Disaster Mitigation Saves
Please reference this document as:
Kelman, I. and C.M. Shreve (ed.). 2013. Disaster Mitigation Saves. Version 12, 13 June 2013
(Version 1 was 30 October 2002). Downloaded from
http://www.ilankelman.org/miscellany/MitigationSaves.doc
Purpose:
People, especially donors, often ask for proof that disaster risk reduction works. This
document compiles quantitative studies of disaster risk reduction projects, namely disaster
mitigation, indicating the savings obtained for the investment. Only studies with such
numbers are included. For instance, studies only describing methods are listed only under
“Useful References Without Ratios”.
Suggestions to:
Ilan Kelman
http://www.ilankelman.org/contact.html
Thanks to:
Bob Alexander
Charles Setchell
Charlotte Benson
Chris Newhall
Daniel Kull
David Crichton
James Lewis
John Twigg
Kate Hawley
Marcus Moench
Reinhard Mechler
Steve Bender
Terry Jeggle
Tricia Wachtendorf
1
Contents
Contents ............................................................................................................................................... 2
The Infamous 7:1 Ratio........................................................................................................................ 4
Acronyms and Abbreviations............................................................................................................... 4
Summary Table of Case Studies .......................................................................................................... 5
Case Studies ......................................................................................................................................... 8
Australia ........................................................................................................................................... 8
Australia ........................................................................................................................................... 8
Austria .............................................................................................................................................. 8
Bangladesh ....................................................................................................................................... 9
Bangladesh ..................................................................................................................................... 10
Belarus ........................................................................................................................................... 10
Canada, Ontario ............................................................................................................................. 10
China .............................................................................................................................................. 10
Costa Rica, Limón.......................................................................................................................... 10
Croatia ............................................................................................................................................ 11
Dominica ........................................................................................................................................ 11
DRC, Kinshasa ............................................................................................................................... 11
Fiji, Navua ...................................................................................................................................... 12
Georgia ........................................................................................................................................... 12
Germany ......................................................................................................................................... 12
Germany ......................................................................................................................................... 13
India ............................................................................................................................................... 13
India ............................................................................................................................................... 14
India, Rohini River Basin, Northeast Uttar Pradesh ...................................................................... 14
Indonesia ........................................................................................................................................ 14
Iran, Dez and Karun catchments .................................................................................................... 14
Jamaica ........................................................................................................................................... 15
Kazakhstan ..................................................................................................................................... 15
Malawi, Mzimba District ............................................................................................................... 15
Maldives: Gaaf Dhaal Atoll Thinadhoo, Gaaf Alif Atoll Villigili, and Thaa Atoll Vilufushi....... 15
Mozambique................................................................................................................................... 16
Nepal .............................................................................................................................................. 16
Nepal .............................................................................................................................................. 17
Nepal, Kailali ................................................................................................................................. 17
Nepal, Kathmandu Valley .............................................................................................................. 18
Netherlands .................................................................................................................................... 18
Pakistan, Lai Floodplain ................................................................................................................ 18
Pakistan, Lai River ......................................................................................................................... 18
Peru ................................................................................................................................................ 19
Philippines...................................................................................................................................... 19
Philippines...................................................................................................................................... 19
Philippines...................................................................................................................................... 19
Philippines...................................................................................................................................... 20
Samoa ............................................................................................................................................. 20
Sudan, Red Sea State ..................................................................................................................... 20
U.S.A.............................................................................................................................................. 21
U.S.A.............................................................................................................................................. 21
U.S.A.............................................................................................................................................. 22
U.S.A.............................................................................................................................................. 22
Vietnam .......................................................................................................................................... 22
2
Vietnam .......................................................................................................................................... 23
Vietnam .......................................................................................................................................... 23
Vietnam, Da Nang Province .......................................................................................................... 23
World, 35 Developing Countries ................................................................................................... 23
Case Studies to Investigate Further .................................................................................................... 25
U.S.A., FEMA’s Project Impact .................................................................................................... 25
U.S.A., Washington, Seattle: Medic One ...................................................................................... 25
World, Community teams related to disaster risk reduction .......................................................... 25
Useful References Without Ratios ..................................................................................................... 26
3
The Infamous 7:1 Ratio
Many continue to quote the World Bank as having calculated that disaster risk reduction saves $7
(sometimes $4-7) for every $1 invested, even though the World Bank no longer promotes that
specific statement and recommends that the ratio not be used. With help from many colleagues, the
earliest source for these numbers found so far is:
Dilley, M. and B.N. Heyman. 1995. “ENSO and Disaster: Droughts, Floods and El Nino Southern
Oscillation Warm Events”. Disasters, vol. 19, no. 3, pp. 181-193.
This paper states (p. 183):
“The World Bank and U. S. Geological Survey calculate that a predicted $400 billion in economic
losses from natural disasters over the 1990s could be reduced by $280 billion with a $40 billion
investment in prevention, mitigation and preparedness strategies”.
No citation is given. It is strongly recommended to avoid using these numbers while investigations
continue regarding:
1.
Checking if the 7:1 ratio originates from the $280 billion / $40 billion figures or other
calculations.
2.
Finding the original study and calculations with either the $280 billion / $40 billion numbers or
the 7:1 ratio.
Acronyms and Abbreviations
BCR, B:C
CBA
DRM
DRR
EWS
FRB
IFRC
NPV
Benefit to Cost Ratio
Cost-Benefit Analysis
Disaster Risk Management
Disaster Risk Reduction
Early Warning System
Flood Retention Basin
International Federation of Red Cross and Red Crescent Societies
Net Present Value
4
Summary Table of Case Studies
This table summarises all the case studies in this document.
Reference
Brown et al., 1997
Location
Canada, Ontario
Hazard
Flood
BTRE, 2002
Australia
Flood
Brouwer and van Ek, Netherlands
2004
Flood
Burton
2009
Flood
and
Venton, Philippines
Chowdhury et al., 1993
Bangladesh
Cyclone
Dedeurwaerdere, 1998
Philippines
DES, c. 2001
Australia
Floods,
lahars
All
EWASE, 2008
Förster et al., 2005
Germany
Germany
Flood
Flood
Ganderton et al., 2006
Godschalk et al., 2009
MMC, 2005
Rose et al., 2007
Gocht, 2003
U.S.A.
All
Germany
Gocht, 2004
Guocai and Wang, 2003
Vulnerability
Economic, direct
Benefit:Cost Ratio
Losses were 0.5%
what they might
have been.
Infrastructure
Given as savings,
not ratios.
Economic, Social, Given as costs and
Ecological
benefits of different
land use scenarios
compared
to
a
baseline.
Mobility disruption 0.7 to 31
and
property
damage
People
US$80 per death
averted.
Economic
3.5 to 30
Economic
and
social
Economic
Agriculture, road
networks,
buildings, fishery
Disaster losses and
repairs
3
Flood
Economic
Germany
Flood
Economic
China
All
Economic
0.80
(mean,
insurance
deliverables); 0.90
(derivatives)
0.10 (mean, Polder
invest)
Reported
as
cost-benefit (1:35,
1:40)
15
Healy and Malhotra, U.S.A.
All
2009
Heidari, 2009
Iran,
Dez
and Flood
Karun catchments
Holland, 2008
Fiji, Navua
Flood
Disaster damage
IFRC, 2009
Property and land
damage
Property
and
livelihoods losses
Carinthia, Austria Flood, mass Property damage,
near the border to movement
building stability,
Slovenia
(especially infrastructure
shallow
damage, possible
landslides) river blockage
Vietnam
Typhoons
Infrastructure,
economic
Philippines
Flood
Economic
IFRC, 2011
Vietnam
Holub and Fuchs. 2008
IFRC, 2002
Flood
Economic,
2.6 to 9
2.2 to 5.8
4
0.29-1.03 (levees);
0.78-1.34 (dams)
3.7 to 7.3
1.67 and 1.21
52
2 of 3 interventions
successful: 4.9-24
3-68
(excluding
5
ecological
IFRC, 2012
Bangladesh
Cyclones,
Flood
Khan et al., 2008
Khan et al., 2012
Pakistan
Vietnam
Nepal
Flood
Khogali
2009
and
Zewdu, Red Sea
Sudan
State, Drought
Kilma et al., 2011
U.S.A.: Florida
Tropical
Cyclones
Kilma et al., 2013
U.S.A.: Florida
Tropical
Cyclones
Kull et al., 2008
India: Rohini River Flood
Basin Uttar Pradesh
Pakistan, Lai River Flood
Kull et al., 2013
Kunreuther
and Global:
Michel-Kerjan, 2012
developing
countries
Direct and indirect 1.3 to 25.0
damage
35 Earthquake, Economic,
Flood
lost
La Trobe and Venton, Mozambique
2003
Flood
Lazo and Chestnut, 2002 U.S.A.
All
Lewis, 2007
Mechler, 2005
Mechler, 2005
Cyclone
Flood
Flood
Vietnam
Piura, Peru
Semerang,
Indonesia
ecological benefits)
28-104
(with
ecological benefits,
yet
to
be
materialized)
Social, ecological, 1.18-3.04
economic
3.05-4.90 (over a
15-yr time frame)
Economic
1-25
Economic
3.5 for boat winch
system, Vietnam;
2 for straw-bale
housing, Nepal
Food,
water, 2.4 to 1,800
agriculture,
and
livestock
Economic loss from Model
compares
property damage
economic loss using
wave pumps to
lower
SST
(hypothetical)
vs.
adding shutters to
houses (hardening);
values reported in
direct economic loss.
Economic loss from Similar to Kilma et
property damage
al.,
2011
but
investigates
storm
surge and wind
damage;
values
reported
in
net
economic loss
Economic
2-2.5
lives >
1
retrofitting
schools
to
be
earthquake resistant;
ave.
60
for
one-meter
wall
around houses in
flood areas, 14.5 for
elevating houses
Damage
and The post-disaster aid
emergency
request was 203
response
times the unfulfilled
pre-disaster
aid
request.
Economic value of 4.4
weather forecasts
Housing damage
>4
Social, economic
3.8
Economic
2.5
6
Mechler et al., 2008
Mertz and Gocht, 2001
Uttar Pradesh, India Drought
Germany
Flood
Nepal Red Cross 2008
Newhall et al., 1997
Nepal
Philippines
Flood
Volcano
PAHO, 1998
Costa Rica, Limón
Earthquake
Perrels, 2011
Nepal
Drought
Setchell, 2008
Venton and
2004
Venton and
2009
DRC, Kinshasa
Flood
Venton, Bihar and Andhra Flood
Pradesh, India
Venton, Maldives
Flood,
tsunami,
heavy
rainfall,
swell
waves
Venton et al., 2010
Malawi, Mzimba Drought
District
mainly
Vermeiren et al., 2004
Dominica
Hurricane
Vermeiren et al., 2004
Jamaica
Hurricane
White and Rorick, 2010 Nepal
Flood
Woodruff, 2008
Samoa, Apia, lower Flood
Vaisigano
catchment area
World Bank, 2008
Belarus, Georgia, All
Kazakhstan
Economic loss
Economic
> 1 to 3.5
0.5 (Flood Retention
Basins) to 5.2 (local
measures)
Social, economic
2 to 20.8
Property loss and > 9
deaths
Water and sewage Given as savings,
system
not ratios.
Agriculture
From
2013-2030,
average is 9.
Economic, direct
> 45
Social, economic
0.67-57.8
Economic losses
0.28-3.65
Food
At least 24.
Infrastructure
Infrastructure
Social, economic
Damages
>3
>6
3.49
1.72 to 44
(0.01 to 0.64 for
structural measures)
Belarus
(3.3),
Georgia
(5.7),
Kazakhstan (3.1)
Economic,
infrastructure
7
Case Studies
Australia
DES (c. 2001):
“Research has shown that every $1 spent on disaster mitigation saves at least $3 in economic and
social recovery costs”.
DES. c. 2001. Disaster Mitigation. Fact Sheet 3, Disaster Mitigation Unit, DES (Department of
Emergency Services), Queensland Government, Brisbane, Australia.
Australia
BTRE (2002):
“In each of the five case studies, there is evidence that the estimated benefits of the various flood
mitigation measures in terms of tangible savings are substantial.
0. Land use planning in Katherine is estimated to have reduced the AAD by around $0.6
million. In a 1 per cent AEP flood, the planning decision is estimated to save around $29
million in direct and indirect costs.
1. Voluntary purchase (VP) in the Kelso area of Bathurst is estimated to have saved $0.7
million in the 1998 flood. If all properties had been purchased before that 1998 event,
savings would have been in the order of $1.2 million. When complete, the scheme will save
approximately $1.8 million in a 1 per cent AEP event.
2. Building controls (minimum floor levels) in Thuringowa appear to have had an effect in
reducing the extent of inundation (and therefore internal damage) in the 1998 flood. Given
that individuals can pay off the higher construction costs over the life of a mortgage,
building design measures enforced through building controls can be a cost-effective and
affordable form of mitigation.
3. Investment in bitumen-sealed roads (which are more flood-resistant) in the Waggamba Shire
is estimated to be economically justified. Analysis suggests that the minimum of 32 trucks
per day required to break even is comfortably exceeded in the Waggamba Shire.
4. A levee proposed for the Tamworth industrial area would significantly reduce flood damage
(the cost of the November 2000 flood is estimated at close to half a million dollars). It is
also estimated that the existing CBD levee would avoid at least $5.36 million potential
direct damage in a 100-year average recurrence interval (ARI) flood.
These savings typically refer only to direct and indirect costs avoided. Intangible savings (such as
reduced stress and ill health) are discussed in the appendices (appendices I to V), but not quantified.
The figures therefore underestimate the full benefit of implementing flood mitigation.”
BTRE. 2002. Benefits of Flood Mitigation in Australia (Report 106). BTRE (Bureau of Transport and
Regional Economics), DoTaRS (Department of Transport and Remedial Services,
Commonwealth of Australia, Canberra, Australia.
Austria
Holub and Fuchs (2008) performed a standardised cost-benefit analysis examining the
risk-minimising effects of local structural measures for an Apline catchment in Carinthia, Austria
with respect to flash flood events with fluvial bed load transport. Results show that mitigation
8
concepts utilizing local structures, detailed below (LSM and LSM+), offer a better cost-to-benefit
ratio of 1.67 and 1.21 compared to conventional measures (e.g. CMM; 0.36, detailed below).
Over the past few decades, the test site has undergone static and dynamic floods, ‘extraordinary’
surface runoff, accompanied by the transport of solids, which has resulted in endangering the
stability of buildings. ‘Two fundamentally different concepts of mitigation were compared in this
study, (i) a concept of conventional mitigation based on the implementation of torrential structures
and (ii) a concept of local structural protection for buildings located in the endangered areas’. The
benefit was defined as ‘prevented damage to buildings in the test site’.
Three scenarios had been defined according to the requirements of the responsible decision maker,
(i) conventional mitigation measures aiming to avoid future design events, (ii) local structural
measures neglecting that they could not fully avoid losses due to design events, and (iii) local
structural measures taking into account these possible losses on the cost side of the mitigation
concept.
a. Scenario 1: CMM
Conventional mitigation measures are implemented; protection for all
elements at risk in red and yellow hazard zones (HZ).
b. Scenario 2: LSM
Local structural protection measures; protection for objects inside the yellow
hazard zone to a deposition height and/or flow depth < 0.7 m (yellow HZ);
no protection for detached garages.
c. Scenario 3: LSM+
Local structural protection measures; additional costs (equals a reduction of
benefit) due to arising losses from those buildings that are not equipped with
local structural protection in red and yellow hazard zones; protection for
objects inside the yellow hazard zone to a deposition height and/or flow
depth < 0.7 m (yellow HZ); no protection for detached garages.
The results of this study are very case-sensitive and not transferable to other regions. Whether or
not the test site is considered and open or closed systems in terms of a sub-catchment within a river
network will impact the different benefit-cost ratios. Local structural measures generally fit better
into the landscape, strengthen individual awareness and offer promising, cost-saving approach in
mitigating natural hazards.
Holub, M. and S. Fuchs. 2008. “Benefits of local structural protection to mitigate torrent-related
hazards”. In C.A. Brebbia and E. Beritatos (eds.), Risk Analysis VI, WIT Transactions on
Information and Communication Technologies, vol. 39, WIT Press, Southampton, U.K., pp.
401-411.
Bangladesh
Regarding the 29-30 April 1991 cyclone which killed approximately 139,000 people, Chowdhury et
al. (1993) write “the cost of averting a death through the construction of formal cyclone shelters
was Taka 3,023 or US$ 80 per death averted (BRAC, 1991b)”.
Chowdhury, A., R. Mushtaque, A.U. Bhuyia, A.Y. Choudhury, and R. Sen. 1993. “The Bangladesh
Cyclone of 1991: Why So Many People Died.” Disasters, vol. 17, no. 4, pp. 291-304.
Their reference to BRAC, 1991b is:
9
BRAC (1991b) Cyclone ‘91: a study of epidemiology. Bangladesh Rural Advancement Committee,
Dhaka.
Bangladesh
IFRC (2012) shows the results from an evaluation of the community-based Disaster Risk Reduction
Programme implemented by the Bangladesh Red Crescent Society between 2005-2011.
Benefit-cost ratios ranged from “1.18 - 3.04 across communities. If future protective benefits are
included (a time frame of 15 years was chosen), BCRs are identified to be between 3.05 and 4.90.
Since many benefits had to be excluded from the calculation, the ‘real’ benefit-cost ratios are
certain to be significantly higher”.
IFRC. 2012. The long road to resilience: Impact and cost-benefit analysis of community-based
disaster risk reduction in Bangladesh. IFRC (International Federation of Red Cross and Red
Crescent Societies), Geneva, Switzerland.
Belarus
World Bank (2008) evaluates the cost-benefit of modernization of certain elements of the National
Meteorological and Hydrological Service (NHMS). BCR reported for proposed modernizations for
Belarus was 3.3.
World Bank, 2008. Weather and Climate Services in Europe and Central Asia. A regional review.
Working Paper 151. The World Bank, Washington, D.C., U.S.A.
Canada, Ontario
Brown et al. (1997) examined similar 1986 floods in comparable locations in Michigan and Ontario.
Ontario, with a sustainable approach to floodplain management since the Hurricane Hazel disaster
in 1954, incurred economic losses less than 0.5% of Michigan’s losses.
Brown, D.W., Moin, S.M.A., and Nicolson, M.L. 1997. “A Comparison of Flooding in Michigan
and Ontario: ‘Soft’ Data to Support ‘Soft’ Water Management Approaches.” Canadian Water
Resources Journal, vol. 22, no. 2, pp. 125-139.
China
Guocai and Wang (2003) reported cost-benefit ratios of 1:35 and 1:40 from a nationwide study
carried out in China between 1994-1996 by the China Meteorological Administration. The study
evaluated the economic benefits of meteorological services and focused on macro-economic
benefits.
Costa Rica, Limón
PAHO (1998) conducted a study on the impact of the 1991 earthquake on water and sewage
systems. “The study concludes that had mitigation measures been applied to the water system in
Limón, there would have been a savings of some US$4 million in repairs to the system following
the 1991 event, and much of the impact on thousands of people would have been lessened.”
10
PAHO. 1998. Natural Disaster Mitigation in Drinking Water and Sewerage Systems: Guidelines for
Vulnerability Analysis. PAHO (Pan American Health Organization), Washington, D.C.
Croatia
Leviäkangas et al (2007) write “If we assume that the annual budget of DHMZ (Croatian
Hydrological and Meteorological Service) is about 8 million € per year, we can estimate that the
services delivered by DHMZ pay themselves back at least 3-fold each year, this estimate being a
conservative one. Taking into account all the excluded sectors, the authors’ conclusion is that
DHMZ’s services generate today an annual benefit which is about five times its budget. By
improving the services, especially their deliverance, the potential ratio between annual costs and
benefits is about 4–5 looking only at analyzed sectors, and correspondingly we can expect that with
a full range of services (i.e. including all beneficiary sectors) the future benefit potential could lie
somewhere in the range of 6–10.”
Pekka Leviäkangas et al., 2007. Benefits of Meteorological services in Croatia. Finnish
Meteorological Institute. VTT Technical Research Centre of Finland, Vuorimiehentie 3,
P.O.Box 1000, FI-02044 VTT, Finland.
Dominica
In 1979, one year after it had been constructed, Dominica’s deepwater port suffered damage from
Category 4 Hurricane David, the reconstruction costs of which equaled 41% of the original
construction cost: “Strengthening the facilities to withstand the forces from Hurricane David would
have increased the original project cost by 10 to 15%.” (Vermeiren et al., 2004). Knowing the cost
to withstand stronger hurricanes would be useful too.
Vermeiren, J., S. Stichter, and A. Wason. 2004. “Costs and Benefits of Hazard Mitigation for
Building and Infrastructure Development: A Case Study in Small Island Developing States”.
Downloaded from http://www.oas.org/en/cdmp/document/papers/tiems.htm on 23 February
2004.
(Also cited in) IADB, IMF, OAS, and the World Bank. 2005 (August). The Economics of Disaster
Mitigation in the Caribbean Quantifying the Benefits and Costs of Mitigating Natural Hazard
Losses. IADB (Inter-American Development Bank), IMF (International Monetary Fund),
OAS (Organization of American States), and the World Bank, Washington, D.C.
DRC, Kinshasa
Following floods in Kinshasa in 1999, Setchell (2008) completed an economic analysis and
concluded that “By adopting conservative assumptions -- and only accounting for direct economic
losses -- one dollar of OFDA ‘investment’ in disaster risk reduction in 1998 resulted in a ‘savings’
of at least $45.58 during the 1999 rainy season. Furthermore, this ‘savings’ has occurred up to the
present time, thereby compounding the initial benefit several times over.”
Further comments from the analysis:
“100,000 project beneficiaries did not have to again incur direct economic losses amounting to $7.1
11
million, or $71.06 each, in 1999 because of the OFDA ‘investment’ of $1.56 per beneficiary in 1998.
On a per-family basis, OFDA-supported disaster risk reduction measures resulted in a ‘savings’ of
$426, or the equivalent of nearly 54 percent of average annual income, thereby enabling families to
purchase the food, clothing, medicine, and other essential items that they may have had to forego in
the event of a flood reoccurrence. Again, these benefits have continued to accrue over time because
there has not been a repeat of the flooding that occurred in 1998.”
“This success was repeated in another commune of Kinshasa in 2000-2001. Torrential rains in late
1999 generated similar damage to the housing, possessions, and livelihoods of 50,000 residents.
Adopting measures used in the earlier project, CRS received a $45,000 grant from OFDA to support
additional mitigation activities, beginning in early 2000. As a result, the commune has not flooded
since 2000, proving yet again that small investments in disaster risk reduction can result in large
benefits for vulnerable people.”
“A 2002 study by the DRC Ministry of Health indicated that project risk reduction measures,
together with the public health education component of the project, combined to improve commune
environmental conditions to such an extent that the incidence of cholera was reduced by over 90
percent when compared to pre-flood conditions.”
Setchell, C.A. 2008 (May). Flood Hazard Mitigation in Kinshasa, DRC: A Disaster Risk Reduction
Success Story. USAID (United States Agency for International Development), Washington,
D.C., U.S.A.
Fiji, Navua
For the twenty years of lifetime of a flood warning system in Navua, Fiji, “overall investment
returns from the warning system would then most likely be a minimum of between 3.7 to 1 to as
high as 7.3 to 1” (Holland, 2008).
Holland, P. 2008 (October). An economic analysis of flood warning in Navua, Fiji. EU EDF 8 –
SOPAC Project Report 122, Reducing Vulnerability of Pacific ACP States, Fiji Technical
Report. SOPAC (Pacific Islands Applied Geosciences Commission), Suva, Fiji.
Georgia
World Bank (2008) evaluates the cost-benefit of modernization of certain elements of the National
Meteorological and Hydrological Service (NHMS). BCR reported for proposed modernizations for
Georgia was 5.7.
World Bank, 2008. Weather and Climate Services in Europe and Central Asia. A regional review.
Working Paper 151. The World Bank, Washington, D.C., U.S.A.
Germany
Förster and Kneis (2005) provide a cost-benefit analysis of the use of retention areas for providing
flood protection for downstream riparian areas in the Elbe River, Germany (2.2 to 5.8). The
retention area consists of 6 larger Polders. Controlled flooding of the retention area was simulated
using a conceptual model and assessed economically for 2 flood scenarios. In the cost-benefit
12
analysis, damage to agriculture, roads, buildings and fishery was assessed. Results suggest the use
of retention area for flood protection is highly cost-effective in economic terms.
Förster, S. and Kneis, 2005. Flood Risk Reduction by Use of Detention Areas at the Elbe River.
Journal of River Basin Management, 3(1): 21-19.
Germany
EWASE (2008): Compares the cost-benefit of structural and non-structural flood reduction
strategies, including Early Warning Systems (EWS), in the Odra and Elbe River basins. Results
show 2.6 to 9 benefit-cost ratio using EWS. Results from Förster and Kneis (2005; Polder use
2.2-5.8), Mertz and Gocht (2001; FRB 0.5, local measures 5.2), Gocht (2003; insurance 0.8,
derivatives 0.9) and Gocht (2004; Polder invest 0.10) are also cited.
EWASE 2008. CRUE Research Report No I-5: Effectiveness and Efficiency of Early Warning
Systems For Flash Floods (EWASE). First CRUE ERA-Net Common Call Effectiveness and
Efficiency
of
Non-structural
Flood
Risk
Management
Measures.
(http://www.crue-eranet.net/partner_area/documents/EWASE_final_report.pdf).
Förster, S. and Kneis, 2005. Flood Risk Reduction by Use of Detention Areas at the Elbe River.
Journal of River Basin Management, 3(1): 21-19.
Gocht, M. 2003. Weather Derivatives as Flood Protection Schemes. Design of Precipitation
Derivativesand Application on Corporate and Municipal Level. MBA Master Thesis, Anglia
Polytechnic University Cambridge, Berlin School of Economics.
Gocht,
M. 2004. Schadenpotentialanalyse für die Unterlieger, Nutzen-Kosten-Analyse,
Handlungsoptionen. In: Bronstert, A.: (Hrsg.): Möglichkeiten zur Minderung des
Hochwasserrisikos durch Nutzung von Flutpoldern an Havel und Oder. Brandenburgische
Umweltberichte, Universität Potsdam.
Merz, B., Gocht, M. 2001. Risikoanalyse Seckach-Kirnau.: Er-mittlung von Schadenpotentialen,
Nutzen-Kosten-Analyse. Gutachten im Auftrag des Zweckverbandes Hochwasser-schutz
Einzugsbereich Seckach/Kirnau, unveröffentlicht, GeoForschungsZentrum Potsdam.
India
Venton and Venton (2004) provide a cost benefit analysis of two disaster mitigation and
preparedness (DMP) interventions in India.
Bihar
 Baseline scenario (utilizing the cost benefit ratio as well as the net present value of the DMP
intervention): 4.58
 Raised hand pumps: (repairing damaged pumps) 3.20
 Modeling potential future initiatives: 0.67
 Low-interest loans: 57.80
Khammam District, Andhra Pradesh
 Baseline scenario (utilizing the cost benefit ratio as well as the net present value of the DMP
intervention): 13.38 to 20.05
13
Venton, C.C. and P. Venton. 2004. Disaster preparedness programmes in India: A cost benefit
analysis. Network Paper Number 49, Humanitarian Practice Network, Overseas Development
Institute, London, U.K.
India
Mechler et al (2008) provides a cost-benefit analysis of utilizing irrigation and insurance to mitigate
drought impacts in the Rohini Basin of India. B:C ratios are reported along a continuum of financial
intervention, reported as “discount rate %” for irrigation only, insurance only, and irrigation plus
insurance, under constant climate and climate change scenarios. A combined approach yields the
best benefits for both climate scenarios (B:C > 1 for all scenarios and discount rates; approximate
range 1-3.5 for 0% discount rate, drops to about half above 5% discount rate).
Mechler R, et al. 2008. ‘The Risk to Resilience Study Team (2008). Uttar Pradesh Drought CostBenefit Analysis’, From Risk to Resilience Working Paper No. 5. Moench M, Caspari E,
Pokhrel A (ed) ISET, ISET-Nepal and ProVention, Kathmandu, Nepal, 32 pp.
India, Rohini River Basin, Northeast Uttar Pradesh
Kull et al (2008) present a case study of alternatives to traditional embankment construction to
mitigate flood risk in India. ‘People-centered’ drought mitigation strategies on rural livelihoods in
Uttar Pradesh are evaluated. Benefit-cost ratios reported were:



future embankment construction < 1
investing in proper maintenance of embankments ~2.0
2-2.5 under both current and future climate change scenarios for "people-centered"
resilience-driven flood risk reduction
Kull, D., Singh, P., Chopde, S., S. Wajih and The Risk to Resilience Study Team, (2008):
Evaluating Costs and Benefits of Flood Reduction under Changing Climatic Conditions : Case
of the Rohini River Basin, India, From Risk to Resilience Working Paper No. 4, eds. Moench,
M., Caspari, E. & A. Pokhrel, ISET, ISET-Nepal and ProVention, Kathmandu, Nepal.
Indonesia
Mechler (2005) provides a cost-benefit analysis of integrated water management and flood
protection scheme for Semarang, Indonesia. Benefit to cost ratio was reported as 2.5 for reducing
direct and indirect economic impacts of flooding.
Mechler, 2005. Cost-benefit Analysis of Natural Disaster Risk Management in Developing
Countries. Working paper for sector project ‘Disaster Risk Management in Development
Cooperation’, GTZ, 2005.
Iran, Dez and Karun catchments
From Heidari (2009) presents a master plan for damage-reduction in the floodplain areas of the Dez
Karun rivers. A B:C ratio for levee construction is found to be 0.29-1.03 depending on location and
14
for detention dams, 0.78 and 1.34 for single and double-dams, respectively.
Heidari, A. 2009. “Structural master plan of flood mitigation measures”. Natural Hazards and Earth
System Sciences, vol. 9, pp. 61-75.
Jamaica
The Norman Manley Law School, University of the West Indies, Jamaica was damaged by
Hurricane Gilbert on 12 September 1988: “The cost of the reconstruction was given as US$90,000
but the University took the opportunity to carry out some deferred maintenance, so the cost of repair
due to the hurricane damage may have been somewhat overstated.” (Vermeiren et al., 2004).
US$13,000 of investment would have prevented the hurricane damage.
Vermeiren, J., S. Stichter, and A. Wason. 2004. “Costs and Benefits of Hazard Mitigation for
Building and Infrastructure Development: A Case Study in Small Island Developing States”.
Downloaded from http://www.oas.org/en/cdmp/document/papers/tiems.htm on 23 February
2004.
Kazakhstan
World Bank (2008) evaluates the cost-benefit of modernization of certain elements of the National
Meteorological and Hydrological Service (NHMS). BCR reported for proposed modernizations for
Kazakhstan was 3.1.
World Bank, 2008. Weather and Climate Services in Europe and Central Asia. A regional review.
Working Paper 151. The World Bank, Washington, D.C., U.S.A.
Malawi, Mzimba District
For a disaster risk reduction and food security programme in Malawi, Venton et al. (2010) report
“for every US$1 invested, the project activities delivered US$24 of net benefits for the communities
to help them overcome food insecurity while building their resilience to drought and erratic weather.
This is a conservative estimate and the true figure could be as much as US$36.”
Venton, C.C., J. Siedenburg, J. Faleiro, and J. Khinmaung. 2010. Investing In Communities: The
benefits and costs of building resilience for food security in Malawi. Tearfund, London, U.K.
Maldives: Gaaf Dhaal Atoll Thinadhoo, Gaaf Alif Atoll Villigili, and Thaa Atoll Vilufushi
Venton and Venton (2009) conduct a cost-benefit analysis for Disaster Risk Reduction (DRR) for
two scenarios: 1) hazards and their impacts on communities “without any DRR measures” and 2)
the reduction in hazard impacts “with” DRR measures. The benefits accrued from hazard reduction
(e.g. reduction in lost assets) are offset against the costs of implementing protection measures to
generate the benefit-cost ratios. Estimated losses for each island from tsunami, swell wave and
storm surge, and rainfall flooding losses are calculated for each island.
BCR Scenarios: Min. hazard occurrence, Max. hazard occurrence, Max. hazard & climate change,
respectively.
15
Thinadhoo
 Safe Island Protection: 0.39, 1.35, 1.40
 Selected Safe Island Protection: 0.52, 1.79, 1.85
 Limited Protection: 1.13, 3.54, 3.65
 All scenarios come out positive once the estimate for intangible losses is added in, yielding
BCRs ranging between 1.07 and 3.43.
Villigili
 Safe Island Protection: 0.28, 0.93, 1.00
 Selected Safe Island Protection: 0.29, 0.89, 0.86
 Limited Protection: 0.42, 1.23, 1.33
Vilufushi
 Safe Island Protection: 0.50, 1.65, 1.95
 The findings indicate that, under current conditions, there is not a financial justification for
the measures undertaken on Vilufushi. The projections under climate change are positive,
though the probability of hazard events will have to be very high to justify the expenditures
on this basis.
 The findings are mostly positive under the sensitivity testing.
Venton, C.C., P. Venton, and A. Shaig. 2009 (September) / 2010. Cost Benefit Study of Disaster
Risk Mitigation Measures in Three Islands in the Maldives. United Nations Development
Programme Maldives and Government of Maldives, Department of Housing, Transport and
Environment, Malé, The Maldives.
Mozambique
Quoting Terry Jeggle, a study by Latrobe and Venton (2003) report “about six months before the
Mozambique floods occurred, the meteorological authority indicated that the country was likely to
experience heavier than usual rainfall. Mozambique put out an appeal to the international
community for US$2.7 million worth of anticipatory measures. However, it received less than half
this amount. Once the floods eventually materialised, Mozambique received US$100 million in
emergency assistance. Then, at a subsequent conference, a further US$450 million was pledged by
the international donor community for rehabilitation costs.”
It might be unfair to assume that no emergency assistance would have been needed if the “US$2.7
million worth of anticipatory measures” was implemented. The figures nonetheless illustrate the
difference in cost between prevention and response.
La Trobe, S. and P. Venton. 2003 (July). Natural Disaster Risk Reduction: The policy and practice
of selected institutional donors. A Tearfund Research Project. Tearfund, London, U.K.
Nepal
Nepal Red Cross (2008) conducted a study on the cost benefit of a Disaster Risk Reduction (DRR)
programme. Benefit-cost ratios ranged from 2 to 20.8, depending on elements of the DRR
programme included or excluded from the analysis:
 4.8 (skills training)
 18.6 (entire DRR programme)
16


20.8 (check dams; 14.8 for sensitivity analysis including check dams)
2 (not including check dams)
Nepal Red Cross. 2008. Cost Benefit Analysis of a Nepal Red Cross Society Disaster Risk
Reduction Programme. Nepal Red Cross, Kathmandu, Nepal.
Nepal
Agriculture is an important part of Nepal’s economy. Studies have shown that improving farmer’s
knowledge and accessibility to meteorological data reduces economic loss. Perrels (2011) performs
a cost-benefit analysis to ascertain the social and ecological benefits of improving weather services
in Nepal.
A simple cost-benefit calculation is made for the period 2013 – 2030 assuming:
 modernisation of 81 weather observation stations (either through complete replacement or
through significant upgrade), on average about 10 stations per year upgraded from 2013 to 2021
 use of radiosonde twice a day year round, with gradual scaling up of the operation in the first
two years
 installation of 3 Doppler double polarization weather radars up to 2020. The first two radars are
supposed to be replaced after 11 years of service (i.e. within the time horizon of this CBA).
Funding of the investments is spread out over 10 years, starting at the year of installation, while
a 4% real interest rate is applied.
 Maintenance and data handling costs are supposed to depend on the number of observation
stations and radars, but with noticeable economies of scale (i.e. growing less than proportionally
compared to the growth of the modernised observation network).
‘Taken over the entire period 2013-2030, the benefit-cost ratio is rated at approximately 9. It rises
from 6~7 in the first years to almost 11 to the end of the period. As a result of the assumptions made
in chapter 4 the bulk of the benefits is generated in the agricultural sector (about 90%)’.
Perrels, A. 2011 (May 5). Social economic benefits of enhanced weather services in Nepal. Finnish
Meteorological Institute, Helsinki, Finland.
Nepal, Kailali
White and Rorick (2010) conducted a cost-benefit analysis of the Disaster Risk Reduction project
sponsored by Mercy Corps and the Nepali Red Cross in Kailali, Nepal. The primary aim of the
programme is to assist riverside communities in the far western Kailali District and the project
components include the development of Early Warning Systems, small scale mitigation works, and
to support young rescuers clubs in schools that are devoted to learning about and passing on
knowledge of disaster risk management. BCRs considering economic impacts ranged from
1.49-2.79. BCRS considering impacts to social and economical capital ranged from 1.55-5.81.
White and Rorick (2010) write “It is our belief that the B:C ratio of 3.49, which was determined
assuming a 10 year benefit duration, a 12% discount rate, best estimates for costs and benefits, and
the inclusion of some social benefits, is the most accurate assessment of the KDRRI project. A B:C
ratio of 3.49 indicates that for every Euro spent on DRR, we expect that 3.49 Euros will be saved by
the community or the aid organization responding to the community’s post-disaster needs.
White, B.A. and M.M. Rorick. 2010. Cost-Benefit Analysis for Community-Based Disaster Risk
Reduction in Kailali, Nepal. Mercy Corps Nepal, Lalitpur, Nepal.
17
Nepal, Kathmandu Valley
Khan et al. (2012) conducted a cost-benefit analysis of using a straw-bale construction instead of
brick or cement-mortar in Nepal to reduce earthquake damage. The CBA yielded a BCR of 2 for
making a house with straw-bales instead of bricks, using a 12% social discount rate and project
period of 30 years.
Khan, F., M. Moench, S.O. Reed, A. Dixit, S. Shrestha, and K. Dixit. 2012. Understanding the
Costs and Benefits of Disaster Risk Reduction Under Changing Climate Conditions Case
Study Results and Underlying Principles. ISET (Institute for Social and Environmental
Transition-International), Boulder, Colorado, U.S.A.
Netherlands
Brouwer and van Ek (2004) investigate the integrated ecological, social and economic impacts of
alternative flood control policies in the Netherlands. They find that traditional flood control policy,
e.g. building higher and stronger dikes, is cost-effective. However, investment in alternative flood
control policy, e.g. land use changes and floodplain restoration, is justifiable on the basis of a
cost-benefit analysis and a multi-criteria analysis when including the longer-term (next 100 years)
social and ecological benefits. Results are reported in present value (in millions) of costs and
benefits of proposed land use and flood plain restoration compared to a ‘do nothing’ baseline
scenario.
Brouwer, R. and R. van Ek. 2004. Integrated ecological, economic and social impact assessment of
alternative flood control policies in the Netherlands. Ecological Economics, vol. 50, pp. 1- 21.
Pakistan, Lai Floodplain
Khan et al (2008) combine social science (CBA) and natural sciences (hydrologic and climate
models) to investigate the cost-benefit of proactive flood mitigation measures in the Lai floodplain,
Pakistan. Benefit-cost ratios ranged from 1-25:
 Early warning: 0.96
 Relocation/restoration: 1.34
 Expressway/channel: 1.88
 JICA options (community pond, river improvement): 8.55, 25
Khan, F., Mustafa, D., D., Kull and The Risk to Resilience Study Team, (2008): Evaluating the
Costs and Benefits of Disaster Risk Reduction under Changing Climatic Conditions: A
Pakistan Case Study, From Risk to Resilience Working Paper No. 7, eds. Moench, M., Caspari,
E. & A. Pokhrel, ISET, ISET-Nepal and ProVention, Kathmandu, Nepal, 24 pp.
Pakistan, Lai River
Kull et al (2013) write ‘we introduce quantitative, stochastic CBA frameworks and apply them in
case studies of flood and drought risk reduction in India and Pakistan, also incorporating climate
change impact projections. DRM interventions are shown to be economically efficient with
integrated approaches more cost effective and robust under climatic changes’. In the Lai River
18
study site the following B:C ratios were given for flood management interventions:
 Expressway: 1.9
 Retention pond: 9.3
 River improvement: 8.6
 Combined pond & river improvement: 25.0
 Early Warning System: 1.6
 Floodplain relocation: 1.3
Kull, D., R. Mechler, and S. Hochrainer. 2013. “Probabilistic Cost-Benefit Analysis of Disaster Risk
Management in a Development Context”. Disasters, forthcoming.
Peru
Mechler (2005) provides a prefeasibility study of the reduction of flood hazards using Polders in
Piura, Peru. Benefit to cost ratio was reported as 3.8 for reducing direct social and economic
impacts of flooding.
Mechler, 2005. Cost-benefit Analysis of Natural Disaster Risk Management in Developing
Countries. Working paper for sector project ‘Disaster Risk Management in Development
Cooperation’, GTZ, Berlin.
Philippines
Regarding the 1991 eruption of Mount Pinatubo volcano in the Philippines, numbers given by
Newhall et al. (1997) put the monitoring and response costs at US$56.5 million while the amount of
property damage averted as a result of the monitoring and response is estimated at a minimum
US$500 million not including over 5,000 lives saved.
Newhall, C., J.W. Hendley II, and P.H. Stauffer. 1997. Reducing the Risk from Volcano Hazards:
Benefits of Volcano Monitoring Far Outweigh Costs —The Case of Mount Pinatubo. U.S.
Geological Survey Fact Sheet 115-97, Vancouver, Washington, U.S.A.
Philippines
Dedeurwaerdere (1998) estimated the benefits of different prevention measures undertaken against
floods and lahars in the Philippines. Results showed calculated benefits of 3.5 to 30 times the
projects’ costs.
Dedeurwaerdere, A. 1998. Cost-benefit Analysis for Natural Disaster Management - A Case-study
in the Philippines. Brussels: CRED.
Philippines
The project undertook a Quality Impact Assessment and Cost Benefit Analysis, to understand the
impacts of disaster risk reduction activities being carried out in the Philippines by the Red Cross.
Two of three interventions are cost effective, benefit-cost ratio results:
 Hanging footbridge: 24
19


Sea wall: BCR = 4.9
Dyke: BCR = 0.67
IFRC (2009). “Assessing Quality and Cost Benefit: A Philippines Case Study.”
Philippines
To avoid mobility disruption due to floods—which were preventing children from going to school
and taking crops to market—“A CBA process was carried out for structural measures in three
barangays – a hanging footbridge, a dyke and a sea wall…The analysis resulted in a range of
Benefit to Cost Ratios, from 24 in the case of the footbridge and 4.9 in the case of the sea wall
(positive returns), to 0.7 in the case of the dyke (negative return).” For the footbridge, “A sensitivity
analysis of the discount rate leads to a BCR ranging from 19 (discount rate of 15%) to 31 (discount
rate 5%).”
Burton, C. and C.C. Venton. 2009 (7 December). Case Study of the Philippines National Red Cross:
Community Based Disaster Risk Management Programming. IFRC (International Federation
of Red Cross and Red Crescent Societies), Geneva, Switzerland.
Samoa
For flooding in the lower Vaisigano catchment of Apia, Samoa, Woodruff (2008) describes various
measures:
 “In the case of an improved forecasting system, the ratio of benefits to costs was estimated
to range from 1.92 to 1.72, depending on the choice of discount rate used to carry out the
analysis.
 “The most significant economic pay-off from investing in flood management options is
found to be from constructing homes with raised floors. For new homes, the benefit cost
ratio is found to range from 4 to 44 for wooden homes, and from 2 to 28 for cement block
homes.”
 “Structural measures, on the other hand, were found not to be economically viable. In the
case of floodwalls, the benefit-cost ratios ranged from 0.11 to 0.64 depending on the choice
of floodwall design and discount rate used in the analysis. For the construction of a
diversion channel, the benefit-cost ratios ranged from 0.01 to 0.09. Although, it is likely that
many of the indirect or non-monetary benefits not captured in the analysis such as avoided
health costs or trauma suffered by residents during flooding, or reduced flood damages to
households and businesses in nearby districts, would raise the benefit-cost ratios, it is
unlikely that they would be significant enough to raise benefit-cost ratios above one.”
Woodruff, A. 2008 (February). Samoa Technical Report – Economic Analysis of Flood Risk
Reduction Measures for the Lower Vaisigano Catchment Area. EU EDF – SOPAC Project
Report 69g Reducing Vulnerability of Pacific ACP States. SOPAC (Pacific Islands Applied
Geosciences Commission), Suva, Fiji.
Sudan, Red Sea State
Drought risk reduction measures were implemented in the Red Sea State of Sudan with the
following results calculated by Khogali and Zewdu (2009):
 “terraces were found to have a cost to benefit ratio of 1:61”.
20



“earthdams/ embankments were found to have a cost to benefit ratio of 1:2.4”.
“communal gardens were found to have a cost to benefit ratio of 1:1800”.
A Hafir is “a large whole dug out in the ground that holds runoff water” and Hafirs “were
found to have a cost to benefit ratio of 1:2.7”.
Khogali, H. and D. Zewdu. 2009. Impact and Cost Benefit Analysis: A Case Study of Disaster Risk
Reduction Programming in Red Sea State Sudan. Sudanese Red Crescent Society, Khartoum,
Sudan.
U.S.A.
Lazo and Chestnut (2002) conducted a cost-benefit analysis of current and improved weather
forecasts in the US. The study elicited values from individuals in nine different cities chosen from
the nine regions defined by the National Climate Data Center for climate summaries: San Diego
(California), Portland (Oregon), Denver (Colorado), Billings (Montana), Oklahoma City
(Oklahoma), Madison (Wisconsin), Columbus (Ohio), Albany (New York), and Miami (Florida).
‘Historical data on weather forecasts and observed weather conditions were used to create indices
of weather variability and forecast accuracy for each city. These indices were used to explore
how individuals’ perceptions of and values for improved forecasts and current forecast services
relate to local weather variability (e.g., persistence) and the quality of forecasts currently
available to the respondents.’
Lazo and Chestnut (2002) write:
“The median household value for current weather forecasts for all weather conditions is
about $109 a year. With about 105 million U.S. households, taking the median value as
an estimate of the average household value, aggregate national values for all current
weather forecast services are $11.4 billion a year. With total federal spending on weather
forecasting services about $25 a year per household (Hooke and Pielke, 2000), this study
suggests a benefit-cost ratio of 4.4 to 1.”
Lazo, J.K. and L.G. Chestnut. 2002. Economic value of Current and Improved Weather Forecasts in
the US Household Sector: Report prepared for the National Oceanic and Atmospheric
Administration. Stratus Consulting Inc., Boulder, CO.
U.S.A.
Based on the findings of MMC (2005) and also referring to Ganderton et al. (2006) and Rose et al.
(2007), Godschalk et al. (2009) summarise “each dollar spent on mitigation grants saves society an
average of $4 in real resource costs. As expected, benefit-cost ratios varied across hazards,
reflecting individual hazard characteristics and local mitigation priorities.” Rose et al. (2007)
highlight “the overall benefit-cost ratio for FEMA mitigation grants is about 4:1, though the ratio
varies from 1.5 for earthquake mitigation to 5.1 for flood mitigation. Sensitivity analysis was
conducted and shows these estimates to be quite robust”. Woodworth (2008) repeats these figures.
Ganderton, P.T., L. Bourque, N. Dash, R. Eguchi, D. Godschalk, C. Heider, E. Mittler, K. Porter, A.
Rose, L.T. Tobin, and C. Taylor. 2006. “Mitigation generates savings of four to one and
enhances community resilience: MMC releases independent study on savings from natural
hazard mitigation”. Natural Hazards Observer, vol. 30, no. 4, pp. 1-3.
21
Godschalk, D.R., A. Rose, E. Mittler, K. Porter, and C.T. West. 2009. “Estimating the value of
foresight: aggregate analysis of natural hazard mitigation benefits and costs”. Journal of
Environmental Planning and Management, vol. 52, no. 6, pp. 739-756.
Millerd, F., Dufournaud, C. M., & Schaefer, K. (1994). Canada–Ontario Flood Damage Reduction
Program: case studies. Canadian Water Resources Journal, 19(1), 17–26.
MMC. 2005. Natural Hazard Mitigation Saves: An Independent Study to Assess the Future Savings
from Mitigation Activities. Volume 1 – Findings, Conclusions, and Recommendations.
Volume 2 – Study Documentation. Appendices. MMC (Multihazard Mitigation Council).
National Institute of Building Sciences, Washington, D.C.
Rose, A., K. Porter, N. Dash, J. Bouabid, C. Huyck, J. Whitehead, D. Shaw, R. Eguchi, C. Taylor, T.
McLane, L.T. Tobin, P.T. Ganderton, D. Godschalk, A.S. Kiremidjian, K. Tierney, and C.T.
West. 2007. “Benefit-Cost Analysis of FEMA Hazard Mitigation Grants”. Natural Hazards
Review, vol. 8, no. 4, pp. 97-111.
Woodworth, B. 2008 (April 30). Questions for the Record from the April 30, 2008, Pre-Disaster
Mitigation Hearing: Responses provided by Brent Woodworth on behalf of the Multihazard
Mitigation Council of the National Institute of Building Sciences. Unpublished.
U.S.A.
Healy and Malhotra (2009) write “Assuming a 4% annual interest rate and a 6% depreciation rate
for preparedness investments, we estimate the NPV [Net Present Value] of $1 of disaster
preparedness to be about $15.14.” over eight years.
Healy, A. and N. Malhotra. 2009. “Myopic Voters and Natural Disaster Policy”. American Political
Science Review, vol. 103, no. 3, pp. 387-406.
U.S.A.
Kilma et al. (2011) examines whether it is potentially cost-effective to lower the wind speed of
tropical cyclones (TCs) by reducing the sea surface temperature (SST) using wave pumps in South
Florida. The FEMA HAZUS-MH MR3 damage model and census data on the value of property at
risk are used to estimate expected economic losses. Wind damages after storm modification with
damages after implementing hardening strategies protecting buildings. Results suggest
‘modification could reduce net losses from an intense storm more than hardening structures.
However, hardening provides “fail safe” protection for average storms that might not be achieved if
the only option were modification. The effect of natural variability is larger than that of either
strategy’. Economic losses are reported in USD in the supplementary materials accompanying the
article.
Klima, K., M. Granger Morgan, I. Grossmann, and K. Emanuel. 2011. “Does It Make Sense To
Modify Tropical Cyclones? A Decision-Analytic Assessment”. Environmental Science and
Technology, vol. 45, pp. 4242-4248.
Vietnam
22
IFRC (2002): Planting of mangroves along coastline in Vietnam results in a benefit-cost ratio of 52
from 1994-2001 period. Mangroves promote savings in reduced cost of dyke maintenance.
IFRC 2002, World Disasters Report 2002. Geneva: International Federation of Red Cross and Red
Crescent Societies.
Vietnam
With respect to housing in Vietnam, “Although every house has different needs, the average cost of
strengthening is about 25 per cent of the house value. Access to credit and financial encouragement
is part of the package...in October 2006, the hundreds of buildings that had been strengthened under
the DWF programme [see http://www.dwf.org/en] withstood the impact of Typhoon Xangsane that
destroyed 20,000 other houses and unroofed 250,000 more in the three central provinces.”
Lewis, J. 2007. “Disaster Reduction Measures for Typhoons and Floods”. Tiempo Climate
Newswatch,
http://www.tiempocyberclimate.org/newswatch/feature071101.htm
and
“Typhoons and floods in Vietnam: Measures for disaster reduction in contexts of climate
change”. Radix, http://www.radixonline.org/resources/Lewis-Floods&typhoonsinVietnam.doc
Vietnam
IFRC (2011) evaluates the cost-benefit of “Community-based Mangrove Reforestation and Disaster
Preparedness Programme” in Vietnam, sponsored by the IFRC. IFRC concludes that the mangrove
afforestation programmes in Vietnam have been very economically, ecologically and socially
successful. However, it warns that mangroves are difficult to plant, requiring suitable environmental
conditions (soil type), local expertise and community capacity, so planting in less suitable regions
will be more expensive.
The report provides two BCR:
 BCR 1 (excludes ecological benefits): 3-68
 BCR 2 (including ecological benefits, yet to be materialized): 28-104
Vietnam, Da Nang Province
Khan et al. (2012) conducted a CBA of the use of a new boat winch system in Da Nang Province,
Vietnam. Existing winch systems are unable to pull all the boats to shore and cannot pull boats
larger than 30 CV. Benefits for this study are calculated by estimating the number of additional
boats that could be pulled in with the new winch. A BCR of 3.5 was calculated using a 12% social
discount rate and a 30-year project period.
Khan, F., M. Moench, S.O. Reed, A. Dixit, S. Shrestha, and K. Dixit. 2012. Understanding the
Costs and Benefits of Disaster Risk Reduction Under Changing Climate Conditions Case
Study Results and Underlying Principles. ISET (Institute for Social and Environmental
Transition-International), Boulder, Colorado, U.S.A.
World, 35 Developing Countries
23
Kunreuther and Michel-Kerjan (2012) conduct a cost-benefit analysis in 35 developing countries
for: (1) retrofitting schools in seismically active countries so that they are earthquake resistant and
(2) reducing losses from severe flooding by either (a) building a one-meter wall around houses in
flood prone regions and (b) elevating houses in the same region. With regards to retrofitting schools
Kunreuther and Michel-Kerjan (2012) write “it would cost ~ $300 billion to retrofit all these
schools in the 35 most exposed countries, saving lives of 250,000 individuals over the next 50 yrs.”
Regarding flood mitigation measures, a BCR of 60 was calculated for erecting a one-meter wall and
14.5 for elevating houses. Further regarding flood mitigation Kunreuther and Michel-Kerjan (2012)
write ‘We find that it would cost nearly $940 billion to undertake the community-based disaster risk
reduction measure of building walls around the affected communities and $5.2 trillion to elevate all
houses exposed to floods in the 34 most exposed countries. Undertaking either of these measures
will save 61,000 lives over the next 50 years. If one invested $75 billion in building one-meter high
walls surrounding communities, the estimated benefits would be $4.5 trillion with an average
BCR= 60. Elevating homes would yield estimated benefits of $1.1 trillion and an average BCR=
14.5 for {d=.03 VoL=$40,000}.’
Kunreuther H. and E. Michel-Kerjan. 2012 (April 12). Challenge Paper: Natural Disasters. Policy
Options for Reducing Losses from Natural Disasters: Allocating $75 billion. Revised version
for Copenhagen Consensus. Center for Risk Management and Decision Processes, The
Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.
24
Case Studies to Investigate Further
The case studies here would be useful projects for aiming to calculate costs and benefits through
verifiable numbers and calculations.
U.S.A., FEMA’s Project Impact
FEMA has written plenty of documents on Project Impact. Do any provide benefit-cost ratios?
FEMA (1997, 1998) as referenced in the next section do not include such ratios.
U.S.A., Washington, Seattle: Medic One
A long-term programme to train most members of the public in basic first aid. Any information on
costs and benefits?
World, Community teams related to disaster risk reduction
See http://www.riskred.org/fav/cst.pdf for more information on these teams.
25
Useful References Without Ratios
Anderson, M.B. 1990. Analyzing the Costs and Benefits of Natural Disaster Responses in the
Context of Development. Environment Working Paper no. 29. The World Bank, Washington,
D.C., U.S.A.
Annand, J. 2008 (June 20). SMGS PDF CRCS Evaluating the environmental losses and benefits
from flooding. RMIT (Royal Melbourne Institute of Technology), Melbourne, Australia,
http://mams.rmit.edu.au/kse6lzj09fet.pdf
Brinkhuis-Jak, M., S.R. Holterman, M. Kok, and S.N. Jonkman. 2003. “Cost benefit analysis and
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