastal flood events are a consequence of a storm surge which is the product of a deep depression and commonly accompanied by high velocity winds and heavy rain. The actual losses estimated to have been produced by an event are thus the sum of the losses produced by wind and flooding; the benefits of flood alleviation works would only be the reduction in flood losses. The consequence of flood alleviation may logically be an apparent increase in wind losses as explained below: the usual sequence during an extreme event is wind damage followed by flood damage so that properties which were first damaged by wind but then flooded (therefore experiencing much greater damage) will currently have all damage ascribed to flooding. If in the future those properties are only subject to wind damage, it will appear that wind damages have increased whilst flood damages have fallen.

In the estimation of the event losses, in some cases financial rather than economic losses will have been estimated. Additionally, the actual events are not uniform in terms of return period or surge height. Table 2.14 gives the results for some events; the criteria for selecting the events to be included were:

•

Coastal events only so that wind effects were included

•

An extreme event

•

Reasonably well documented estimate of losses and population affected

•

Adequate information on regional GDP/capita

Event

Table 2.14: Historical losses from natural disasters

Loss N o

. people GDP/capita Loss/(GDP/capita)

41


Katrina

Hypothetical: St

Petersburg,

Russia

Guyana 2005 flood (ECLAC,

2003)

Venezuela;

Vargas alluvial fan flooding 1999

20 billion US

(USACE, 2006)

4 billion

US$2002

(EBRD) affected

454,865

4.6 million

US$ 368 million 275,000

Estimated at

US$ 1.79 billion 300,000

$33,852 (1998)

145,503.3 rubles

US$ 5006

1.3

0.17

US$1116

US$3670

1.2

3.2

All of these estimates are based upon data of varying qualities; estimates of the number of people affected are particularly open to interpretation. Similarly, widely differing loss estimates were found for some of these events; for example, the BBC web site gives a loss of US$15 billion for the Venezuelan alluvial fan flooding as opposed to the US$1.79 billion figure used here and taken from the USGS (Wieczorek et al., 2001) report on the event.

Nevertheless, it proved difficult to find an event where the ratio of losses to GDP per capita exceeded 1. The mudflows in Vargas largely wiped the land clear of buildings – only 1000 bodies of the estimated 30,000 dead were recovered - and so it represents as near complete loss as it is possible to conceive. The ratio of loss to GDP per capita recommended in this methodology therefore appears appropriate. However, in small island states, much higher loss ratios have been reported such as in Montserrat and St.

Lucia (Charveriat, 2000).

2.5 Limitations

The non-availability of data for application to logical arguments was one major limitation of this study. Although given datasets were often known to patchily exist in a small number of countries, it is unfeasible to generalise from these local trends to global ones.

Also, despite the fact that trends may exist between, for example, net fixed assets and the rate of net fixed asset formation, it is very difficult to establish exactly how to utilise this relationship. The standard of given datasets was an additional limitation on this study with some sub-standard datasets available.

The resolution of some datasets may also cause limitations for use in estimating the value of losses from flooding; data which is only available at coarse resolution has the capacity to obscure underlying trends. This may present a particular problem in estimating losses from coastal flooding as coastal areas frequently have comparatively higher GDP/capita.

One type of information that would be particularly useful for future studies is the estimated value of assets in a greater number of countries to allow estimation of the value of assets at risk. Currently this information is restricted to approximately six countries. Furthermore, it would also be useful to know the proportion of fixed assets that can be attributed to different categories in a greater variety of countries. The present study makes use of data from the USA as this is the most detailed breakdown. However, it is not possible to say how applicable the US breakdown is globally.

The information relating to the average number of storeys in urban areas would be particularly useful for estimating exposure to flooding. Such data is again, only patchily available and it is not possible to generalise these trends. As a result of this lack of data, conservative estimates of exposure have instead been recommended.

42


With regards to estimating the susceptibility of structures to flood damage, a number of generalisations had to be made. Although a diversity of domestic structure types exists in reality, this was simplified to three classes based on geographical location and the national economy. These generalisations were necessary in order to simplify the problem and should not significantly compromise the standard of results.

Appropriate depth-damage curves for the structure types were selected from a range of options. Curve selection was based on the availability of information regarding the derivation of the curves, the ability to express losses proportionally and the performance of curves in previous studies; statistical function based curves were rejected. These curves are assumed to be representative of the proportional damage caused to the classes of structures defined.

The typically more diffuse distribution and greater numbers of consequential losses means that their estimation is particularly problematic. Therefore, despite their potential importance, the complex nature of their estimation has meant that they have not been able to be evaluated in this study. Further discussion on the issue is available in

Appendix III.

2.6 Future Research

As numerous assumptions have had to be made in order to derive a methodology for estimating flood losses globally, future research may wish to focus on testing these assumptions and may also wish to focus on how these assumptions are likely to change in the future.

Future research may wish to focus on determining a methodology for establishing the value of assets within given countries. This study was unable to determine a relationship between asset formation and the total value of assets within countries; large differences between the proportions of GDP invested in fixed asset formation and variations over time in this rate were very noticeable. However, it is unclear whether more detailed statistical analysis might reveal standard rates that might be applied to identifiable groups of countries thus providing a more reliable methodology for estimating the value of assets within countries.

It would also be interesting to investigate how the recommended ratios of net fixed assets to GDP of 3:1 and 1:1 in developed and developing countries is likely to change in future. Additionally, it will also be necessary to address the point of when an economy can be considered develop ed rather than develop ing – this is especially important considering the emerging economy of China.

Research may also wish to focus on determining the exposure of assets to flooding. In this study a conservative estimate of 50% of assets to be considered at risk of flooding is used although this is expected to significantly over-estimate assets at risk in areas where buildings are typically high rise. An insufficient sample of studies on building footprint to floor area currently exists. As such, it is not possible to generalise existing findings with any confidence. Further studies into the trends in the number of storeys in buildings in urban areas will aid future assessment of vulnerability to flooding.

This research has focused on producing a method applicable on a global scale. In order to obtain more accurate loss estimates on smaller scales, more focussed studies will be required over smaller geographic areas. A number of localised depth-damage curves exist as shown in Appendix IV and work is also currently underway to produce regionalised depth-damage curves for Europe under the CLIMSAVE project.

43


Finally, it was not possible to derive estimates of consequential losses in this investigation since neither the appropriate models nor the data with which to calibrate those models are available. However, this type of loss is still expected to be significant.

Attempts to quantify these losses would be highly valuable and should be investigated in detail in future.

2.7 Summary

The physical losses from a flood can be no more than the value of the assets exposed to the risk. The net capital assets of a country have been found to vary in a range of between 1 and 4 times the GDP of that country and in this study the following ratios of

Net Fixed Assets to GDP are recommended:

•

A ratio of 3:1 for developed economies

•

A ratio of 1:1 for other economies

It is possible to argue for lower ratios in low income economies but there is a lack of data to develop more than the above approximation. This is lower than widely used in the insurance industry where a ratio of 5:1 is the norm (Nicholls et al., 2008).

In turn, only a proportion of those assets are exposed to flooding. In densely populated urban areas, a significant proportion of buildings are multi-storey and hence a large part of the assets are above any conceivable flood level. Due to a lack of information relating to the average number of storeys in urban areas globally, a conservative estimate which considers 50% of assets to be at risk of flooding is suggested here as appropriate for an indicative analysis. It is perhaps important to note that these ratios are intended to be right on average but will be to varying degrees wrong in specific cases.

Taken together, these two approximations mean that, on average, maximum physical losses will be between 0.5 and 1.5 times the area’s GDP. For physical losses, this is considered to be an upper bound.

As to the breakdown of those assets into different categories, the best approximation that could be derived from available data was to adopt the breakdown in the USA as follows:

Table 2.15: USA proportional value of assets as a percentage of total fixed asset value

Asset type

Non-domestic buildings and structures

Residential buildings

Equipment

Proportional Value

42

36

14

44


Domestic durables 9

The actual loss is then a function of the susceptibility of the assets, expressed through depth-damage curves multiplied by the values at risk. Hence, the final step is to apply a series of depth-damage curves, expressing the loss as a proportion of the value of asset at risk. Different depth-damage curves for dwellings and for other types of building are proposed. This study recommends the use of three different curves in different parts of the world in order to reflect differences in dominant building technologies in those countries. The details of the depth-damage curves to be utilised are shown at the end of each of the corresponding sections on susceptibility to flood damage.

Due to the highly complex nature of estimating consequential losses, it was not possible to derive a methodology for evaluating their cost.

A discussion on the likely future of flood losses is included in Appendix V.

The methodologies presented in this study should be applicable for estimating the value of losses from coastal flooding in both domestic and non-domestic structures globally.

They are presented as summary flow diagrams in Figures 2.23 and 2.24 and should be applicable worldwide in order to estimate coastal flood losses. These results will also be indicative.

45


Sensitivity

Analysis

Figure 2.23: Summary of the methodology recommended for estimation of losses from coastal flooding for domestic structures

46


Sensitivity

Analysis

Figure 2.24: Summary of the methodology recommended for estimation of losses from coastal flooding for non- domestic structures

47


3.0 COSTS OF ADAPTATION

3.1 Background

While the costs of individual coastal defence projects are usually well known to the sponsors, this information is usually lost after project completion and there is surprisingly little systematic cost information available at national scales.

By investigating the costs of adaptation it will be possible to improve our understanding of how costs of protection vary globally. This will help us understand how existing defences may change under scenarios of climate and socio-economic change in the future.

Dikes and other related coastal defence measures have previously been costed at a global scale by IPCC CZMS (1990) and Hoozemans et al. (1993). The two studies used similar methodologies to obtain cost estimates although the studies did consider some different measures to combat SLR.

3.1.1 IPCC CZMS (1990)

The study by IPCC CZMS (1990) produced global cost estimates for construction works to offset a 1 m SLR. To accomplish this, a number of systematic and pragmatic assumptions were made. The defence measures considered were sea dikes, raising sea dikes, closure dams, beach nourishment, port upgrade and island elevation.

The study made detailed definitions of these measures including specification of structural dimensions, materials and construction methods. Following this, ‘all in’ unit costs could be calculated based on Dutch experience. All in costs accounted for design, execution, taxes, levies and fees and were produced using experience obtained during construction projects worldwide. A summary of these costs is shown in Table 3.1 in both 1989 and 2009 USD.

Table 3.1: Summary of Dutch ‘all in’ unit costs from IPCC CZMS (1990)

Adaptation Measure

1 m high sea dike

1 m high sea dike with regular maintenance

Raising low sea dikes by 1 m in rural areas

Raising high sea dikes by 1 m in rural areas

Raising sea dikes by 1 m in urban areas

Closure dams

Beach nourishment

Raising industrial areas and harbours by 1 m

Island elevation by 1 m

Unit Cost (1989US$)

0.4 million per km

0.6 million per km

0.5 million per km

1 million per km

10 million per km

15 – 25 million per km

3 – 6 per cubic metre

15 million per km 2

12.5 million per km

2

Unit Cost (2009 US$)

0.56 million per km

0.84 million per km

0.70 million per km

1.40 million per km

14.04 million per km

21.07 – 35.11 million per km

4.21 – 8.43 per cubic metre



48


To obtain global cost estimates, a multiplier known as a ‘country factor’ was employed to translate Dutch costs into equivalent costs elsewhere. The country factor for the Netherlands is 1.0 with all other countries greater than or equal to this factor. Country factors accounted for the following:

•

Presence of a ‘wet’ civil construction industry

•

Availability and cost of human resources

•

Availability and quality of construction material

•

Possibility for mobilisation of foreign equipment

•

Possible effects of project scale

•

Land acquisition costs

•

Local market situation.

To determine worldwide costs of adapting to a 1 m rise in sea level, the length of coastline to be protected was estimated and appropriate defences were selected.

The coastal length to be protected was then multiplied by the unit cost of defence measures. The calculations led to an overall global cost estimate for basic coastal protection against 1 m SLR of nearly US$ 500 billion (prices at 1989 levels) over a

100 year period.

3.1.2 Hoozemans et al. (1993)

Hoozemans et al. (1993) built on the results of IPCC CZMS (1990) by improving estimates of dike costs. Rather than adopting a fixed increase in coastal defence heights as performed by IPCC CZMS (1990), Hoozemans et al. (1993) assume defences will have to be raised by a factor twice that of SLR to account for changes in hydraulic conditions such as wave run up.

Again, standard measures were defined, this time for sea dikes and sand dune construction. These definitions again stated specific dimensions and construction materials and were assigned all in costs according to Dutch practice. These unit costs are summarized in Table 3.2. Again, costs were multiplied up using country factors based on the same criteria as IPCC CZMS (1990). The coastline length to be protected as suggested by IPCC CZMS (1990) is also used.

Table 3.2: Summary of Dutch ‘all in’ unit costs from Hoozemans et al. (1993)

Adaptation Measure

Stone protected sea dike

Clay covered sea dike

Sand dune

Unit Cost (1991US$)


2.5 million per km

4.5 million per km

Unit Cost (2009 US$)


3.37 million per km

6.07 million per km

The results of the study can be considered an update to the work of IPCC CZMS

(1990) and show a marked increase in the costs of adapting to SLR; Hoozemans et al. (1993) suggest a value of US$ 1000 billion (at 1990 levels), roughly twice the value suggested by IPCC CZMS (1990); an increase solely due to the better description of dike heights.

3.1.3 The Present Study

Despite being produced over 15 years ago, unit cost estimates presented by

Hoozemans et al. (1993) are still the main source of unit cost data used in global vulnerability assessments such as FUND (Tol, 1997), DIVA (Hinkel, 2005; Vafeidis et

49

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities al., 2008) and Sugiyama et al. (2008). The present study aims to critically evaluate these cost estimates and their inherent assumptions. It is intended that the estimates will be updated according to recent costs and in line with current engineering practice.

It is important to have an accurate source of unit costs for coastal defences since the protection of cities is expected to be a major cost of accelerated SLR (Turner et al.,

1990). By producing accurate cost estimates for protective measures it will be possible to improve estimates of the global costs of adaptation.

The main responses to coastal flooding which will be considered in this study are sea dikes and beach nourishment, as undertaken by IPCC CZMS (1990) and

Hoozemans et al. (1993) but also vertical seawalls. Dikes and nourishment are popular responses to coastal flooding and erosion worldwide and their inclusion in this study provides a direct comparison with both previous costing studies. Vertical seawalls have been included here based on the apparent popularity of the approach worldwide and because unit cost estimates are comparatively plentiful. Other approaches are considered in minor detail if sufficient evidence exists to suggest their importance.

Unit costs are to be used so they can be easily translated into total costs for the protection of given areas. Future studies are likely to have better resources to produce good estimates of the length of coastline that requires protection

(Hoozemans et al., 1993) and thus produce estimates of the cost of adaptation.

This study aims to improve on the methodology of both IPCC CZMS (1990) and

Hoozemans et al. (1993) by considering actual unit costs for coastal defence measures as opposed to adopting the Dutch worldview advocated by previous studies. By recording actual costs it will be possible to remove the assumptions of country factors. Additionally, the consideration of associated uncertainties in cost estimates will allow the findings of previous studies to be improved.

As far as possible, this study also aims to consider the varying approaches to coastal adaptation made worldwide. One of the shortcomings of the IPCC CZMS (1990) and

Hoozemans et al. (1993) reports is that Dutch solutions to coastal engineering problems are imposed globally – no consideration is given to local solutions utilising local knowledge.

3.2 Methodology

3.2.1 Data Acquisition

Costs of defences were assessed in numerous ways reflecting that there are no public databases available on the topic and that information exists in unpublished reports, databases and with experienced engineers. Sources utilised are as follows:

Communication with government and national agencies. In many cases, appropriate organisations were identified through extensive internet searches and leads from other publications. An email survey was then sent to the appropriate department (a copy of this survey can be found in Appendix VI). Questions aimed to determine if estimates of unit costs were available, the number of different defences it would be appropriate to cost in the context of a given country and ideas on how best to capture these costs. In addition, organisations were requested to comment on national agreement with Hoozemans et al.’s (1993) assumption that defences would have to

50

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities be raised by a factor twice that of SLR to account for changing hydraulic conditions.

Qualitative and quantitative responses were recorded in a computerised database.

A large portion of the organisations contacted were unable to offer sufficiently detailed information. In a small number of cases however, publications comprehensively outlining national unit costs for coastal defences were available

(such as those held by the Environment Agency, UK and the Ministry for Ecology,

Energy, Sustainable Development and the Sea, France). These documents are not publicly available and are supplied only upon request. In a number of other cases, sources describing unit costs for a small subset of defences were identified by these organisations.

Personal and professional contacts were used extensively as a potential source of unit cost information. Professionals from numerous backgrounds including academic institutions, engineering consultancies and local, regional and national government were contacted. These contacts were also sent a copy of the email survey and responses were recorded.

Further information was gleaned by holding meetings with representatives from experienced international coastal engineering consultancies, HR Wallingford and TU

Delft. These workshops facilitated in depth discussion of the research objectives, potential sources of information and scrutiny of the methodology used. Colleagues at

TU Delft produced Appendices I and II (Hillen et al., 2010; Geldenhuys, 2010) containing further unit cost information. These meetings also produced additional contacts who were again, sent copies of the email survey.

Academic journals were utilised extensively as a source of information on unit costs.

By searching appropriate journals a number of valuable articles were found. Where possible and appropriate, the authors of such articles were contacted via email to gain further information.

Finally, extensive internet searches played an important role in identifying appropriate data sources and additional contacts. Such data sources included local, regional and national government reports and reputable websites. A small number of anecdotal data sources were also identified which included online news articles, although the reliability of such sources is more questionable.

3.2.2 Normalisation of Costs

In order to make unit cost estimates comparable between countries, it was necessary to normalise them by converting to 2009 US dollars (USD).

Costs were first converted to USD for the reference year using historic exchange rates. In many cases, the reference year for cost data was explicitly stated. Where this was not the case costs are assumed to be relative to the year in which the document was published. Due to the variability of exchange rates on a day to day basis, currencies were converted according to the historic exchange rate on July 1 st of the reference year unless a more accurate date was available. July 1 chosen as a mid-point in the year and to maintain consistency in conversions. st was

Costs were then converted to 2009 USD using the construction Producer Price Index

(PPI). Where only cost reference years were available, costs were converted to

2009 USD using the annual PPI value for the reference year. Where more exact information regarding the cost reference period was available, monthly PPI values were used.

51


3.3 Results

3.3.1 Critical Evaluation of Previous Costing Studies

One of the largest shortcomings of both IPCC CZMS (1990) and Hoozemans et al.

(1993) is the limited range of response options considered. These options are based on Dutch experience which fails to account for the full range of options available worldwide. Extensive research has highlighted the importance of coastal adaptation measures not considered by either IPCC CZMS (1990) or Hoozemans et al. (1993).

The decision to cost only a limited number of defences is understandable given that costing all measures would be incredibly time consuming. However, a number of seemingly important measures have been neglected. Chief among these is the vertical seawall, extensively used worldwide as a coastal defence measure although presumably ignored by IPCC CZMS (1990) and Hoozemans et al. (1993) due to a lack of application in the Netherlands. Elsewhere, revetments, surge barriers and offshore structures such as breakwaters are popular measures but are neglected by these studies.

In addition to structural measures, a diversity of non-structural options exist for mitigating coastal flooding. These measures include provision of flood shelters, flood proofing measures, storm tide warning services and the implementation of appropriate building regulations. No such measures are considered by IPCC CZMS

(1990) or Hoozemans et al. (1993). Table 3.3 highlights the measures of greatest importance not considered by these previous studies.

Table 3.3: Coastal adaptation measures which are important globally in addition to those costed by IPCC CZMS (1990) and Hoozemans et al. (1993)

Measures are listed roughly in order of importance

Adaptation Measures

Vertical Seawalls

Revetments

Planning Regulations

Surge Barriers

8

Groynes

Breakwaters

Storm Warning Services

Storm Shelters

Minimum Reclamation Levels

Flood Proofing

Source: Research into coastal defences applied in the 136 port cities

Further information is available in Section 4

Many of the coastal adaptation options available are complimentary and in many cases are employed simultaneously; for example, embankments, seawalls, a surge barrier and storm warning system are all employed as part of the city of London’s

8

IPCC CZMS (1990) do consider closure dams which can be similar in nature to surge barriers.

52

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities response to coastal flood risk. Elsewhere, hard protection is frequently employed alongside soft measures such as planning regulations and flood proofing measures.

However, other measures are in direct competition and cannot be simultaneously employed; such measures include vertical seawalls, dikes and revetments which cannot all be employed at the same location concurrently. It is common however, to see such competing measures employed simultaneously at different locations within a given city.

Upon evaluating the dike costing methodology utilised by both IPCC CZMS (1990) and Hoozemans et al. (1993), it is clear that both studies failed to account for the presence of dike drainage measures. Drainage is an important feature of any dike system which lowers the phreatic water level of the dike, thus increasing stability of the landward slope by ensuring water is no longer able to escape from the dike

(Pilarczyk, 1998). This has the effect of minimising piping and thus, risk of failure.

Drainage is a necessary dike feature and its non-inclusion will have caused underestimation of the costs of employing dikes. Inclusion of drainage will raise unit costs by increasing the necessary land-take and materials and by increasing construction requirements.

Finally, Hoozemans et al. (1993) assumed that structures would have to be raised by twice SLR to account for hydraulic conditions. This assumption is investigated in more detail in Sections 3.3.2 and 3.3.3 but recent studies have indicated that other aspects of structure design in addition to crest height will also need to be changed with SLR (Burgess & Townend, 2004). It remains difficult to determine how this will affect cost estimates.

3.3.2 Coastal Defence Unit Costs

The costs of relevant adaptation measures for 17 of the 76 countries studied during the course of this research are presented in Table 3.4. The original data can be found in the accompanying Excel database which can be accessed via the AVOID

Stakeholders website ( www.avoid.uk.net/private2/ ). A summary of the contents of this database can be found in Appendix VII.

During the course of this study it was found that there is a considerable lack of information relating to unit costs of coastal defences in the majority of the countries studied.

As can be seen, unit costs for beach nourishment and vertical seawalls are among the most accessible information. Despite being considered by both IPCC CZMS

(1990) and Hoozemans et al. (1993) as a fundamental defence type, information on the costs of dikes globally is especially deficient. In some cases, costs of other measures deemed important on a national scale are available; reclamation fill appears to be important in south-east Asia with both Hong Kong and Singapore having enforced minimum reclamation levels for coastal areas. Appendix VIII contains further information on nationally important defence types which were not considered by IPCC CZMS (1990) or Hoozemans et al. (1993).

53


Table 3.4: Unit costs of coastal defence measures normalised to 2009 US Dollars

Country and locality if appropriate

AUSTRALIA

Adelaide

Vertical Seawall (per km) Millions USD

Construction

1.9

Reconstruction

0.9

EGYPT

Alexandria

FRANCE

National

(Tucker et al., 2005)

4.1

(Tetratech,1986)

655 – 1030 9

(per m 2 of surface area)

(Igigabel, 2002)

GERMANY

National

GREECE

National

2.9 – 4.2

(Koutitas, pers. comm.,

2010)

Block work

22.4

HONG KONG

National

Upgrade by 1 m height

0.26

(Yim, 1995)

ITALY

National

MALAYSIA

National

Dike (per km)

Millions USD

Unit Cost (2009 USD)

Beach Nourishment (per cubic metre material)

6.4


5.6 – 8.4

(Igigabel, 2002)

6.0 – 11.0

(Dette, pers. comm., 2009) n/a

6.1 – 8.5

(Lupino et al., 2005)

Other Measures

Marine Fill Reclamation

3.9/m 2

Land Fill Reclamation

6.4/m 2

(Yim, 1995)

Reclamation Fill

3.0 – 5.0/m 3

(Reinen-Hamill, pers. comm., 2010)

9

Costs presented in dollars not millions due to format of cost which is presented as cost per square metre of surface area of structure

This cost suggests a 2 m high seawall would cost in the range of US$1.31 to 2.06 million – comparable with cost estimates elsewhere

54



MOZAMBIQUE

Maputo

THE NETHERLANDS

National

NEW ZEALAND

National

SINGAPORE

National


0.4 – 2.9

(Reinen-Hamill, pers. comm., 2010; Cartwright et al., 2008)

0.4 – 7.7

(Chou & Lim, 1991)

Dike (per km)

Millions USD

Concrete

1.0

(McGeown & Hirst, 2009)

Dike heightening (per m)

12.2 – 14.6 (rural)

(Kok et al., 2008)

5.4 – 14.9 (rural)

(Eijgenraam, 2006)

9.3 (rural)

(Arcadis & Fugro, 2006)

24.3 – 29.2 (urban)

(Kok et al. 2008)

18.6 (urban)




3.0 – 9.0

(Stive, pers. comm., 2009)

4.1

(Kok et al., 2008)

3.8


5.0 Foreshore Nourishment

(RWS, 2009)

10.2 Beach Nourishment

(RWS, 2009)

8.8 – 73.3


SOUTH AFRICA

National

0.4 – 3.8

(Cartwright et al., 2008)

0.4 – 5.3

(Geldenhuys, 2010)

14.3

(Mather, pers. comm., 2010)

Other Measures

Storm Surge Barrier

0.7 – 3.4 million per km unit width

(Hillen et al., 2010)

Maintenance

0.14 million per km length of flood defence per year

(AFPM, 2006)

Reclamation Fill

3.0 – 5.0/m 3


Groynes

115/m

(Cartwright et al., 2008)

Managed Retreat

10

242 – 393/m 2

(Geldenhuys, 2010)

SPAIN

National

5.1 – 10.1

(Sanchez-Arcilla, pers. comm., 2006)

10

This value only includes the weighted average cost of property lost; the real cost will be higher and include compensation for property owners

55


Country and locality

UK if appropriate

National

USA

New Orleans


Earth

1.0

Dike (per km)

Millions USD

0.7 – 6.4

(Environment Agency,

2007)

Protected

5.1

(Evans et al., 2004)

Concrete Floodwall

5.0 – 6.1 per m floodwall height

(Bos, 2008)


6.8 – 10.8

(Dijkman, 2007; Jonkman et al., 2009)


Beach Nourishment (per cubic

4.6 – 46.4 metre material)

(CIRIA, 1996)

Other Measures

Revetments


Revetment & Wall


Dune Construction


(Environment Agency, 2007)

Storm Surge Barrier

0.7 – 3.4 million per km unit width

(Hillen et al., 2010)

Marshland Stabilisation

1.9/m 2

(Dijkman, 2007)

Marshland Creation

4.1/m 2

(Dijkman, 2007)

Freshwater Diversion/Culvert

13.5

(Dijkman, 2007)

Marshland Stabilisation Maintenance

0.09 per m 2 per year

(Dijkman, 2007)

Closure Dam

5.0 million per km per metre height

(in water)

(Dijkman, 2007)

Levee Armouring

19.6 – 26.5/m 2

11

(Devlin, pers. comm., 2010)

11

Although these costs include labour, plant and materials, they are not believed to accurately the difficult site working conditions. Consequently costs are likely to be higher

56



USA

California

VIETNAM

Northern Provinces


4.4 – 27.5

(Heburger et al., 2009)

Dike (per km)

Millions USD

New

2.5 – 7.6

Upgrade

0.8 – 3.7

(Heburger et al., 2009)


0.9 – 1.6

(Hillen, 2008)

1.0

(Mai et al., 2008)



7.9 – 15.7

(Clausner, pers. comm., 2009; Kraus, pers. comm., 2009)

Other Measures

Maintenance

0.03 million per km dike per year

(Hillen, 2008)

0.04 million per km dike per year

(Mai et al., 2008)

57


Where possible, figures in Table 3.4 are presented as ranges to represent the likely maximum and minimum unit costs for a given country. The aim is to represent uncertainty associated with costs occurring as a result of differences in wave exposure, water depth, and proximity to raw construction materials among other factors.

Limitations exist within these results however;

•

Defences with both height and length attributes (such as seawalls and dikes) must be interpreted carefully since the majority of results shown in Table 3.4 are a factor only of length; the effect of height on unit costs is regularly neglected in data sources.

•

The degree to which additional costs such as overheads have been included in costs is largely unknown. The inclusions in the UK dataset (Environment

Agency, 2007) are explicitly stated although the breakdown in other countries is not available.

Despite these limitations, it is hoped these cost estimates will provide a good order of magnitude approximation of defence costs.

It is possible to compare actual estimates of the unit costs of beach nourishment against the estimates of IPCC CZMS (1990) for ten countries. IPCC CZMS (1990) estimates are obtained by scaling Dutch costs using country factors followed by normalisation to 2009 price levels. Actual estimates were obtained by review of reports, personal communications and by examination of the costs of previous projects, also normalised to

2009 levels. The comparison of costs predicted by IPCC CZMS (1990) and actual unit costs is shown in Figure 3.1.

58


40

20

80

60

1

2

Range of costs

1:1 relationship

Average Cost

0

0 5 10 15

Nourishment Costs Estimated by IPCC CZMS (1990)

2009 USD/cubic m

20

Figure 3.1: Comparison of nourishment costs estimated by IPCC CZMS (1990) and known nourishment costs

Numbers 1 and 2 indicate UK and New Zealand costs respectively

Through extensive research, actual nourishment costs have been shown to vary from

US$3.0 to US$73 per cubic metre of nourishment. The variation in costs between countries and indeed, projects is a result of a number of factors which include:

59


•

Project size and consequent economies of scale

•

Bathymetry of borrow area and site – determinant of dredger size

•

Distance between dredge and target sites

•

Recharge material – coarser material causes greater equipment wear and tear which is likely to be passed on to customers

•

Estimated material losses

•

Availability (and size) of dredgers

•

Degree of site exposure – determinant of type of dredger to be used

•

Third party requirements

Box 3.1: Factors affecting nourishment costs (CIRIA, 1996)

The most important factors contributing toward nourishment costs are the sailing time – influenced by the distance between dredge site and target, the size and volume of the dredger used – which influences the number of cycles required to complete a nourishment and can also affect the method of pumping sand onshore and finally, the type of nourishment material (Burgmans, pers. comm., 2010).

It has been noted in the Netherlands that the costs of nourishment have increased rapidly in recent years; the costs of both foreshore and beach nourishments in the

Netherlands have increased almost three-fold in the past six years (Hillen et al., 2010).

This has been attributed to the limited number of large contractors available, international market prices and the large increase in demand for nourishment projects

(Hillen et al., 2010).

With the exception of two points (marked 1 and 2), estimated and actual costs show good agreement, therefore indicating that the methodology and considerations of IPCC

CZMS (1990) are acceptable when scaled to present day price levels.

Outlying point 1 corresponds to data from the UK where recorded nourishment costs range in value from US$4.6 to 46.4/m

US$9.27/m 3

3 compared to a maximum estimated cost of

(IPCC CZMS, 1990). UK nourishment is likely to be more costly because it comprises a large portion of shingle nourishment, whereas the estimates of IPCC CZMS

(1990) only consider sand nourishment. Shingle nourishment is typically more costly than sand due to equipment wear and tear and because dredgers are forced to carry reduced loads because of the increased density and volume of shingle compared to sand (Burgmans, pers. comm., 2010). To complete a project dredgers are therefore forced to perform more cycles with consequent increases in cost. Additionally, the typically large tidal ranges in the UK mean beach nourishment activities are also constrained by tide – this has the capacity to increase project timescales and therefore costs (Burgmans, pers. comm., 2010).

Point 2 can be attributed to the scarcity of dredge sites in New Zealand. As a result, where there are no readily available sources of sand, beach managers are forced to pay the same rate as for construction sand. However, where dredged sand is available,

60

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities typical unit costs (US$8.80/m

(1990) (US$8.40/m 3 ).

3 ) are comparable with those estimated by IPCC CZMS

When these explanations are considered, it is likely that sand nourishment in all of the countries studied is not wildly dissimilar from those estimates of IPCC CZMS (1990) and suggests that the methodology used is applicable today.

To improve the methodology of IPCC CZMS (1990), nourishment country factors should perhaps attempt to account more comprehensively for those factors outlined in Box 3.1.

The DIVA model also estimates the costs and volumes of beach nourishment required into the future. The tool estimates the costs and volumes of nourishment based on a mathematical formula. The decision to nourish is based on cost-benefit analysis which accounts for factors such as the value of the beach for tourism and topographic characteristics of the area at risk. Costs and volumes of nourishment are also heavily based on the Bruun rule factor which accounts for the proportion of the coastline which is erodible (Vafeidis et al., 2008). Greater erodibility leads to lower unit costs as fill material is assumed to be plentiful. However, with greater erodibility, larger volumes of fill are necessary. Based on these factors DIVA produces values for the cost and volume of beach fill required for over 12,000 coastal segments.

DIVA provides outputs at five year intervals and here, national beach nourishment costs and volumes are presented for the year 2010. Costs are normalised to 2010 US dollars in Table 3.5.

Table 3.5: DIVA estimated national nourishment costs and volumes for 2010

Country

Australia

France

Germany

Italy

Netherlands

New Zealand

South Africa

Spain

UK

USA

Total Annual Cost

(2010 US$ millions)

118.12

46.79

36.09

21.44

47.27

7.36

8.24

8.87

42.89

361.76

Total Annual Volume

(millions m

3

)

28.87

7.61

4.41

3.24

9.20

0.99

1.16

1.09

7.97

59.07

Unit cost

($/m

3

)

4.09

6.15

8.18

6.63

5.13

7.40

7.09

7.24

5.38

6.12

In Figure 3.2 the costs from DIVA are contrasted with actual unit costs of nourishment taken from Table 3.4 and scaled to 2010 values. It can be seen again that with the exceptions of New Zealand and the UK, costs are in reasonable agreement with the estimates from DIVA.

61


70

60

50

40

30

20

10

0

0

Cost including upper and lower limits m = 1

2 4 6

DIVA nourishment cost

(2010 US$/m

3

)

8 10

Figure 3.2: Comparison of actual nourishment costs with those estimated by DIVA

The reported unit costs for raising sea dikes are compared against the estimates of

IPCC CZMS (1990) in Figure 3.3. It was possible to compare the costs of both urban and rural dike heightening using the values found.

62


30

25

20

Netherlands (urban)

15

10

Netherlands (rural)

New Orleans, USA

5

0

0

Vietnam (Rural)

5 10 15 20

Cost of raising sea dikes by 1 m ($M/km)

(IPCC CZMS, 1990)

25 30

Figure 3.3: Comparison of the actual costs of raising sea dikes with those estimated by

IPCC CZMS (1990)

The dashed line represents the 1:1 relationship

It can be seen that there is no consistent over- or under-prediction of dike heightening costs when using the methodology of IPCC CZMS (1990). Estimates from IPCC CZMS

(1990) under-predict both rural and urban dike heightening costs for the Netherlands.

On the other hand, IPCC CZMS (1990) estimates have the capacity to grossly overpredict the likely costs for urban dike heightening in the US. Despite these discrepancies, the costs of dike heightening in Vietnam appear to be well predicted by the IPCC CZMS (1990) methodology.

Other estimates of dike costs are not so accurately reported. Although dike construction and upgrade costs are a function of both height and length, a lack of standardisation is present in the majority of the data found; the effect of height on dike costs is routinely ignored. Despite this drawback, Figure 3.4 attempts to compare reported unit costs of dikes with the estimates of Hoozemans et al. (1993). It is important to note that due to the lack of standardisation in reporting of unit costs in defences with both height and length attributes, the actual values shown are likely not to be directly comparable with the estimates of Hoozemans et al. (1993). Nonetheless, some attempt at comparing these values should be made and this analysis may give an indication of the degree of error present in cost estimates as a result of non-standardisation.

63


10

8

Range of costs

1:1 relationship

Average Cost

6

USA

4

UK

2

Mozambique

0

0 5 10 15 20 25

Estimated cost per km from Hoozemans et al. (1993)

2009 USD

30

Figure 3.4: Comparison of actual unit cost per km length of dikes against estimates from

Hoozemans et al. (1993)

The study of Hoozemans et al. (1993) indicates that until a defence height of approximately +4.5 m MSL is reached, costs are stationary. As such, the minimum estimated costs shown in Figure 3.4 are the minimum suggested by Hoozemans et al.

(1993). However, maximum estimated costs are based on the assumption that defence height does not exceed +8 m MSL. Conceivably, estimated costs may rise further if height increases above +8 m MSL. The average estimated cost is for a dike 6 m above

MSL.

Figure 3.4 suggests that Hoozemans et al.’s (1993) estimates significantly over-predict the actual costs of constructing dikes, at least in the three countries where unit cost information is available. The results clearly show that the minimum costs estimated by

Hoozemans et al. (1993) still over-estimate when even the upper cost limit of actual data is used. Even though data is not standardised, this result indicates a tendency for the

Hoozemans et al. (1993) method to over-predict dike costs. This tendency now requires further investigation.

This over-prediction may be due to a lack of flexibility in the suggested design of dikes.

Hoozemans et al. (1993) designed and costed these dikes according to Dutch practice.

64


However, in reality dike design is likely to vary worldwide and for these complex structures, designs could differ substantially, therefore impacting construction costs.

Maintenance costs are another important issue that must be considered. This cost is ongoing for the life of the structure and is therefore likely to result in significant levels of investment through a project’s lifetime. It is highly important to continue maintenance efforts in order to ensure defences continue to provide design levels of protection. The case of Hurricane Katrina in 2005 demonstrates one example where maintenance issues contributed to defence failure. Again, very few sources of maintenance cost information are accessible. The only available data is for the Netherlands and Vietnam. In these cases dike maintenance costs range from $0.03 million/km/year in Vietnam (Hillen,

2008) to $0.14 million/km/year in the Netherlands (AFPM, 2006). These costs appear to be quite variable; costs in Vietnam are almost five times lower than in the Netherlands.

Despite the large amount of available cost data for vertical seawalls, it is unfortunately not possible to compare unit cost estimates against previous studies such as IPCC

CZMS (1990) and Hoozemans et al. (1993) as this measure has not been considered by these studies. This does however highlight a weakness of these previous studies in that only Dutch methods of coastal protection were considered despite the popularity of other approaches outside of the Netherlands.

As already mentioned, storm surge barriers were neglected by both IPCC CZMS (1990) and Hoozemans et al. (1993). However, they provide an important alternative to closing off estuaries and also reduce the required dike strengthening behind these barriers

(Hillen et al., 2010). This option has been employed in London, New Orleans, the

Netherlands, Providence, Shanghai, St. Petersburg and Singapore amongst potentially many more. Hillen et al. (2010) attempted to produce unit cost estimates for surge barriers but concluded that these costs depend on many factors including the type of barrier/gate, local soil characteristics, desired height and hydraulic head. The issue therefore requires further research.

The assumption of Hoozemans et al. (1993) that defences would have to be raised by twice that of SLR in order to account for increased wave run up was investigated using an email survey. Upon questioning experienced coastal professionals on the use of this rule, feedback appears to be mixed. Many countries do not currently plan for any increase in SLR. Elsewhere SLR may be matched by increases in defence height despite the likelihood that such an approach is likely to lead to a reduction in the standard of protection offered over time as a result of hydraulic changes. In some locations, including Denmark and France, this assumption is seen to be an over-estimate of the likely required rise in defence heights. Although in Mozambique, it is possible that some sections of the shoreline may require an increase in defence heights greater than twice that of SLR due to the additional effect of cyclones (Brundrit & Mavume, 2009; van

Logchem, pers. comm, 2010). In summary, this assumption is widely disputed.

3.3.3 Associated Uncertainties

In this section, the uncertainties associated with unit costs of coastal defences are addressed to aid the interpretation of costs in this and future studies. Because this study shows actual defence costs from completed projects, it was mostly possible to present costs as a range describing top and bottom end costs. This is important in terms of communicating the degree of uncertainty associated with unit costs.

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One of the largest uncertainties present in this study is a lack of standardisation of unit cost data worldwide. To accurately represent costs, data for coastal structures with both length and height attributes should account for increases in costs with both of these characteristics. Current practice appears largely to focus on communicating defence costs per linear metre whilst ignoring the effect of height on cost. The unit cost data found during the course of this study systematically failed to provide cost information describing the effect of length and height on unit costs.

Another point of uncertainty is exactly how costs will rise with SLR. This issue is investigated in some detail by Burgess and Townend (2004) and Townend and Burgess

(2004). These studies highlight that costs of coastal defence construction are likely to rise non-linearly with SLR. Because wave height and energy at a structure is depthlimited, changes in water depths will cause changes in the wave conditions that structures must be able to resist (Burgess & Townend, 2004). Thus, SLR is likely to lead to something of a positive feedback mechanism; higher water levels will produce greater water depths, increasing the size of depth-limited waves impacting upon the structure. In turn, higher orbital velocities and greater wave energy reflection from the structures will increase the mobility of sediments and decrease the retention potential for sediments causing foreshore steepening and possible lowering. As a result of foreshore lowering, further increases in the water depths will occur thus causing larger waves at the structure (Burgess & Townend, 2004). The required increase in coastal defence heights as a consequence of SLR is much larger at locations experiencing depth-limited conditions as this limiting condition is reduced and wave energy is greatly increased

(Burgess & Townend, 2004).

These changes are likely to have impacts particularly in the design of coastal structures.

Hoozemans et al. (1993) assumed coastal defence upgrades would need to be double that of SLR – this was assumed to be a conservative estimate to account for changes in hydraulic conditions at the structure. However, structural integrity in the form of greater structural mass, revised slopes or increased rock size are likely to be as important as the need for crest raising to cope with changes in overtopping (Townend & Burgess, 2004).

Increased foundation levels for coastal structures may also be necessary to prevent undermining in the presence of foreshore lowering (Burgess & Townend, 2004). All of these changes will affect unit costs through revised structure designs.

This study captured costs as a range to represent uncertainty in wave exposure, water depth, and proximity to raw construction materials. Hoozemans et al. (1993) accounted for the degree of wave exposure and availability of construction materials in some measure by allowing selection of different dike designs depending on local conditions.

However, this was a simplified process which did not fully account for the large degree of variation in wave exposure or the potentially significant variation in proximity to materials which may be present within given countries.

Proximity to raw materials is a key determinant of uncertainty in costs. This is especially so in beach nourishment as illustrated by the case of New Zealand where sand sources are scarce and beach managers are sometimes forced to pay the same rate as for construction sand (Reinen-Hamill, pers. comm., 2010). In contrast, the Netherlands has a plentiful supply of sand on the continental shelf and nourishment costs are comparatively lower. Even within a given country, unit costs may vary significantly in accordance with proximity to sources of raw materials.

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Unit costs may also be impacted by the future uptake of coastal defence projects worldwide. It is unclear whether raw materials for the construction of defences will increase in cost as demand increases. There is also significant uncertainty in the extent to which prices will rise because of uncertainty in SLR scenarios and the various coastal defence projects that cities may adopt. The working assumption in this study is that prices will not rise with demand although this may warrant further investigation.

Economies of scale could potentially affect unit costs. This study was forced to assume that coastal protection comprises mature technologies and was less likely to be affected by economies of scale. This issue is more likely to affect costs in countries where coastal engineering projects are historically limited where maturation of the industry will lead to falling unit costs. This was accounted for to some degree by IPCC CZMS (1990) and Hoozemans et al. (1993) in the use of country factors which accounted for the presence of a ‘wet’ civil industry.

3.4 Limitations

Data availability was a very significant problem in achieving this objective; it is incredibly rare for comprehensive national data on unit costs to be reported in publicly available documents. This information was therefore not readily available and considerable time had to be expended investigating and researching where this information could be obtained. It is very likely that information in addition to that identified in this study is available but exists with the appropriate authorities for coastal defence in particular countries or with experienced private engineering consultancies. With such a large selection of countries it is extremely difficult to identify the appropriate authority for national coastal protection or even identify if such an authority exists. Identification of all the possible holders of this type of information is a huge task and if accomplished, is still no guarantee that information will be forthcoming.

It is hoped that the unit cost information presented by this study can be gradually updated and added to in the coming years by experienced engineers with knowledge of defence costing.

In many countries, local landowners are responsible for financing defences. Therefore, in many of these cases the possibility of comprehensive data existing is even smaller. In these cases there is no clear responsibility for the collection of this type of data and this created obvious problems with regards to data availability.

Relevant information is often only available within unpublished reports. If these sources can be identified and information obtained, further problems are likely to exist in the translation and interpretation of information. Understandably, these sources are mainly recorded in local languages. Due to the small number of people working on this project and short time scale, this presented a problem in several cases.

As previously stated, a lack of standardisation in the reporting of unit costs is also problematic. Ideally, costs should reflect both the length and height attributes of defences but this is rarely the case. Available data was frequently presented in different formats often with no consideration given to the fact that structure height is a major determinant of cost per unit length.

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Further limitations existed in that there was often little indication of what costs had and had not been accounted for (such as construction costs, overheads, associated construction works, etc.). This makes direct comparisons of costs more problematic.

Finally, structures such as levees and seawalls have a number of environmental and social costs (Heburger et al., 2009). Armouring of the coast using such structures prevents natural movement and migration of the beach and associated ecosystems and can cause increased vulnerability by encouraging development in flood-prone areas by promoting a false sense of security (Heburger et al., 2009). However, these costs are not reflected in unit cost estimates (Heburger et al., 2009).

3.5 Discussion

Through attempting to bring together this database on unit costs, it has become overwhelmingly clear that availability of unit cost data on coastal defences is extremely limited. In addition, much of the data which is available is un-standardised, making interpretations liable to error.

Although construction costs are likely to be well known to the sponsors of such structures, this information appears not to be recorded in public databases or may be lost entirely following project completion.

Identification of all the possible sources of this information is a massive task made all the more difficult when little or nothing is known about the responsible organisations for coastal defence in individual countries. It is possible that the information does exist but it is likely to lie with experienced engineers or in private databases and frequently in languages other than English.

If this problem is to be overcome in future, it is necessary to clearly delegate responsibility for the collection of cost information at a national level. In many countries, the wide range of individuals and organisations responsible for the provision of coastal flood defences means there is little incentive to collect cost data. In addition to clearly delegating responsibility for the collection of this information, standardisation of the recording of such data is desperately required. At present, unit costs for defences with both height and length attributes largely ignore the effect of height on cost and therefore costs are not comparable between schemes. Without standardisation, future studies of this nature will not be able to draw meaningful conclusions.

One of the main objectives of this project was to compare actual unit costs against global cost estimates from IPCC CZMS (1990) and Hoozemans et al. (1993). Direct cost comparisons were possible for beach nourishment and dike heightening both of which have been evaluated against the results of IPCC CZMS (1990). Due to non standardisation of data further dike costs were not directly comparable with previous studies.

Overall, actual nourishment costs show very good agreement with IPCC CZMS (1990) with a few exceptions, both of which can be explained to a certain degree. Agreement between these two costs suggests that the methodology for estimating nourishment costs adopted by IPCC CZMS (1990) is appropriate for estimating nourishment costs today when scaled to present day values using the PPI index. Agreement between estimates and observations is perhaps not especially surprising because nourishment

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities procedures are unlikely to vary significantly from country to country as perhaps they might for the construction of more complex structures such as dikes.

The methodology used to estimate nourishment costs in DIVA also seems accurate when compared to actual unit costs. Again, outliers are present but can be explained.

This improves confidence in the use of DIVA for estimating nourishment costs in future studies.

It must be stressed however that when interpreting comparisons between actual unit costs and those from IPCC CZMS (1990) and DIVA, there is still a lack of data; only a small number of countries have been studied here. Contact with experienced professionals in the dredging sector suggests that unit costs for fill material are typically in the range €1-20 which fits well with the values obtained thus far. Future investigations will no doubt improve our understanding.

It was possible to compare the costs of dike heightening from IPCC CZMS (1990) against urban and rural dike heightening costs from the Netherlands, USA and Vietnam.

This comparison shows that estimates from IPCC CZMS (1990) do not consistently overor under-predict actual unit costs. It is likely that under-prediction of costs in the

Netherlands is a result of differences between idealised dikes such as those designed and costed by IPCC CZMS (1990) and actual construction costs which, in practice, often encounter more complex problems and consequent increases in costs (Hillen et al.,

2010). The significant over-prediction of costs observed in New Orleans is likely to be partially caused by the high country factor of 2.0 applied. It can be seen that even with a country factor of 1.0 (in line with Dutch costs) the IPCC CZMS (1990) methodology still over-predicts dike heightening costs for New Orleans. The cost estimates for Vietnam sea dikes are taken from Hillen (2008) and were determined in a similar way to the IPCC

CZMS (1990) costs thus explaining agreement between predicted and observed costs.

The fact that coastal defence costs at project level are higher compared to idealised dikes was also found by Royal Haskoning (2007). This study concluded that it is not possible to estimate real project costs by relying on calculations based on idealised dike cross-sections and material unit costs. Instead it was suggested that expert judgement be used to provide cost estimates in the form of a range in order to overcome the large number of variables.

Further analysis of dike costs was possible using data which made no account for the effect of dike height on costs. Despite dike costs being a factor of both height and length, the majority of sources appear to neglect the effect of height on cost, presenting costs as a factor only of length. Comparisons between these costs and those of

Hoozemans et al. (1993) were made. The limitations imposed by the use of nonstandardised data and the consequent restrictions upon the analysis were explicitly stated. From this analysis it appears that the approach of Hoozemans et al. (1993) overpredicts actual costs of dike construction, at least in the countries for which data is available. This result has two possible causes; (1) that global costs of construction of dikes are in fact lower than estimated by Hoozemans et al. (1993) or; (2) that structures of a lower standard than designed by Hoozemans et al. (1993) are being built thus causing costs to be lower.

Maintenance costs are yearly costs and as such are likely to result in a significant level of investment over a project’s lifetime. It is important to make this investment so that

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities defences continue to provide adequate protection from coastal flooding. Variation in these costs globally appears to be significant.

Despite the availability of data on vertical seawalls, it was not possible to compare these costs against previous studies because both IPCC CZMS (1990) and Hoozemans et al.

(1993) do not evaluate this response to coastal defence. This issue reflects a significant limitation of these previous studies in that only Dutch solutions are analysed. Similarly, other measures deemed important elsewhere are also ignored by these previous studies

(Table 3.3). If the true cost of adapting to climate change is to be assessed, due consideration must be paid to responses other than those applied in the Netherlands.

It can be seen that unit costs vary significantly at a global scale. Hillen et al. (2010) address the issues most likely to influence variations in costs. These include:

(1) Planning and engineering costs: Where large, uniform sections can be used, such as in rural areas, unit costs may be low. In residential areas however, where non-uniform conditions exist, costs may be comparatively higher

(2) Material costs: This is very site dependent. A scarcity of construction materials can significantly affect unit costs and methods of construction

(3) Labour costs: The cost of labour varies considerably between countries and where costs are low, labour is used intensively. Where costs are high, mechanised equipment is more widely applied

(4) Implementation costs: This includes two main factors: i) Flood defence land requirements; land has to be purchased which can be financially and legally challenging ii) Rural or urban implementation: in urban environments space is usually scarce and more expensive, space-saving solutions are often required

(5) Management and maintenance costs: An organisation is required for the management and maintenance of flood defences which will result in an additional percentage of costs on the total expenses

Hillen et al. (2010) also propose that additional costs will be imposed if measures are implemented in urban or ecologically sensitive environments due to land take or legally imposed environmental surveys and studies such as EIAs

A number of the uncertainties affecting unit costs were discussed. The costs shown in

Table 3.4 were all presented as a range where possible to account for variation in unit costs caused by factors such as water depth, wave exposure and proximity to construction materials.

Previous studies have indicated that future costs are likely to be uncertain when considering SLR. Burgess and Townend (2004) suggest that cost increases are likely to be non-linear. SLR may even cause something of a positive feedback mechanism for cost increases (Burgess & Townend, 2004). In addition, the assumption of Hoozemans et al. (1993) that structure heights should be raised by twice that of SLR is potentially insufficient; factors other than height will need to change in order to cope with increased sea levels. Structural integrity in the form of greater structural mass and revised seaward slopes are likely to be as important as the need for crest raising (Townend &

Burgess, 2004).

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Finally, it should be noted there is a drawback in only considering the monetary costs of adaptation. Many coastal defence structures also have indirect impacts on their surroundings which are not accounted for in the costs presented. For example, nonmarket impacts would consider factors such as aesthetic considerations and attractiveness and for very large increases in sea level these costs may become significant and will need to be balanced against the benefits of “hard” protection

(Hallegatte et al., 2008). Additionally, structures may impact upon a coastline’s natural ability to respond to change or may increase vulnerability by encouraging development in risky areas (Heburger et al., 2009). These costs are not considered at all in this investigation.

3.5.1 Future Research

This topic now requires significant further investigation and expansion. This document has however provided a useful foundation upon which a comprehensive, global unit cost database can be compiled. In order to make future research both straightforward and meaningful, standardisation of costs must first be achieved.

As found in this study, future research is sure to be limited by data availability, therefore it is hoped that the database created by this study can be elaborated upon country by country by engineers with experience in the construction of coastal structures in a range of countries. The studies by Hillen et al. (2010) and Geldenhuys (2010) contained in

Appendices I and II respectively, demonstrate how organisations with experience in given locations are able to contribute significantly to the collection of unit cost data.

The further addition of cost information to that available in this report will enable a more comprehensive analysis of the applicability of the IPCC CZMS (1990) and Hoozemans et al. (1993) studies than possible in this study. This should shed light on whether these cost estimates are still practical at the present day. Additionally, a more detailed database describing unit costs will also enable more confident conclusions to be drawn on the likely costs of adapting to future climate change.

We must also aim to understand more fully how SLR will affect the design requirements for coastal projects if we are to fully understand how the costs of adaptation are likely to change in the future. SLR is certain to affect dike heights and footprints, required nourishment volumes, dike volumes and the costs of implementing certain projects

(Hillen et al., 2010). In addition, the rate of SLR and whether this is linear or non-linear will affect how often and how much defences will have to be strengthened over time

(Hillen et al., 2010).

The value of land has not emerged as a significant influence on the unit cost of coastal defence measures in this study or in previous vulnerability assessments (IPCC CZMS,

1990; Hoozemans et al., 1993). However, IPCC CZMS (1990) appear to have considered this issue to a degree by suggesting different costs for dike raising in urban and rural areas. It seems only logical that land values would be an important control upon unit costs; construction of defences in certain locations prevents the use of land in other applications. As such, coastal defences are expected to have to compete for available land. The influence of land values on unit costs would be expected to be significantly higher in cities where land values are high. As such, it is recommended that future work investigates more carefully the effect of land prices on unit costs.

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In order to fully understand why costs are so variable between countries it would be very interesting to attempt a cost breakdown for coastal structures. Such a study would facilitate an understanding of the factors which are most important in terms of their contribution to overall costs and whether these factors change from country to country.

Work is also required into the factors affecting the unit costs of storm surge barriers.

Hillen et al. (2010) have found costs to be influenced by a number of factors. To accurately report unit costs for surge barriers in future, these must be fully understood.

3.6 Summary

Very little information on unit costs globally is available and what little information is available is often un-standardised making analysis of results highly problematic. The available information is summarised in Table 3.4.

Information that was obtained supports the use of the IPCC CZMS (1990) methodology for estimating unit costs of beach nourishment using sand although these estimates become much less accurate when other nourishment materials such as shingle are utilised.

Comparison of the costs of dike raising in both rural and urban areas in the Netherlands,

US and Vietnam were made with estimates from IPCC CZMS (1990). This analysis shows that IPCC CZMS (1990) estimates both significantly overand under-predict actual costs depending on location. Cost under-prediction can be attributed to increased costs on individual projects as a result of on site complexities compared to the idealised dike designs utilised by IPCC CZMS (1990). Over-prediction is likely to be a result of some inaccuracy in the country factors suggested by IPCC CZMS (1990). Review of these factors may be necessary.

Results also suggest that significant over-prediction of costs occurs when utilising the

Hoozemans et al. (1993) approach for costing dikes. This suggests either a lower design standard than that advocated by Hoozemans et al. (1993) is employed globally or that costs are generally cheaper than predicted. The cost information used in this analysis is non-standardised however and as such, a number of issues must be borne in mind when interpreting this result. This issue now requires further research.

Numerous uncertainties in unit costs exist; these include, but are not limited to:

•

Uncertainty in how costs will increase with SLR (Burgess & Townend, 2004)

•

Non-standardisation of costs

•

Differences in wave exposure

•

Differences in water depth

•

Proximity to construction materials

•

Changes to raw material prices

Several factors could affect the development of coastal defence costs over time and could lead to changes in unit costs. Uncertainty in the development of costs and market prices (e.g. oil prices) has the capacity to significantly influence unit costs, as do the development of innovative techniques. However, beach nourishment and dike construction may be considered mature technologies and as a result cost reductions may be minimal.

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4.0 APPLIED STANDARDS OF PROTECTION

4.1 Background

Nicholls et al. (2008) estimated the number of people exposed to climate extremes in the

136 port cities studied. Their study made no attempt to account for protection offered by coastal defences however because of a lack of comprehensive and accurate data

(Nicholls et al., 2008). By using the exposure metric, the study essentially produced a worst case scenario for exposure to climate extremes (Nicholls et al., 2008). Using this metric, it is difficult to obtain a realistic idea of the population and assets at risk beyond the worst case. Many coastal cities have extensive natural or artificial defences such as sand dunes or marshes, or dikes and storm surge barriers (Nicholls et al., 2008).

By considering the presence of natural and artificial defences and other coastal adaptation measures, the emphasis of research is able to shift from exposure analysis toward risk analysis. By doing so, it is possible to formulate a more accurate representation of risk. This provides an opportunity to evaluate vulnerability to coastal flooding and erosion more realistically through a more complete investigation of coastal adaptation measures.

The aim of this study is to compile a database describing risk perception in the 136 port cities, this will illustrate whether coastal flooding and erosion are issues of concern.

Additionally, coastal adaptation measures applied in each of the 136 port cities will be compiled if such measures exist. This information is generally drawn from academic and government reports and through contact with experienced coastal engineers worldwide.

The collection of this data is intended to illustrate the approximate level of protection provided against coastal flooding and erosion. At present, no comprehensive database exists on this subject.

The importance of evaluating protective measures is illustrated by recent winter storm

Xynthia in Western Europe (February 2010). At least 55 people died when the storm struck the coast. France was hit particularly hard with wave surges flooding coastal regions and hurricane-force winds causing significant damage (Roberts, 2010a). The storm also caused waves up to eight metres in height to batter ageing sea defences eventually causing some structures to collapse (Roberts, 2010b) and allowing seawater to surge hundreds of metres inland (Roberts, 2010a). By determining the level of protection offered by existing coastal defences it should be possible to establish those most vulnerable and focus efforts on mitigating the potential effects of SLR.

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Figure 4.1: Recent storm damage on the western coast of France during winter storm

Xynthia (source Roberts, 2010a)

In the absence of such a database, existing methods for estimating the standard of protection offered by coastal defences rely on econometric functions. DIVA is one example of the use of such a function. DIVA’s demand for safety is essentially based on a cost benefit analysis which accounts for GDP/capita, coastal population density and surge regime among other factors. Based on this information, DIVA is able to suggest an econometrically ‘optimum’ level of defence. Higher GDP/capita and coastal population densities suggest higher demand for safety while larger surges reduce the protection offered by defences of a given height. The function complies with the assumption that standard of coastal protection is closely linked to wealth. However, there are known exceptions to this rule and it has been shown that where data exists, econometric functions tend to overestimate protection standards in comparison to reality, especially in poorer countries (Nicholls et al., 2008).

By comparing applied standards of protection to those suggested by demand for safety functions it should be possible to evaluate the performance of these functions. It should also be feasible to appraise their usefulness in suggesting what the standard of protection is likely to be where information does not exist. The aim is to calibrate demand for safety functions against observations so that we can generalise the result to the full population of 136 cities. By doing so, the reasons why differing levels of protection are applied in different locations can also be investigated. It is important to understand what factors contribute toward the decision to build defences to a given standard and why the attitude toward risk is so variable between locations.

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4.2 Methodology

The level of defences which cities choose to build was assessed in a similar way to that of unit costs; through review of reports, email surveys, meetings with specialist consultancies and discussions with experts. This again reflects that this type of information tends to exist in unpublished reports and with experienced engineers.

Most of the organisations and individuals approached in relation to the issue of unit costs were also questioned on standards of coastal protection applied in particular cities, again using an email survey. The aim was to determine if coastal flooding and erosion were important problems in the cities, what adaptation measures the cities have applied, and specific information relating to these measures.

Specific measures such as the type of structural defences employed, the SoP offered by defences or other measures, absolute height of defences, basis for the design of defences and the presence of additional planning regulations relevant to coastal flooding and erosion were all sought. Additional organisations approached in relation to this objective included state and city emergency management agencies, regional departments of environmental protection, city officials and the global reinsurance company, Munich Re. The main data required were SoP estimates in the format of a return period against which a city is defended. This enabled directly comparison with the demand for safety function from DIVA.

A large amount of data was gathered describing the above attributes as well as a substantial quantity of supplementary data. This information is available through the accompanying Excel database which can be accessed via the AVOID Stakeholders website at www.avoid.uk.net/private2/ . The contents of this database are summarised in

Appendix VII.

It quickly became apparent that structural defences were only a small subset of the available adaptation measures. In many cities, planning and building regulations played an important role in reducing exposure to coastal flooding and erosion. In some cases, only these measures existed. Frequently, these regulations prevent development from occurring in at risk areas thus avoiding the need for application of structural defences.

The obvious benefits of employing planning regulations over structural defences are the lower associated costs, greater flexibility for future coastal management decisions and increased levels of safety resulting from removing the risk of defence failure.

It also became clear that many cities were apparently unconcerned about coastal flooding and erosion and as such adopted few if any coastal adaptation measures. In these cases, obtaining information on the coastal defences applied was unnecessary.

Level of concern appears to be closely linked to exposure with cities with low exposed populations unlikely to implement significant adaptation measures.

In many cases defence height was not statistically based on a storm return period but was instead based on historic storms or in some cases, seemingly arbitrary heights. In these cases the best available information to describe SoP was defence height. Where this information was available it was intended to convert defence heights above MSL to

SoP using extreme water level datasets available from previous studies, analysis of

GLOSS tide gauges where these were present and using the extreme water level data from the DIVA database.

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As shown in Figure 4.2, extreme water levels were to be plotted against return period on a log scale and regression performed. The regression equation would then be used to equate the height of defences to the return period of that water level.

Figure 4.2: Procedure for finding SoP using defence height data

Defence height is y and SoP is x

Multiple problems with this approach were encountered. Only very few previous studies on extreme water levels in the cities of interest here had been conducted and GLOSS data required significant editing and formatting (such as the removal of periodic trends and SLR from the dataset) which would have been incredibly time-consuming. In addition, all three types of data failed to account for wave run up thus causing gross over-predictions of applied SoP. Because of the sensitivity of SoP to multiple criteria, it was not possible to create a methodology for converting defence heights to SoP in the timeframe given. Instead, defence heights are presented in a raw format for potential use in future studies.

4.3 Results

Various information relating to coastal defence measures was assembled for approximately 50 of the 136 port cities under study. This information includes the types of coastal defences present, SoP offered, defence heights, level of concern over coastal flooding and erosion and the presence of other measures to combat coastal flooding and erosion. The absence of information relating to the remaining cities reflects a substantial gap in available knowledge.

In many of the port cities studied, coastal flooding is not an issue of concern; this could be due to a number of factors including a high degree of protection afforded by local topography, physical location away from susceptible areas (e.g. Sapporo, Japan which has a port although the city itself is located some distance inland) or shelter from wave attack to name a number of reasons.

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Table 4.1 summarises which of the 136 port cities are known to be at risk of coastal flooding while Table 4.2 illustrates those cities known to be at minimal risk. Table 4.2 also includes the exposed population in each city as estimated by Nicholls et al. (2008).

It can be seen that exposed population in each of these cities is low; therefore these findings are consistent with Nicholls et al. (2008).

The information shown in these tables is taken from numerous sources and is shown in much more detail in the accompanying Excel database. This list is not definitive; for many cities, information on the level of risk was simply unavailable and as such, no conclusions could be drawn. Appendix II contains a detailed case study of Cape Town.

Tables 4.1 and 4.2 can be used in future studies to target the assessment of vulnerability in cities where risk is known to exist. Those cities not named in these tables should not be discounted; non-availability of information on these locations clearly indicates that further research is necessary.

Table 4.1: Port cities studied known to be at risk of coastal flooding or erosion under present conditions

Alexandria

Amsterdam

Auckland

Belém

Boston

Buenos Aries

Cape Town

Chittagong

Copenhagen

Dhaka

Dublin

Durban

Fukuoka-Kitakyushu

Fuzhou Fujian

Glasgow

Grande Vitória

Guangzhou Guangdong

Hai Phòng

Hamburg

Hangzhou

Havana

Helsinki

Cities

Hiroshima

Ho Chi Minh City

Hong Kong

Houston

Incheon

Jakarta

Khulna

Kochi

Kolkata

London

Maceió

Madras

Maputo

Miami

Mumbai

Nagoya

N'ampo

Naples

New Orleans

New York-Newark

Ningbo

Osaka-Kobe

Philadelphia

Port-au-Prince

Porto Alegre

Providence

Pusan

Rangoon

Recife

Rio de Janeiro

Rotterdam

Santos

Seattle

Shanghai

Shenzen

Singapore

St. Petersburg

Stockholm

Surat

Tokyo

Vancouver

Virginia Beach

Visakhapatnam

Zhanjiang

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Table 4.2: Port cities studied reported to be at minimal risk of coastal flooding or erosion under present conditions and associated exposed populations (from Nicholls et al.,

2008)

Cities

Adelaide

Athens

Fortaleza

Istanbul

Izmir

Marseille-Aix-en-Provence

Montréal

Portland

Salvador

Sapporo

Exposed Population (000s)

70

27

14

4

3

12

25

13

9

5

Despite consulting a wide range of sources, information relating to the coastal adaptation measures in place in many cities was seemingly unavailable. This would suggest that either no coordinated defence measures exist at these locations or that the availability of information on this topic in the English language is severely limited. Table

4.3 illustrates the standard of protection provided by coastal adaptation measures where this information was available. Extensive information relating to the types of coastal adaptation applied and other information can be found in the attached Excel database, the contents of which are summarised in Appendix VII.

Country

ARGENTINA

AUSTRALIA

BANGLADESH

CANADA

CHINA

CHINA

Table 4.3: Applied standards of protection in port cities

City

Buenos Aries

Adelaide

Dhaka

Vancouver

Guangzhou

Ningbo

SoP Offered

(protected from the 1 in x year storm)

<1:5 to <1:100

(Barros et al., 2008)

1:100 from seawalls although twice this level is provided by sand dunes


1:1 (Marshall, 2009) to 1:50

(Asian Development Bank, 2002)

1:200

(City of Vancouver Community Services, 2007)

1:20

(Nathwani et al., 2009)

1:20


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Country

CHINA

CHINA

CHINA

CHINA HONG KONG

DENMARK

EGYPT

FINLAND

GERMANY

INDIA

INDIA

IRELAND

ITALY

JAPAN

JAPAN

JAPAN

MOZAMBIQUE

NETHERLANDS

NETHERLANDS

Kolkata

Mumbai

Dublin

Naples

Nagoya

Osaka-Kobe

Tokyo

Maputo

Amsterdam

Rotterdam

City

Qingdao

Shanghai

Tianjin

Hong Kong

Copenhagen

Alexandria

Helsinki

Hamburg

SoP Offered


1:20


1:1000

(Nicholls et al., 2008)

1:20


1:40 to 1:900

(Yim, 1991; Yim, 1995)

≥

1:120

(Hallegatte et al., 2008)

1:20


<1:100 to 1:200

(Lehtonen & Luoma, 2006; Wahlgren, 2007)

≥

1:650

(Much, pers. comm., 2010)

Defences may protect against up to the 1:5000 year storm but this is not statistically proven)

1:20


1:20


1:70

12

(Cooke et al., 2005)

1:20 to 1:50

(Vicinanza, pers. comm., 2010)

1:100


1:300


1:1000


1:10 to >1:100


1:10000

(Huisman et al., 1998)

1:10000

(Huisman et al., 1998)

12

Currently under upgrade to offer 1:200 standard of protection

79


Country

NEW ZEALAND

RUSSIAN

FEDERATION

SINGAPORE

SOUTH AFRICA

THAILAND

UK

UK

USA

USA

USA

USA

VIETNAM

VIETNAM

City

Auckland

St. Petersburg

Singapore

Durban

Bangkok

Glasgow

London

Miami

New Orleans

New York-Newark

Virginia Beach

Hai Phong

Ho Chi Minh City

SoP Offered


1:100

(Kench, pers. comm., 2010)

1:1000

(Whitelaw, 2009)

1:1000 to 1:2000

(Nicholls, pers. comm., 2010)

1:50 to >1:500


1:50


<1:200

13

(Halcrow Fairhurst, 2007)

1:1000


<1:100

(Flynn, pers. comm., 2010)

1:100 14

(USACE, 2010)

1:100 – nominal; no comprehensive system of flood defences exist


1:7 to 1:140

(Roehrs, pers. comm., 2010)

1:1 to 1:50 15

(Hillen et al., 2010; Mai et al., 2008)

1:1 to 1:50

15

(Hillen et al., 2010; Mai et al., 2008)

From Table 4.3 it can be seen that the SoP offered within many cities is variable – this may be a result of intentional differences in protection level, for example to protect important infrastructure. Alternatively, differences in exposure to wave attack and surges within a city can cause defences of uniform height to provide varying levels of protection dependent on location. Through this analysis it has also become apparent that many cities apply non-continuous defences. One such example is Sydney, Australia

13

Currently under upgrade to offer 1:200 standard of protection

14

Following Hurricane Katrina USACE is currently on track to provide a 1:100 standard of protection by

2010. Pre-Katrina, defences were thought to offer 1:200 to 1:300 level of protection (Nicholls &

Leatherman, 1995) although this is now thought to have reduced over time with dike settlement

15

Standards applied over much of Vietnam are dubious as they are not consistently based on accurate statistical risks. Although many dikes are designed to fail once every 20 to 25 years, the sea defence system might fail almost every year (Mai et al., 2008)

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities where defences range in height between +0 and +8 m Australian Height Datum (Gordon,

1989), where AHD is equal to mean sea level for the period 1966-1968

(Intergovernmental Committee on Surveying and Mapping, 2006). In many cases, small stretches of defence appear to be employed primarily for coastal erosion control. Where defences are non-continuous, the level of protection offered can be very unclear as flood events are likely to out-flank defended areas.

Table 4.3 also shows how applied SoPs between the studied port cities are highly variable; these range from minimal levels of protection such as the annual to ten year event to protection against very extreme events such as the Dutch 1 in 10000 year event. This is illustrated in Figure 4.3 which shows Rio de Janeiro’s city airport located in the downtown area. Although the likely range in SoP is not known for Rio de Janeiro,

Brazil, the airport is clearly vulnerable to potential coastal flooding yet appears to have minimal levels of protection despite its likely importance to the city’s economy. This serves to illustrate the surprising range of responses to coastal flooding globally; from the very relaxed approach adopted by Brazil to the very high levels of protection offered by countries such as the Netherlands.

Figure 4.3: The airport at Rio de Janeiro located in the downtown area of the city (image provided by Claudio Freitas Neves)

It can be seen that many of the more developed countries have applied high levels of protection against coastal flooding. For example, Amsterdam and Rotterdam have 1 in

10000 year SoPs, Singapore has a 1 in 1000-2000 year SoP and London and Tokyo have 1 in 1000 year protection levels. These high levels of protection are largely in line with the value of assets at risk from coastal flooding according to Nicholls et al. (2008); cities found to employ SoPs greater than or equal to the 1 in 1000 standard largely fall within the top 20 in terms of ranked exposed assets with the exception of Singapore and

St. Petersburg. The application of significant defences in these cities suggests that factors in addition to wealth and development play important roles in deciding the level of defence against coastal flooding in port cities.

81


In many of the cities which have not been named in Table 4.3, it is likely to be difficult to determine the SoP applied even if specific details of these structures are known. Natal,

Brazil provides an excellent example where a lack of design criteria for constructing coastal defence structures (Neves, pers. comm., 2010) means there cannot be any real idea of the level of protection provided.

A link between wealth and the level of protection offered has long been presumed to exist (e.g. Nicholls et al., 2008) although the relationship is not presumed to be automatic (Nicholls et al., 2008). Although rich countries have a larger capacity to protect their cities, they may or may not choose to do so (Nicholls et al., 2008). In order to test this presumed relationship Figure 4.4 compares applied SoP and country GDP per capita. b e

10000

8000

6000

SoP consistent at this level city-wide

Variation in SoP across a city

4000 c

2000 a

0

0 10000 d

20000 30000

GDP/capita

40000 f

50000

Figure 4.4: Comparison of country wealth measured in terms of GDP/capita and applied standards of protection

Letters draw attention to cases of interest; a = St. Petersburg & Shanghai, b = the

Netherlands, c = Singapore, d = USA, e = Copenhagen, f = Japan (specifically Nagoya &

Osaka-Kobe)

From Figure 4.4 it can be seen that there is no strong or coherent relationship between country wealth and applied standards of protection. Cases of interest have been

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities highlighted by letters a-f. It should be noted here that the level of protection afforded to

Copenhagen, marked e, is highly variable across the city. Minimum levels of protection approximate the 1 in 120 year surge level (Hallegatte et al., 2008) although the city’s highest defences offer protection against all foreseeable surge events effectively affording infinite levels of protection (Hallegatte, pers. comm., 2010). However, 1 in 120 year protection at its minimum is low for a city of Copenhagen’s wealth. Additionally, some port cities in the US (marked d) and Japan (marked f) have applied low levels of protection despite their high GDP/capita. In contrast, the Netherlands (marked b) have applied consistent levels of protection well in excess of any other country. This result clearly demonstrates the importance of factors other than wealth in determining the SoP which should be applied in port cities.

Further complicating the relationship between wealth and applied SoP are the cases of

St. Petersburg and Shanghai which have both employed SoPs equivalent to the 1 in

1000 year surge (comparable to London and Tokyo) despite very low national values for

GDP per capita. This may be partially explained by significant differences in GDP per capita within these countries however; both Shanghai and St. Petersburg are likely to have significantly higher GDP per capita than the country averages. The use of national rather than regional GDP values is therefore potentially misleading.

Using regional GDP values where these were available, Figure 4.5 attempts to investigate the relationship between applied SoP and wealth at a more detailed scale.

City GDP values were taken from PricewaterhouseCoopers Global City GDP Rankings

2008-2025 (PricewaterhouseCoopers, 2009). With the exceptions of Amsterdam,

Rotterdam and Copenhagen with comparatively low city GDP per capita, the data appears to suggest that wealth is important to a certain extent in deciding the level of protection to apply. Many of the cities at the lower end of the GDP scale have applied low SoPs, these are circled in Figure 4.5.

The PricewaterhouseCoopers (2009) dataset only gives city GDP values for the world’s

151 richest cities in 2008 – consequently, many of the 136 port cities studied here are not named. However, these correspond closely with those cities for which information on SoP was not available. It is hypothesised that these cities have minimal if any formal defences; if this is the case, these results would agree with the regional wealth theory.

Nevertheless, even regional wealth does not fully explain variation in the applied SoPs worldwide. Clearly additional factors are also at work.

83


10000

8000

6000

4000



2000

0

0 200 400 600 800 1000 1200

Estimated regional GDP in 2008

($bns at PPPs)

1400 1600

Figure 4.5: Comparison of city GDP (from PricewaterhouseCoopers, 2009) and applied standards of protection

Following the limited relationship between wealth and applied levels of protection, the assumption that economic growth in the coming years will allow a general improvement in protection levels and a corresponding decrease in flooding risks in coastal cities around the globe (Nicholls, 2004; Nicholls et al., 2007) is potentially flawed.

Using wealth as a measure of ability to provide higher levels of protection from coastal flooding, Nicholls et al. (2008) stated that very few of the top ten countries in terms of exposed population would be able to provide high protection against an extreme event, the only exception being the Netherlands and the US. To investigate if this is currently the case, Figure 4.6 plots applied SoP against exposed population.

84


100

80 a



60

4000

2000

0

0 500 b c d e

1000 1500 2000

Exposed population (000s)

2500 f

3000

Figure 4.6: Exposed population (from Nicholls et al., 2008) plotted against applied SoPs

Letters draw attention to cases of interest; a = the Netherlands, b = Tokyo, c = New

Orleans, d = New York, e = Ho Chi Minh City, Kolkata & Miami, f = Mumbai &

Guangzhou

It can be seen that many of the more exposed populations are afforded lower levels of protection in line with the assumptions of Nicholls et al. (2008). As hypothesised by

Nicholls et al. (2008), the Netherlands (marked a on Figure 4.6) can afford to apply very high levels of protection. However, despite being able to afford high levels of protection,

New Orleans, New York and Miami (marked c, d and e respectively) have still chosen to apply low SoPs. Worryingly, many of the world’s most exposed populations are afforded very low levels of protection. SoP was obtained for 18 of the current 20 cities with most exposed populations according to Nicholls et al. (2008). With the exceptions of

Shanghai, Osaka-Kobe, Amsterdam and Rotterdam, these cities are typically protected against a maximum of the 1 in 100 year storm. This result indicates that large numbers of people are significantly vulnerable to coastal flooding.

Taking the applied SoPs where this information is available, it was possible to compare the level of protection predicted using a demand for safety function (in this case performed by DIVA) and the applied SoP for available cities. The aim here is to evaluate how accurate assumptions made by econometric functions are and to calibrate this method against observations in order to generalise results to the full population of 136 cities.

85


Figure 4.7 comprises applied SoPs taken from Table 4.3 plotted against demand for safety as calculated by DIVA. Both demand for safety and applied SoP are presented in the form of protection against a storm of given return period. As in Figures 4.4 to 4.6, some of the applied SoPs are variable across cities; as such, ranges are shown by elongated grey points. Where only the point representing average SoP is present, it can be assumed that SoP is consistent across the city; for example, the city of London is comprehensively protected to the 1 in 1000 year standard by a system of flood embankments and surge barriers (Stenhouse, 1987; Dawson et al., 2005). c

10000 a d

1000 b

100 e

10

1

0.1

0.1 1 10 100 1000

Demand for Safety (1 in x year storm)



10000 m = 1 DFS ± factor of 10

Figure 4.7: Comparison of applied SoPs with demand for safety as calculated by DIVA

Letters draw attention to cases of interest; a = Shanghai, b = St. Petersburg, c = the

Netherlands (Amsterdam & Rotterdam), d = Tokyo, e = New York

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From Figure 4.7 it can be seen that DIVA’s demand for safety function typically predicts applied SoPs to within a factor of 10. Using a factor of 10, under-prediction of applied

SoPs is largely accounted for although over-prediction of applied SoPs using this margin still occurs.

On the whole, demand for safety tends to over-estimate applied levels of protection in the majority of cases. A limited number of exceptions to this rule do exist though; notably Shanghai (marked a on Figure 4.7), St. Petersburg (b) and the Netherlands (c).

These locations currently apply levels of protection in excess of calculated demand for safety which implies that these populations are ‘risk averse’. Nicholls et al. (2008) suggested risk aversion is likely to occur more frequently in richer populations as a result of pressure upon local and national authorities to reduce natural hazard risks. However, the occurrence of risk aversion in both Shanghai and St. Petersburg suggests this behaviour is not limited to richer populations but must be influenced by further factors.

A number of cities have their SoP well predicted by the demand for safety function; these cities are Singapore, London, Durban, Dhaka, Hai Phong, Ho Chi Minh City and Maputo.

In these cases it would seem that the parameters accounted for by the demand for safety function provide a good basis for predicting the level of protection against coastal flooding.

Those cities termed ‘risk averse’, can be contrasted with the remaining cities which are here referred to as ‘risk tolerant’. In these cities demand for safety appears to overpredict, significantly in some cases, the level of protection against coastal flooding that will be offered. In these cases authorities have chosen to apply SoPs that are lower than is perhaps affordable.

Notably, demand for safety significantly under-predicts applied SoP in Tokyo (marked d on Figure 4.7) where a comprehensive 1 in 1000 year SoP is offered. Despite the fact that the 1000 year protection level is significantly greater than offered in most other locations, the demand for safety function still suggests that this level of protection is sub optimal. Protection against the 1 in 5526 year storm is suggested by DIVA, significantly higher than the level applied at present. New York provides another prime example of over-prediction of defence heights based on demand for safety. Currently the city has no comprehensive system of flood defences and has a nominal defence level against the 1 in 100 year storm. DIVA suggests optimal protection in New York is from the 1 in

3921 year storm, significantly higher than the present level. Other cases of interest are presented in Table 4.4.

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Table 4.4: Additional cities which can be termed ‘risk tolerant’; applied SoP is significantly over-predicted by the demand for safety function

Country

DENMARK

FINLAND

JAPAN

JAPAN

USA

USA

USA

City

Copenhagen

Helsinki

Nagoya

Osaka-Kobe

Miami

New Orleans

Virginia Beach

Min. Applied SoP

( 1 in x year storm)

120 16

<100

100

300

50

100

7

Demand for Safety

(1 in x year storm)

8930

1890

3234

3022

2468

1385

1830

The seemingly low level of protection offered in Helsinki is likely to be a result of the low value of assets and low population levels exposed to coastal flooding; Nicholls et al. th th (2008) ranked Helsinki 119 and 89 out of 136 for exposed population and the value of exposed assets respectively. The same cannot be said of the other seven cities. With the exception of Copenhagen, these cities are consistently ranked in the top 10 for either exposed population or assets, if not both (Nicholls et al., 2008).

The fact that the demand for safety function does not accurately predict applied SoP in the majority of cases implies that factors in addition to those considered by DIVA must be important influences on the decision to apply a given level of protection. The potential factors influencing this decision will be reviewed in Section 4.5.3.

By plotting the median value for standard of protection against the demand for safety, it was possible to draw a line of best fit through the data. By doing so it demonstrates the deviation from the econometric function and perhaps suggests a more appropriate function based on applied levels of protection. Figure 4.8 shows average standard of protection against demand for safety with a linear regression line forced through the origin.

16

Note that defence heights in Copenhagen are highly variable and that at their maximum, defences offer protection from all conceivable storms (Hallegatte et al., pers. comm., 2010)

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AVOID WS2/D1/R14

10000

1000

100

10

Costs of Adaptation to Climate Change in Large Port Cities y = 0.46x

R 2 = 0.06

1

1 10 100

Demand for Safety

(1 in x year storm)

1000 10000

Figure 4.8: Regression of average applied SoP against demand for safety

Figure 4.8 shows an apparent relationship between the two factors, albeit a weak one

(R 2 value equal to 0.06). This relationship could provide a useful starting place for reassessing the demand for safety function in future.

Hillen et al. (2010) attempted to determine the optimal protection levels for the

Netherlands, New Orleans and Vietnam. In this analysis incremental investments in greater safety are balanced against reduction of risk to obtain an optimal protection level

(for more information see Appendix I). Their analysis found that river dike rings in the east of the Netherlands and defences for both New Orleans and Vietnam all require heightening to provide optimal safety levels. Table 4.5 provides a comparison of the values obtained using Hillen et al.’s (2010) methodology and that of DIVA.

Table 4.5: Comparison between DIVA demand for safety and the economic optimisation method

Location

Amsterdam

Rotterdam

New Orleans

Hai Phong

Ho Chi Minh City

DIVA Demand for Safety

(return period [years])

1739

1396

1385

14

1

Hillen et al. (2010) Optimal

Protection Level

(return period [years])

20000

4000

1000 – 5000

50

90

89


As DIVA is a global assessment tool, the factors accounted for when determining demand for safety are more general than those used in the economic optimisation method. Additionally, when considering Dutch dike rings it has been found that optimal levels of safety are directly related to the number of inhabitants in a potentially flooded area and the length of the defence system (Hillen et al., 2010). As such, it is recommended that these factors be used to aid determination of optimal levels of safety.

Investigation into how these factors could be incorporated into the DIVA model is now recommended.

Further information was ascertained during this study on the absolute height of defences above MSL. As outlined in Section 4.2.1, it was intended to use defence heights to estimate SoP based on extreme water levels. As a methodology to reliably do so could not be formulated, it was not possible to translate these defence heights into SoPs.

These values are however presented in Table 4.6 for future reference and for use if a suitable methodology for converting these heights to SoPs is devised. Availability of both SoP and defence height for a small number of cities reinforces the belief that availability of this type of information is very skewed toward a small number of locations.

90


Table 4.6: Absolute height of coastal defences above various datums

Country City Absolute Height of Defences

AUSTRALIA

CHINA

CHINA

DENMARK

EGYPT

GERMANY

KUWAIT

MOZAMBIQUE

NIGERIA

SINGAPORE

SOUTH AFRICA

SOUTH AFRICA

USA

USA

Sydney

Shanghai

Hong Kong

Copenhagen

Alexandria

Hamburg

Kuwait City

Maputo

Lagos

Singapore

Cape Town

Durban

Miami

Providence

+0.00 TO +8.00 m

Australian Height Datum

(Gordon, 1989)

+3.00 to +5.00 m MSL

(Han et al., 1995)

+2.35 to +3.05 m MSL

(Yim, 1995)

+1.50 to +3.50 m MSL

(Hallegatte et al., 2008)

+2.50 m MSL

(Frihy, 2003)

+7.20 to 9.25 m Normal Null

(Gönnert & Triebner, 2004)

+6.50 m Kuwait Land Datum (which approximates

MLLW)

(Kana et al., 1986)

+4.00 to +7.00 m MSL


+4.00 m MSL

(The Chagoury Group, 2006)

Marina Barrage +3.50 m MSL

Reclamation Levels +3.0 to +3.5 m MSL

(Nicholls, pers. comm., 2010).

+4 to +9 m MSL

(Holtzhausen, pers. comm., 2010)

+4.00 to +16.00 m MSL


+2.10 to +2.90 m North American Vertical Datum 1988

(Flynn, pers. comm., 2010)

+6.10 m MSL

(City of Providence Dept. Public Works, 2006)

4.4 Limitations

It has been shown in the Floris project (Ministry of Transport, Public Works and Water

Management, 2005) that SoP is often poorly understood in many coastal structures.

Current practice assumes that extreme water levels will be the main cause of flooding.

However, this only reflects one aspect of the true probability of flooding. In order to assess the real risk of flooding, all defence failure modes – not only overtopping – must be considered. These may include revetment damage, sliding of slopes, piping, erosion or structural failure to name some common failure mechanisms.

91


In this study, SoP is based on the return period extreme water level from which a city is defended. It is used in this study because it makes the degree of offered safety appear easy to compare. However, this is only one indication of the actual safety and the probability that a given water level will be exceeded is not equivalent to the probability that a defence will fail (Jorissen et al., 2000). In practice, the applied data, design procedures, criteria and safety margins determine actual safety.

By concentrating only on extreme water levels, measures which reduce the probability of defence failure, such as increased stability are not considered to contribute to increased safety which is a major pitfall. This issue is well illustrated by winter storm Xynthia;

Napoleonic era defences existed along the French coast but collapsed in the presence of strong wind and waves causing deaths and economic losses. Due to this concentration on extreme water levels, many of the SoPs reported here may in fact be over-estimates because the full range of failure mechanisms are not considered.

Copenhagen is one example where over-prediction of the upper defence limit is likely.

The approach advocated by the Floris project where the risk of defence failure is a factor of numerous failure mechanisms appears to be a more accurate and comparable way of comparing flood risk for future studies. However, data availability is likely to limit this approach.

The very limited availability of accurate and comprehensive data on flood protection measures applied in many cities is a real issue. There are a small number of exceptions where vast amounts of data are available including the Dutch Deltworks project and the

Thames Barrier although these cases are uncommon. Information frequently does not exist within the public domain but with experienced engineers and within unpublished reports and government databases. Making contact with the appropriate persons or organizations worldwide is very challenging. Additionally, the balance of information appears to be skewed in favour of a small number of locations. Consequently very little information is available in many cities.

The provision of coastal flood defences in many countries does not appear to be a joined up process; numerous organizations, both public and private, are potentially involved in the provision of flood defences. As a result, there is regularly a lack of information comprehensively describing coastal defences in cities and as such, little idea of the level of protection offered. This is demonstrated well in the US where the United States Army

Corps of Engineers (USACE) is a key organization in the provision of flood defences but where local and regional level government are additionally involved. This frequently results in a lack of understanding between the organizations involved over the measures implemented. This is frequently compounded by the construction of small-scale defences by seafront residents in attempts to protect properties from coastal flooding and erosion. The involvement of numerous groups in provision of coastal defences means a comprehensive overview of a city’s strategy is often lacking.

The level of protection offered by coastal defences is often not presented in the form of a recurrence interval storm but as a defence height which is very problematic to convert to a SoP because the parameter is dependent on multiple criteria. As a result, the level of protection offered by coastal defences in each port city is difficult to compare.

Another limitation of this study was that many documents describing local defences are likely to be written in the native language. Due to the small team working on this project, it was not possible to translate many documents; this consequently excluded the use of

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities many potentially useful documents. The findings of this report could easily be enhanced and improved with the assistance of experienced coastal engineers with foreign language skills and experience worldwide.

It is also difficult to obtain information relating to the continuity of defences. Although information may be available to describe the SoP offered or defence height, often little information exists to describe the portion of the city which is defended. It appears to be quite rare for a city to implement a coastal defence which systematically protects the entire city to the same level – such as the case of the Thames Barrier and associated protective measures in London. It is more common for defences to offer protection to a certain locality while neglecting other areas.

In some cases, the reliability of SoP data is also questionable. For example, most

Vietnamese sea dikes are based on loads with a return period of 20-25 years. In 1996 however, Dutch engineers noted the true probability of failure exceeds by far the design frequency and were in fact more likely to fail almost every year (Mai et al., 2008). This is often the result of return periods not being appropriately based on statistical risk. Return periods are often adopted on a rather arbitrary basis (Vrijling et al., 2000). Conversely,

SoP may actually be higher than advertised at other locations due to consideration of factors such as dike settlement, SLR and wind gusts.

4.5 Discussion

4.5.1 Coastal Adaptation Measures Applied

Through the investigation of coastal defences and adaption measures applied in the world’s large port cities it is apparent that responses to the threat of coastal flooding and erosion vary considerably between cities. Such responses may include structural defences such as embankments, surge barriers and seawalls, land use policies so as to avoid inappropriate development of hazardous areas and careful preparation of emergency procedures to manage such hazards when they occur. A comprehensive database of the coastal adaptation measures applied and significant amounts of supplementary information are supplied in the accompanying Excel database available on the AVOID Stakeholders website. For an overview of the availability of information on specific ports, see Appendix VII.

Large amounts of information are available regarding coastal flood defences globally; however, this information appears to concentrate quite heavily on a small number of countries or locations. The available information appears to preferentially focus on those locations where comprehensive flood defence systems exist (such as the Netherlands or

London). Despite consulting a wide variety of sources, it was incredibly difficult to find information relating to coastal adaptation measures in numerous port cities; this lack of data suggests that the information is either not in the public domain, was not in an accessible language or alternatively, does not exist. A lack of information in less developed countries could also suggest an absence of comprehensive flood protection policy.

In order to provide consistent information on flood defence policies and other measures it is recommended that coastal communities delegate responsibility for collecting data on the coastal flood and erosion management projects undertaken at different localities.

Such an approach would provide clear records and would also mean data on the level of

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities protection offered would be easily accessible from one point of contact. The current situation in many cities leaves separate organisations in charge of different aspects of coastal flooding and often means no single organisation has a complete idea of the flood risk to a given city.

Differences in the adaptation measures applied are very interesting. Whilst many cities employ structural defences to protect populations and assets, planning and emergency preparedness are not to be underestimated as responses to coastal flooding. In New

Zealand, there is heavy emphasis on removing people and assets from the hazard zone with coastal protection works only considered as a last resort (New Zealand Coastal

Policy Statement, 1994). In New York, the current approach is to plan to be flooded rather than to prevent flooding (Hill, 2008); the city has invested most of its efforts in emergency management such as storm tracking and notification, evacuation and sheltering of the public, public information and recovery and restoration (NYC Office of

Emergency Management, 2006). Similar measures appear prevalent in Bangladesh where cyclone shelters are an important adaptation measure which has helped to reduce the number of casualties during storm surges (Akhand, 1996).

Whilst considering the protection offered by structural measures and planning measures it is also important to note the effectiveness of the two approaches under conditions which exceed the SoP. In this scenario, physical defences such as embankments and seawalls are considered less safe than planning measures which avoid development below a given flood water level. The consequences of a flood in excess of the design standard will have greatly differing results, as shown in Figure 4.9.

A B

C D

Figure 4.9: Differing levels of safety offered by structural (A & B) and planning (C & D) approaches to flood defence in the presence of a flood event in excess of design standard

Figure 4.9 clearly demonstrates how planning measures (C and D) offer a greater level of protection in the event of floods in excess of the design standard. In addition,

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities planning measures are not susceptible to the additional risk of defence failure from mechanisms other than overtopping. In contrast, structural measures are potentially subject to slope sliding and damage, piping, erosion and overtopping (Ministry of

Transport, Public Works and Water Management, 2005).

With future SLR, the levels of protection offered by existing coastal adaptation measures will reduce. In addition, socio-economic scenarios are likely to increase the population and assets at risk of coastal flooding in the future (Nicholls et al., 2008). Therefore, maintenance or improvement of the current levels of protection offered by these measures into the future requires standards to be raised by a value in excess of SLR.

4.5.2 Performance of Demand for Safety Functions

This study provides one of the first opportunities to validate demand for safety functions which have previously been used to suggest applied SoPs in the absence of available data. In the vast majority of cases, demand for safety over-estimates the applied SoP.

This is not a rigid rule however; some levels of protection are estimated correctly and still more have been under-estimated. From this analysis it is clear that demand for safety does not consistently over- or under-predict applied SoPs but the decision to apply a given SoP must also be influenced by factors outside of the consideration of the demand for safety function.

Until now, studies have applied the values provided by demand for safety functions without knowing entirely how accurate these values were. It has been suspected that this approach tends to overestimate protection standards in comparison to reality, especially in many poorer countries (Nicholls et al., 2008). Using the values obtained through this research it is possible to validate the function and assess why given countries chose to apply defences which offer protection in excess of demand for safety or measures which fall short of this level. Such factors are investigated in detail in

Section 4.5.3.

From this analysis it is clear that many factors in addition to wealth, population density and surge regime, as considered by demand for safety functions, play important roles in determining the SoP to be applied in coastal cities. These are now addressed in Section

4.5.3. As a result of the numerous influencing factors, calibration of the function is not straight forward. Additional factors appear to be important to differing degrees in differing locations which further complicates calibration.

4.5.3 Factors Influencing Applied Standards of Protection

From Section 4.3 it is clear that the applied levels of protection in the world’s large port cities is highly variable and the decision to apply defences of a given standard is obviously also affected by a number of factors in addition to GDP, population densities and surge regime. Such potential factors are now addressed below.

Recent occurrence of flood events appears to be a very significant factor in the decision to apply given SoPs. It is well known that people tend to forget about the risk if a flood event has not occurred recently (Jorissen et al., 2000). The examples of London, the

Netherlands and Hamburg illustrate this point excellently. Both London and the

Netherlands were severely affected by the North Sea flood of 1953, causing extensive damages and deaths. The decisions to commence the Thames Barrier and Deltaworks projects in London and the Netherlands respectively were direct consequences of this

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities event with both projects providing comparatively high standards of protection. Similarly,

Hamburg was hit by a significant storm surge event in 1962 which caused severe damage along the entire North Sea coast of Germany, the destruction of many dikes in

Hamburg and around 300 deaths (von Storch et al., 2008). This event also led to massive investments in coastal defences for the city (von Storch et al., 2008) and consequently a high SoP.

In contrast, the city of New York has implemented no comprehensive coastal defence system and currently has a nominal SoP of approximately the 1 in 100 year surge. This decision is likely to be influenced by a lack of recent catastrophic events in the city and the fact that disruptive coastal flooding such as the 1962, 1991, 1992 and 1993 nor’easters are quickly forgotten (Hill, 2008). Despite this observation, other factors are clearly also important; New Orleans still only intends to provide a 1 in 100 SoP (USACE,

2010) despite the occurrence of Hurricane Katrina in 2005 with a final death toll of well over 1,000 (Catalano, 2007).

As stated in Section 4.3, the exposed population and exposed assets are likely to be an important factor in determining the level of defence to apply against coastal flooding in port cities. As shown in Table 4.4, Helsinki was found to offer protective measures against coastal flooding well short of the demand for safety. This is however linked to the population level exposed to the risk and also the value of assets exposed. Nicholls et al. (2008) showed that Helsinki was ranked low in terms of exposure to both. As a result of this low exposure, it appears that the level of defence offered has been tailored accordingly.

The relative and absolute importance of flood defence to a location is another reason for varying levels of protection. In the Netherlands flood defence is a matter of national importance and large flood events would have the capacity to seriously disrupt the entire country. As such, flood defence is a national priority (Jorissen et al., 2000) and correspondingly high levels of protection are afforded.

Cultural factors are well known to play an important role in deciding the SoP to apply against flooding. ‘Flood’ is a relative concept and varies amongst cultures and individuals in its perception and understanding (Green et al., 2000). In many cases, societies may be well adapted to flooding as a result of cultural factors and may even expect annual floods to occur. This expectation and subsequent adaptation to live with the effects of flooding means implementation of elaborate physical flood protection structures is unnecessary. Despite this, distinctions should be made between floods for which a society has adapted and those which represent abnormal or unwanted flooding which causes loss (Paul, 1984).

Another important control which is likely to affect decisions on the level of protection to be offered is the political background of a country or region. A comparison between the

Netherlands and Denmark can be shown as an example. In the Netherlands flood legislation is prescriptive; protection levels are legally prescribed, providing a very solid base for flood defence (Jorissen et al., 2000). In Denmark however, coastal flood defence is based on permissive legislation, as such there is no legal obligation to provide flood defence measures and this type of project often has to compete with other local expenditure needs for resources (Jorissen et al., 2000). By comparing these two cases it can be seen that prescriptive standards are non-negotiable and are likely to provide high levels of protection. Permissive legislation on the other hand means flood

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities defence projects can be based upon economic efficiency and are likely to be much more variable in the level of protection they offer.

Finally, the sources of funding for flood defence schemes are an important determinant of the level of protection which they are able to provide, this is independent of country wealth as measured by per capita GDP. For example, large and comprehensive protection structures such as the embankment system and surge barriers protecting

London cost hundreds of millions of dollars. Such systems will be unaffordable if it falls upon private stakeholders to protect their interests. As a consequence, SoPs are likely to be low in developing countries where no centralized authority exists for flood protection. However, such a situation is also known to exist elsewhere in the developed world, for example, a large portion of the Virginia Beach seafront in the US is protected from coastal erosion by privately constructed bulkheads in an attempt to protect private properties (Reohrs, pers. comm, 2010).

The preceding paragraphs are by no means a definitive inventory of the factors which are likely to influence decisions on the level of protection to offer a given city. However, this breakdown should highlight some of the more important factors which impact this decision.

4.5.4 Future Research

It is clear that in order to move from a vulnerability based approach to a risk based approach we need to have reliable information on SoPs from coastal flooding. The timeframe of this project meant it was not possible to collect information on all 136 cities.

However, it is hoped that collection of this information will be an ongoing process.

The database presented in the accompanying spreadsheet provides a strong starting point upon which future studies can elaborate in order to compile a full and comprehensive database of coastal protection measures in port cities. It may also be interesting to expand the current selection criteria of coastal cities to include important port cities with populations below 1 million or those large and important coastal cities without ports.

It has been seen that many cities simply have no publicly available information on the measures to combat coastal flooding and erosion. Tables 4.1 and 4.2 highlight cities known to be at risk of coastal flooding and those known to be at minimal risk but even now, little is known about the cities not named in these tables. It is highly important to address this in future through targeted research of cities where little is known. If possible, the most complete way of achieving this would be to make detailed surveys of the cities although this approach is likely to be prohibitively expensive.

The foundation of this study has also made it possible to move from exposure analysis toward risk analysis. Detailed studies of key cities are now required to gain an understanding of the population and assets at risk. It is suggested that Table 4.1 be used to target future research toward those cities where coastal flooding is known to be a significant issue.

Of high importance is finding a reliable method of converting defence heights to SoPs; in the majority of cases direct SoP estimates are unlikely to be available and only defences heights will be obtainable. This was not possible in this study due to a lack of available and easily accessible information and due to time constraints. Such a methodology would need to account for the multiple criteria to which SoPs are sensitive including

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities extreme water levels and wave heights. If such a methodology can be derived, it will also be possible to evaluate existing SoP estimates where both types of information exist.

Finally, future research should also focus on calibrating the demand for safety function in order to produce estimates of SoP which are closer to those applied in reality. Such research must focus on accounting for those factors named in Section 4.5.3 to some degree in a similar way to which wealth, population density and storm surge regime are currently accounted for. If this can be achieved it should be possible to apply such a function to locations where no SoP data exists.

4.6 Summary

In many cases it was difficult to ascertain the SoP offered by existing natural and artificial defences due to a lack of information in the public domain. Limited information availability appears to be a recurring theme throughout this study, having already proven problematic when estimating losses from coastal flooding and searching for coastal defence unit costs in Sections 2 and 3 respectively.

Estimates of SoP given in this study were extracted from a diverse range of sources.

Because relevant information is held in such a variety of locations the identification of all possible information sources can be problematic and time consuming.

Where information is available, it is clear that applied SoPs are highly variable between cities and in some cases, within cities. In addition, a wide range of responses to coastal flood risk are apparent ranging from hard and soft engineering options to policy decisions and emergency planning.

The reasons for applying different levels of protection are wide ranging and are likely to be influenced by the following:

•

Wealth

•

Exposed population/assets

•

Recent flood experience

•

Relative and absolute importance of flood defence

•

Cultural factors

•

Political background

•

Sources of funding

Despite assumptions of a link between wealth (as measured by GDP/capita) and the level of protection applied (Nicholls et al., 2008), the findings of this study indicate that there is no solid relationship between the two factors. Both relatively wealthy and poor countries have been shown to apply high levels of protection for differing reasons. In addition, some relatively wealthy cities have applied surprisingly low SoPs.

Many cities with high exposed populations have been shown to have low levels of protection. This is particularly worrying as large numbers of people are therefore at risk of flooding.

The performance of demand for safety functions was assessed. It was found that these functions typically over-estimate applied SoPs in agreement with the suspicions of

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Nicholls et al. (2008). However, some exceptions occur and in these cases, populations may be termed risk averse.

It was not possible to calibrate the DIVA demand for safety function due to the wide range of often unquantifiable factors influencing the decision to protect against coastal flooding. However, it is hoped that the function can be modified in future to produce more reliable results. Factors that have been shown as important in determining optimal levels of protection are the number of inhabitants in a potentially flooded area and the defence system length (Hillen et al., 2010). Investigation into how these factors can be incorporated into DIVA is now advised.

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5.0 DISCUSSION AND CONCLUDING THOUGHTS

Looking at history, it seems clear that populations largely prepare for flooding only after the occurrence of disastrous events. This appears to be the case in London, the

Netherlands and Hamburg. In order to avoid such events however, it is important to begin planning for them today because effective coastal engineering projects have long lead times (Hanson et al., 2010). As coastal flooding becomes more frequent with climate change, these delays will become increasingly intolerable (Hill, 2008).

Preparation for extreme flood events is essential in those cities with both high exposed populations (Nicholls et al., 2008) and low levels of protection. Adaptive measures in these cities are likely to provide the greatest returns on investment through the preservation of human life. The cities of New Orleans, New York, Miami, Kolkata,

Mumbai, Ho Chi Minh City and Guangzhou are highlighted here as a priority due to low applied levels of protection and high exposed populations. However, cities for which data was unavailable may provide similar cases.

A severe lack of information provided a significant barrier to comprehensively achieving all objectives set out in this project. Nevertheless, extensive databases describing the following have still been compiled. This information is available through the appendices in this report and via the accompanying Excel database which can be found on the

AVOID Stakeholders website ( www.avoid.uk.net/private2/ ).

•

Depth-damage curves applied worldwide

•

Unit costs of coastal adaptation measures

•

Applied SoPs in port cities

•

Corresponding adaptation measures in port cities

Collation of these databases was a painstaking task but the information gleaned can now be applied in future studies into costs of adaptation. It is also hoped that these databases can be enhanced by future studies.

This study has produced methodologies for estimating flood losses in both domestic and non-domestic buildings through the application of carefully selected, existing depthdamage curves and empirically based assumptions. This is a step forward in the estimation of flood losses which until now have comprised a suite of depth-damage curves with little guidance on how to scale up to provide a global overview. The approach will allow the generalisation of flood loss results to make broad assessments of potential flood losses from climate change. This is a significant result as the estimation of flood losses is an essential part of determining the optimum level of protection against flooding.

Costs of adaptation measures have also been assessed. Despite a lack of information, unit costs for coastal adaptation measures have been assembled for a number of countries. This is one of the first unit cost databases to be compiled using real life unit cost data. The collection of this information has allowed comparison of these costs against widely used cost estimates currently used in the absence of direct data.

Comparison of beach nourishment costs with estimates from both IPCC CZMS (1990) and DIVA broadly support the use of these methodologies although some underprediction of costs occurs indicating the full range of influences is not accounted for.

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Dike heightening costs were compared with estimates from IPCC CZMS (1990). The analysis showed both under- and over-prediction of costs. Under-prediction is likely a result of individual project complexities and over-prediction in the case of New Orleans is likely to be caused by the use of inappropriate country factors. Further crude comparison of actual unit costs for dikes with estimates from Hoozemans et al. (1993) suggests that Hoozemans et al.’s (1993) methodology over-predicts unit costs, although this now requires further investigation.

This investigation has highlighted the possibility that previous global vulnerability assessments (IPCC CZMS, 1990; Hoozemans et al., 1993) have over-estimated the costs of adaptation by assuming the uptake of only Dutch engineering solutions; despite this, the costs of adapting are still likely to be significant.

This study has also highlighted the wide range of adaptation options available to deal with coastal flooding and erosion as well as the wide ranging levels of protection offered to coastal cities. This involved the collation of a comprehensive database describing existing coastal adaptation measures and the applied levels of protection in port cities.

Again, this is one of the first such databases to be produced and will provide a useful source of information in future studies.

DIVA’s demand for safety procedure was compared against actual SoPs with mixed results. Although over-prediction by the function is widespread, under-prediction is not unknown. Clearly, numerous factors in addition to those accounted for by econometric functions are important in the decision to apply a given SoP.

This analysis has focussed on a global scale approach. It is very likely that as more localised scenarios are considered, smaller details will become important as a control upon flood losses, the costs of adaptation and the exact level of protection applied.

Nonetheless, this study has provided an indicative assessment of the costs of adapting to climate change which the authors hope can now be built upon by focussed studies in cities at risk.

Given the importance of adapting to climate change, ensuring the availability of information to fully assess the future costs of adaptation is essential. As such it is important that the holders of such information begin to make it widely accessible. The costing of adaptation to climate change should be a high priority given that the protection of cities is expected to be a major cost of accelerated SLR (Turner et al., 1990).

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APPENDIX I:

Coastal defence cost estimates

Case study of the Netherlands, New Orleans and Vietnam

Delft University of Technology, in cooperation with Royal Haskoning

April 2010

M.M. Hillen MSc (Royal Haskoning), S.N. Jonkman PhD (DUT), W. Kanning MSc

(DUT), M. Kok PhD (DUT), M.A. Geldenhuys BSc (DUT-COMEM) and prof.

M.J.F. Stive (DUT)

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1 Background and objective

Background

A large and fast-growing part of the world’s population lives in low-lying coastal zones.

To sustain economic activities and living in these areas a wide range of coastal defence measures has been constructed. These coastal defence measures reduce the risk to economic values and populations in coastal zones prone to flooding. Coastal defence measures can even help to enable living in areas that are below sea level, for example in parts of the Netherlands and New Orleans.

Climate change, and more specifically sea level rise, poses a direct threat to these areas

(Ericson et al., 2006; Nicholls et al., 2008). Sea level rise requires the coastal defence measures to be adapted to higher water levels and more intense hydraulic boundary conditions (such as waves and storm surges). The exposure of coastal zones and especially coastal cities to flooding was determined by Nicholls et al. (2008). However the risk of flooding and the costs of adaptation to sea level rise are greatly influenced by coastal defence measures. The study of Linham et al. (2010) builds upon Nicholls et al.

(2008) to determine the risk and impact of flooding in port cities.

Objectives

This study is part of a global study on the costs of adaptation to the effects of climate change (Linham et al., 2010). It adds information from three specific case studies (the

Netherland, New Orleans and Vietnam) to the global study. The case study areas are comparable by type of coast; all are low-lying deltaic coastal areas. This study investigates the unit cost estimates of coastal defence for the full range of hard and soft engineering measures, such as dikes/levees, sea walls, (beach) nourishments and other measures, for example storm surge barriers.

In considering the costs of coastal defence and adaptation to climate change different scale levels can be recognized (see Figure A1.1). At the highest level of detail specific information from actual projects and designs can be utilized. This requires detailed insight in the actual design and as built status of coastal defence projects. By combining information from individual projects, cost estimates can be provided for one enclosed coastal defence system, e.g. a dike ring or polder in the Netherlands or New Orleans.

Cost estimates at a national level can be obtained by aggregating information from different defence systems. For example, Kok et al. (2008) report estimates of the costs of adaptation of the flood defences in the Netherlands to different levels of sea level rise.

This is done by combining assessments of the response of different sub systems and dike rings to the sea level rise (see also section 2.1). Finally, estimates for different systems and countries can be aggregated to cost estimates at a regional, continental or even global level.

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities global

Level of detail country

Coastal defence system project

Figure A1.1: Different levels of detail for coastal defence cost estimates

This study largely focuses on cost estimates at the project and system level, whereas previous studies (e.g. IPCC CZMS, 1990; Hoozemans et al., 1993) provide global estimates. The project and system based estimates can be used as input for the cost estimates at higher levels. The coastal defence cost estimates in this study are derived from several studies conducted by the authors for the case study areas considered.

In addition to the three case studies for the Netherlands, New Orleans and Vietnam, another case study has been included in this research. M.A. Geldenhuys BSc studied the unit cost prices of coastal defence measures for Cape Town (South Africa) and this work was conducted as part of the COMEM MSc program at the Delft University of

Technology. The results are included in Appendix II of this report and the main results and unit cost prices are also included in the main report. This is an interesting comparison, as the three case studies (the Netherlands, New Orleans, Vietnam) are lowlying deltaic coasts, whereas the coast of Cape Town is more variable in terms of elevation, protection and coastal management strategies.

Structure of this report

This report is structured as follows. Section 2 provides a summary of relevant information for the three case studies. A summary of the coastal defence cost estimates is given in section 3. This section also includes a discussion of relevant aspects, such as the relationship between the sea level rise rate and the unit cost prices. Section 4 reviews various studies for the three case studies that give insight in the optimal standard of protection. The most important conclusions and recommendations are given in section 5.

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2 Case study areas

This study focuses on three study areas: the Netherlands, the city of New Orleans

(United States) and Vietnam (Figure A1.2). These three areas are all subjected to the risk of coastal flooding. The case study areas have a similar type of coast, a low-lying deltaic coast, and are all affected by sea-level rise.

This chapter gives a brief introduction of each case study area. The history, geography and coastal defence measures of the area concerned are described. Furthermore the studies as conducted by Delft University of Technology are introduced and the main relevant literature is discussed. For each case study area the cost information on coastal defence measures is provided and unit cost prices are derived.

Next to the overview of coastal defence measures and the main characteristics of the case study area, the background of the cost data is given. This provides insight in the background of the quantitative data and how to interpret these results.

Chapter 2.1 describes the Netherlands, in chapter 2.2 the New Orleans case study is described and chapter 2.3 concerns the case study of Vietnam.

Costs are provided in euro (€), where US$ were used in studies a conversion rate of 1€

= 1.35 US$ was applied.

Figure A1.2: World map with case study areas

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2.1 The Netherlands

2.1.1 Background, history

The Netherlands, situated in the North-West of Europe, is a low-lying coastal zone of which the Southern coastline is largely formed by a delta of three European rivers; the

Rhine, Meuse and Scheldt. About one-forth of the country is below sea level and half of the country is situated below less than one meter above mean sea level. In the current situation 65% of the Netherlands is prone to flooding (this includes river-flooding).

The history, existence and the present day landscape of the Netherlands has been primarily influenced by water. Flooding events have shaped the Dutch landscape and efficient water management has shaped the country’s organization: the water boards are the oldest democratic organization in the Netherlands (13 th century). Through land reclamation by polders, a combination dikes and drainage, the Netherlands was shaped, continuously balancing natural processes and human needs. More in general, the polder concept as applied in the Netherlands can be considered a way to live in a delta; it is the result of a continuous optimization to live and cultivate the land on the one hand and sustain economic activities by controlling the water on the other.

In the current situation a flood defence system is in place to protect most of the

Netherlands from flooding. This system consists of several flood defence measures; dikes, storm surge barriers and several management systems such as dike rings and beach nourishments. Large well-known coastal defence structures in the Netherlands are the Afsluitdijk (direct translation: ‘Closure dike’) which closed off the tides of

Zuiderzee (former sea, adjacent to the Wadden Sea) and the Deltaworks, an extensive system of dikes and storm surge barriers which protects the South-Western delta after the catastrophic flooding of 1953. The strategy to dam rivers and close off estuaries which shortens the coast line and the length of flood defences (Figure A1.3) has been regarded an effective coastal defence strategy. Nowadays the Dutch flood defences have safety standards up to 1/10000 years (Figure A1.4); e.g. these defence measures can withstand a flooding event with a 1/10000 year frequency.

106


Figure A1.3: Shortening of the coastline of the Netherlands over time (Kok et al., 2008)

Figure A1.4: Dike-ring areas and their corresponding safety standards in the

Netherlands

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2.1.2 Coastal defence measures

As mentioned above, the coastal defence system of the Netherlands consists of several coastal defence measures. The dike ring areas along the coasts have two different safety standards (1/4000 and 1/10000) and are closed systems consisting of dunes, sea dikes and storm surge barriers on the sea side. In addition to these coastal defence measures, beach nourishments are applied along the Dutch coastline, which help to sustain the sandy beaches and dunes (Figure A1.7).

Figure A1.5: Examples of sea dikes in the Netherlands (photos: Royal Haskoning)

Figure A1.6: Cross-section of a typical sea dike

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Figure A1.7: Beach nourishment in the Netherlands (www.rijkswaterstaat.nl)

2.1.3 Cost estimates

For the Deltacommittee Kok et al. (2008) investigated the sustainability and financial durability of the Dutch polder concept. The technical feasibility of the polder concept was investigated; e.g. is it possible to maintain the polder approach with climate change by keeping the current system of water defences in place? Also alternative strategies and other measures were researched: reduction of flooding impact, alternative enhancements of the flood defences and a different approach for the polder concept.

The costs to maintain the current safety standards with sea level rise and the costs to adopt higher safety standards with sea level rise up to 2200 were investigated for the primary water defences of the Netherlands. The costs mainly concern raising dikes, construction of new (or strengthening of) storm surge barriers and maintenance of the coastal defence measures.

Dikes

Kok et al. (2008) based their estimates on several studies conducted for the

Rijkswaterstaat (Ministry of Public Works). These studies investigated the safety standards of dike ring areas. Arcadis and Fugro (2006) conducted such a study for three dike ring areas along the coast and the Central Planning Agency (CPB) of the

Netherlands did investigate these standards in the same time period (Eijgenraam, 2005;

2006) for a larger number of dike rings, including river dikes.

The cost estimates to raise the sea dikes are presented in Table A1.1 (Arcadis and

Fugro, 2006) and Table A1.2 (Eijgenraam, 2005). The cost estimates of Eijgenraam

(2005) were found to be linear with the dike heightening (Figure A1.8).

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Table A1.1: Cost estimates of three coastal dike-ring areas (Arcadis and Fugro, 2006)

Dike heightening

[m]

0.8

1.6

2.4

Arcadis and Fugro (2006)

North Sea dikes Western Scheldt dikes

[M€/km]

4.36

5.82

7.3

[M€/km]

4.46

6.37

8.28

Averaged

[M€/km]

4.41

6.095

7.79

Table A1.2: Cost estimates of coastal dike-ring areas (Eijgenraam, 2005)

CPB Cost estimates (Eijgenraam, 2005)

Dike ring number

15

16

22

23

24

35

Name

Lopiker- en Krimpenerwaard

Alblasserwaard en Vijfheerenlanden

Eiland van Dordrecht

Biesbosch (Noordwaard)

Land van Altena

Donge

Average costs

6.8

8.5

6.6

2.5

3.5

4.7

5.4

0.5

Dike Heightening

0.75 1

[M€/km]

8.9

11

8.4

3.2

4.7

6.4

7.1

11.1

13.3

10.2

4.3

6.1

7.9

8.8

10,0

8,0

6,0

4,0

2,0

0,0

0 0,2 y = 6,7667x + 2,0417

0,4 0,6 0,8 dike heightening [m]

Averaged costs function coastal dike rings

Linear (Averaged costs function coastal dike rings)

1 1,2

Figure A1.8: Averaged cost function of coastal dike-ring areas (Eijgenraam, 2005)

Nourishments

Due to the availability of nourishment material and the large amounts of beach nourishments in the Netherlands the costs of nourishments in the Netherlands used to be relatively low. Arcadis and Fugro (2006) estimated these costs to be 2.85 euro per m 3 , where Kok et al. (2008) used a slightly higher number: 3 euro/ m 3 .

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However, both the Ministry of Transport, Public Works and Water Management (RWS,

2009) and the Algemene Rekenkamer (2009) (‘court of audit’) noted that the costs of nourishments in the Netherlands have increased rapidly over the last five years (Figure

A1.9).

Figure A1.9: Price development nourishments in the Netherlands (RWS, 2009)

In the Netherlands more nourishments are required in the coming years and the

Deltacommittee (2008) anticipates even larger amounts of sand are needed in the (near) future. Therefore, at the Ministry of Transport, Public Works and Water Management

(RWS, 2009) there is a concern about the current price development of nourishments.

Due to the current market situation; e.g. the limited number of large contractors available, the international market-prices and the large increase in demand the prices of nourishments have increased significantly. The Algemene Rekenkamer (2009) informed the Dutch parliament about this situation in a letter (Algemene Rekenkamer, 2009).

Structural increase in cost prices from 2004 till 2009 (in 2009 price level) as determined by RWS/ Ministry of Transport, Public Works and Water Management (2009):

•

Foreshore nourishments: from €1.11 to €3.72 (Figure A1.10)

•

Beach nourishments: from €2.54 to €7.55 (Figure A1.11)

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Figure A1.10: Price development foreshore nourishments in the Netherlands (RWS,

2009)

Figure A1.11: Price development beach nourishments in the Netherlands (RWS, 2009)

Maintenance

The yearly costs for management and maintenance for primary flood defences in the

Netherlands is estimated to be approximately € 350 million per year (AFPM, 2006). With a total length of primary flood defences of about 3600 km the estimated costs for management and maintenance become € 100,000 per km flood defence per year.

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Unit costs and relation to sea level rise (Kok et al., 2008)

Table A1.3 provides an overview of the unit cost prices as applied for the Netherlands.

Table A1.3: Overview cost estimates the Netherlands

Dike (Millions € per km)

Beach Nourishment (€ per m

3 material)

The Netherlands


•

9 – 10.8 (rural) (Kok et al., 2008)

•

18 – 21.6 (urban) (Kok et al., 2008)

•

•

4 – 11 (rural) (Eijgenraam, 2006)

6.9 (rural) (Fugro and Arcadis, 2006)

•

13.8 (urban) (Arcadis and Fugro, 2006)

•

•

•

•

•

2.3 – 6.7 (Stive, pers. comm., 2009)

3 (Kok et al., 2008)

2.85 (Arcadis and Fugro, 2006)

3.72 (Foreshore nourishments) (RWS, 2009)

7.55 (Beach nourishments) (RWS, 2009)

0.1 M€/km flood defence/year (AFPM, 2006) Maintenance

Kok et al. (2008) applied these cost prices to determine the costs of sea level rise for the

Netherlands. Therefore several factors need to be applied to the unit costs to determine the costs of the coastal defence system. These factors include the length of the coastal defences, the cost of storm surge barriers (section 2.4) and the costs of beach nourishments. Also the required height of the defence measures was determined based on its relation with sea level, by several conversion factors. As shown in Table A1.3, a different unit cost for rural and urban areas was applied. The results of this exercise are shown in Figure A1.12 A1.12, depicting the contribution of several aspects of the coastal water system.

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160

140

120

100

80

60

40

20

0

0

Sandy coast

Storm surge barriers

Sea dikes

Total

1 2 3

Sea level rise [m]

4 5

Figure A1.12: Cost function of coastal water system (Kok et al., 2008)

6

2.2 New Orleans (U.S.)


New Orleans is situated in the delta of the Mississippi River (Figure A1.13). The city originated at the natural levees (higher grounds) along the Mississippi river. On the North side the city bounded by Lake Ponchartrain. Over time New Orleans gradually expanded into the marsh area in between the Mississippi river and Lake Ponchartrain and from the

West Bank of the river further to the South.

Figure A1.13: Location of New Orleans in the state Louisiana of the United States

(Wikipedia)

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Currently, the city and its surrounding suburbs make up a metropolitan area that is partly below sea level and entirely surrounded by levees (American synonym for dikes). Since a large part of the city is below sea level (around 50%), with an average elevation between one and two feet (0.5 m) below sea level the area has a polder character and can be considered a bowl in between high waters (river and lake; see Figure A1.14).

Figure A1.14: Geological cross-section of New Orleans

(www.tulane.edu/~sanelson/Katrina/katrina_images.htm)

Because New Orleans is constructed on marsh area, large parts of the city continue to sink. The soft sand, silts and clay beneath the city settle over time because of natural consolidation but also groundwater pumping. The marsh area around the city also shows subsidence and due to the lack of sediment input from the river, this area deteriorates at a high rate.

As a consequence of its geographical situation, the area is vulnerable to flooding from hurricanes, high discharges of the Mississippi River and heavy rains. Large-scale pumping systems are installed for dewatering the city from rainfall and levees along the river, Lake Ponchartrain and the marsh areas of the Mississippi delta protect the city from storm surges. The vulnerability to flooding from hurricanes was tragically shown when 80% of the city flooded when it was hit by hurricane Katrina in 2005.


The New Orleans area consists of three levee rings (Figure A1.15) and has a safety standard of a 1/100 year storm surge. These levee rings are constructed of Mississippi river levees along the Mississippi river (considered outside the scope of this study), hurricane levees along Lake Ponchartrain (Figure A1.16) and the marsh areas on the

South and East and storm surge barriers (under construction). In the city levee ring (#1) several outfall canals are constructed which used to be in direct contact with the waters of Lake Ponchartrain. Along these canals floodwalls are constructed (see Figure A1.16).

New Orleans is situated in the Mississippi delta and the surrounding areas are marsh areas. These wetlands can be regarded as a natural storm surge defence system, since the marshes cause storm surge energy dissipation. The costs of these areas are hard to determine, however, marsh-creation and marsh-restoration costs can be estimated.

115


Figure A1.15: Levee rings New Orleans (Dijkman, 2007)

Figure A1.16: Lakeview levee and outfall canal floodwall (photo: Royal Haskoning)

Figure A1.17: Schematic cross-section New Orleans levee (Dijkman, 2007)

116



Floodwall

In New Orleans often concrete floodwalls are constructed on the top of levees to heighten the levee (Figure A1.18). After the flooding of hurricane Katrina in 2005 many floodwalls needed to be reconstructed. The data on the costs of these constructions varies due to different construction methods, but due to the reconstruction some construction cost data was available.

Figure A1.18: Two types of New Orleans floodwalls: T-Wall (left) and I-Wall (right)

(Tulane, 2008)

Bos (2008) used costs of different types of concrete floodwalls to determine the optimal safety standard of the New Orleans East polder (Figure A1.15, #2). The costs were derived from historical construction costs. To determine the unit costs, the costs of floodwall per m heightening were derived in this study (Table A1.4).

117


Table A1.4: Overview of costs of different type of floodwalls (Bos, 2008) costs

Type of floodwall $/Ft €/m

7-Foot High L-Wall with 6-Foot Wide Monoliths 3200 7874

M€/km

7.87 height

(m)

2.13

8-Foot High T-Wall with 8-Foot Wide Monoliths 3400 8366 8.37

10-Foot High T-Wall with 8-Foot Wide

Monoliths


Monoliths

4100 10089 10.09 3.05

5100 12549 12.55

2.44

3.66

14-Foot High L-Wall with 11-Foot Wide

Monoliths


Monoliths


Monoliths


Monoliths


Monoliths


Monoliths


Monoliths


Monoliths


Monoliths

6300

7000

8300

9900

15502 15.50

17224 17.22

20423 20.42

24360 24.36

10800 26575 26.58

12200 30020 30.02

14600 35925 35.93

15500 38140 38.14

16800 41339 41.34

4.27

4.88

5.49

6.1

6.71

7.32

7.92

8.53

9.14

3.31

3.43

3.63

3.53

3.72

3.99

3.96

4.1

4.54

4.47

4.52 in

M€/km per m heightening

3.7

3.43

Hurricane levees

The costs of sea dikes (hurricane levees) are based on the Dutch perspective on coastal

Louisiana study (Dijkman, 2007), conducted by a team of experts from the Netherlands as part of the Louisiana Coastal Protection and Restoration planning and technical effort

(LACPR).

The main design principle used is an earth fill levee body with a flexible asphalt protection cover on top. This design allows for flexibility in settlement and can safely deal with considerable wave overtopping without the risk of a levee breach. Redundancy in the design (applied as flexible asphalt protection) aims to reduce the possibility of a catastrophic breach in a levee in case of wave overtopping or surge overflow. This design consideration will result in strong and redundant structures, but also in relatively costly levees.

The main dimensions of the levee have been derived from the surge level and the wave conditions. Slopes of 1:6 have been chosen at the surge side. Such slope is costeffective for wave energy dissipation. The inner slope is chosen at 1:4, which is a safe value considering overflow and soil mechanical stability.

The proposed levee construction principles for upgrading existing of Dijkman (2007) are identical to the principles applied for the design of new levees. Dijkman (2007)

118

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities determined unit cost prices for New Orleans levees to be 5 to 8 million euro per kilometer for a meter dike heightening.

The focus in the Dutch perspective study is on so-called levee-rings (Figure A1.15). The levee rings, considered in the Dutch perspective on LACPR, consist of the following elements. Where openings are needed in such a ring (for shipping for example) a storm surge barrier is constructed.

•

The construction of new levees

•

Upgrading of existing levees

•

Constructing storm surge barriers in navigation canals

•

Construction in storm surge barriers in waterways that are currently in open connection with the Gulf of Mexico

The unit cost price of levee strengthening depends on the expected height of the levee and hence on the return period of the design water level (Figure A1.19). As mentioned above, the costs are considered relatively high, because the levees are constructed as unbreachable levees by the flexible asphalt protection. Table A1.5 provides an overview of the different levee upgrading costs and the costs for new alignment of hurricane levees for a range of return periods.

7

6

5

4

3

2

10 100 1000

Return period [years]

10000 100000

Figure A1.19: Storm surge levels along Lake Ponchartrain (after Dijkman, 2007)

Table A1.5: Levee costs for return periods as determined by Dijkman (2007)

Price [M€/km]

Upgrade existing levees

New alignment levee

Return Period [years]

50 100 500

14.5

35.7

19.2

37.8

22.6

44.4

1000

26.1

46.7

5000 10000 100000 1E+06

29.8

51.4

33.5

56.1

41.5

66.1

50

76.7

Armouring

Personal communications with Ray Devlin (Haskoning Inc.) gave an overview of the costs of levee armouring (Table A1.6). These costs reflect the averaged cost prices

119

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities quoted by armouring vendors of three types of armouring. Although they include labour, plant, and material costs, they are believed to not accurately reflect difficult site working conditions. Therefore, these numbers will probably increase once account has been taken of the large plant and restricted access required to work in very remote and inaccessible areas.

Table A1.6: Costs of armouring for levees in New Orleans (Devlin, pers. comm. 2010)

Type of armouring

Fabrics and Filled Mat

Open Mat

Concrete systems/ACB

Installation costs including labour-, plant-, and material costs

[$/SY] [€/m

2

]

16.4

33.4

126.9

14.51

19.56

11.31

Marsh restoration

In Dijkman (2007) also ecological restoration is considered, there the restoration and stabilization of marsh areas around New Orleans was considered. It is expected that these marshes reduce the wave run-up and hence reduce the flood risk. By several measures (Figure A1.20) and via fresh water diversions the marsh areas are stabilized.

For marsh restoration the following activities were expected:

The development of ridge-levees

•

•

Salt water marsh restoration

Fresh water cypress swamp creation by hydraulic fill

•

•

Fresh water cypress swamp creation by artificial polders

•

The development of structures to divert fresh water, nutrients and sediments from rivers to wetlands.

Figure A1.20: Measures undertaken for marsh stabilization (Dijkman, 2007)

Not the whole marsh restoration- and stabilization process is explained, but the costs to stabilize large marsh areas in Barataria Bay and around Lake Ponchartrain were

120

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities provided. The unit costs are derived from these costs, taking into account the one-time investments for structures to enable marsh stabilization (Table A1.7).

Table A1.7: Unit costs of coastal defence measures in New Orleans

Dike (Millions € per km)

New Orleans

Dike heigthening per m:

5 – 8 (Dijkman, 2007; Jonkman et al., 2009)

Concrete floodwall; L/T-wall type (M€ per km per floodwall height)

3.7 – 4.5 (Bos, 2008)

Marshland stabilization


•

2 (Dijkman, 2007)

Marshland creation

•

1.4 €/m

3 €/m

2

(Dijkman, 2007)

Freshwater diversion/culvert

•

10 M€ (Dijkman, 2007)

Marshland stabilization costs (€ per m

2

•

0.07 (Dijkman, 2007) per year)

Closure dam (M€ per km per m height)

Levee armoring (€ per m2)

3.7 (in water) (Dijkman, 2007)

14.5 – 19.6 (Devlin, pers. comm. 2010)

2.3 Vietnam


The Socialist Republic of Vietnam is with 88.6 million inhabitants a densely populated country in South East Asia (CIA World Factbook, 2009). From North to South the country is 1,650 kilometers in length and only 50 kilometers across in its narrowest point.

Vietnam has two major river deltas, the Red River delta in the North and the Mekong delta in the South, and a relatively long coastline, which measures 3,260 kilometers. The coastal areas of Vietnam are subject to almost yearly flooding by typhoons formed in the

South China Sea.

Many activities take place in the fertile, but also vulnerable coastal areas. The river deltas are the most densely populated areas of Vietnam and are prone to flooding from both the rivers and the sea. Although the river deltas are low-lying areas of land, all coastal land is above mean sea level. In the Northern and Southern part of Vietnam the coastal land is, from shoreline to approximately 20 kilometers inland, between 0.5 and

10 meters above mean sea level (Figure A1.21). In central Vietnam some higher areas are found.

121


Figure A1.21: Population density within and outside 10m low elevation coastal zone;

Vietnam (Columbia University; http://sedac.ciesin.columbia.edu/gpw/lecz.jsp)

The government of Vietnam wants to use the coastal zone to its fullest potential. This is illustrated by one of the objectives stated after the dike breaches in Nam Dinh province

(Northern Vietnam) in 2005. The coastal defence strategies of Vietnam with respect to sea dikes, their construction and maintenance are the responsibility of a ministry and several dike departments. In total they maintain over 3,000 kilometers of coastal and estuarine dikes. A large sea dike project to review and upgrade the sea dikes of Vietnam and also formulate new guidelines for the construction of sea dikes was initiated in 2007.

122


The current state of many of the sea dikes is far from optimal and many breaches of sea dikes in the Northern coastal provinces of Vietnam showed this vulnerability.


For the Vietnam case study modern sea dikes have been investigated. In Vietnam there is no land area below sea level; dikes are constructed because of storm surges, riverand rainfall flooding and typhoon flooding.

Figure A1.22: New sea dikes in Vietnam (Nam Dinh province)

In some parts of Vietnam a tandem dike system is in place, however that system is not considered in this study. The cost estimates in this chapter are based on completely new sea dikes that have been and are constructed in Northern Vietnam in rural areas (Figure

A1.22). These dikes consist of a sand/clay body and have revetments on the sea side of the dikes. The dikes have relatively steep slopes and are constructed up to heights of 8 m. A typical Vietnamese dike profile is shown in Figure A1.23.

123


Figure A1.23: Representative cross sections of sea dikes in Nam Dinh province

(Northern Vietnam) (adjusted from Mai, 2004)


The costs of the Vietnam sea dikes were investigated to determine safety standards for the Northern provinces of Vietnam. Dike costs vary because of varying costs of material, land use and applied inner/outer protection or revetments. The costs of labour are highly variable, but relatively small and labour is often paid for by local departments – no clear insight into labour costs was obtained.

Hillen (2008) determined the costs of dike construction by data of local dike departments, cost data of stretches newly constructed sea dikes and interviews with dike departments, ministries and academic staff of the Hanoi Water Resources University.

The dike costs as presented by Hillen (Figure A1.24) represent a new type of sea dike in the Northern provinces with only sea side revetment. This concerns dikes in rural areas where land-use costs are small. The dikes did not account for wave run-up and wave overtopping. Based on dike department and ministry budgets, the yearly dike maintenance costs for a 1 kilometer dike stretch were estimated to be 20,000 €/km.

In parts of the Northern provinces experiments with mangroves are conducted. The mangroves are re-introduced at some coastal areas as a natural barrier in front of sea dikes. Since the effects of these mangroves were not yet tested and only very young mangroves were placed in wetlands in front of the sea dikes, these costs are not taken into account in this study.

124


5

4

7

6

3

2

9

8 Dike body

Land-use

Berm

Revetment

Total costs

1

0

0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9 9.5 10

Dike height [m]

Figure A1.24: Costs of dikes as a function of dike height according to Hillen (2008)

Mai et al. (2008) determined costs of dike heightening in an effort to illustrate a comparable probabilistic approach to determine safety standards of Vietnam. Mai et al. determined the safety standards for the Nam Dinh province, so this concerns dikes in rural areas. The background of his cost data is unknown, but comparable safety standards to Hillen (2008) were found. The costs of dike heightening are also comparable to the costs as determined by Hillen. Mai et al. (2008) used both outer- and inner slope protection and included the costs of maintenance in his dike costs graphs

(Figure A1.25) (Note that the costs in this figure are given in US$).

125


Figure A1.25: Dike heightening costs according to Mai et al. (2008)

The costs of the coastal defence for the Vietnam case study are based on the two previously mentioned studies. Relatively little data is available on sea dike construction in Vietnam and most of the data presented here is based on estimates, basic calculations and interviews.

Table A1.8: Unit cost estimates Vietnam

Dike heightening per meter for a kilometer stretch in

Millions €

Maintenance

Vietnam (Northern provinces: Hai Phong, Nam Dinh)

•

•

•

•

0.7 – 1.2 (Hillen, 2008)

0.75 (Mai et al., 2008)

0.02 M€/km dike/year (Hillen, 2008)

0.03 M€/km dike/year (Mai et al., 2008)

2.4 Storm surge barriers

In various locations around the world storm surge barriers have been constructed.

Famous examples are the storm surge barriers in the Netherlands (Figure A1.27) in the

Southwest of the country.

In New Orleans a storm surge barrier is being built after Katrina at the eastern side of

New Orleans to protect the city from surges and reduce the length of the directly exposed system (see Figure A1.26). Storm surge barriers are often chosen as a preferred alternative to close of the estuaries and reduce the required dike strengthening behind the dams. Another important characteristic is that they are often partly opened during normal conditions and this will allow the tide and saltwater to enter the areas behind the barrier. An overview of the main characteristics of storm surge barriers around the world is given in Table A1.9.

126


Figure A1.26: Construction of the Inner Harbour Navigation Channel/St. Bernard storm surge barrier (photo Royal Haskoning)

Figure A1.27: Maeslant storm surge barrier (near Rotterdam) and the Eastern Scheldt barrier (South-Western delta)

127


Table A1.9: Overview storm surge barriers

Name barrier

The Netherlands

Measlant barrier (New

Waterway, Rotterdam)

Hartel channel) barrier (Hartel

Type Year

Width

[m]

Floating sector gate

Vertical gates lifting

Vertical gates lifting

1991 360

1991 170

1986 2400 Eastern Scheldt Barrier

Ramspol

IJssellake)

(near

Europe

Bellow barrier 1996 240

Ems (Germany) Sector gates 1998 360

Thames (Great-Britain)

Venice MOSE project

(Italy)

New Orleans

Sector gates

Flap gates

1980 530

2010 3200

Seabrook barrier (New

Orleans)

IHNC barrier (New

Orleans) - only gates

(excl. floodwall)

Vertical gates/sector gates

Sector gates lifting

2010 130

2010 250

Height

[m]

22

9.3

14

8.2

8.5

17

15

8

Head

[m]

5

5.5

5

4.4

3.8

7.2

3

4

Construction costs [M€]

450

98 *2

*1

2500

*3

100

290

800

4678

114.7 *4

Construction

656

143

4021

132

368

1449

4678 costs

2009 price level [M€]

115

8 4 518 *5 518

Remarks Table A1.9:

1) Maeslant barrier has a relatively low cost price due to heavy competition for the contract.

2) The Hartel barrier has one very large horizontal span which increased the cost price.

3) The Eastern Scheldt barrier is relatively inexpensive due to its repetitive character.

4) The Seabrook barrier (New Orleans) has two different types of gate in a small span.

5) From the IHNC/St. Bernard storm surge barrier only the parts containing the gates have been taken into account, the floodwall was excluded.

128


The costs of a storm surge barrier depend on many factors, such as the type of barrier/gates, the local soil characteristics, the desired height and hydraulic head over the barrier. A first attempt to provide an estimate of a unit cost price per unit width has been given below. The cost price per unit width has been deduced from the available data. This ranges between 0.5 M€ per meter width and 2.7 M€ per meter width.

As the hydraulic head will be an important determinant for the forces on the barrier and the required construction properties and costs, the relationship between the head and the unit cost prices has been plotted (Figure A1.28). It shows that there is a weak relationship between the head and the unit costs for storm surge barriers. It is recommended to further investigate which factors determine the unit costs for storm surge barriers.

3

2,5

2

1,5

1

0,5

0

3 4 y = 0,2959x + 0,074

R

2

= 0,2648

5 head [m]

6 7 8

Figure A1.28: Storm surge barrier unit cost estimates; costs per unit length vs. the hydraulic head for the nine barriers shown in Table A1.9

129


3 Coastal defence cost estimates and analysis

3.1 Unit cost prices for coastal defences

3.1.1 Overview

In this study we have analysed information on the costs of coastal defences for a number of different areas. Table A1.10 summarizes some of the main characteristics of these case studies areas. The results for Cape Town (SA) have been obtained from

Appendix II. Although all the case studies have different conditions and circumstances, it can be stated that the first three case studies are representative for a low-lying delta coast, whereas the Cape Town case is more representative for a coast that is more variable in terms of elevation and protection and coastal management strategies.

Table A1.10: Overview main characteristics case study areas

Netherlands

New Orleans (LA,

USA)

Vietnam

Cape Town (SA)

Standard of protection [per year]

Main threat for coastal defences

1/4000 – 1/10000 Storm surge

1/100 Hurricane

-

1/50 (expert judgement)

Typhoon

Storm surge

Surge level for design conditions [m]

6

6 – 12

Wave height for design conditions [m]

8

2

4 – 10

1.6

5

11*

* value for a 100 year return period (off-shore)

The unit cost data as provided in Table A1.11 is based on cost estimates as found on project level. These studies and projects were not intentionally set up to determine unit costs, but did include coastal defence cost estimates for a number of different reasons.

The costs in Table A1.11 can be considered all in costs, which means they account for the total engineering process. However, the results of the different case studies show a large variability. Although for some estimates ranges are provided, it must be noted that cost estimates largely differ from project to project and can be considered location dependent. It can be stated that the unit cost of Table A1.11largely reflect the Dutch perspective on coastal defence costs, since most of the data was determined by Dutch projects.

As mentioned, the available information on unit cost estimates for the case studies has been summarized in Table A1.11. These numbers provide a first indication based on studies for the four cases. There are several issues and uncertainties associated with the interpretation of these unit numbers and their use in the context of national or global studies on adaptation of the coastal defences to sea level rise. These issues are discussed in section 3.2 to 3.4.

130



NETHERLANDS

National

UNITED STATES

New Orleans

Table A1.11: Unit costs of coastal defence measures, converted to 2009 price levels

Unit Cost (2009 price levels)

-

Vertical Seawall

(Million € per km length)

Concrete floodwall construction; Twall type (per m floodwall height)

•

3.7 – 4.5

(Bos, 2008)

Dike (Millions € per km) Beach Nourishment

(€ per m

3 material)


•

9 – 10.8 (rural) (Kok et

•

•

•

• al., 2008)

18 – 21.6 (urban) (Kok et al., 2008)

4 – 11 (rural)

(Eijgenraam, 2006)

6.9 (rural) (Fugro and

Arcadis, 2006)

13.8 (urban) (Arcadis and Fugro, 2006)

•

•

•

•

•

Dike heightening (per m):

•

5 – 8 (Dijkman, 2007;

Jonkman et al., 2009)

-

Storm surge barriers

2.3 – 6.7 (Stive, pers. comm.,

2009)

3 (Kok et al.,

2008)

2.85 (Arcadis and

Fugro, 2006)

3.72 (Foreshore nourishments)

(RWS, 2009)

7.55 (Beach nourishments)

(RWS, 2009)

Costs per unit width

(m) of a storm surge barrier

0.5 – 2.5 M€ (this study)

Unit costs related to hydraulic head over barrier (m).

Other Measures

Maintenance

0.1 M€/km flood defence/year

(AFPM, 2006)


•

1.4 €/m 2 (Dijkman, 2007)

Marshland creation

•

3 €/m

2

(Dijkman, 2007)

Freshwater diversion/culvert

•

10 M€ (Dijkman, 2007)

Marshland stabilization costs (€ per m

2 per year)

•

0.07 (Dijkman, 2007)

Closure dam (M€ per km per m height)

•

3.7 (in water) (Dijkman, 2007)

Levee armoring (€/m

2

)

•

14.5 – 19.6 (Devlin, pers. comm. 2010)

131



VIETNAM

Hai Phong/Nam

Dinh

SOUTH AFRICA

Cape Town

(Geldenhuys,

2010; Appendix II of this study)

Unit Cost (2009 price levels)

-

Vertical Seawall

(Million € per km length)

Dike (Millions € per km) Beach Nourishment

(€ per m

-

3 material)


•

•

0.7 – 1.2 (Hillen,

2008)

0.75 (Mai et al., 2008)

-

Storm surge barriers

0.3 – 3.96

-

•

•

1.2 – 1.5 M€ per km beach ( note: different unit than other nourishment indicators )*

14.3 (Mather,

2009)

-

Other Measures

Maintenance

•

•

0.02 M€/km dike/year (Hillen,

2008)

0.03 M€/km dike/year (Mai et al., 2008)

Managed retreat

•

€ 180 - € 290 per m

2 surface

* The actual amount of nourishment material per beach was not available for this study; this number was included to give a rough indication. This indicates that the nourishment costs for the non-generic South-African coastline are much higher than for the

Netherlands situation

132


3.1.2 Comparison with IPCC CZMS (1990)

In the past, unit cost prices of coastal defence measures have been determined by IPCC

CZMS (1990) and later adjusted by Hoozemans et al. (1993). In the IPCC CZMS (1990) effort the costs of a number of typical coastal defence measures were calculated based on assumed standard dimensions of these measures. With material costs and assumptions based on construction ‘all-in’ costs for several coastal defence measures were determined.

Table A1.12: Comparison unit costs IPCC CZMS (1990) with findings of this study

Type of coastal defence measure

New 1 m high sea dike

Unit Cost IPCC CZMS

(1990); 2009 price level

0.41 M€/km

New 1 m high sea dike with regular maintenance

Raising low sea dikes by 1 m in rural areas

Raising high sea dikes by 1 m in rural areas

Raising sea dikes by 1 m in urban areas

Beach nourishment

0.62 M€/km

0.52 M€/km

1.04 M€/km

10.39 M€/km

3.12 - 6.24 €/m

3

This study (the Netherlands);

2009 price level

Not included, no real project data available

Maintenance costs: 0.1 M€/km flood defence/year

Only existing (high) dikes taken into account

4 - 10.8 M€/km

13.8 - 21.6 M€/km

2.3 - 7.6 €/m

3

Table A1.12 shows a comparison of the coastal defence measures found both in IPCC

CZMS (1990) and this study. In the table the dike construction costs are compared. The method as applied by IPCC CZMS (1990) gives the costs for an ideal situation, the dike heightening costs for the Netherlands as found in this study are therefore higher (both for rural and urban conditions) than the estimated costs of IPCC CZMS (1990). This can be attributed to the difference between an idealized dike of standard dimensions (as applied by

IPCC CZMS) and the actual construction costs, because in practice projects often encounter more complex problems which cause an increase in costs. Hillen (2008) determined the costs of the Vietnam sea dikes in a similar way as by IPCC CZMS (1990) and these costs can be considered comparable.

The fact that coastal defence costs on project level are higher compared to idealized dikes was also found in a study to include the costs of dike construction in a flood damage computer model (Royal Haskoning, 2007). In that study it was concluded that to determine the costs of flood defence measures in the Netherlands (both river-, lake- and sea dikes) one could not rely on calculations based on a idealized dike cross-section and unit costs of materials. In the report it is stated that ‘due to the large number of variables, no cost calculation with unit costs is applied (…) instead expert judgement is used to provide dike construction cost estimates including ranges.’ There is a large difference between theory and practice. The increase in costs between IPCC CZMS (1990) and Hoozemans et al.

(1993) may also be attributed to this effect, as Hoozemans et al. (1993) focused on the construction of a type of dike section.

The coastal defence unit cost estimates of this study are intended to contribute to the global effort to determine unit costs (Linham et al. 2010). Compared to the numbers found by

Linham et al. (2010) especially the dike (heightening) costs of this study are much larger.

This accounts especially for the dike construction costs. It is recommended that the dike construction costs are based on dike heightening and actual project data. This gives comparable data and accounts for the additional costs that are always included in large engineering projects.

133


3.2 Overview of factors that determine the unit cost price

General costs factors

In order to assess the cost of flood defences, a distinction can be made between five different categories of factors that determine the costs (see below).

1. Planning and engineering costs

2. Material costs

3. Labour costs

4. Costs for implementation in the environment (urban or rural)

5. Costs for management and maintenance

Ad 1: Planning and engineering costs: This concerns the dike design and planning of the flood defence. In case of large uniform sections in rural areas, the unit costs may be low, while in residential areas with non-uniform conditions, the unit cost are relatively high.

Ad 2: Material costs: The cost of materials is very site dependent. In deltaic regions, there is sometimes scarcity of construction material (e.g. clay in New Orleans; stones for revetments in the Netherlands). This highly influences the unit price and method of construction.

Ad 3. Labour costs : the cost of labour is varying a lot between countries. However, when the cost of labour is low, labour is more intensely used, while in the case of expensive labour, mechanized equipment is more widely applied.

Ad 4. Costs for implementation in its environment.

An important factor concerns the implementation of the flood defence in its environment.

Two main factors are:

Land use by flood defences. The required width of a flood defence usually increases with its height. The required amount of land has to be obtained, which could be financially and legally and challenging and thus a costly and time consuming task.

However, in a rural environment, fewer challenges are expected.

Rural or urban implementation. In an urban environment, space is usually scarce and space-saving solutions are needed for the implementation of flood defence projects.

The solutions needed in urban environment (e.g. sheet piles) are usually more expensive than the relatively cheap rural purchases of land.

Figure A1.29 gives an illustrative example that concerns the strengthening of a flood defence. The first “round” of heightening does not lead to conflicts with the urban environment. However, the second round would require alternative solutions or removal of parts of the urban environment. second round of strengthening

First round of strengthening

Figure A1.29: Example of strengthening of a flood defence and possible conflicts with the existing urban environment

134


Ad 5) Costs of management and maintenance

An organization is needed for the management and maintenance of flood defences. This will result in an additional percentage of cost on the total expenses. The management and maintenance in the Netherlands is carried out by so-called Water Boards. In other countries there are usually also (semi-) governmental bodies for management and maintenance.

To give an indication: The yearly costs for management and maintenance for primary flood defences in the Netherlands is estimated to be approximately € 350 million per year (AFPM,

2006). With a total length of primary flood defences of about 3600 km the estimated costs for management and maintenance become € 100,000 per km flood defence per year.

Discussion: Comparison of costs between countries

As mentioned above, the different unit costs vary per country and per location. The differences between locations in a region will be largely determined by the exact design and the implementation.

Country specific factors will be related to the local economic situation. The contribution of the categories to the unit price is likely different is for each country. The costs for material and labour will also affect the selected design, the materials used and the construction method.

In countries with low labour cost, and high material cost, another choice is made for e.g. dike revetments than in countries with low material and high labour cost.

The relative contributions may be compared. Though in case of comparison per country, the development (GDP, specific education etc) needs to be taken into account. This is be illustrated by comparing the derived average unit cost prices for dikes the three countries

(see section 3.1) to the GDP per capita (source: CIA World factbook; assumed exchange rate 1 Euro = 1.34 US $). This shows that the estimated unit cost prices for Vietnam are relatively high in comparison with the GDP per capita.

7

6

9

8

3

2

5

4

1

0

0

Vietnam

5000

Netherlands

New Orleans

10000 15000 20000 25000

GDP per capita (Euro)

30000 35000 40000

Figure A1.30: Comparison between the average unit cost prices for dikes and the relationship with the GDP per capita

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3.3 Cost estimates at a system level

The unit cost of flood defences on a project level were discussed in the previous section. In this section, we discuss some main factors and issues that determine the cost estimates at a system level.

Main factors that determine the costs at a system level

The transition from unit cost prices to system level cost estimates are influenced by three main factors:

1. Measures and solutions chosen for individual reaches

2. The system length

3. Modifications in the system’s alignment

Ad 1: the cost factors for individual projects have been discussed in section 3.2

Ad 2: system length : the total cost for (adaptation) of a flood defence system is determined by the length of the flood defences in the system. The total costs are found by integrating the unit costs prices for invidual reaches over the total system length.

Obviously, the costs will be high for a system with a large length. A good example concerns the protected areas that are found in the so-called Plaquemines area in Louisiana, south

East of New Orleans. These are wide scarcely populated areas along the Mississippi that are protected by levees / dikes from river and hurricane flooding. Due to the large system length protecting the values in this area will be relatively costly. This also has a relationship with the cost benefit analysis and optimal protection level that would be found for such an area (see also section 4). An area with a relatively low economic value but high systems adaptation costs, will have a lower optimal protection level (or “demand for safety”) than an area with a high concentration of values and a relatively small systems length.

Figure A1.31: Plaquemines area in Louisana, SE of New Orleans. Green and purple lines indicate the current levees. North to South is app. 120km.

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Ad 3 Modifications in the system’s alignment : The length of a coastal flood defence system may be shortened by closing off estuaries. This could bring additional advantages for for example navigation and agriculture (availability of fresh water), but could also have negative effects on the ecological system. Such an adaptation is usually done when the benefits (e.g. less costs due to a smaller system length and reduction of the risk) outweigh the costs of such a modification (e.g. additional dams or storm surge barriers). Examples of such projects are:

Netherlands: construction of storm surge barriers, such as the Eastern Scheldt and

Maeslant barriers, to close of the estuaries and reduce the required dike strengthening behind the dams and barriers (see Figure A1.32 for an overview of some of the dams in the Dutch delta plan that was constructed after the 1953 storm surge disaster)

New Orleans: A storm surge barrier is being built after Katrina at the eastern side of

New orleans to protect the city from surges and reduce the length of the directly exposed system. In addition, gates were built in the outfall canals in the north of the central city to prevent that the levees along these canals could be directly exposed during surges (see Figure A1.33 for an overview – new gates and barriers in red).

Figure A1.32: Overview of dams (indicated with numbers) that were constructed after the

1953 storm surge disaster in the Netherlands

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Figure A1.33: Overview of new dams and gates (in red) that were constructed in New

Orleans after hurricane Katrina (source: Times Picayune newspaper)

Costs made for other functions

The costs of a project will depend on the exact solution or measure that is chosen. A measure or project will never be solely based on the flood defence requirements. The flood defence function (and its cost) is in this case will only form a part of the total project. Other functions (recreation, infrastructure, ecological quality etc.) will influence the design as well.

Multifunctional and integrated approaches become more and more common and the total costs of these solutions would be generally higher than would only be the case for the flood defence function. Examples of recent projects where this played a role are given below.

Room for Rivers in the Netherlands: Instead of heightening the river dikes, the room for rivers strategy has been adopted. This strategy is more expensive than strengthening the dikes. Ecological and landscape issues were important factors in the choice for this strategy.

The ‘Sand engine’, which is a single sand nourishment that is large enough to replace many years of future nourishments. While obviously involving a large safety aspect, additional costs have to be made as more sand is needed for merely ecological values.

The plans for the multi-functional Afsluitdijk (closure dam) in the Netherlands: the proposed multifunctional solutions have much higher costs than a basic strengthening of the Afsluitdijk.

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Figure A1.34: One of the proposed designs for the Afsluitdijk / closure dam in the

Netherlands, with several additional functions, such as nature development and tidal energy generation

- Multifunctional defence types and concepts: o

Delta dikes, super levees that integrate wide dikes with spatial development o

Comcoast project: wide coastal zones that integrate coastal zones with nature development.

Figure A1.35: Example of a multifunctional super levee in Japan that combines a flood defence with urban development

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Figure A1.36: Example from the Comcoast project of a coastal development zone that combines flood protection and nature development

3.3 Relationship between sea level rise and coastal defence costs

General

In this section we discuss the possible extrapolations of these coastal defence costs into future expenses to adapt to sea level rise. One must carefully distinguish two relationships:

1. The development of the hydraulic loads over time (largely determined by the sea level rise rate) and the required adaptation of flood defences

2. The relationship between the adaptation of the flood defence and the the associated costs

The combination of these two relationships determines the eventual the development of costs of adaptation over time. If both relationships are linear, the costs will shows a linear increase over time (see Figure A1.37). If one of the two relationships is non-linear, the eventual development of costs over time will be non-linear as well. The underlying factors are briefly discussed below.

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Dike height Sea level

2) costs of adaptation of the flood defence

Costs

1) development of sea level over time time

Costs time

Figure A1.37: Conceptual scheme that shows how the development of adaptation costs over time depends on the development of sea level rise and the relationship between costs and sea level

Adaptation of existing flood defence structures to sea level rise

It is noted that the required adaptation of flood defences will be based on the local value of the relative sea level rise rate 17 . The combination of sea level rise and subsidence is usually referred to as relative sea level rise. In New Orleans, it appeared that the crest elevation of many of the levees and floodwalls around New Orleans was substantially lower during hurricane Katrina than at the moment of design and construction due to the effects of subsidence.

Regarding the adaptation of existing flood defence systems, one should consider different design parameters and how they change with sea level rise. Parameters that increase linearly with a constant SRL rate are:

The required nourishment volumes

Dike height

Footprint of the dike and required purchases of land

Parameters that will increase not-linearly with a constant SLR rate are:

the dike volume and thus the required amount of soil.

Expected costs of implementation. The wider the footprint of the dike, the higher the probability that houses or other buildings or objects have to be removed, or that specific and costly measures have to be implemented to prevent this.

It depends on local circumstances which parameters are dominant, and thus it depends on local circumstances whether the costs develop linear or non-linear.

17

This means that subsidence of the land has to be considered in addition to the effect of sea level rise.

Subsidence can have several causes: Inclination of organic materials (which is usually the case in delta), extraction of natural resources (oil, gas, water) and tectonic movement (e.g. post-glacial rebound of Scandinavia causes subsidence in the Netherlands)

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Effects of the sea level rise rate

The future sea level rise (SLR) rate will determine required dike strengthening and investments. In case of an existing dike system, this results in:

Linear SLR rate: same strengthening every interval. Note that with a higher, yet constant SLR rate, the costs will go up, but linearly.

Non-linear (concave) SLR rate: the required strengthening becomes larger in time.

Linear SLR: the heightening steps remain Exponential SLR: The heightening steps constant. increase in time.

Dike height /

Sea level Dike height /

Sea level

Dike height

Dike height

Sea

Level

Sea level time time

Figure A1.38: The effects of the sea level rise rate on the dike heightening steps

It must be noted that for instance for sea dikes, the required dike height goes up faster that the SLR rate, as one has to incorporate the effect of increased wave height on the dike design. However, the relationship will still be linear.

Findings for the Netherlands (Kok et al., 2008)

For the Netherlands a prediction of the development of the future costs of flood defences has been made (Kok et al., 2008) as part of the investigation of the Deltacommittee. A sea level rise scenario was assumed that concerned a sea level rise of 0.85m in 2100 and a total sea level rise of 2.0m in the year 2200. The development of costs for different subsystems has been predicted. The figure shows the (average) yearly costs.

In general, a linear relationship between the costs of adaptation and the sea level rise was found. The most important design and cost parameters (height, width, land use) of the flood defences showed a linear increase over time. An important reason was that a constant sea level rise rate was assumed. However, replacement of existing major flood defence structures, such as storm surge barriers, was expected to lead to small “jumps” in the cost function, see example below.

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Figure A1.39: Development of yearly costs for flood defence in the Netherlands over time

(Kok et al., 2008)

Other considerations and factors

Several (other) factors will affect the development of coastal defence costs over time and some of those have been discussed in the previous sections. A specific issue is the prediction of cost estimates for future expenses. Several developments could to changes in the unit cost price levels:

uncertainty in development of costs and market prices (e.g. oil price)

new innovative techniques with different price levels

Possible strengthening of the primary flood defence system could affect the internal water management system, e.g. drainage and pumping systems, especially in low-lying delta areas. For example if the sea level rises pumps with higher capacity are needed to drain these areas.

An important driver for changes in coastal protection could be the economic and population growth. This results in an higher need for safety and thus in the improvement of flood defences. This effect is discussed in chapter 4. This could lead to the decision to raise the level of protection. With that it could also be decided to adapt the alignment of the system.

Linear or non-linear development of the costs of coastal protection over time?

In summary, it is not easy to determine whether the costs of flood defences and coastal management will develop linearly or non-linearly over time. This will determine on local factors that have been described above. Some important factors that would contribute to a linear of non-linear development are summarized below:

Linear development (unit cost prices remain constant over time)

Constant (relative) sea level rise rate

Same measures can be used for higher design water levels

Most design parameter increase linearly with a linear SLR rate

Relative costs levels for labour and material remain constant over time

No increase of the costs of purchasing land for additional widening and strengthening

Level of protection remains constant over time

Non-linear development (unit cost prices increase over time)

sea level rise rate increases

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System modifications required (e.g. storm surge barrier replacements)

Important design parameter increase non-linearly with sea level

Construction of new flood defences required

Relative costs levels for labour and material increase over time

Adaptation of the defences requires measures in “difficult” areas, e.g. urban areas

Level of protection increases over time

There are factors that could contribute to a decrease of the unit costs over time. When material or labour costs decrease or when new cheaper techniques and constructions are invented the marginal costs of adaptation could decrease. The relationship between sea level rise and costs will be determined by a combination of the above factors.

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4 Optimal protection levels

This section focuses on the determination of optimal protection levels in a so-called economic optimization or cost benefit analysis. The unit cost prices that have been discussed in the previous sections will be important input, but not the only input, in determining the optimal protection levels. The general approach and theory is presented in section 4.1. Findings for the three case studies are included in section 4.2. Section 4.3 compares the results of the case studies with the demand for safety that follows from the

DIVA model.

4.1 Background and general approach

After the 1953 flood disaster a Delta Committee was installed to investigate the possibilities for a new approach towards flood defence. The committee proposed to reduce the vulnerability by shortening the coastline and closing off the estuaries in the Southwest of the country. In addition, safety standards for flood defences were proposed. In an econometric analysis the optimal safety level was determined for the largest flood prone area, South

Holland (van Dantzig, 1956). In this economic optimization the incremental investments in more safety are balanced with the reduction of the risk. The investments consist of the costs to strengthen and raise the dikes. In the simple approach it was assumed that flooding could only occur due to overtopping of the flood defences. Thereby each dike height corresponds to a certain probability of flooding (the higher the dikes the smaller the probability of flooding). Dike heightening leads to reductions of the probability of flooding and the expected damage (= probability x damage). By summing the costs and the expected damage or risk, the total costs are obtained as a function of the safety level. A point can be determined where the total costs are minimal, this is the so-called optimum. The approach has been applied after the 1953 storm surge to determine an optimal safety level was determined for the largest flood prone area, South Holland.

The equation for the optimal protection level is as follows:

I ' rB

P opt

=

D

Where:

•

P opt

– optimal protection level [1/year];

•

I’ – costs per unit of heightening / strengthening of the flood defence;

• r’ – nett discount rate (economic growth minus inflation);

•

B – constant related to the statistical distribution of the water levels [-];

•

D – potential damage in case of flooding [Euro]

This shows that the marginal costs of improvement of the safety and the potential damage will be important factors that determine the optimal protection level. The other two factors (B, r’) are generally constant and do not depend on regional or local characteristics of the area under study. The economic optimization is often also referred to as cost benefit analysis.

145


Figure A1.40: Principle of the Economic optimization approach by the Delta Committee.

In recent work (Eijgenraam, 2006) some modifications of the approach have been proposed.

In essence, the difference is that van Dantzig assumes one major improvement at the current moment, while Eijgenraam considers the periodical character of the improvement of the flood defence system under changing conditions such as economic growth, sea level rise etc.. As a result the optimal flooding probability will change over time, e.g. due to economic growth (see Figure A1.41). Comparison of both these methods for some practical case studies for the Netherlands and New Orleans shows that they give similar results for the first decades of the considered time period.

Figure A1.41: Development of the optimal flooding probability over time (Kind et al., 2008)

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4.2 Case studies

This section briefly presents the results for three case studies for which the method of economic optimization was applied. Further background is given in the publications that are referred to.

4.2.1 Netherlands

Background

After the 1953 disaster a delta committee was installed. The analysis of the Delta Committee laid the foundations for the new safety approach, in which dikes are dimensioned based on a design water level with a certain probability of exceedance. The current design criteria and the process for safety evaluation of the flood defences are based on these design water levels. This approach to flood protection is laid down in the flood protection act of 1996. The flood prone areas in the Netherlands are divided in so-called dike ring areas, i.e. areas protected against floods by a system of water defences (dikes, dunes, hydraulic structures) and high grounds. The safety standards for the various dike depend on the (economic) value of the area and the source of flooding (coast or river). For coastal areas design water levels have been chosen with exceedance frequencies of 1/4000 per year and 1/10,000 per year.

For the Dutch river area the safety standards were set at 1/1250 per year and 1/2000 per year. Some smaller dike ring areas bordering the river Meuse in the south of the country have a safety standard of 1/250 per year.

Recent economic optimization

More recently, the cost benefit analysis / economic optimization, has been applied to all major dike rings in the Netherlands. This was done by applying the “dynamic” model proposed by Eijgenraam (2006). A first indication of the results was presented in (Kind,

2008). The results are shown in Figure A1.42. These are the so-called “middle” optimal safety levels. This means that these are the middle probabilities in the bandwidth shown in

Figure A1.41. When these results are compared with the current safety standards it is found that especially in the dike rings in the river system in the east of the country would need to receive a higher protection level than the current level. It is noted that the results below are a first indication, as further extensive studies are ongoing. Final results will be used for a possible update of the existing safety standards.

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Figure A1.42: Optimal safety levels for dike rings in the Netherlands

4.2.2 New Orleans

The economic optimization has been applied to New Orleans. As part of the broader “Dutch perspective study” (Dijkman, 2007) the optimal safety levels for the three polders that are shown in Figure A1.43 have been determined. Table 1.13 and Figure A1.43 give the results for the central part of New Orleans (dike ring 1). As part of the approach design surge levels and their return periods were determined. The costs have been based on the unit cost estimates that have been presented in section 3. Damage estimates have been used based on various studies that were published after hurricane Katrina.

148


Figure A1.43: Overview of New Orleans metropolitan area and proposed flood protection systems in de Dutch perspective: (1) Northern dike ring 1 (central part of New Orleans); 2)

Northern dike ring 2 (East Orleans and St Bernard); (3) Southern levee ring (West bank)

Table A1.13: Economic optimization for Northern dike ring, central part of Orleans: Input information and results

Return period (yr) 100 500 1,000 5,000 10,000 100,000 1,000,000

Design surge level

Lake Pontchartrain (ft) 9

Investments ($)

11 13 15 17 21 25

2.2E+09 2.4E+09 2.6E+09 2.9E+09 3.1E+09 3.6E+09 4.1E+09

Investments Risk Total costs

1,8E+10

1,6E+10

1,4E+10

1,2E+10

1,0E+10

8,0E+09

6,0E+09

4,0E+09

2,0E+09

0,0E+00

10 100 1000 return period (yr)

10000 100000 1000000

Figure A1.44: Results of economic optimization for the Northern dike ring, central part of

New Orleans

149


For the central area (northern dike ring 1) an optimal safety level of about 1/5000 per year has been found. For the other two polders optimal safety levels of around 1/1000 per year were obtained. Given the preliminary character and the uncertainties in the assumptions

(See Jonkman et al., 2009 for discussion) the presented outcomes can be regarded as a first indication.

4.2.3 Vietnam

In a number of publications the approach has been applied to Vietnamese sea dikes, (Hillen,

2008; Mai et al., 2008; Mai, 2010). A case study has been done for the Nam Dinh province, in the northern part of the country. This was also the area that was seriously flooded after typhoon Damrey in the year 2005. This event caused about US $ 500 million of damage.

Based on cost estimates for the sea defences (see section 3), information on typhoon induced surges and their return periods, and assessments of damage in coastal areas the economic optimal level of protection was determined. Figure A1.45 shows the results for

Nam Dinh province for the current level of economic development. This leads to an optimal protection level of about 1/50 per year. Vietnam has a fast growing economy. If future economic development is taken into account, leading to a growth of the potential damage, a higher protection level is found of about 1/90 per year.

Figure A1.45: Economic optimization for Nam Dinh province for the current economic situation (Mai, 2010)

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4.3 Discussion and comparison with the DIVA model

The results for the three case studies have been compared with the “demand for safety” that resulted from the DIVA model (personal communications with Linham, 2010), see Table

A1.14. It is clear that both approaches given different results.

Table A1.14: Comparison between the optimal protection level determined with the economic optimization and the demand for safety that resulted from the DIVA model

Location

Demand for safety according to DIVA (return period [yr])

Netherlands

1739 (Amsterdam)

1396 (Rotterdam)

New Orleans (USA) 1385

Vietnam

14 (Hai Phong)

1 (Ho Chi Minh City)

Optimal protection level (return period [yr])

20,000 (Rotterdam area)

4000 (Amsterdam area)

(Kind et al., 2008)

1000 – 5000 (Jonkman et al., 2009)

50 (Nam Dinh, current situation)

90 (Nam Dinh, incl. economic growth)

(Mai Van, 2010)

A further general comparison of similarities and differences between the two approaches is given. Table A1.15 compares the factors that are included in the DIVA approach (Anon,

2010) and the factors that are included in the economic optimization.

Table A1.15: Comparison between the factors included in DIVA and the economic optimization

DIVA

•

GDP

•

•

Coastal population density

Storm surge regime

Higher GDP and coastal populations generate greater demand for safety

Economic optimization

•

Damage in case of flooding

•

Marginal cost of improving the level of protection (determined by system length and costs of measures)

•

Nett discount rate

•

Return periods of hydraulic load levels

Generally speaking one can see that DIVA includes more general factors whereas the economic optimization focuses on more specific factors that relate to the system’s characteristics. This is not surprising as DIVA as used for global assessments, whereas the economic optimization is more used as a design supporting approach for flood defence systems.

Two important factors in the economic optimization are the potential damage and the marginal costs of improving the level of protection. The information on the GDP and coastal population density in DIVA are related to the damage potential. One additional factor that is not included in DIVA but is important for the damage potential is the amount of flood prone / low-lying areas in the considered region.

In the DIVA model the (marginal) costs of improving the level of protection are not directly included. One important factor that will determine these costs will be the length of the defence system. The longer the alignment, the more expensive raising the level of protection will be. That the system’s length is an important factor was also found in the economic

151

AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities optimization (Eijgenraam, 2006). For dike rings in the Netherlands it was found the the optimal level of protection was directly related to the ratio of the number of inhabitants and the system’s length (see Figure A1.46). The number of inhabitants will be proportional to the damage, and the system’s length will influence the costs of improving the level of safety.

These two factors (damage and marginal costs) are the most important determinants of the optimal protection level (see also the formula in section 4.1). Following this approach a smaller system with a high concentration of people and values will receive a higher optimal level of protection than a very long system with a low population density.

Figure A1.46: Optimal safety level (return period) versus the number of inhabitants per unit dike length (Eijgenraam, 2006)

The above shows that the number of inhabitants per unit of the length of the defence is a good approximate measure for the optimal protection level. It is recommended to use this measure as a representative for the optimal standard of protection, and to investigate if and how the length of the defence system can be added to the approach implemented in DIVA.

More overall, it is recommended to compare the approach of the economic optimization and the DIVA method for determining the “demand for safety” at a methodological level and for a number of selected case studies.

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5 Main findings and recommendations

Information on the costs of coastal defences has been investigated for the full range of hard and soft engineering measures, such as dikes/levees, nourishments and storm surge barriers. Information and cost estimates from previous studies have been used to derive unit cost estimates for the Netherlands, Vietnam, New Orleans (LA, USA) and Cape Town

(South Africa)

An overview of the resulting unit cost estimates is given in Table A1.11. Some main findings are summarized below:

•

Dikes : for the Netherlands the unit costs for strengthening of dikes range between 4 and 11 M€ per km per m heightening for rural areas and between 14 and 22 M€ per km per m heightening for rural areas (2009 price levels). The cost estimates for dike and floodwall heightening for New Orleans are between 4 and 8 M€ per km per m heightening.

•

Storm surge barriers : the cost price per unit width has been deduced from the available global data. This ranges between 0.50 M€ per meter width and 2.7 M€ per m width

•

Beach nourishment : for beach nourishment in the Netherlands the available literature sources indicate a unit cost price of about € 3-4 per m foreshore nourishment and € 7-8 per m 3 somewhat higher unit cost € 11 per m 3 obtained for South Africa.

3 material for material for beach nourishment. A material for beach nourishment has been

•

The unit cost prices will depend on the measure selected and consequently on the costs for planning and engineering, labour, equipment, materials. There are two important factors:

1. Local economic factors : The average unit costs for dike strengthening in

Netherlands and New Orleans are about eight times higher than those for

Vietnam. It is necessary to use different cost estimates for regions with different economic development levels.

2. Implementation in urban or rural areas : Additional costs have to be made if measures are implemented in urban or ecologically sensitive environments.

For the Netherlands the unit cost price for strengthening dikes in urban environments is about two times higher than the unit cost price for rural areas

•

The costs estimates at the level of a coastal protection system will depend on the unit cost prices, the system’s length, the chosen alignment and costs made for other functions than coastal flood protection (e.g. recreation, ecology). All these factors have to be taken into account when predicting the costs of adaptation to sea level rise.

•

A comparison between the unit cost estimate from IPCC CZMS and the findings of this study shows the following. The unit costs in the IPCC study are higher, likely because the IPCC numbers are based on dike construction or strengthening in an idealized situation, whereas the numbers from this study are based on actual project data.

•

It has been investigated whether there is a linear or non-linear relationship between the sea level and the costs for adaptation of flood defences. Current studies for the

Netherlands (Kok et al., 2008) suggest a linear relationship. A number of factors have been identified that would affect this relationship. Important factors are the sea level rise rate, future changes in price levels (labour, materials), the need for modification of the system’s alignment and the need for adaptation of large structures, such as storm surge barriers.

153


•

Given all these factors, the derived unit costs estimates should be considered as indicative and they can only be applied with a considerable bandwidth / uncertainty margin.

•

The optimal levels of protection that have been found by applying the economic optimization / cost benefit analysis to three case studies differs from the “demand for safety” that is found with the DIVA model. One important difference is that the economic optimization takes into account the potential damage and the actual length and improvement costs of the flood defence system, whereas the DIVA model is based on more global indicators, such as the population density, GDP and storm surge regime.

Recommendations

•

For consideration of the costs of measures at a system or higher level (country or regional) it is essential to specify which measures are implemented. This means that studies on the costs of adaptation to sea level rise would also require specification of the (assumed) measures, the system alignment and the strategies that are implemented.

•

Given the uncertainties and / or lack of knowledge of underlying factors it is recommended to express unit cost estimate by means of bandwidths.

•

Further analysis of existing cost information for storm surge barriers is recommended. It can be investigated whether a relationship between various barrier characteristics (width, height, hydraulic head, barrier type) and the barrier costs could be found. A general formula could be derived to give a first indicative prediction of the costs of storm surge barriers.

•

In New Orleans approximately US $ 15 billion has been invested in recent years to repair and improve the safety of the hurricane protection system. Although a lot of cost information is confidential, analysis of public information on levee projects could improve the empirical basis of the cost estimates for this region. It is recommended to set up a specific investigation for this system.

•

It is recommended to review and update the county factors that are used in the IPCC

CZMS study based on more actual data from costs of coastal defence projects and regional economic indicators.

•

In an economic optimization an optimal level of protection can be determined based on the required investments in providing a higher safety level and the benefits in terms of reduction of the economic risk. The investments will be highly dependent on the design of the flood defence system for the system and possible changes in the alignment and the implemented defence measures. A good approximate measure for the optimal protection level is the number of inhabitants per unit of the length of the defence. It is recommended to use this measure as representative for the optimal standard of protection, and to investigate if and how the length of the defence system can be added to the approach implemented in DIVA.

•

More overall, it is recommended to compare the approach of the economic optimization and the DIVA method for determining the “demand for safety” at a methodological level and for a number of selected case studies.

154


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Hillen, M.M. 2008. Safety Standards Project, Risk Analysis for New Sea Dike Design

Guidelines in Vietnam. Technical Report Delft University of Technology / Hanoi Water

Resources University; Sea Dike Project, pp.68.

Hoozemans, F.M.J, Marchand, M. and Pennkamp, H.A., 1993. “A global vulnerability analysis: Vulnerability assessment for population, coastal wetlands and rice production on a Global scale”, 2nd Edition. Delft Hydraulics, the Netherlands

IPCC CZMS, 1990. “Strategies for Adaptation to Sea-level rise.” Report of the Coastal Zone

Management Subgroup, Response Strategies Working Group of the Intergovernmental

Panel on Climate Change. Ministry of Transport, Public Works and Water Management, the Netherlands, pp.122.

Jonkman, S.N., Kok, M., van Ledden, M. and Vrijling, J.K., 2009. “Risk-based design of flood defence systems: a preliminary analysis of the optimal protection level for the New

Orleans metropolitan area.” Journal of Flood Risk Management, 2(3), 170-181.

Kind J. 2008. Waterveiligheid 21e eeuw – Kengetallen kosten baten analyse. Rapport

WD2008.044

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Kind J. 2008. Cost benefit analysis to determine efficient flood protection standards for the

Netherlands. Proceedings of the 4th international conference on Flood Defence, 105/1 –

105/8

Kok, M., Jonkman, S.N., Kanning, W., Stijnen, J. and Rijcken, T., 2008. “Toekomst voor het

Nederlandse polderconcept.” (in Dutch) Appendix to “Working together with water.”

Deltacommittee 2008, the Netherlands

Linham, M.M., Green, C.H. and Nicholls, R.J. in preparation. “Costs of adaptation to the effects of climate change in the world’s large port cities.”

Mai, C.V. et al. 2008 - Risk analysis of coastal flood defences: a Vietnam case. 4th

International Symposium on Flood Defence, Toronto, Canada.

Mai C.V. (2010) Probabilistic analysis and risk-based design of water defences in Vietnam

Draft PhD thesis, Delft University.

Nicholls, R.J., Hanson, S., Herweijer, C., Patmore, N., Hallegatte, S., Corfee-Morlot, J.,

Château, J. and Muir-Wood, R., 2008. “Ranking Port Cities with High Exposure and

Vulnerability to Climate Extremes.” OECD Environment Working Papers, No 1.

Royal Haskoning, 2007. Doorontwikkeling HIS SSM; definitiestudie naar kosten herstel waterkeringen en opname in HIS SSM (study determine repair costs of flood defences for HIS SSM) for RWS (Ministry of Transport, Public Works and Water Management, the

Netherlands).

RWS, 2009. Nourishment presentation of Alex Roos (Ministry of Transport, Public Works and Water Management, the Netherlands) for the municipality of The Hague. Ppt presentation.

Van Dantzig D. (1956) - Economic decision problems for flood prevention. Econometrica Vol.

24 pp. 276-287

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APPENDIX II:


Coastal Adaptation to Climate Change:

Measures and Costs

A Cape Town Case Study

M.A. Geldenhuys BSc (TU Delft – CoMEM program)

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1 Introduction

Much of the world’s population is living along the coast. Climate change, along with the corresponding rising sea levels, and population growth is putting much pressure on existing coastal defences and could cause significant damage to unprotected coastlines.

There is a need to quantify the potential adaption measures and costs in terms of climate adaption worldwide. Research is currently done about the impact of climate change on 136 port cities around the world (Linham et al 2010); this project is coordinated by Robert

Nicholls from Southampton University. Delft University of Technology, in cooperation with

Royal Haskoning, has been approached to research coastal defense unit costs in more detail; with real costs from case studies relating to The Netherlands, Vietnam and New

Orleans projects. This report is an additional case study provided as an annexure to this abovementioned coastal defence cost project report. It should be noted that this report only gives an indication of costs related to coastal protection in Cape Town due to the limited scope and timeframe that was available for this project.

The City of Cape Town Municipality (hereafter referred to as the City of Cape Town) has experienced increasing coastal damage relating to more frequent and bigger storms and is vulnerable to rising sea levels. The most significant hazards to the Cape Town coastline are erosion and wave run-up during storm events. This leads to large economic risk and damage, for both the City of Cape Town and private property owners, to infrastructure and assets in proximity to the coast. This study is a brief review of relevant literature to give indicative costs for climate change adaption in Cape Town. Information relating to the damage caused by a recent storm, which took place in 2008, is provided along with an estimate about economic risk to the City of Cape Town in event of a design storm.

Figure A2.1 gives the location of Cape Town on the Southern tip of Africa.

Figure A2.1: Location of Cape Town on the world map

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2 Description of the Local Situation

2.1 General

The City of Cape Town Municipality administers approximately 307 km of coastline; which is arguably its single greatest economic and social asset (Cartwright et al, 2008 – Phase 1).

Cape Town is the second most populous city in South Africa, with an estimated population of approximately 3.5 million inhabitants (Statistics SA, 2007); and with an area of 2,450 km2, which is the largest city area in South Africa. Figure A2.2 shows the 8 district municipalities managed by the City of Cape Town.

Table Bay

False Bay

Cape Point

Figure A2.2: Cape Town districts

Cape Town has a Mediterranean climate, with cold wet winters and dry hot summers, with an annual ambient air temperature of 19°C (Wikipedia).

Cape Town is arguably the most popular tourist destination in South Africa; in 2006 foreign tourist expenditure in the Western Cape totaled R19.80 billion (US$2.64 billion), while domestic tourism receipts were R1.50 billion (US$200 million). The forecast for 2008 for total

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities tourism revenue is R24 billion (US$3.2 billion) (Cartwright et al, 2008 - Phase 3). According to the five year plan, Cape Town currently generates about 78% of the Gross Geographic

Product (GGP) of the Western Cape and some 12% of South Africa’s Gross Domestic

Product (GDP) (City of Cape Town Annual Report, 2009). The 2008 GGP for the City of

Cape Town was R165 billion (Based on 2006 figures of R123.6 billion) (Cartwright et al,

2008 - Phase 3). An exchange rate of R7.5 for $1 is used throughout the study.

2.2 Topography

Cape Town is a city interspersed with mountains, most notable Table Mountain and the

Cape Point mountain range. The topography is therefore very variable with some low lying sandy areas, such as the Cape Flats (Figure A2.3), as well as maximum elevations in excess of + 1,500 m MSL (Figure A2.4). The Cape Town coastline is extremely variable and differs between mountain cliffs, rocky outcrops and pocket beaches as found along Cape

Point to gentle beaches with dunes behind them as found along False Bay and Table Bay

(refer to Figure A2.2 for locations). Generally it can be said that most of the Cape Town area is high enough not to be prone to inundation after the breach of coastal defences, but rather that it is vulnerable to erosion during storms (a situation which is exacerbated by the variation between rocky and sandy coastline and occurrence of pocket beaches).

Cape Flats

Figure A2.3: Satellite Image of central Cape Town (www.Geology.com)

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Figure A2.4: Topographical map of Cape Town centre (www.mapstudio.co.za)

2.3 Bathymetry

The bathymetry of the ocean surrounding Cape Town is also highly variable, the general trend is however that most of the exposed coastline has steep gradients as shown in Figure

A2.5, which allows big waves to propagate close to the shore. Other areas are sheltered, such as False Bay, and have shallower gradients. The gradient of the zone just offshore of

Sea Point can be approximated from Figure A2.5 as 20 meters divided by 600 meters, which gives a slope of 1:30. This is a relatively steep slope; deep water can be found close to the shore on many locations along the Cape Town coast.

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0.7 km

- 20 m contour

1.38 km


1.38 km

Figure A2.5: Section of Cape Town Naval chart (South African Navy Hydrographic Office)

2.4 Tides

The maximum tidal variation between Lowest Astronomical Tide (LAT) and Highest

Astronomical Tide (HAT) is approximately 2 meters. The offset of Chart Datum (CD) relative to Land Levelling Datum (LLD) is -0.843 metres at Simon’s Town Naval Harbour in False

Bay (www.satides.co.za), HAT is equal to LLD + 1.24 metres.

2.4 Sea Level Rise and Surge

According to the IPCC report on sea level rise in South Africa (Goschen et al, 2009) the greatest hazards to the South African coastline is that of short term events caused by extreme storms and floods. The abovementioned report indicated relative sea-level trends for Cape Town provided in Table A2.1.

Table A2.1: Relative sea-level trends for Cape Town. Stations are from the Permanent

Service for Mean Sea Level (PSMSL) data holdings (Mather et al., 2009) (adapted from

Goschen et al, 2009)

Tide station

Table Bay

Simons

Town

Period of

Record

Years of record

Completeness of record (%)

1957

1972

1957

2007

16

51 78

Observed annual sea-level trend using monthly data

(mm yr-1)

Insufficient data

Observed annual sea-level trend using annual data

(mm yr-1)

+1.6 ± 0.2 +1.2 ± 0.5

The maximum still water effects as recommended by Theron and Rossouw (2008) are given in Table A2.2, it should be noted that the values in this table are mean values for the whole

South African coastline.

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Table A2.2: Parameters and estimated maximum effects on still-water levels for the South

African coast (Theron and Rossouw, 2008) (adapted from Goschen et al, 2009)

Parameters and effects

Mean high water spring tide

Highest Astronomical Tide (HAT)

Severe wind set-up

Maximum hydrostatic set-up

Wave set-up

100 year sea-level rise

Elevations (m to mean sea level) and setup (+ m)

1.0

1.4

+0.5

+0.4

+1.0

+0.2 to +0.6 (say 0.4)

This can be compared with the overall monthly maximum deviation in sea level (without tidal impact), in a recorded period of 30 years, which was recommended to be +0.4 metres in the

City of Cape Town Sea-Level Rise Risk Assessment (Cartwright et al, 2008 – Phase 1) and is much smaller than the potential combined set-up of 0.9 metres recommended in Table

A2.2. The sea levels of LLD +1.54 m at a return period of 100 years and LLD + 1.63 m for a return period of 500 years are extrapolations used in further studies by the City of Cape

Town (Cartwright et al, 2008 - Phase 1).

2.6 Waves

A summary of the wave climatology for Cape Town as described in Phase 5 of the Sea Level

Rise risk assessment report (Brundrit et al, 2009) is given:

•

A deep water wave recording site, Slangkop, situated 14 kilometres offshore in 170 metres deep water provided records for 12 years (1976-1988) (11424 records at 6 hourly intervals = 63% coverage).

•

A median peak period of 12.4 seconds was measured for the wave date in Table

A2.3.

Table A2.3: Significant Wave Height Statistics from Slangkop 1976-1988 (adapted from

Brundrit, 2009 – Phase 5A)

Significant wave height H

S

Median value

Value at a return period of 1 year

Value at a return period of 10 year

Metres

2.6

7.6

9.4

Value at a return period of 100 year 11.1

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Figure A2.6: Bathymetry around the Cape Peninsula down to a depth of 70m at 5m intervals. (Brundrit et al, 2009 - Phase 5A)

The coastline is more exposed to extreme events from the South West as shown in Figure

A2.6. Wave information is summarized below (Cartwright et al, 2008):

•

A big wave event is defined as one which has a significant wave height exceeding

6.5 metres for at least 6 hours (Van der Borsch, 2004).

•

Thirty two big wave events were identified at Slangkop over the 21 year measurement period (1983 to 2003).

•

It should be noted that the distribution of these events are grouped and seem to correspond to years that had persistently warmer sea surface temperatures.

•

The average significant wave height within these 32 big wave events is 7.7 metres, with standard deviation 1.0 metres, which can be compared with the value of the significant wave height at a return period of one year of 7.6 metres, as given in Table

A2.3.

•

The average of the maximum individual wave heights within each big wave event is

12.7 metres, with a standard deviation of 1.8 metres, so that the events can certainly be classed as big wave events.

•

The overall maximum individual wave within these 32 big wave events reached 17.1 metres.

•

There is a restricted directional spread, with 95% of the records taken within the big wave events being from the south-west between 200 and 260 degrees.

•

Big waves also occur from the South-East, but at somewhat lower chances of occurrence.

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The following scenario is assumed to by the present day worst case scenario for Cape

Town; the maximum sea levels that can be expected taking into consideration storm setup, wave height and tides (rounded up to the 0.5 metres to fit the GIS system).

• a 2.5 metre increase in sheltered environments

• a 4.5 metre increase in exposed environments

• a 6.5 metre increase in very exposed environments

This scenario would see 25.1 km2 covered by the sea (1 percent of the Cape Metro’s total area of 2,499 km2), albeit for a short time (Cartwright et al, 2008 - Phase 1), as can be seen in Figure A2.6. The analysis was also done for two other future scenarios, but would not be considered in this report. It is assumed that Scenario 1 has a 95% chance of occurring in the next 25 years (Cartwright et al, 2008 - Phase 3). Figure A2.7 gives an indication of the elevation of vulnerable coastal areas. The areas in blue will be flooded in event of a total storm surge of +2.5 metres (this includes wave and tidal impact); in red in event of a +4.5 metres storm surge (as could be expected in exposed environments according to Scenario

1) and orange the flooding in event of a storm surge of +6.5 metres all above LLD.

LLD+2.5m (sheltered environments)

LLD+4.5m (exposed environments)

LLD+6.5m (very exposed environments

Exposure to Worst Case Storms

Figure A2.7: The exposure of the City of Cape Town to the worst case storms to be expected ( Brundrit, 2009 - Phase 5)

These vulnerable areas are mostly built-up (with the exception of two estuaries) and are of high economic value. It includes parts of the central business district of Cape Town and also much of the most expensive housing in the city (such as housing along Clifton beach as shown in Figure A2.8).

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Figure A2.8: Expensive real estate along Clifton beach (www.about.com)

Figure A2.8 also gives an indication of the vulnerability of some of these developments that are situated directly along the beach against the steeply inclined slope of Lion’s Head

Mountain.

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3 Current Coastal Protection and Management Strategy

The City of Cape Town does not currently have generic coastal defence solutions implemented along shore, but rather tailored solutions (where necessary) to accommodate the variations of the coastline. Most of the coastline is not, in essence, protected by artificially designed solutions, but rocky cliffs (such as along Chapman’s Peak and Cape

Point) and coastal dunes (e.g. along False Bay and Table Bay) provide natural protection. In many instances the natural dune protection has however deteriorated due to encroaching development and would need maintenance and potentially have to be expanded in future.

There are parts of the coast protected by sea walls such as the reclaimed area Sea Point

(which is also an old landfill site). The Port of Cape Town and V&A Waterfront leisure development is protected by breakwaters. A wide variety of protection measure is needed for

Cape Town’s constantly changing coastline. Figure A2.9 shows the differing types of coastal protection around the central part of the city. It again highlights the variability of the coastline and the associated need for different protection measures.

Hard protection: Breakwaters and Dolosse

Hard protection: Vertical Sea Wall

Soft protection: Dunes and Beach

Sea Point Sea Wall

Figure A2.9: Broad protection types along coast

A Coastal Act was passed in 2009 (Government Gazette), which aims to establish integrated coastal and estuarine management by means of a legislative basis. It provides the base for creating coastal ‘buffer zones’, in an attempt to stop inappropriate development

(Government Gazette, 2009). The current protection level for the coastline is estimated to range between 1:20 and 1:200, but is not freely available or known for all areas.

It is apparent that the current coastal protection measures need to be studied in more detail to provide integrated solutions for the whole coastline. To reach the abovementioned goal the City of Cape Town has been proactive in developing its own Coastal Zone Strategy

(2003). This Coastal Zone Management Strategy was adopted, by the City of Cape Town,

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities with the intention to manage and safeguard the coast. Previously this coastal zone was managed in a fragmented way by three different governmental agencies (Cartwright et al,

2008 - Phase 1) and was mainly reactive.

According to the Coastal Zone Management Strategy it offers a unique opportunity to introduce a paradigm shift in coastal management practises (Coastal Zone Strategy, 2003):

•

‘A coordinated and integrated approach to coastal zone management from a citywide perspective

•

Recognition of the coastal zone as a distinct and unique management area

•

Recognition of the coastal asset in terms of economic and social development

•

The establishment of a multi-disciplinary coordinating coastal management team

•

Responsibility, accountability and action

•

Centralised planning and budgeting around coastal issues

•

Equitable access to our coast and its associated economic and social opportunities

•

Participative, open and transparent approaches to coastal zone management

•

Creative, dynamic and new approaches to coastal zone management’

The City of Cape Town sees climate change and rising sea levels as an important part of its future coastal zone management and has therefore embarked upon a thorough study of the impacts of this on Cape Town titled ‘Global Climate Change and Adaption – A Sea-Level

Rise Risk Assessment’ . The study involves different phases of which the following has been completed:

•

Phase 1: Sea Level Rise Model (Brundrit, 2008)

•

Phase 2: Risk and Impact Identification (Fairhurst, 2008)

•

Phase 3: A Sea-Level Rise Risk Assessment for the City of Cape Town (Cartwright,

2008)

•

•

Phase 4: Sea-Level Rise Adaption and Risk Mitigation (Cartwright et al, 2008)

Phase 5A: Full investigation of alongshore features of vulnerability on the City of

Cape Town coastline, and their incorporation into the City of Cape Town Geographic

Information System (GIS) (Brundrit, 2009)

•

Phase 5B: Sea-level rise vulnerability assessment and adaption options (Cartwright,

2009)

The aim of the Sea-Level Rise Risk Assessment Project (according to Phase 1 - 5) is to:

•

Model the predicted sea-level changes in a range of scenario’s

•

Model the form that those changes will take

•

Understand the associated impacts on existing coastal systems, infrastructure and property

•

Provide guidance and implications to future coastal development (to be included in the City’s Coastal Development Guidelines)

•

Identify high risk areas

•

Develop long-term mitigation measures

The primary objective of this study is therefore (according to Phase 1 - 5):

•

To model and understand the ramifications of predicted sea-level rise and increased storm events for the City of Cape Town, thereby providing information that may be used for future planning, preparedness and risk mitigation.

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The Sea-Level Risk Assessment Project identified vulnerable parts of the coastline. As much economic activity is located along the coast the financial losses and risks in event of flooding and storm damage would be very significant. Figure A2.10 shows the proposed impact a

Scenario 1 event could have on Cape Town’s central business district (CBD) and port.

Figure A2.10: Cape Town Centre flooding (Cartwright et al, 2008 – Phase 3)

The rise in water level is not necessarily such a big risk to the Port of Cape Town, but the increase in storminess would most likely lead to increased downtime in port operations which is linked to significant loss of potential income for the port. Figure A2.11 shows the low-lying and generally unprotected Strand coast; which is situated on the eastern end of

False Bay. The sea wall along the beach road is insufficient protection against bigger storms. The area is urban and contains housing and commercial facilities.

Figure A2.11: A snap shot image (1:7,222) of the Strand area, depicting the three inundation areas used in the GIS inundation model (Brundrit et al, 2009 – Phase 5A)

Figure A2.12 shows a proposed upmarket development site situated on False Bay coast; the narrow dunes protecting this region and the corresponding exposure to sea level rise should

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities be noted. In some areas development has taken place almost up against the beach; the road along the coast is a main transport hub and it is noticeably vulnerable to sea level rise.

Figure A2.12: Photograph of a proposed upmarket development site on False Bay coast

(Cartwright, 2008 - Phase 3 report)

The Cape Town coastline is very vulnerable to coastal erosion during storm events and many of the climate adaption options are focused on this aspect. Selected climate adaption options advised for the proactive coastal management of the Cape Town coastline

(Cartwright, 2008 - Phase 4) are shown in Table A2.4.

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Table A2.4: Climate adaption options for Cape Town (Cartwright et al, 2008 - Phase 4)

It has become apparent to the City of Cape Town municipality that the current level of coastal protection is not in all instances sufficient to handle the larger and more frequent storms influenced by rising sea levels. Figures A2.13 and A2.14 were taken in August 2008 when the biggest storm in 7 years hit Cape Town. Figure A2.13 shows the Sea Point sea wall which is currently being restored; it is visible that the wall is not designed to withstand these bigger storms.

Figure A2.13: Waves breaking on prime property at Glen Beach

(lesterhein.blogspot.com)

Figure A2.14: Waves overtopping the Sea

Point Sea Wall (lesterhein.blogspot.com)

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4 Overview of existing cost estimate information

Relevant literature relating to climate adaption cost estimates, potential damage costs and actual damage costs for Cape Town are recapitulated in this section. All tabulated costs are given in terms of 2008 values in South African Rand (ZAR) and United States Dollar (US$).

4.1 General

In Phase 3 and 4 of the City of Cape Town Sea-Level Rise Risk Assessment report

(Cartwright et al, 2008) an attempt is made to quantify the opportunity costs in event of environmental damage. The following paragraphs briefly highlight some of the findings in abovementioned reports for a Scenario 1 event.

Cape Town is associated with its beautiful beaches and a Scenario 1 Sea-Level event would presumably lead to foregone tourism revenue (it is assumed that tourism will decrease by 3 percent during the year of the event). This is related to the erosion of beaches such as

Camps Bay, Clifton and Llundudno which would decrease their aesthetic appeal as was illustrated in the tourism losses experienced after an extreme storm took place during 2007 in Durban on South Africa’s east coast (Cartwright et al – Phase 3; Mather et al, 2007b).

The cost of replacing public infrastructure (which falls under the City of Cape Town’s authority – this excludes the Port of Cape Town which is the responsibility of national government) is a financial risk to the municipality. Storm water and electrical distribution infrastructure and municipal transport lines are assumed to be some of the most affected services. It is assumed that 1.5 percent of the city’s storm water infrastructure would need to be repaired in a Scenario 1 event. The estimated cost of road replacement is R900 million and should be compared to the annual road maintenance budget for the City of Cape Town, which is approximately R200 million (Cartwright et al, 2008 - Phase 3). The estimation is that

1 percent if the above surface energy infrastructure will need repair or replacement. A cumulative risk cost is estimated for the City of Cape Town using the occurrence probabilities for the event during the next 25 years, it should be noted that this is an extreme value as the assumption is made that flooding occurs all along the coastline whereas it is generally more localized. The values therefore represent the cumulative risk and coasts over a 25 year period. The cost of damage according to Phase 3 (Cartwright et al, 2008) is summarized in Table A2.5.

Table A2.5: Cost of Damage in a Scenario 1 sea-level rise event (2008 values) (Cartwright,

2008 – Phase 3)

Item

Real Estate

Tourism

Stormwater

Value in ZAR Value in US$

R 3 255 000 000 $434 000 000

R 720 000 000

R 167 000 000

$96 000 000

$22 266 667

Roads

Electricity

R 900 000 000

R 94 800 000

$120 000 000

$12 640 000

Probability of occurrence in next 25 years 0.95

Total potential cost to city R 5 136 800 000

0.95

$684 906 667

Value of risk to city R 4 879 960 000 $650 661 333

The Sea Point seawall is currently being repaired. According to Phase 3 (Cartwright et al,

2008) provisional estimates given to the city indicate that at least R 12.6 million (US$ 1.68 million) will be required for immediate repair and an additional R250 000 (US$ 33 300) per annum should be budgeted for maintenance. The Sea Point sea wall dimensions can be

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AVOID WS2/D1/R14 Costs of Adaptation to Climate Change in Large Port Cities approximated as a length of 4.8 kilometres and a height of 6 metres above the mainly rocky shore.

The different adaption options presented in section 3 above (Table A2.4) were also compared in terms of their relative implementation cost and the suitability of their implementation. Table A2.6 gives a summary of the available cost information about climate adaption.

Table A2.6: Indicative costs for different climate adaption options (Cartwright et al, 2008 –

Phase 4)

Option

Managed retreat

Sea walls

Beach and dune replenishment

Rock armour and gabions

Barrages and barriers

Raising infrastructure

Wetland and estuary rehabiltation

Cost (2008 values)

Description

Weighted average property prices for City's coastline given

High and ongoing maintenance costs

Moderate, but ongoing cost

Depends on availability of rock

Very expensive

Expensive

Could be low cost

Value ZAR

R 1 800 – 2 900 /m2

Value US$

240 - 390 / m2

R 3 000 - R 30 000 /m 400 – 4 000 /m

R12 000 - R15 000 /m beach*

1 600 – 2 000 /m*

*A value per cubic metre of US$14.3 is given in Linham et al (2010) (sourced A Mather, pers. comm.)

It should be noted that the cost given for managed retreat in this instance only includes the weighted average cost of the property which will be lost; the real cost will be higher and include compensation to property owners, lost public infrastructure and loss of real estate.

The unit cost for sea walls are dependent upon the height of the wall, the design of the cross section and the materials used; however the unit cost provided in Table A2.6 was not defined in terms of height or other factors in Sea Level Rise Risk Assessment (Cartwright et al, 2008 – Phase 4) and therefore is given as a wide range of possible values with a potential difference of a factor 10 as could easily be the case in practice. Two costs for beach nourishment are given; one is sourced from the Sea Level Rise Risk Assessment

(Cartwright et al, 2008) for Cape Town and is in cost per meter, whereas the other is from

Linham et al (2010) and in cubic metres. Due to the variability of beach profiles, widths and lengths in Cape Town it is not really feasible to estimate a generic nourishment volume in cubic metres per metre and the value provided in Linham et al (2010) is favoured as a unit cost. As seen in Table A2.6 cost information is not freely available and it is difficult to source accurate unit cost values for local projects. This makes it difficult to budget for future adaption. In this instance the tendering process for government projects is very competitive and consultants are therefore not eager to provide costing information. It is recommended that the City of Cape Town should build up a costing database relating to coastal protection projects (if it does not already exist).

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4.2 Estimated damage cost for specific storm event

4.2.1 Details of Storm

Cape Town was affected by a ‘super storm’ over the weekend of the 30th – 31st of August

2008. This storm was associated with the passage of an intense mid-latitude cold front.

Violent North-Westerly winds of 50 km/h were experienced, with gusts of 80 km/h, which caused a storm surge by piling up the water against the coast. These factors contributed to an increase in mean sea level of over 5 metres; which had a damaging impact on the coastline. Sea swell and waves in excess of 10 metres were experienced as shown in Figure

A2.15; this caused major damage to property and altered the beach profiles. Heavy rainfall was experienced during the storm. (Beckman, 2008)

Figure A2.15: Significant Wave Height during storm (Beckman, 2008)

4.2.2 Recorded losses and damage

It is estimated that most of the damage that occurred during the storm was to formalized private and commercial property and referred to insurers. Unfortunately this information is confidential and has not been made available by insurance companies. Much infrastructural damage transpired along the coastline; including damage to retaining walls, buildings, transport and parking areas etc. The total estimated damage to coastal facilities and structures is valued at roughly R4 937 500 (US$ 655 300). This could be compared to an approximate damage estimate to municipal infrastructure at eThekweni Municipality

(Durban) of R100 million (US$13.4 million) during a low pressure storm system, which coincided with the 18.6 year highest tide, on 19 and 20 March 2007 (Mather, 2007b) (This cost is given in 2007 values). Table A2.7 gives a summary of the estimated damage cost of the August 2008 storm in Cape Town to the municipality.

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Table A2.7: Cost of damage to municipal property during storm event (RADAR, 2008)

Facility/Feature Damage Description

Bikini Beach Ablutions

Bikini Beach Nodal

Kogel Bay Resort

Strand Beach

Glencairn Walkway

(close to subway)

Soetwater Resort

Seawater-flooded ablutions

Sand and rocks on beach to be removed

The sand next to the wall of the tidal pool was removed by the sea

Excessive damage and flooding of building

Due to severe storm damage - the retaining wall was badly damaged.

Damaged stonewall, walkway paving, poles, roof at Busses Parking area.

Refuse and cottage access gates broken

Wooden and glass doors damaged

Fish Hoek Beach

Simonstown Country

Club

Fish Hoek Beach

Fish Hoek Beach

Fish Hoek Beach

Seaforth Beach

Fish Hoek Beach

Fish Hoek Beach -

Jaggers Walk

Muizenberg Pavilion

Surfers Corner Beach

Road

Sonwabi – Baden Powel

Drive

St. James Public Toilets

Silwerstroom resort

Total

Damages to the pumps under subway

Pathway and retaining wall badly damaged

Steps and railings dislodged

Railing on pathway to changing cubicles were damaged, and railing on main steps were washed away.

Access steps and wheel chair access point were damaged

Jaggers Walk and retaining wall badly damaged

Stormwater pipes blocked with sand, doors damaged.

Footpath paving damaged, wooden rail handrail broken, outlet pipes blocked.

Parking lot tarmac and kerbing damaged.

Toilet doors & windows broken.

External shower damaged. Paving slabs around bathing boxes washed away.

Slipway damages (extensive)

Estimated cost

(2008)

ZAR

50 000

15 000

US$

6 667

2 000

25 000

100 000

3 333

13 333

2 500 000 333 333

100 000

180 000

10 000

12 000

75 000

60 000

80 000

60 000

13 333

24 000

1 333

1 600

10 000

8 000

1 500 000 200 000

12 000

15 000

60 000

10 667

8 000

1 600

2 000

8 000

3 500 467

80 000 10 667

4 937 500 658 333

The cost of storm damage is potentially very significant in Cape Town as seen in Table A2.7.

This indicates that future coastal zone management should focus on protecting the coast and minimizing the damage during storm events; which is also a goal of the City of Cape

Town municipality. The extreme storm experienced in KwaZulu-Natal (in South Africa) during

March 2007 showed that areas which were either only sandy or only rocky were generally more resilient to the storm, whereas mixed coastlines of rock and sand (such as much of the

Cape Town coastline), especially pocket beaches, were severely impacted (Mather, 2007a;

Goschen et al, 2009). Extensive damage was incurred during the extreme storm in KwaZulu-

Natal and the statement above indicates that Cape Town could be potentially be even more vulnerable due to the variable nature of the coastline.

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5 Discussion and conclusions

5.1 Challenges in terms of protection and coastal management

Cape Town has a long and variable coastline. Much of the coastline has also been encroached with development; unwisely so in some instances. This means that adaption will be difficult and a diverse mix of solutions would be needed. A generic solution for coastal protection cannot in this instance be formulated for the whole coastline. This makes the adaption process much more expensive and time consuming.

Currently there is no specified protection level or recommended hydraulic boundary conditions for building along the coast. There has however been much work done by local and national government in terms of coastal policies and the protection of the coast. It can be said that the City of Cape Town municipality is taking the risk of climate change very seriously and that they are proactively looking at the issue.

5.2 Comparison between Dutch and Cape coasts

To illustrate the variability of the impact of climate change on coastlines around the world a brief comparison is made between the Dutch and Cape Town coasts. As introduction it can be said that more than one-fifth of the Netherlands is situated below sea level and is therefore much more vulnerable to the sea than Cape Town is; coastal defence is therefore a case of national safety and taken much more seriously in The Netherlands than in Cape

Town. The main risk in The Netherlands is that a breach of the coastal defences could lead to flooding of the hinterland, whereas the main risk in Cape Town is that of erosion and short term flooding during storm events.

The Dutch coast is a low-lying deltaic coast (Hillen et al, 2010) and generally sandy. It can be separated in three generic sections; Zeeland in the south consists of islands, river mouths and estuaries; the Holland coast in the middle; and the Wadden Sea coast with a big tidal basin and barrier islands in the north. The coastline is sandy throughout and is in most instances protected by dunes, with the exception of some sections sea dike. The estuaries and tidal basin require more intervention and this led to the building of storm surge barriers such as the Oosterscheldt and Maestlandkering. The generic nature of the Dutch coast makes it simpler to develop standard design solutions such as dune protection, which can be used along most of the coast with only slight adaption’s necessary for the specific location.

Coastal protection costs would therefore also be easier to estimate.

In comparison the Cape Town coastline is extremely variable. Some areas such as False

Bay have gentle sandy beaches and dune protection solutions similar to that used in the

Netherlands is suitable here. However large parts of the Cape Town coastline are rocky and mountainous. Figure A2.16 of Cape Point shows rocky outcrops with a narrow pocket beach in between. Other areas are protected by sea walls, revetments or breakwaters as described in Section 3.

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Figure A2.16: Cape Point (www.capepoint.co.za)

The Cape Town coast is also very rich in ecological and marine biodiversity. It is one of only three cities in the world classified as urban biodiversity hotspots. It is also one of the smallest of the 25 biodiversity hotspots in the world, which means that it is one of the places in the world with the richest and most threatened plant and animal life (Green Map of Cape Town,

2009). The warm Agulhas current that sweeps down the east coast and the cold Agulhas that flows north along the west coast meet at Cape Town, which leads to rich biodiversity in marine life (Beaches: A diversity of coastal treasures, 2009) . There are various marine and land based nature reserves in the city limits (where no development is allowed) and all new development in the coastal zone now requires an Environmental Impact Assessment (this would also be required for coastal protection work). Figure A2.17 (Green map of Cape Town,

2009) and 5-3 (City of Cape Town Beaches: A diversity of coastal treasures, 2009) shows the land and marine nature reserves within the city limits.

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Figure A2.17: Land based nature reserves

Figure A2.18: Marine protected areas

The diversity in terrain and ecosystem along the Cape Town coast complicate the development and implementation of coastal protection solutions, it is generally necessary to develop a new design solution for each part of the coast. It is also difficult to determine unit costs for coastal protection in Cape Town due to a big range in solutions and costs (as well as the fact that the available information is limited).

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In Cape Town much of the coastline is a focus for economic activity. This is not traditionally the case in the Netherlands where the economic hotspots were generally situated more inland (although connected to the coast by rivers, estuaries and channels e.g. Rotterdam and Amsterdam). Population growth and economic expansion in The Netherlands have however led to development encroaching upon the coast, although the coastal protection legislation of the Netherlands still limits the development. Main highways in the Holland region are generally not situated along the coast as can be seen in many coastal cities, including Cape Town. In Cape Town development started along the coast (as a Dutch colony) and expanded inland, the harbour was one of the first areas developed and businesses and industry was developed around it.

Cape Town’s Central Business District (CBD) is situated in close proximity to the sea and the coast is a hotspot of economic activity and investment as Figure A2.19 illustrates. The World Cup stadium cost R4.4 billion (or approximately US $600 million) to build and was completed in 2010 (Wikipedia). The V&A Waterfront shopping mall and entertainment area is arguably the most visited tourist destination in South Africa; Sol Kerzner’s One and Only Hotel was completed in 2009 and cost approximately R1 billion (US$134 million) to build (The Property Magazine) . The

Port of Cape Town handled 774000 TEU’s in the 2008/2009 financial year

( Transnet ). In Figures A2.19 and 2.17 it is also visible that space for further development of the city centre is restricted by the sea and Port of Cape Town, as well as by the surrounding Table Mountain nature reserve.

V&A Waterfront

World Cup Stadium

Port of Cape Town

One and Only Hotel

CBD

Figure A2.19: Economic activity along the coast

The Cape Town coast is a very valuable tourist attraction and many businesses are catering for the foreign tourist market. It is famous for its beautiful beaches (such as

Clifton shown in Figure A2.20) and nature reserves. If the beaches are damaged and eroded due to a big storm it could affect their attractiveness to tourists. Tourism in the

Netherlands is dominated by visitors to Amsterdam, Keukenhof and cultural locations

(such as dikes and windmills); beaches are not such an important attraction.

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Figure A2.20: Clifton beach (www.southafrica.to)

In The Netherlands the geography and shallow water depths of the North Sea basin leads to very high storm surge, the design storm surge level is therefore 6 meters, whereas in Cape Town the design surge is lower than a meter. Cape Town can however experience bigger waves due to the deep water close to shore and thus wave penetration are not as restricted by water depth as in the Netherlands.

A very common protection measure in The Netherlands is beach nourishment. This is a relatively uncomplicated exercise in The Netherlands due to the availability of dredgers and also potential for offshore sand mining close to site. This solution is much more difficult in Cape Town, where offshore sand mining is much more expensive and environmentally damaging.

The level of available information about shoreline movement and hydraulic records

(wave, wind, water level etc) is very high and of a long duration in The Netherlands.

Most information is freely available and hydraulic design conditions have been established by a governmental organization for the whole Dutch coastline. In Cape

Town there is a significant lack of freely available information about coastal protection, hydraulic records and shoreline movement.

To conclude it is apparent that the Dutch and the Cape coasts are very different and that this also necessitates different protection measures. Adapting coastlines around the world would also require site specific solutions and the cost of solutions would be influenced by local conditions such as the cost of labour.

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References

Beckman, T. (2008) August 30th, 2008 Cape Town ‘Super Storm’ Report: A Weather

Analysis (sourced by Colenbrander, D. – City of Cape Town)

Brundit, G. and Cartwright, A. (2009) Global Climate Change: Coastal Climate

Change and Adaptation - A Sea-level Rise Risk Assessment for the City of Cape

Town. Cape Town: LaquaR Consultants. (Phase 5)

Cartwright, A., Brundrit, G. and Fairhurst, L. (2008) Global Climate Change: Coastal

Climate Change and Adaptation - A Sea-level Rise Risk Assessment for the City of

Cape Town. Cape Town: LaquaR Consultants. (consists of Phase 1 – 4)

Cape Official Travel Website: http://www.capetown.travel/ (front page photographs)

Cape Point Nature Reserve: www.capepoint.co.za

Cape Town Mapstudio: www.mapstudio.co.za

City of Cape Town Reports and Publications: www.capetown.gov.za

(2009). Beaches – A diversity of coastal treasures

(2009) Green map of Cape Town; www.capetowngreenmap.co.za

(2009) City of Cape Town Annual Report

(2008) RADAR: Risk and Development Annual Review – Cape Town ‘Super Storm’

(sourced Colenbrander, D. – City of Cape Town)

(2006) State of the Coast – Summary Report

(2003) Coastal Zone Strategy

Goschen, W. et al (2009) Sea-level rise: trends, impacts and adaption for South

Africa – Phase I: Qualitative overview and analysis . Prepared for the

Intergovernmental Panel on Climate Change (IPPC)

Government Gazette, (2009) Coastal Act . Prepared for South African Government

Hillen, M.M. et al (2010) Coastal defence cost estimates – case study of the

Netherlands, New Orleans and Vietnam . TU Delft in collaboration with Royal

Haskoning

Internet: www.Geology.com: www.about.com: www.southafrica.to : lesterhein.blogspot.com:

Satellite image of Cape Town

Clifton beach estates

Clifton Beach photo

Storm photos

Linham et al (2010) Costs of adaption to the effects of climate change in the world’s largest port cities: Draft report

Mather, A. (2007a) Coastal Erosion and Sea-Level Rise: Are Municipalities ready for this?. eThekekweni Municipality

Mather, A. and Vella, G.F.(2007b) Report on the March 2007 Coastal Erosion Event for the KwaZulu-Natal Minister of Agricultural and Environmental Affairs . eThekweni

Municipality

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Mather, A. (2009) Projections and modeling scenarios for sea level rise at Durban,

South Africa. Report prepared for the eThekwini Municipality

The Property Magazine: www.thepropertymag.co.za

Statistics SA, (2007) Community Survey: Basic results: Municipalities,

South African Navy Hydrographic Office: www.sanho.co.za

South African tidal portal: www.satides.co.za

Theron, A. K. and Rossouw, M. (2008) Analysis of potential coastal zone climate change impacts and possible response options in the southern African region.

Science real and relevant: 2nd CSIR Biennial Conference, CSIR International

Convention Centre Pretoria

Transnet National Port Authority: www.transnet.co.za

Van der Borch, E & Van Verwolde (2004). Characteristics of extreme wave events along the South African coast. Applied Marine Science taught Masters Dissertation.

University of Cape Town, 124pp.

Wikipedia: Cape Town, World Cup 2010

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APPENDIX III: Additional Information on Consequential Losses

The losses from a flood are not restricted to the physical damages; the effects of a flood on the socio-economic system ripple outwards. These consequential losses are conceptually confusing (van der Veen et al., 2003) and this not helped by the practice in cost-benefit analysis of definition by antithesis so that ‘indirect’ losses are everything that is not a direct loss. Similarly, ‘intangibles’ are everything which is not tangible; that is, easily evaluated losses. The nearest to a common factor in ‘indirect’ losses is that they are easiest to express in terms of changes in flows whereas direct losses are easiest to express in changes in stocks. In turn, it is then only correct to add the two together if the changes in flows which are evaluated are not included in the evaluation of the changes in stocks.

The example of a bakery is adopted here to illustrate the nature of consequential losses. In flood loss analysis, the loss of a baker’s oven will include the loss to the baker of not being able to sell bread but not the loss to the consumer of not being able to buy bread from that producer. The loss of the baker’s oven will be included as a direct loss; the latter is a consequential loss.

Consequential losses are a socio-economic system’s response to perturbations caused by the flood. Short term effects occur as adjustments are made throughout much or all of the system. Thus, the adjustments made by the most immediately affected components: firms or households, in turn generate further adjustments by other components. Hence, there are first, second and lower order effects. These adjustments are then spread over time. The first order effects are the socio economic system’s immediate response to the perturbation; the second order effects are how that socio-economic system changes over time, perhaps permanently or recovers to its previous path.

The nature of consequential losses is illustrated in Figure A3.1. In this diagram a very simple system is subjected to an external perturbation and the subsequent paths through which that shock is then transmitted to one element (A) are indicated by heavy arrows. The adjustments made and transmitted to other elements are shown by dashed arrows. The various feedback loops included will either amplify or dampen these changes.

A

B

Purturbation or

External Change

C

D

E

Figure A3.1: Socio-economic system and response to perturbations

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In an economy in the general equilibrium of the microeconomics textbooks, there would be no consequential losses because general equilibrium requires that there are Perfectly Competitive markets for all goods and services. One of the conditions for the existence of a Perfectly Competitive market is that entry and exit to the market must be costless, and a second that no one supplier or consumer can have any effect upon the balance of supply and price (Frank, 2006). In such perfectly competitive markets, the loss of one producer or consumer as a result of a flood would be too small to have any overall effect. However, the hidden assumptions in that definition of a perfectly competitive market are that the adjustment will be both instantaneous and costless. In addition, more recent economic work has pointed up that there are considerable frictional costs in any real economy including what Coase

(1988) and North (1990) have described as transactional costs and the information costs of Stiglitz (2008). These frictional costs are sufficiently important that Coase

(1992) argued that they have to be a central concern of economics; Wallis and North

(1986) further concluded that over 70% of the US GDP was made up of transaction costs.

Here, the term ‘frictional costs’ is used to cover all of the costs that are incurred because unlike the assumptions of Perfectly Competitive markets, the required resources have to move to the right places in the right quantities at the right time and the same is also true of consumption. They are the costs that in the hypothetical ideal economic world would not exist; so, unless the journey itself gives pleasure, transport costs are all frictional costs. These costs can be significant; for example,

UNCTAD reports that for Colombia, transport costs of imports from Africa represent

16% of cost, insurance and freight (CIF) value compared to the transport costs of imports from Europe representing 8.4%. Transport costs as a proportion of CIF values are even higher for some African countries. In turn, large amounts of money are spent on transaction costs simply to enable the combinations of resources and consumption to be combined most effectively.

So, unlike the hypothetical world of General Equilibrium, adjustments will not be costless or instanteous, and the time delays in adjusting will themselves create costs.

We return here to the bakery example to explain the point. A simple production to consumption chain is bread making. To make bread, traditionally requires flour, yeast, water, salt, plus energy. Industrial bread making requires a number of other ingredients as well. If the supply of wheat flour to a small bakery is disrupted by a flood, then the bakery may be able to switch to an alternative supplier. In the worst case, it could switch to an alternative grain and make bread from maize, rye, barley, potato or rice flour instead of wheat flour. That is, providing that the oven can maintain the appropriate temperature for the substitute bread. If the supply of water is cut off, then there is no substitute for water in recipes for bread making; only an alternative source of water will do. Simply, if the supply of energy is cut off, then only an alternative supply of energy compatible with the baking technology is a possible substitute. Thus, in an old-fashioned oven any material which would maintain an adequate temperature when burnt to bake the particular grain flour dough is a possible substitute. But in electric fired ovens, only electricity will do; for example, from emergency generators.

Going down the chain, if one bakery is closed either by a flood or as the result of disruption to the supply chain making it impossible to produce, the consumers who usually buy from that bakery have a number of options (Parker et al., 1987):

1. Defer

2. Transfer

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3. Substitute

Deferral is not a possibility for food although it is for many other goods and services.

The individual consumer may be able to buy from another bakery – the assumption of a Perfectly Competitive Market – but in doing so that consumer will incur either additional costs or buy a less desired loaf. By definition, the consumer experiences a loss because otherwise they would have chosen that alternative when both alternatives had been available. Those additional costs may either be in terms of price or travel or simply in finding out what are the alternatives and where they are available.

If transferral is not possible, then substitution may be an option. Considered as nutrition, potatoes were the nineteenth century substitute for bread. But to be a substitute, there must be a functional equivalent. Again, by definition, the consumer must experience a loss through substitution otherwise they would have previously chosen that option.

What this means is consequential losses should be expected to fall largely on the consumer side of the producer-consumer equation. Since these are typical both more diffuse and larger in number, it is much more problematic evaluate these costs than those to the producers. For example, the UK’s ‘Red Manual’ (Parker et al.,

1987) essentially covers only the losses to producers.

To adequately model the responses to some shock such as a flood, it would be necessary to have:

1. Details of all the production chains which result in intermediate products and consumption

2. The physical, chemical and biological production functions for all the transformations and conversions in those chains. For example, in bread making, the exact combinations of materials, and possible substitutions both between those materials and with other materials

3. The physical location and distribution of the activities which make up the production chains

4. The degree of specialisation and concentration of each of those activities. In practice, this will not be available from published statistics because they are carefully aggregated to prevent identification of either the single firms or small numbers of firms dominating an area of production.

5. The costs and time taken to move items along each of those production chains together with the constraints and capacity of each of those transfer linkages

6. The extent of buffer stocks held at each point in the production chain down to final consumption and;

7. The dependence of these physical flows upon the flows of money and information.

Nevertheless, at the macro level, attempts have been made to build models of an economy as a whole and used to assess the consequences of an extreme perturbation. The best known of these are Input-Output tables (Rose & Miernyk,

1989; Rose and Liao 2005) but CGE (Computable General Equilibrium) models

(Morridge et al., 2003) have also been used. Both are series of chained production functions but each makes different assumptions about the form of those production functions. Unfortunately, what we lack is a set of theoretically derived, empirically grounded production functions (Mishra, 2007). Here, there are two problems:

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1. These macro-models are based upon production functions which specify how some set of input resources can be combined to produce one or more outputs. The problem here is that theoretically we can assert that the form of such production functions must be non-additive (otherwise, if electricity, labour and iron are the input factors for steel production, then we could, if there is no electricity, maintain the same level of production by increasing proportionately the inputs of labour and iron). However, whilst a multiplicity of different production functions have been proposed (Mishra, 2007), with the

Cobb-Douglas function being the most popular, the evidence to support that function has been found to be a statistical artefact (Shaikh, 1974). In consequence, we do not generally have the data with which to calibrate any model other than an Input-Output table.

2. The models use money flows. These imply far greater possible substitution than is actually possible between the input factors. In reality, any production function is determined by the laws of physics, chemistry or biology. So, for example, the production of crude iron from iron ore is governed by the chemical laws (de Beer et al. 1998), which equations are either exothermic

(producing energy) or endothermic (requiring input energy in order to occur).

If energy is insufficient, then adding more oxygen will not help. Thus, in practice, production functions are the laws of physics, chemistry or biology, and the current state of technology determines how closely we succeed in approximating to the theoretical limits determined by those laws.

In particular, the Input-Output model uses an additive production function; this implies that if there is no energy, one can simply increase the input of iron ore to compensate and still produce the same quantity of iron. Thus, Input-Output tables are static descriptions of the economy at one point in time; they are not appropriate to model the transient or long term impacts of a perturbation to the system. In the longer term, the interest in Input-Output tables is how the coefficients change as a consequence of technological change.

What happens in practice in a disaster is that inefficiencies are squeezed out; when there is a shortage of inputs, those inputs are used more efficiently. It is generally true that there is scope for such improvements in efficiency and this has been frequently demonstrated with regard to both energy and water usage. The interesting question to the economist is why such inefficiencies normally exist and the answer seems to be in terms of transaction costs, information costs and the costs of management attention; management focuses upon what is important at a particular point in time and in consequence do not pay attention other factors. So, when there is no problem with energy availability then management attention will instead be concerned with some other factor such as quality assurance. If following a flood, energy supply becomes limited or intermittent, management attention will switch to what has now become a critical factor in maintaining profitability or revenue generation.

A hidden assumption of the neo-classical economic approach underlying the concepts of perfectly competitive markets and general equilibrium is thus that whilst physical resources are scarce, attention is infinite. Conversely, in practice, both at the individual and organisational level, attention is finite and must be allocated between competing needs.

Supposing that we had an adequate model of the system of the economy. In assessing the first order effect of some stock change on flows, a conventional

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1. Where there are economies of scale, marginal cost may be constant, zero or declining rather than the textbook assumption of rising marginal costs

2. Economies of scale are characteristic of capital intensive activities; in such conditions, a producer must be concerned with recovering fixed costs, notably the returns to loan capital (where loan capital is cheaper than equity capital for the obvious reason that the risks are less). Marginal cost analysis is only appropriate for a region of the supply-demand balance where marginal costs exceed average costs

3. In capital intensive industries, disequilibrium between supply and demand may predominate because increasing production requires capital investment and hence a significant time delay in responding to predicted increases in demand. Further causes of disequilibrium are events such as recessions

In addition, those frictional costs that may change after a flood need also to be included. For example, the consumer incurs information and time costs in determining what replacement to buy and unless the purchase is made on the net, there is a time and resource cost to physical visiting one or more shops. If a loan is required to finance the purchase, then the proportion of the cost of the loan above the cost of capital for the assessed level of risk is a frictional cost.

In addition, given a shock, the adjustment mechanism to achieve a short run balance of supply and demand may be through price adjustment or the government may choose instead to ration supplies. The obvious problem with the first approach is that income determines the allocation of available supplies and hence there are immediate questions of equity. Thus, in the case of food, the poor starve. A more general question is: how should a government respond, given a flood, in order to achieve a resilient response? This parallels the response of a household: how should the affected household respond in order to have a resilient response?

Equally, from an efficiency viewpoint, the result will be inefficient unless the existing distribution of income is optimal: otherwise, scarce bricks will be used to rebuild garden walls rather than schools.

However, demand may also be affected rather than remaining constant. Flooded households may experience a fall in income and other households may have reduced income earning opportunities under the changed conditions. Faced with reductions in income, households may dissave or change their pattern of expenditure, reducing consumption of income elastic goods to maintain some level of expenditure on basic goods.

Demand for replacement household durables should be expected to rise in flooded areas in the post-flood period; complaints of ‘price gouging’ by builders are quite common, as increased demand bids up the price of scarce supply.

What is suggested by some preliminary analysis is that the primary impact is on

Consumer Surplus rather than on the producers.

The second effect of a flood will be to displace capital investment away from other uses in order to replace the assets which were destroyed or damaged in the flood, or alternatively to reduce the amount available for consumption. Thus, a government

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Consequent costs may therefore well be significant but neither are the appropriate models available nor the data with which to calibrate those models.

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APPENDIX IV: Depth-damage curves; additional information

A variety of depth-damage curves have been compiled in a number of countries

(Table A4.1). Here, we aim to differentiate between real differences and those differences which are the result of methodological variations or random error. Those starting differences include:

•

The different curves have been derived by a number of different methods

•

Where those curves have been derived by statistical analysis of the losses reported from one or more different floods, those floods differed and the sample sizes also differed

•

The curves were derived at various dates and in different currency units

•

Some of the curves were derived simply as academic exercises; in other cases, the curves have been used either in some specific project appraisal or were intended for general application for such purposes

•

In some cases financial losses rather than economic losses appear to have been used, and the detail in which the nature of the data used and the methodology adopted varies in the detail in which it is reported

•

What therefore is included amongst the losses also probably varies

•

The number of land use categories used varies

•

The number and level of depths used varies

•

Where there are existing data bases publically available as to the value of assets of different kinds at risk (e.g. USA), the curves are derived as loss as a proportion of the value at risk. Where such data bases are not available (e.g. the UK), depth-damage curves are expressed in the form of loss per property or loss per unit area. For the purposes of this study, the former form are required

•

In some cases, the intellectual property rights associated with the particular curve are unclear and consequently it is not possible to give details of the particular curve or curves

There are two main approaches and several subdivisions to developing depthdamage curves, each with their particular strengths and weaknesses:

1. Synthetic

2. Statistical

Both approaches are based upon sample surveys of the population of properties that are at risk of flooding or which have experienced flooding in the past. Hence, the reliability of both for the prediction of flood losses depends upon the degree to which the sample used to generate it is representative of the population to which it is applied; here those properties which will be affected in future floods. Again, the generic difficulty is that it is desired to determine what are the significant differences in the potential losses from different combinations of activity and built form before it is

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It can be seen that the twin problems are consequently that very large sample sizes are required in total and equally it may be difficult to find sufficient cases to test a specific hypothesis.

Conceptually, we may see the process as one of hoped for progressive differentiation; from a state where the best estimate is that all combinations of activity and built form have the same but unknown susceptibility to flood losses. What it is hoped to achieve are some clearly distinct combinations of activity and built form, within each of which categories there is little variance in the losses experienced as a function of some characteristic of flooding, but where there are meaningful differences between these categories of activity and built form in their susceptibility.

The synthetic approach involves specialist loss assessors examining a sample of activity/built form combinations and making expert judgements as to the value of the loss to be experienced at different depths. In the UK, this has been the approach adopted to derive depth-damage curves for dwellings. In effect, this involves a sample of one or two experts assessing the loss from a single typical dwelling within each category. Thus, the ‘Blue Manual’ (Penning-Rowsell & Chatterton, 1976) pioneered the use of standard house types, represented by floor plans and photographs of typical elevations. The hypotheses upon which the categorisation of dwelling types was adopted were: the building type (detached, bungalow, flat etc); building age (largely a proxy for construction technology); and social class (a proxy for household income).

The potential biases here are the degree to which the experts used are adequate as a representative sample of the cadre of such experts and whether, in turn, such experts make accurate and reliable assessments of potential flood losses. A weakness is that losses to building fabric are not related to the construction technology embodied in the particular building.

The alternative approach is statistical analysis of data taken for individual properties.

There are a number of variants of this approach; firstly, whether the survey data is collected from properties which have been flooded or those which are potentially at risk. The second, whether the average loss at each of the specified flood depths is used to define the curve or a function is fitted to the data.

Where the sample is restricted to flooded properties, the data on losses may be insurance data, compensation paid, self-report or, in some cases, as in China

(Ministry of Water Resources, 1998) formally collected using standardised reporting instruments. In principle, because flood loss data is collected in a standardised way using a national standard, China has the best flood loss data in the world.

Restricting the sample to properties that have been flooded is limiting in two ways.

Firstly, there is only data for events that have occurred and hence it will generally exist for the higher frequency events which in turn are normally associated with shallow flood depths. It is, by definition, unusual for a 200 year return period flood to

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The alternative approach is to survey properties which might potentially be flooded.

The advantages of this approach are that it is possible to get data for all depths of flooding and to use a representative sampling approach. The disadvantage is that the data is hypothetical and may be derived by people with differing experience of coping with floods.

One approach that has then been applied is seek to fit some statistical function to the data. An obvious problem here is; what function should be fitted? It is a statistical truism that any function can be fitted to any set of data more or less badly, and therefore it is desirable to start with some theoretical expectation of what function is appropriate. A second problem is that the samples of actual flood losses are usually not a representative sample of what could happen. For example, often flooding was restricted to a limited range of depths so there is no data with which to fit a curve above, say, 1 metre of flooding. Even when there is data for some of the more extreme depths, there are generally only a few cases and those are often outliers.

So, the location of the curve at extreme depths is based on very limited data but those few cases can determine the shape of the curve. In addition, the confidence intervals about a fitted curve are always widest at the extremes of a data set than anywhere else – since the curve must go through the grand mean – but it is often the losses in both very shallow floods and very deep floods in which we are most interested. Finally, the sample size is often small – which in this case means a few hundred - and that makes it impossible to pull out statistically more than one or two secondary determinants of flood losses.

The alternative approach is to take the sample of data of losses at a particular depth of flooding, and to take the average loss for that depth of flooding. This is the approach used in the UK for non-domestic properties. The adequacy of this approach then depends upon the sample size; the number of properties which are considered to have similar flood loss potential. Historically, more differentiations were used in the UK than could be supported by the data. But the logic there was that in undertaking a loss assessment in a particular area, it was preferable to undertake surveys of those properties which initial estimates would contribute the largest proportion of the losses.

The detail in which the different curves are reported and the detail of the derivation of those curves also varies. In some cases, only a graphic of the depth-damage curve is given; this makes it impossible to accurately compare that curve to other curves.

In other cases, no data is given as to the form or derivation of the curves. For example, Barredo et al. (2008) reports that for the European Flood Alert System

(EFAS) project depth-damage curves were derived for all 27 member countries of the

EU but there is no documentation available on the derivation of those curves.

Rusmini (2009) goes on to show the curves derived from the EFAS project for use in

Italy but since the curves are not given as a table, they are unusable for other purposes, including this one. They, like the broader set of depth-damage curves produced, are also specified in terms of the CORINE land use categories which, from experience in assessing flood losses in Paris and in Hungary, are very problematic in urban areas.

191


For completeness, it may be noted that some work has been done using hedonic price analysis (Green, 2003) to explore to what extent the price of a package of land and associated building is impacted by the degree to which that land is at risk of flooding. Such hedonic price analyses are subject to the usual criticisms of the limitations of hedonic price analyses (Green, 2003). To those problems of torturing data in the hope that it will cry out something are added the further problem of finding sufficient data within a single homogenous housing market to be able to undertake the statistical analysis. Yeo’s (2003) comprehensive analysis of existing hedonic price studies shows that there is no clear effect of flooding experience on house prices. A meta-analysis might reveal more but meta-analysis in other areas of environmental economics tend to show that a large proportion of variance explained is accounted for by methodological differences rather than causal factors.

Country

Argentina

Australia

Austria

Bangladesh

Brazil

Canada

Chile

China

Composite

Czech Republic

France

Germany

Table A4.1: Depth-damage curves around the world

Form

Statistical

Synthetic

Unknown

Statistical

Statistical

Synthetic

Statistical

Unknown

Statistical

Unknown

Statistical

Statistical

References

INCyTH (pers. comm.)

Higgins (1981)

Dale et al. (2009)

Faber (2006)

Islam (1997)

Thompson & Tod

(1998)

Nascimento et al.

(2007)

ECOS (1983)

KGS group (2000)

Gonzalez (pers comm.)

Research Institute of Water Economy

(2001)

Barredo et al.

(2008) refer to but without giving any details of functions used or derivation.

Genovese (2006)

Genovese (2006)

Torterotot et al.

(1992)

Knogge (pers. comm.)

Buck (1988)

Elmer et al. (2009)

Gunther (1987)

Kreibich et al.

(2007)

Merz et al. (2004)

Meyer and Messner

(2005)

Notes

Combined losses for contents and fabric

Combined losses for contents and fabric

Details not given

Report by Huizinga on which they are based not apparently available

192


Country

Iran

Italy

Japan

Norway

Poland

Russia

South Africa

Taiwan

Thailand

The Netherlands

Turkey

UK

USA

Vietnam

Yemen

Form

Statistical

Unknown

Unknown

Statistical

Statistical

Statistical

Unknown

Statistical

Synthetic

References

Rusmini (2009)

Luino et al. (2009)

River Planning

Division (1990)

Yamada (n.d.)

Dutta (pers. comm.)

Notes

Commercially confidential

Appear to be derived from the

Dutch curves

Saelthun (n.d.)

Concludes that there is no statistical significant relation between loss and depth


Known to exist but not found in the

English language literature

Booysen et al.

(1999)

Viljoen et al. (1981)

Chang & Su (n.d.)

Kanchanarat (1989)

Statistical

Statistical

Believed to be statistical but insufficiently clear

Statistical

Jonkman et al.

(2008)


Synthetic

Synthetic

Statistical

Unknown

Penning-Rowsell et al. (2003a, 2003b)

Appelbaum (1985)

USACE (2004)

Das Gupta et al.

(2004)

Dutta et al. (n.d.)

Neither form nor details reported

Thus, the real differences that must be sought are those which reflect real differences in the nature and value of what is at risk, and do not simply reflect methodological artefacts. In fact, for validity, there should be differences when real differences ought to be expected and no differences when there is no logical reason why such a difference should exist.

Rather than simple parochialism, there are a number of reasons for taking the UK depth-damage data as the baseline:

193


1. It has been developed over the last thirty years and continually refined in the face of practice

2. It is well documented both in terms of methodology and in detail

The data for the USA has been around slightly longer but revisions appear too occasional and they are not very well documented.

The differences that may exist are either or both in:

1. Shape

2. Height

For the contents of a building, for each floor, losses should reduce above some height, around head height, because of the inconvenience of storing items above a level within convenient reaching distance. There are currently some differences in the average height of populations in different countries; compare, for example, China and the Netherlands. Importantly, where storage is automated or mechanical (e.g. palleted warehouses, discount warehouses, container storage yards), the relevant height is that of the maximum operating height of the handling gear. However, the form of the curve at lower depths is much more problematic and it can reasonably be expected to vary between countries. At shallow depths, the primary loss will be from floor coverings, and cultures differ in both the structural form of the floor and the nature of any coverings. It might be argued that there is an income related element in preferences for floor coverings but this argument seems rather tenuous.

For structures, it is the construction form, and hence the susceptibility of both individual components and materials as well as the assemblage as a whole to physical, chemical or biological attack that determines the shape of the curve. A rather speculative relative ranking of the susceptibility of different material assemblies to flood damage is:

•

High : dried mud, plaster, reassembled wood (e.g. chipboard, fibre board, wood veneers, plywood); electrical systems; thermal insulation (unless impermeable); electronic controls;

•

Medium : lightweight vertical sheets of metal (e.g. metal grills) or glass

(windows); electrical systems; thin timber sections including timber panelling; structural wood plank flooring;

•

Low : baked brick, mass or reinforced concrete; concrete block work; large timber sections; aluminium; most plastics; terrazzo or mosaic or clay tile flooring

The shape of the curve should then be expected to reflect the variation in distribution of these materials over height. Again, a key difference is in the form of the floor assemblage. But a key assumption is that the building is allowed to flood; if there is a significant (say, one metre) difference in water level between inside the building and outside, then lightweight buildings (e.g. mobile homes) will float and heavy weight buildings will suffer some form of structural failure as a result of the pressure differential (Kelman, 2002).

Higgins (1981) developed a simple way of looking at the comparative shape of the depth-damage curves. If the loss is normalised to some depth, then the loss experienced at lesser and greater depths can be expressed as a ratio of the loss at that standard depth (Figures A4.1 and A4.2).

194


5

4

3

7

6

2

1

0

0

UK - FLAIR

UK -suvrey

USA

Japan

Bangladesh

Australia

Taihu Basin, China

Canada

1 2 3

Figure A4.1: Comparative contents losses for dwellings

10

8

6

FLAIR

USA (Appelbaum, 1985)

Japan

Australia (SMEC)

Canada

Buenos Aires

Taihu Basin, China

4

4

2

0

0 1 2 3 4 5

Depth of flooding (m)

Figure A4.2: Comparative structural losses for dwellings

6

195


APPENDIX V: The Future of Losses

It is readily shown that increases in annual flood losses may be associated with increases in efficiency (Green et al., 1993). Hence, future flood losses may increase simply as a result of increases in efficiency in the use of land.

Two main reasons exist to anticipate that losses from flooding will increase. Firstly, since it is assets which are lost, economic growth should be expected to be accompanied by increases in flood losses faster than the rate of economic growth.

This will be particularly marked in those countries where the proportion of household income spent upon food is still above 25%. As the proportion of household income falls, the amount of money available to be spent upon those consumption durables liable to damage in a flood increases faster than the rate of growth in household income. A significant uncertainty associated with this expectation is future movements in the real prices of basic food stuffs.

Simultaneously, the development of the economy typically increases vulnerability.

Economies of scale induce centralisation and specialisation whilst the technologies involved are more susceptible to damage by water. Electronic technologies are much more susceptible to water damage than mechanical or electro-mechanical technologies. Additionally, it is not known whether the built forms that will result from a requirement for sustainable development (for example, levels 4 and 5 of the Code for Sustainable Homes) will be more or less susceptible to flood damage. On balance, it is likely that they will be more susceptible to damage because of the thermal insulation required.

Those new technologies also require clean operating environments therefore cleaning up after a flood requires more time and cost. In addition, the principle of sustainable development, of doing more with less, reduces the resilience of the system; there is less redundancy and diversity in the system.

Climate change is a third factor: flooding is weather coupled to land form as modified by land use. The weather component in this case is the deep depressions, the tracks of which are believed to be influenced by the jet streams. Recent evidence suggests the jet streams have been moving away from the equator. If climate change results in more frequent deep depressions, or deeper or larger depressions, the losses from such events can be expected to increase.

A possible countervailing factor is that the shift to a low carbon economy may have the effect of significantly reducing shipping movements, although a hydrogen based economy might still possibly involve significant shipping movements. Some forms of sustainable development may also involve a shift away from moving goods substantial distances and hence reduce the pressure on development on the coast.

A major imponderable is future population. Whilst much of the world is still urbanising, the most recent predictions of population levels in Europe are for significant falls in population over the coming century (EUROSTAT, 2008). That fall will be associated with an ageing population which in turn may affect decisions as to where to live.

196


APPENDIX VI: Email survey

1. Is coastal flood risk an issue of concern in the city?

2. Is erosion risk an issue of concern in the city?

3. How is flood/erosion risk managed in the city? (e.g. structural defences, planning regulations, etc.)

4. Can you provide any information on these measures for each city? For example:

•

Type of structural defence (e.g. dykes, seawalls, etc.)

•

Level of protection offered by defences (e.g. city protected against the 1 in

200 year storm)

•

Absolute height of defences above MSL or other datum

•

What the basis for the design of these defences is -- historic storm plus allowance, risk based approach, etc?

•

Are any planning regulations relevant to coastal flooding/erosion in force?

•

Any other measures employed by the city to combat coastal flooding or erosion?

5. How many different types of defences would it be sensible to analyse in the context of your country?

6. How are costs best captured? Sand costs are simple as a cost per volume.

However, a cost of a dyke will be a function of the length, but also the height.

Your comments would be welcome.

7. How do the height of defence structures grow with rising sea levels --

Hoozemans et al. (1993) assume a height increase double that of sea level rise, but is this reasonable based on experience in your country?

8. How might we obtain similar information elsewhere in this region?

9. Any other thoughts?

197


APPENDIX VII: Matrix summarising the main data contained within the accompanying Excel database

Shaded boxes denote data availability. The full Excel database can be accessed through the AVOID stakeholders website at www.avoid.uk.net/private2/

Country Port City Additional Port City Information Available

ALGERIA

ANGOLA

ARGENTINA

AUSTRALIA

AUSTRALIA

AUSTRALIA

AUSTRALIA

AUSTRALIA

BANGLADESH

BANGLADESH

BANGLADESH

Algiers

Luanda

Buenos Aries

Adelaide

Brisbane

Melbourne

Perth

Sydney

Chittagong

Dhaka

Khulna

18 19

Most severely affected areas for coastal erosion

Planning policy permits development only above the 1:100 year flood level

Susceptibility to storm surge

Estimated 1:100 year surge depth

Non-structural flood prevention measures noted

BRAZIL Santos

Flooding of the coastal plain known to be significant

Elevation of port known

18

The western part of the city has an organised flood defence system with an estimated SoP. The measures proposed to protect the eastern half of the city have not yet been started

19

Average embankment height in the western part of the city known

198

AVOID WS2/D1/R14

Country Port City

BRAZIL Belém

BRAZIL

BRAZIL

BRAZIL

BRAZIL

BRAZIL

BRAZIL

BRAZIL

BRAZIL

CAMEROON

CANADA

CANADA

CHINA

CHINA

CHINA

CHINA

CHINA

CHINA

Fortaleza

Grande Vitória

Maceió

Natal

Recife

Porto Alegre

Rio de Janeiro

Salvador

Douala

Montréal

Vancouver

Dalian

Fuzhou Fujian

Guangzhou

Guangdong

Shenzen

Hangzhou

Ningbo


Additional Port City Information Available

Prone to river flooding

Influence of ocean waves is null





No criteria for design of coastal structures



Prone to river flooding

Influence of ocean waves is null



Highest astronomical tide known

Coastal flood risk not an issue

Planning policy flood construction level known

Coastal flood risk on this coast among most significant in China

Previous extreme water level known


Previous extreme water levels known



Previous extreme water level known


199

AVOID WS2/D1/R14


CHINA

CHINA

CHINA

CHINA

CHINA

CHINA

CHINA

CHINA

Qingdao

Shanghai

Taipei

Tianjin

Wenzhou

Xiamen

Yantai

Zhanjiang

CHINA HONG

KONG

COLOMBIA

CÔTE D'IVOIRE

CUBA

DEM. REP.

Korea

DENMARK

DOMINICAN

REPUBLIC

ECUADOR

EGYPT

Hong Kong

Barranquilla

Abidjan

Havana

N'ampo

Copenhagen

Santo Domingo

Guayaquil

Alexandria

FINLAND Helsinki

FRANCE

Marseille-Aixen-Provence





Previous extreme water levels known


Low flood risk

Older areas of city at lower flood risk

Minimum new construction level known


At low coastal flood risk

Few defence works present

Neighbouring cities known to be vulnerable to flooding

Reclamation fill

200



GERMANY Hamburg

GHANA Accra

GREECE

GUINEA

HAITI

INDIA

INDIA

Athens

Conakry

Port-au-Prince

Madras

Kochi

INDIA

INDIA

INDIA

INDIA

Kolkata

Mumbai

Surat

Visakhapatnam

INDONESIA

INDONESIA

Jakarta

Palembang

INDONESIA Surabaya

INDONESIA Ujung Pandang

IRELAND

ISRAEL

ITALY

Dublin

Tel Aviv-Jaffa

Naples

20

Structure design water levels known

Design rationale outlined


Established master plan in Shleswig-Holstein setting design standards for flood defences

Vulnerable to coastal erosion

No holistic policy present – management is traditional and reactive

Generally not susceptible to coastal erosion or flooding

Historically affected by surges due to Bay of Bengal basin bathymetry



Susceptible to flooding from rainfall

Future plans outlined including desired SoP

20

SoP in Hamburg is not known exactly as the structure designs are based on historical extreme water levels rather than statistical analysis of surge return periods

201

AVOID WS2/D1/R14


JAPAN

JAPAN

JAPAN

JAPAN

JAPAN

JAPAN

KUWAIT

LEBANON

LIBYAN ARAB

JAMAHIRIYA

LIBYAN ARAB

JAMAHIRIYA

MALAYSIA

MOROCCO

MOROCCO

MOZAMBIQUE

Fukuoka-

Kitakyushu

Hiroshima

Nagoya

Osaka-Kobe

Sapporo

Tokyo

Kuwait City

Beirut

Banghazi

Tripoli

Kuala Lumpur

Casablanca

Rabat

Maputo

MYANMAR Rangoon

NETHERLANDS Amsterdam

NETHERLANDS Rotterdam



Situated inland and therefore requires no coastal defences

Erosion is severe along newly developed waterfront projects

SMART tunnel to alleviate storm water flooding from extreme rainfall

Many structures in poor repair

Mixture of defence structures along the coast

Hit by Cyclone Nargis in 2008 killing 85,000+ people

Nargis caused a surge in excess of 3 m height

Nargis is estimated to be a 1:20 year storm

Reclamation fill

Maintenance

Surge barrier

202



NEW

ZEALAND

NIGERIA

PAKISTAN

PANAMA

Auckland

Lagos

Karachi

Panama City

21

Coastal erosion and flooding an issue in some places

Regulatory environment focussed on removing people from the hazard

Structural defences are a last option

Coastal erosion can be very severe

PERU

PHILIPPINES

PHILIPPINES

PORTUGAL

PORTUGAL

PUERTO RICO

REPUBLIC OF

KOREA

REPUBLIC OF

KOREA

REPUBLIC OF

KOREA

Lima

Davao

Manila

Lisbon

Porto

San Juan

Pusan

Ulsan

Inchon

Much of the city is up to 100 m above sea level and therefore not susceptible to flooding

Densely populated, low-lying areas may be at risk following SLR in future

Susceptible to typhoons

Reclaimed areas are especially flood-prone

Susceptible to coastal erosion

Occurrence of coastal flooding mainly due to heavy typhoon rains

Presence of defence structures in shipyard and port

Severe erosion due to high waves

Seldom affected by typhoons

Coastal flood risk exists due to high tides

Tidal range approx. 10 m

No severe erosion

21

Although this project is limited to Bar Beach and does not represent a consistent defence height for the city

203

AVOID WS2/D1/R14


RUSSIAN

FEDERATION

SAUDI ARABIA

SENEGAL

St. Petersburg

Jiddah

Dakar

SINGAPORE Singapore

Mogadishu

Cape Town

SOMALIA

SOUTH

AFRICA

SOUTH

AFRICA

SPAIN

SWEDEN

THAILAND

TOGO

TURKEY

TURKEY

UKRAINE

Durban

Barcelona

Stockholm

Bangkok

Lomé

Istanbul

Izmir

Odesa



Cost of flood protection barrier (1.8 bn 2008 GBP)

Marina barrage has multiple functions – amenity, water supply and flood defence

Minimum reclamation levels

Marina Barrage cost (167m 2008 USD)

Some susceptibility to coastal flooding and erosion

No specific structural guidelines exist for coastal flood structures in South

Africa

Multiple measure employed

Structural defences applied only along a small portion of the Durban coast

Some planning controls in place

Municipality sea level rise vulnerability assessment undertaken

No official coastal defence system

Artificial beaches created for 1992 Olympics

Height of piers in harbour area known

Turkish storm surge hazard is not critical

Presence of steep coastal cliffs reduces flood vulnerability

Turkish storm surge hazard is not critical

Presence of steep coastal cliffs reduces flood vulnerability

Reclamation fill

Groynes

Managed retreat

204



UNITED ARAB

EMIRATES

UK

UK

UNITED

REPUBLIC OF

TANZANIA

Dubai

Glasgow

London

Dar-es-Salaam

22

USA Baltimore

USA

USA

USA

Boston

Houston

Los Angeles-

Long Beach-

Sanata Ana

USA Miami

Coastal defence upgrades currently underway


Thames Barrier cost (535m 1982 GBP)

Coastal flood risk is a concern

Coastal erosion is less problematic

Significant areas at high risk of flooding

Information on Galveston seawall including height

Proposed ‘Ike Dike’

Coastal flooding and erosion both problems

Planning regulations in place

Majority of city’s shoreline is privately owned and maintained

Many coastal structures in poor repair

Large amounts of data available on reconstruction of coastal defences following Hurricane Katrina USA New Orleans

22

This is the target SoP for defence upgrades scheduled for completion in 2011

Revetments

Dunes

205

AVOID WS2/D1/R14


USA

New York-

Newark

USA

USA

USA

USA

USA

USA

USA

Philadelphia

Portland

Providence

San Diego

San Francisco -

Oakland

San Jose

Seattle

USA

Tampa-St

Petersburg




Highly vulnerable to storm surge

Information describing damage from varying strength storms

Critical infrastructure at risk of flooding


Three areas of the city susceptible to erosion

Coastal flooding is problematic

Coastal erosion not such a problem

Many neighbourhoods lie in the 100 year floodplain

City wide emergency flood plan exists

Mainly soft measures to combat flooding

Coastal flood and erosion risk not an issue

Many non-structural measures adopted

Cost of Fox Point Hurricane Barrier (16 m 1960 USD)

Lack of a comprehensive database describing defences

Detailed information on Alaskan Way seawall

Seawall in poor state of repair

Plans for new defences currently underway

Coastal flooding and erosion are issues of concern


Mainly soft measures to combat flooding

Coastal structures only protect small pockets of land

Surge barrier

Marshland stabilisation

Marshland creation

Freshwater diversion

Marshland stabilisation maintenance

Closure dam

Levee armouring

206

AVOID WS2/D1/R14


USA

USA

URUGUAY

VENEZUELA

Virginia Beach

Washington

DC

Montevideo

Maracaibo

VIETNAM Hai Phòng

VIETNAM

Ho Chi Minh

City



Cost of beach nourishment and seawall project

Two significant coastal erosion projects exist on this seafront

Detailed information on recent projects

Susceptible to subsidence from oil removal

Progressive dike heightening has become necessary

Flood risk remains significant despite significant investment

Structural and non-structural measures employed

Stated SoPs are likely to be lower than advertised

Flood risk remains significant despite significant investment

Structural and non-structural measures employed

Stated SoPs are likely to be lower than advertised

Dike maintenance

207


APPENDIX VIII: Coastal adaptation neglected by IPCC CZMS (1990) and

Hoozemans et al. (1993)

Country

Australia

Bangladesh

Hong Kong

Denmark

Greece

Italy

Japan

Mozambique

New Zealand

Singapore

Spain

South Africa

UK

USA

Adaptation Measures

Seawalls

Rubble revetments

Elevated shelters

Flood forecasting and warning

Public Information

Flood proofing

Coastal and floodplain regulations

Reclamation levels

Groynes

Shore parallel breakwaters

Natural rock groynes

Natural rock detached breakwaters

Rock revetments

Detached breakwaters

Groynes

Sloping walls

Breakwaters

Revetments

Rip rap

Revetments

Bio-engineering

Reclamation levels

Storm surge barrier

Vertical seawall

Sloping rock revetments

Offshore structures

Gabion retaining walls

Dolosse

Geofabric bags

Re-establishment of natural systems

Reno mattresses

Gabions

Rock armour

Vertical seawalls

Dunes

Shingle nourishment

Storm surge barriers

Storm tide warning service

Seawalls

Flood insurance

Revetments

Public information

208


APPENDIX IX: Persons Contacted

Al Raey, M.

Burgmans, S.H.

University of Alexandria, Egypt

Van Oord, the Netherlands

Office of Public Works, Ireland Casey, J.

Clayton, D. Florida Dept. of Environmental Protection, USA

Colenbrander, D. City of Cape Town, Local Government, South Africa

Cosby, J.

Cox, D.

Duperault, J.

Eichhorn, L.

Director of Public Works, Virginia Beach, USA

Oregon State University, USA

Florida Division of Emergency Management, USA

City of Seattle Government, USA

Fairhurst, L.

Flynn, B.

Gaynor, P.

Gebert, J.A.

Gönnert, G.

Haigh, I.

Hallegatte, S.

Harel, M.A.

ICLEI, South Africa

Miami-Dade Dept. of Environmental Resources Management,

USA

Providence Emergency Management Agency, USA

Philadelphia District, Corps of Engineers, USA

LSBG, Germany

University of Western Australia, Australia

CIRED - Météo-France, France

City of Philadelphia Government, USA

Holmes, J.

Holtzhausen, A.

Hughes, T.

Hunter, J.

Jimenez, J.A.

Kamphuis, J.W.

Kench, P.

Koutitas, C.

Kraus, N.

Lee, G-H

Lenôtre, N.

Lind, N.C.

Lott, J.

Marten, S.

Mather, A.

Miller, G.

La’ala Al-Kuwait Real Estate, Kuwait

Prestedge, Retief, Dresner, Wijnberg Ltd., Cape Town, S.A.

Pennsylvania Emergency Management Agency, USA

Antarctic Research Centre, Tasmania

Universitat Politècnica de Catalunya, Barcelona, Spain

Queen’s University, Ontario, Canada

The University of Auckland, New Zealand

Aristotle University of Thessaloniki, Greece

USACE, USA

INHA University, Korea

Bureau de Recherches Géologiques et Minières, France

University of Waterloo, Canada

National Oceanic and Atmospheric Administration, USA

City of Seattle Government, USA eThekwini Municipality, Durban, S.A.

Tampa Bay Regional Planning Council, USA

209


Mimura, N.

Much, D.

Neves, C.F.

Ibaraki University, Japan

Hamburg Port Authority, Germany

Universidade Federal de Rio de Janeiro, Brazil

Pekar, G.

Post, A.

Texas Dept. of Public Safety, USA

New York City Office of Emergency Management, USA

Prinos, P. Aristotle University of Thessaloniki, Greece

Reinen-Hamill, R.R. Tonkin and Taylor Ltd., New Zealand

Roehrs, P. City of Virginia Beach, Public Works Engineering, USA

Shaughnessy, G. Maryland Dept. of Natural Resources, USA

Sørensen, P.

Uhl, F.

Danish Coastal Authority, Denmark

Ministère de l’Écologie , de l’Énergie, du Développement

Underwood, S. durable et de la Mer, France

USACE, USA van Logchem, B. National Disaster Management Institute, Mozambique

Vicinanza, D. Second University of Naples, Italy

Withycombe, G. Sydney Coastal Councils, Australia

Woodroffe, C.

Wright, I.

University of Wollongong, Australia

Environment Agency, UK

210


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Akhand, M.H. (1996) Bangladesh cyclone shelters and local communities. Stop

Disasters, 29 (3), p10.

Alcamo, J. et al. (2003) Ecosystems and Human Well-being: A Framework for

Assessment . Washington D.C.: Island Press.

Alhadaddad, B.I, Roca, J., Burns, M.C. and Garcia, J. (2004) Satellite imagery and

LIDAR data for efficiently describing structures and densities in residential urban land uses Beijing. Available from: www.isprs.org/proceedings/XXXVII/congress/8_pdf/1_WG-VIII-1/07.pdf [Accessed:

26/03/10] classification .

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Matrix in the case of a Major Catastrophe: Flooding in the Netherlands

Budapest

, 13 th annual conference of the European Association of Environmental and Resource Economics,

Bureau of Economic Analysis (2003) Fixed Assets and Consumer Durable Goods in the United States, 1925-97 . Washington DC: US Department of Commerce

Delft Cluster (2003) The role of Flood Impact Assessment in Flood Defence Policies, seminar , Delft du Plessis, L.A. (2001) The generation and use of cumulative probability distributions in flood risk assessment for the Mfolozi flood-plain. Water South Africa , 27 (1), 27-34

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Managing Coastal Vulnerability , Elsevier

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Assessments and Vulnerability Analysis

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Assessment and Vulnerability Analysis . Dhaka: Bangladesh Institute of Development

Studies

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(3), 524-541

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