Climate Information and Early Warning
Systems to Support Disaster Risk Reduction
and Management under Future Climate
Conditions in South Africa
REPORT No. 2 FOR THE
LONG TERM ADAPTATION SCENARIOS FLAGSHIP RESEARCH PROGRAM (LTAS)
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Contents
LIST OF FIGURES.................................................................................................................................3
LIST OF TABLES ..................................................................................................................................4
LIST OF ABBREVIATIONS.....................................................................................................................5
ACKNOWLEDGEMENTS ......................................................................................................................7
REPORT OVERVIEW ............................................................................................................................8
EXECUTIVE SUMMARY ..................................................................................................................... 10
1.
INTRODUCTION ........................................................................................................................ 13
2.
METHODOLOGY........................................................................................................................ 18
3.
CLIMATE HAZARDS AND SOCIO-ECONOMIC IMPACTS ................................................................ 20
3.1. OBSERVED TRENDS IN CLIMATE VARIABILITY AND HAZARDS ........................ ERROR! BOOKMARK NOT DEFINED.
3.2. PAST EXTREME EVENTS ........................................................................ ERROR! BOOKMARK NOT DEFINED.
3.3. ECONOMIC AND SOCIAL IMPACTS OF PAST CLIMATE HAZARDS .................................................................. 37
3.3.1.
Economic impacts of disasters ................................................ Error! Bookmark not defined.
3.3.2.
Social impacts of disasters ...................................................... Error! Bookmark not defined.
3.4. GAPS AND CHALLENGES ....................................................................... ERROR! BOOKMARK NOT DEFINED.
4.
DISASTER RISK REDUCTION AND MANAGEMENT IN SOUTH AFRICA ........................................... 41
4.1. THE ACT AND THE FRAMEWORK ......................................................................................................... 41
4.2. MANDATE OF THE NATIONAL DISASTER MANAGEMENT CENTRE ............................................................. 43
4.3. EXISTING DRR-M SYSTEMS ............................................................................................................... 44
4.4. IDENTIFIED GAPS AND OPPORTUNITIES FOR DRR-M SYSTEMS ................................................................. 45
4.4.1.
Legislation ........................................................................................................................... 45
4.4.2.
Institutional ......................................................................................................................... 46
4.4.3.
Funding mechanisms for DRR-M ......................................................................................... 51
4.4.4.
Opportunities ...................................................................................................................... 53
5.
CLIMATE INFORMATION AND EARLY WARNING SYSTEMS IN SOUTH AFRICA .............................. 56
5.1. MANDATES, CAPACITY AND LINKS ....................................................................................................... 56
5.1.1.
Production of weather and climate forecasts (including warnings and advisories) ..... Error!
Bookmark not defined.
5.1.2.
Links with other government departments ......................................................................... 60
5.1.3.
Community response........................................................................................................... 61
5.2. CLIMATE ADVISORIES AND EARLY WARNING SYSTEMS TO SUPPORT DRR-M ............................................... 64
5.3. IDENTIFIED GAPS AND OPPORTUNITIES IN CURRENT CLIMATE INFORMATION AND EARLY WARNING SYSTEMS.... 69
5.3.1.
Legislative, institutional and mandate issues ..................................................................... 69
5.3.2.
Technical issues ................................................................................................................... 70
5.3.3.
Social issues ......................................................................................................................... 71
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6. RECOMMENDATIONS FOR ENHANCING CLIMATE INFORMATION AND EARLY WARNING SYSTEMS
FOR BUILDING CLIMATE RESILIENCE ................................................ ERROR! BOOKMARK NOT DEFINED.
6.1.
6.2.
6.3.
7.
OPERATIONAL RECOMMENDATIONS .................................................................................................... 73
INSTITUTIONAL AND PROCESS RECOMMENDATIONS ............................................................................... 74
POLICY RECOMMENDATIONS ............................................................................................................. 76
CONCLUSION ........................................................................... ERROR! BOOKMARK NOT DEFINED.
REFERENCES .................................................................................................................................... 79
List of Figures
Figure 1: The key concepts of DDR-M and CCA ......................................................................................... 14
Figure 2: Progression of Risk Model (Pressure and Release Model) .......................................................... 21
Figure 3: NDMC floods Hazard Map ........................................................................................................... 24
Figure 4: Public health impacts ................................................................................................................... 28
Figure 5: Drought Hazard Index Map for the Limpopo Basin ..................................................................... 32
Figure 6: Occurrence (including Tsunamis)................................................................................................. 34
Figure 7: Economic damages in US$ ........................................................................................................... 34
Figure 8: Number of people affected.......................................................................................................... 35
Figure 9: Number of people killed .............................................................................................................. 35
Figure 10: NDMC historic disasters map for South Africa .......................................................................... 36
Figure 11: NDMC disaster situation report incidents (1990-current) map................................................. 37
Figure 12: Extreme weather events in South Africa ................................................................................... 37
Figure 13: An upward trend in the disaster intensive years 1981 to 2013 ................................................ 39
Figure 14: A cost indication per hazard type from 1981- 2013 .................................................................. 39
Figure 15: All Hazard related costs recorded in the NDMC Annual reports from 2006-2011 .................... 40
Figure 16: Structures and responsibilities of disaster management across all spheres of governance ..... 42
Figure 17: Functioning of Disaster Risk Management structures per province ......................................... 47
Figure 18: Let’s Respond Toolkit ................................................................................................................. 53
Figure 19: Step by step approach to integrate climate change in the IDP process .................................... 54
Figure 20: Some of the over 5000 youths employed by Working on Fire .................................................. 55
Figure 21: SAWS forecasting system (SAWS CEO Dr Makuleni, 2011) ....................................................... 57
Figure 22: Flow of information from SAWS to DMC ................................................................................... 58
Figure 23: South African Weather Service Severe Weather Alerts............................................................. 64
Figure 24: Snapshot at 06 hr SA time of basins where flooding were expected ........................................ 65
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Figure 25: Hourly breakdown issues by SAWS for the floods ..................................................................... 66
Figure 26: Storm surge alert process (Stander 2011) ................................................................................. 68
Figure 27: Framework for integrating local knowledge and scientific information on early warning ....... 71
Figure 28: Meteorological station, Northern Cape .................................................................................... 74
List of tables
Table 1: Summary of flood impacts in South Africa.................................................................................... 24
Table 2: Summary of storms impacts ......................................................................................................... 28
Table 3: Summary of drought impacts in South Africa ............................................................................... 31
Table 4: Summary of impacts of veldfires in South Africa .......................................................................... 33
Table 5: Disasters in South Africa 1983-2013 ............................................................................................. 35
Table 6: An example summary of direct damage costs of disasters - 1981 to 2013 .................................. 38
Table 1: Capacity challenges faced by the Disasters Centres in terms of fulfilling their Mandate..………..48
Table 8: Challenges experienced by local, district and provincial municipalities ...................................... 50
Table 9: Research institutions involved in interpretation, packaging and dissemination of early warning
and climate information ............................................................................................................................. 59
Table 10: Government department linkages with DDR-M and EWS ………………………………………………………61
Table 11: Identified areas of skills shortage ............................................................................................... 72
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List of abbreviations
ACDS
ADRMP
AFIS
COGTA
CSIR
DAFF
DHI
DMA
DMISA
DoCG
DPLG
DRR
DRR-M
DST
EMDAT
EWS
FPA
GCM
GEOSS
GIZ
IDP
ILRC
IPCC
KPA
LTAS
MDMC
MHEWS
MIG
MODIS
NAC
NCCRP
NCEC
NDMAF
NDMC
NDMF
NDMIS
NFDRS
NISL
NOAA
African Centre for Disaster Studies
Agricultural Disaster Risk and Management Plan
Advanced Fire Information System
Cooperative Governance and Traditional Affairs
Council for Scientific and Industrial Research
Department of Agriculture, Forestry and Fisheries
Drought Hazard Index
Disaster Management Act
Disaster Management Institute of Southern Africa
Department of Cooperative Governance
Department of Provincial and Local Government
Disaster Risk Reduction
Disaster Risk Reduction and Management
Department of Science and Technology
Emergency Events Database
Early Warning Systems
Fire Protection Association
Global Circulation Model
Global Earth Observation Systems of Systems
Deutsche Gesellschaft für Internationale Zusammenarbeit
Integrated Development Plan
(National) Interdepartmental Legislative Review Committee
Intergovernmental Panel on Climate Change
Key performance area
Long Term Adaptation Scenarios
Municipal Disaster Management Centre
Multi hazard Early Warning System
Municipal Infrastructure Grant
Moderate Resolution Imaging Spectro-radiometer
National Agro-meteorological Committee
National Climate Change Response Paper
National Crop Estimate Committee
National Disaster Management Advisory Forum
National Disaster Management Centre
National Disaster Management Framework
National Disaster Management Information System
National Fire Danger Rating System
National Information Society Learnerships
National Oceanic and Atmospheric Administration
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PDMC
RAVAC
SABC
SAFFG
SALGA
SANHO
SARVA
SAWS
SPI
TTT
UNFCCC
UNISDR
WAMIS
WMO
WMO
WoF
Provincial Disaster Management Centre
Risk and Vulnerability Assessment Centre
South Africa Broadcasting Cooperation
South Africa Flash Flood Guidance
South Africa Local Government Association
South African Navy Hydrographic Office
South Africa Risk and Vulnerability Atlas
South Africa Weather Services
Standardised Precipitation Index
Technical Task Team
United Nations Framework Convention on Climate Change
United Nations International Strategy for Disaster Risk Reduction
Wide Area Monitoring Information System
(Australian) Wildfire Management Overlay
World Meteorological Organization
Working on Fire
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Acknowledgements
The Long-Term Adaptation Flagship Research Programme (LTAS) responds to the South African National
Climate Change Response White Paper by undertaking climate change adaptation research and scenario
planning for South Africa and the Southern African sub-region. The Department of Environmental Affairs
(DEA) is leading the process in collaboration with technical research partner the South African National
Biodiversity Institute (SANBI) as well as technical and financial assistance from the Gesellschaft für
Internationale Zusammenarbeit (GIZ).
DEA would like to acknowledge the LTAS Phase 1 and 2 Project Management Team who contributed to
the development of the LTAS technical reports, namely Mr Shonisani Munzhedzi, Mr Vhalinavho
Khavhagali (DEA), Prof Guy Midgley (SANBI), Ms Petra de Abreu, Ms Sarshen Scorgie (Conservation
South Africa), Dr Michaela Braun, and Mr Zane Abdul (GIZ). DEA would also like to thank the sector
departments and other partners for their insights to this work, in particular the Department of Water
Affairs (DWA), Department of Agriculture, Forestry and Fisheries (DAFF), National Disaster Management
Centre (NDMC), Department of Rural Development and Land Reform (DRDLR), South African Weather
Services (SAWS) and Stellenbosch University.
Specifically, we would like to extend gratitude to the groups, organisations and individuals who
participated and provided technical expertise and key inputs to the Climate Information and Early
Warning Systems to Support Disaster Risk Reduction and Management under Future Climates in South
Africa report, namely Dr Julia Mambo, Ms Claire Davis, Ms Karin Stronkhorst, Ms Miriam Murambadoro,
Dr Emma Archer van Garderen and Mrs Willemien van Niekerk (CSIR, Natural Resources and
Environment, and Built Environment); Ms Moddy Sethutha, Mr Mark van Staden and Mr Terry (NDMC);
Ms Vimbai Chasi (Stellenbosch University, Disaster Mitigation for Sustainable Livelihoods Programme);
and Mr Eugene Poolman (SAWS).
Furthermore, we thank the stakeholders who attended the LTAS workshop held at the Sun International
Hotel on 22-24 January 2014 for their feedback and inputs on proposed methodologies, content and
results. Their contributions were instrumental to this final report.
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Report overview
This technical report presents the LTAS Phase 2 findings on climate information and EWSs for supporting
disaster risk reduction and management under future climate conditions. The report focuses on climate
change vulnerabilities and potential adaptation responses for disaster risk reduction and management
(DRR-M) in South Africa. Specifically, it takes stock of past extreme weather events and disasters,
including the economic costs as a result of damages from disasters, and the social impacts on
communities. The most common occurring hazards and the impacts on sectors are also presented. The
report further takes stock of disaster risk reduction and management (DRR-M), analysing the existing
systems and their effectiveness in addressing disasters risk in the country. The report covers the
mandates outlined in different legislation and institutions relating to DRR-M, the existing DRR-M
systems, and the challenges in implementing DRM activities in the country.
The report further takes stock of climate information availability relevant for EWSs (EWS) that have
been developed for supporting disaster risk reduction and management in South Africa, EWS
governance, and how EWS effectiveness can be enhanced under future climatic conditions. The
document describes the mandates, capacity and links between various levels of government including
the communities at risk with regards to the EWSs and climate information. It also assess the current
stakeholders involved in production, interpretation, packaging, dissemination and community response
to EWSs and climate information. The current status of EWSs in South Africa (issued by SAWS as well as
independent organisations) is documented and gaps and opportunities are highlighted.
Recommendations for EWSs as well for institutions and processes governing disaster management in
South Africa are provided.
The report provides a synthesis of the status and capacity of disaster risk reduction and EWSs at the
different levels of government, the analysis of legislation guiding both EWSs and disaster risk reduction
as well as the communication and dissemination of early warning information. An analysis of past
extreme weather related disasters, disaster risk reduction management systems and policy
recommendations were carried out, in order to assess the current extent and costs of disasters due to
shortcomings in EWS and DRR-M, and identify future priorities for adaptive improvements. Analyses
were based on the results of relevant past and current research and policy, including the South Africa’s
National Climate Change Response White Paper (NCCRP) (DEA 2011a) and the Second National
Communication to the United Nations Framework Convention on Climate Change (UNFCCC) (DEA,
2011b).
A brief description of each chapter of the technical report follows:
Chapter 1 (Introduction) provides an overview of the importance of disaster risk reduction, EWSs and
specific legislation and policy instruments and the institutional structures governing disaster risk
reduction. The chapter describes the overall aim of the assignment, notably developing policy
recommendations for strengthening DRR-M, climate information and EWSs within the LTAS process.
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Chapter 2 (Methodology) provides a brief overview of the methods used in this study. This being a desk
top study, the methods employed comprised mainly a review of literature from various government
documents annual reports, other grey literature, peer reviewed literature where available, and other
publications.
Chapter 3 (Climate hazards and socio-economic impacts) provides an overview of past weather-related
disasters in the country, the costs of disasters and the costs of disaster risk reduction, rehabilitation and
recovery. The chapter further gives an overview of the socio-economic impacts of the various types of
disasters experienced in the country, building on work that was conducted under the Initial and Second
National Communications to the UNFCCC.
Chapter 4 (Disaster risk reduction and management in South Africa) provides an overview of disaster
risk reduction management systems, including legislative instruments available and the institutional
arrangements currently governing DRR-M activities in the country. The chapter also discusses the
shortcomings of legislative and institutional structures in implementing DRR-M activities.
Chapter 5 (Climate information and EWSs in South Africa) describes the mandates, capacity and links
between national, provincial, municipal and local community levels with regards to EWSs, including the
production, interpretation, packaging and dissemination of weather and climate forecasts and related
information, including warnings and advisories across relevant sectors. The chapter further describes
current capacity (technical, human and institutional) with regards to climate information and EWSs for
floods, fires, droughts and storm surges, including decision support tools available cross-sectorally.
Lastly, the chapter identifies gaps and opportunities in the current climate information and EWSs.
Chapter 6 (Recommendations for enhancing climate information and EWSs for building climate
resilience) outlines policy recommendations for strengthening climate information and EWSs for
building climate resilience.
Chapter 7 (Conclusion) concludes the report, highlighting the findings and the implications of the
findings for the scope of Phase 2 in assessing adaptation response options.
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Executive summary
The observed climate trends for South Africa, over the last five decades, 1960 to 2010 indicate a
tendency towards extreme rainfall events, increasing in frequency annually and especially in spring and
summer, with reduction in extremes in autumn and increased dry spell duration. Other trends indicate
an increase in mean annual temperatures, in almost all seasons, with part of the country expected to be
drier (DEA, 2013a). This implies that the country is exposed to a wide range of weather related hazards
including floods, fires, droughts and storm surges. Weather-related disasters pose significant challenges
for South Africa and negatively impact economic infrastructure such as mining and electricity
generation, health, tourism, agriculture, forestry, biodiversity, water and human settlements (DEA
2013a). . Between 2000 and 2009, the total costs of weather-related disasters have been conservatively
estimated to be in the region of R9.2 billion (due to incomplete data and records), and possibly at least
twice this amount. The lack of uniform reporting structures in key state departments regarding the
reporting and costing of damages due to disasters makes it an intractable task to obtain the accurate
figures. South Africa’s National Climate Change Response Paper (NCCRP) (DEA, 2011a) and the Second
Communication to the UNFCCC (DEA, 2011b), highlight disaster management as a key area of
development for the country.
Disaster risk reduction management and early warning information systems in South Africa, are some of
the most advanced and comprehensive, including legislation and institutional arrangement in place to
facilitate disaster risk reduction across all sectors of government. However, disaster risk reduction
implementation has faced and continues to face challenges, in the implementation of disaster risk
reduction in South Africa. The main challenges posed include the interpretation and implementation of
the legislative instruments, the poor institutional structures, and a lack of capacity at all levels of
government, national, provincial and local government which affects the implementation of disaster risk
reduction activities. The findings are discussed in detail below.
Climate hazards and socio-economic impacts
There is an increase in the number of weather related extreme events in the country over the past
years, with extensive damage caused to the economic and social sectors resulting in the increase in
direct and recovery costs. Some of the impacts of the major natural hazards include:
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Health impacts and mortality, physical and mental disease, alcoholism and reduced air quality.
Impacts on human settlements which include damage to property, homelessness, no access to
services, resettlement, and migration.
Impacts on infrastructure include damage, expensive repairs, closures, social services reduced,
no electricity supply;
impacts on agriculture & food security,
employment and tourism are reduced or no income, including food shortage, increase of food
prices, layoffs, debts,
impact on water resources including contamination, acid mine drainage, water restrictions.
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
Impact on ecosystems are land degradation, biodiversity loss and extinctions, loss of
ecosystems and their services, erosion, alien plant invasion, salinization of groundwater, flood
plumes containing pesticides etc.
The impacts of disasters are thus wide-ranging in these different sectors. The number of people affected
by drought, at over 15 million, is the highest of the hazard types, followed by floods with approximately
483 000. Other hazard types also record number of people affected, however these figures are lower.
Between 1980 and 2013, the highest costs from disasters (above R3 billion) were incurred in 1987, 2007,
2010, 2011 and 2013, with 2010 and 2011 being the highest (over R6 billion). It is important to note here
that accuracy of these figures is questionable due to difficulty in compiling and verifying data because of
the inconsistent reporting of damages and reduction costs by the key line ministries and departments
such as the NDMC. Other challenges noted include local government focus on disaster recovery rather
than risk reduction, lack of disaster risk measures, lack of involvement by the private sector, limited
community based funding and little to no reporting on investment in DRR-M activities. Long lead times
in transferring the Municipal Infrastructure Grant (MIG) results in the delay in the release of funds
(between when a disaster occurs and when funds are released). This is due to the conditions that need
to be met before funding can be channelled from the national budget to the Department of Cooperative
Governance (DoCG) and eventually to the MIG fund.
Disaster risk reduction management
South Africa’s legislation and policy instruments for disaster risk reduction, which includes EWSs are one
of the best in Africa, having adopted a proactive rather than a reactive approach. Both the Disaster
Management Act (DMA) (RSA, 2002) and the National Disaster Management Framework (NDMF) (RSA,
2005) guide DRR-M implementation in the country, with the National Disaster Management Centre
being the lead institution for DRR-M. Despite this, the implementation of disaster risk reduction has
been problematic. Various challenges faced in the implementation of DDR-M were noted, such as the
Act not being clear about the roles and responsibilities of the various actors in disaster risk reduction.
This has resulted in poor institutional implementation at local government level and poor access of
funding for both DRR-M and response and rehabilitation at the different levels of government. The lack
of capacity at national, provincial and local level government has hindered the implementation of the
DRR activities, while the poor understanding of the core concepts of disaster risk at provincial and local
municipality as well as at sector department levels, and the language used in both the Act and the
Framework make their interpretation and implementation difficult. Other reasons cited for the poor
implementation include the lack of a dedicated focal point for disaster management, poor participation
of key stakeholders and communities before and during a disaster, and the lack of cooperation and
communication between departments to establish and maintain advisory forums. The challenges faced
in the implementation of the DMA and the NDMF affect disaster risk reduction and climate change
adaptation, especially for key economic sectors such as agriculture, water housing and environment
sectors, and the effectiveness of EWSs in the country.
The placing of the NDMC in the national DoCG has been questioned, with suggestions to house the
centres in a strong and influential department which would allow the NDMC to enforce the Act and the
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framework. The decentralisation of the DRR-M activities to the three tiers of government is mandated
by the Act, with provincial, district and metropolitan disaster centres being set up. This process has also
faced challenges and some centres are still not operational. A lack of political understanding of the
importance of disaster risk reduction and a lack of political will, as well as the lack of capacity and
understanding hinder disaster risk activities, with most of the focus being response and recovery. It is
hoped that the current review of the Disaster Management Act that will address some of the issues
raised. The current review has attempted to redress increased coordination at all levels of government
including increased focus on risk assessments, planning, and strategies for various sectors, provinces and
local municipalities.
Climate information and early warning systems
The South Africa Weather Service (SAWS), is the legally mandated institution, as per the Weather
Service Act (RSA, 2001), responsible for weather and climate forecasting and the issuing of severe
weather related alerts in South Africa. South Africa has a number of, and is in the process of developing
more EWSs for different sectors and different weather elements. Examples are the Advanced Fire
Information System (AFIS), the South African Weather Service’s severe weather events warning system,
and the South African Flash Flood Guidance System (SAFFG). The information and warnings from these
systems are made available on websites and are distributed to provincial, district and local
municipalities via SMS and email, for them to incorporate into their own EWSs or to take action. SAWS
adopted the Multi Hazard EWS (MHEWS) which makes use of multiple monitoring systems,
meteorological, hydrological and climate information to prepare and respond for the multiple weatherrelated hazards. MHEWS requires closer cooperation with disaster management structures at national,
provincial and local level. The SAWS severe weather system covers potentially damaging weather events
(e.g. heavy rain, heat waves and cold weather) that are common in the country. National warnings and
advisories are compiled and issued with the longest possible lead-time. Alerts are issued by SAWS and
are used by disaster management centres in preparation and readiness for emergency actions such as
evacuation in the face of the hazard. The alerts are also issued directly to the public through the media,
internet and cellphone service providers. For example, using the Flash Flood Guidance System, warnings
were issued for Gauteng on the night of the 15-16 December 2010 flash flood.
The current legislation and institutional arrangements do not acknowledge independent early warning
information producers such as local farmers in Limpopo and the Northern Cape and that access to early
warning information does not always reach the people who need it despite the warning being issued.
Further, the packaging of early warning information needs to be improved, and needs to be translated
into local languages, while the reliability of issuing of early warning information is questioned and needs
to be more reliable. Some of these challenges require longer term focus, while some may be doable in
the short term, with a low resource realignment, or refined focus. Some recommendations may require
a departure from traditional ways of thinking and approaches to DRM in South Africa, given a changing
physical and social environment.
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1. Introduction
Over the last five decades, South Africa has experienced a significant increase in mean annual
temperatures with hot and cold extremes increasing and decreasing respectively in frequency across the
country, particularly in the western and northern interior. Extreme rainfall events have shown an
increasing trend across the country in spring and summer with the intensity of rainfall events and dry
spell duration also showing increasing trends. Climate change projections for South Africa indicate that
temperatures will continue to increase with both drying and wetting trends in almost all parts of South
Africa. A higher frequency of flooding and drought extremes could be expected which will intensify
existing and create additional socio-economic consequences for vulnerable populations in South Africa.
These affects would in particular be linked to the increase in extreme weather events such as floods,
fires, droughts and severe storms. This trend is supported by evidence, globally and in southern Africa
(DEA, 2013a).
Globally, the Intergovernmental Panel for Climate Change (IPCC) expects negative short- to mediumterm impacts as a result of climate change particularly for low income earners (Hay, 2010; Vermaak and
Van Niekerk, 2004). The increase in extreme weather related disasters, increases the economic and
fiscal exposure of developing countries, including an increase in the impacts, making the need to
address the preparedness, readiness and response to distress while adapting to climate change,
essential (SALGA, 2013). South Africa’s Second National Communication (SNC) under the UNFCCC (DEA,
2011b) acknowledges the importance of institutions in adapting to climate change as well as the
important role of integration across on-going activities. This includes, in particular, aligning climate
change adaptation and disaster risk reduction and management (DRR-M) activities such as planning and
implementing DRR-M to help build resilience including developing effective EWSs. The National Climate
Change Response Paper (NCCRP) (DEA, 2001a) and the SNC (DEA, 2011b), highlight disaster
management as a key area of development for building resilience to the expected increase in the
frequency and intensity of extreme weather related hazards.
Disaster risk reduction and management and climate change adaptation
Disaster risk reduction (DRR) is defined as “the systematic development and application of policies,
strategies and practices to minimize vulnerabilities and disaster risks throughout a society, to avoid
(prevent) or to limit (mitigate and prepare) adverse impacts of hazards, within the broader context of
sustainable development” (UNISDR, 2009). This definition highlights disaster risk reduction as a complex
and multi-disciplinary element that aims to decrease mortality, livelihoods and property damage,
including environmental, economic and social obstructions, caused by disasters. The objectives of DRR
are to strengthen resilience against natural disasters and are aligned to development initiatives so as not
to increase vulnerability to hazards (NDMC, 2006). Disaster risk management refers to integrated multisectoral and multidisciplinary administrative, organisational and operational planning processes and
capacities aimed at reducing the impacts of natural hazards and related environmental, technological
and biological disasters. This broad definition encompasses the definition of ‘disaster management’ as it
is used in the Disaster Management Act, 2002 (RSA, 2002).
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Adaptation to climate change concerns both human and natural systems, and refers to the process of
adjustment to actual or expected climate and its effects so as to moderate harm and take advantage of
beneficial opportunities. In natural systems, adaptation could include human activities which facilitate
adaption (Lavell et al., 2012:36). The notion and practices of disaster risk reduction and climate change
adaptation have overlaps and are beneficial to each other, despite DRR-M including other hazards that
are not climate change related for example earthquakes, while climate change adaptation focusses on
reducing vulnerability (O’Brien et al., 2012). Overlaps do exist in terms of reducing vulnerability to
extreme weather related hazards such as floods, droughts and heat waves, with both practises aiming to
reduce the impact of both extreme events and climate change. This has prompted the call by
international organisations such as the IPCC (2012) to integrate DRR-M and climate adaptation to
improve the resilience of poor communities who are the most affected by disasters and climate change
(O ‘ Brien et al., 2012).
Figure 1: The key concepts of disaster risk reduction management and climate change adaptation
(Lavell et al., 2012).
The IPPC SREX report (Lavell et al., 2012) dealing with disasters and extreme events has called for the
integration of disaster risk reduction and climate change adaption, based on the similarities and
objectives of these two practises (see figure 1). Both disaster risk reduction and climate change adaption
aim to mitigate climate-related risks by reducing and modifying environmental and human factors, in
order to support sustainable economic and social development (Lavell et al., 2012). Both also endorse
the preparedness for disasters and include the importance of education in dealing with adaptation and
disaster reduction to current and future or projected climate changes. The two practises have been
regarded as separate in the past, in terms of the concepts, methods, interpretation and institutional
structures; however, disaster risk reduction has undergone an evolution, resulting in the possible
alignment with adaptation. The changes in risk reduction are leaning more toward developing resistance
to potential impacts of extreme events thereby building resilience of the affected communities. Both
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also focus on development, and if the developmental aspects are expanded, synergies could be easily be
identified that will enhance adaptation and risk reduction (Lavell et al., 2012).
Climate information and EWSs
One way of getting better equipped to mitigate disasters is an EWS (EWS) which provides timely and
effective information, through identified institutions and allows individuals exposed to a hazard to take
action, to avoid or reduce their risk and prepare for effective response (UNISDR, 2010). A response
strategy for disaster risk reduction and management (DRR-M) noted in the NCCRP (DEA, 2001a) and the
Second National Communication to the UNFCCC (DEA, 2011b) highlight the expansion and enhancement
of EWSs for severe weather events, in order to achieve increased resilience to and develop adaptation
strategies for climate change. This encompasses outreach of the systems as well as communication of
early warning information to the potentially affected populations.
The SAWS Severe Weather System disseminates early warning information to affected communities
about potentially damaging weather events (e.g. heavy rain, heat waves and cold weather) that are
common and high risks in the country and which can result in severe impacts. SAWS also collaborate
with other government and research institutions to gather early warning information (see chapter 5).
Further, SAWS and its collaborators have a myriad of monitoring systems in place; especially for the
different hazard types experienced in the country and also have an extensive dissemination system. In
order for EWSs to be effective they should address four key elements as defined by the United Nations
International Strategy for Disaster Risk Reduction (UNISDR): (i) risk identification, (ii) monitoring and
warning system, (iii) warning dissemination, and (iv) response actions (Seng & Stanley 2012).
Legislation and policy environment
The South African Disaster Management Act (RSA, 2002) and the National Disaster Management
Framework (RSA, 2005) guide DRR-M in the country. The framework is an essential planning tool for
disaster management, pursuing to expansively influence the management of most disasters, despite not
specifically addressing climate change issues or impacts (see Chapter 4 for details on the Act and
Framework). It is important to note here that the DMA is currently under review by the NDMC, with the
public having been called to make inputs or comments on the Act. Other legislative instruments geared
towards addressing disaster risk reduction and management in the different key sectors in the country
are being developed, some already being operational. The development of these instruments is in
accordance with the requirement by the DMA, for example the Agricultural Disaster Risk and
Management Plan, the Agricultural Flood Management Plan, Agricultural Cold Spells Management Plan
and the Agricultural Veld Fire Management Plan. All these plans are still in process and are at various
stages of development (DEA, 2013). The Drought Management Plan of 2005 is another plan addressing
issues of disaster risk reduction. While it does not take climate change into consideration, the plan seeks
to reduce the impacts of droughts, by providing an information management, monitoring and evaluating
system for drought situations (DEA, 2013) (see chapter 4 of this report). Given that the drought
management plan is not a policy as such, the development of drought policy is also underway.
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Intergovernmental structures
The mandate for disaster risk management in South Africa is the responsibility of the National Disaster
Management Centre (NDMC), whose objective is to coordinate and promote integrated disaster
management at all levels of government, national, provincial and local municipalities as well as with
other role players (chapter 4). The Act further calls for the decentralisation of DRR-M activities to other
tiers of government, provincial, district and local, with the NDMC playing a coordinator role for other
disaster centres that are set up across the country. These structures may however change due to the
review process on the DMA.
Despite South Africa leading in the integration of disaster risk reduction and climate change adaptation
through the DMA and the NDMF, which focus on hindrance, decentralisation of DDR governance, and
the integration of the DRR in development planning, the implementation of the Act and Framework has
been problematic. According to a review conducted by the South Africa Local Government Association
(SALGA), and the African Centre for Disaster Studies (ACDS) gaps exist within the Act as well as other
factors that hinder effective implementation. Another review by the National Interdepartmental
Legislative Review Committee (ILRC) also highlighted the DMA as in need of a review, which has been
conducted with an amendment bill awaiting approval (SALGA, 2012).
Overall aim of the study
South Africa as a developing country, with high rates of poverty, is extremely vulnerable to increases in
extreme weather events. The challenges faced in the implementation of the DMA and the NDMF affect
DRR-M and climate change adaptation, especially for key economic sectors such as agriculture and the
water sector, and the effectiveness of EWSs in the country. This further affects vulnerable populations
and communities, with a special focus on human settlements and other sector departments that are
directly affected by extreme weather events. The poor, in particular, will be most vulnerable because of
their limited access to livelihood opportunities, information, technology and assets as well as limited
access to areas that are fit and safe for healthy habitation. Consequently the poor will be more exposed
to these increases in climate related hazards. This vulnerability will be exacerbated by current
inadequate comprehensive planning, implementation and insurance cover for disaster losses which will
further add pressure to the public resources (SALGA, 2013). DRR-M is and continues to be a topical issue
in South Africa, needing urgent attention, especially for the poor due to their limitations to implement
disaster risk reduction or to cope with the impacts of the disasters (UNEP, 2004). Therefore the overall
aim of this study is to develop policy recommendations for the improvement and management of DDR,M and EWSs within the LTAS process with specific aims to:
 develop policy recommendations for strengthening climate information and early warning
systems in South Africa,

review current capacity with regards to climate information and early warning systems for
floods, fires, droughts and storm surges,
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
review decision support tools available cross sectorally and the mandates, capacity and links
between national, provincial, municipal and local community levels with regards to early
warning systems,
4
5

review the production, interpretation, packaging and dissemination of weather and climate
forecasts and related information across relevant sectors.
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
determine the socio-economic impacts of past extreme weather events, including a summary
where feasible of the approximate costs of disaster risk reduction and rehabilitation/recovery in
terms of government and private infrastructure such as roads, bridges and dams at provincial,
and municipal level for past events.
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2. Methodology
The work, conducted as a desktop study, references existing South African research combined with
selected insights from international and local case studies of best practice for disaster risk reduction and
early warning. The study included a review of relevant literature on EWSs currently available for
weather related hazards in South Africa, literature of past extreme weather events, disaster risk
reduction, early warning and case studies, as detailed below.
The analysis was undertaken through secondary data analysis of literature from national government
department annual reports, ancillary information sources, grey literature, peer reviewed literature and
other publications. Due to time and budgetary constraints, other data collection methods such as
interviews could not be conducted for this study. The secondary data analysis was appropriate for this
study, given scope and timelines, further providing an overview of the gaps and opportunities in current
climate and early warning systems.
Data collection methods used for this study were mostly secondary literature reviews (desktop studies),
focus group discussions, and key stakeholder interviews. Secondary literature reviews included the
review of hard copy and electronic journal articles, reports (e.g. NDMC, SALGA and DEA), policy
documents, and newspaper articles. These provided insight into climate information and EWSs for
supporting disaster risk reduction; the socio-economic impacts of the extreme weather events; disaster
risk reduction and management; climate information and EWSs in South Africa; and policy, operational
and strategic recommendations.
A focus group discussion is an interactive approach used to get insight into the perceptions, beliefs and
opinions of a group of people (Goldman and Schmalz, 2001). A focus group discussion during the LTAS
workshop on 22-24 January 2014 provided stakeholders with the research questions and presented the
draft findings that were compiled by the team using literature reviews and stakeholder interviews. The
stakeholders were then given an opportunity to discuss the draft findings and give inputs which were
incorporated into the final report.
Interviews were conducted to elicit useful information from key stakeholders from the South African
Weather Services and the National Disaster Management Centre. Certain disaster risk reduction and
management experts identified in the LTAS workshop as key stakeholders who could provide more
insight on the research were not available during the time period for a face to face, telephonic or Skype
interviews.
Local and international websites reporting on disasters as well as print media were also reviewed to
obtain case studies on best practices which were integrated within the chapters. These include the UN
International Strategy for Disaster Reduction UNISDR (http://www.unisdr.org/) and the World
Meteorological Organization (http://www.wmo.int/). Case studies on the implementation of EWSs in
South Africa are poorly documented, and very little academic research has been published to assess
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good practice. Information on the actual implementation of disaster management centres was obtained
by contacting the respective disaster management centres relevant for each case study.
Limitations and challenges
 While the report attempts to capture all the disasters that have occurred in the country, gaps still
exist in the data due to inconsistent reporting of disasters and costing which made this task difficult.
 Disaster costs for rehabilitation, recovery and reduction costs are often reported in NMDC Annual
reports as one figure with no separation of each component at both municipal and provincial level
where funding is allocated.
 The social impacts and economic costs in tables 1 – 4 and 6 were consolidated from internet
searched articles, research papers, SARVA, CSIR publications, Emdat 2014 data and government
annual reports which exclude the costs reported in the NDMC Annual Reports. Many disasters are
documented but without information on the damage values especially over the last couple of years.
 Cumulative or secondary costs of flooding such as epidemics are difficult to assess and have
therefore not been included in the costs in Table 6 The data in the table is unverified and is only
meant to illustrate total disaster costs and the increase of costs over time.
 It was difficult to find in the municipal budgets or IDP documents how municipalities are proactively
funding disaster risk reduction and the expenditures thereof are not classified as such, and are
integrated into other funding and costs.
 Most of the literature pays more attention to climate change adaptation as compared to EWSs,
therefore case studies on the implementation of EWSs in South Africa are poorly documented, and
few to none academic research has been published to assess good practice.
 Case studies where EWSs such as AFIS are being used are lacking despite these systems being
mentioned in the NDMC annual reports between 2008 and 2010.
 Access to NDMC annual reports was a problem since these are not available online and hard copies
had to be fetched from Pretoria.
 Getting response on this cost reporting issue from the NDMC directly was also a problematic.
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3. Climate hazards and socio-economic impacts
Natural hazards are naturally occurring physical phenomena caused either by rapid or slow onset events
which can be geophysical (earthquakes, landslides, tsunamis and volcanic activity), hydrological
(avalanches and floods), climatological (extreme temperatures, drought and wildfires), meteorological
(cyclones and storms/wave surges) or biological (disease epidemics and insect/animal plagues) (EMDAT
2014).
Hazards can be human-made or natural and all hazards are not disasters. A hazard, by definition, is any
event, phenomenon, or human activity that may cause loss. Natural and human-induced factors may act
together to create a hazard. For example, earthquakes are normally considered to be natural hazards,
but they can also be triggered by mining activities or the impoundment of large dams. A landslide can be
caused by a combination of heavy rains, light earth tremors, and deforestation.
The link between hazards and disasters is the degree of vulnerability of the affected people and
ecosystems as described in the definitions below:
•
•
•
Hazards: Threats to life or wellbeing, material goods and/or the environment. Extreme natural
processes or technology causes them. When a hazard results in great suffering or collapse, it is
usually termed a disaster.
Disaster: A natural or human-caused event, occurring with or without warning, causing or
threatening death, injury or disease, damage to property, infrastructure or the environment, which
exceeds the ability of the affected society to cope using only its own resources.
Vulnerability: Vulnerability is a function of exposure to climatic factors, sensitivity to change and
the capacity to adapt to that change. Systems that are highly exposed, sensitive and less able to
adapt are vulnerable. The degree to which an individual, family, community or region is at risk of
experiencing misfortune following extreme events (Department of Constitutional Development,
1998).
The poor because they have limited options often live where natural hazards are most likely to occur,
and are therefore most vulnerable to natural hazards. There is however not a one-to-one relationship
between extreme events or hazards and disasters. Disasters entail social, economic, or environmental
impacts that severely disrupt the normal functioning of affected communities. Extreme weather and
climate events will lead to a disaster if:


Communities are exposed to those events; and
Exposure to potentially damaging extreme events is accompanied by a high level of
vulnerability (a predisposition for loss and damage).
Disasters are also triggered by events that are not extreme in a statistical sense. High exposure and
vulnerability levels will transform even some small-scale (slow-onset) events into disasters for some
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affected communities. Recurrent small or medium-scale events affecting the same communities may
lead to the serious erosion of its development base and livelihood options, thus increasing vulnerability
(IPCC, 2012:33). While natural hazards are a part of the natural environment, disasters are not, with
disasters occurring only when a natural hazard intersects with the built environment and also natural
hazards cannot be managed (FEMA, 2004). Didier Cherpitel (n.d.) argues that “disasters push people
further into poverty and poverty forces the exploitation of the environment.” One way of
conceptualising and improving understanding of risk and vulnerability (in order to develop appropriate
risk reduction as well as response strategies) is the use of the Progression of Risk Model (Pressure and
Release Model)(see figure 2). The model helps one to understand the complexity of community
vulnerability. Vulnerability according to this model does not just happen but often develops as a
progression from root causes to dynamic pressures that create unsafe conditions.
Figure 2: Progression of Risk Model (Pressure and Release Model)1 (Blaikie, et al.; 1994 & Global Crisis Solutions, (n.d.))
1
Root causes are the fundamentals and ideologies on which society and communities are built. These help answer questions on
why unsafe conditions persist. Dynamic pressures are the structural causes (institutions, policies, processes and practices)
which translate root causes into unsafe conditions. Unsafe conditions are the proximate cause of vulnerability in the vulnerable
community/ system which is exposed to the risk of a disaster for example people living in an informal settlement on a wetland.
Responding to these risks needs to be done in an integrated effort by different sectors and stakeholders i.e. those who are
affected and those who can affect the achievement of disaster reduction and resilience (Blaikie, P. et al. 1994 & Global Crisis
Solutions (n.d.)).
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Damage and recovery/rehabilitation costs are reactive while disaster risk reduction costs are proactive
costs. There is a need to be cautious when basing estimates of adaptation costs on disaster loss
estimates. The increase of these reactive costs indicate then need for more investment in proactive
measurements, in order to mitigate the impacts of slow or rapid onset disasters. According to Kofi
Annan: “Building a culture of prevention is not easy. While the costs of prevention have to be paid in the
present, its benefits lie in a distant future. Moreover, the benefits are not tangible; they are the
disasters that did NOT happen” (UNISDR, 2007:8). A few international studies have tried to prove this.
For example an international study by the World Bank conducted on 3 countries from 1998 to 2008
found that there are two main trends of pre- and post-disaster expenditure: first, total post-disaster
expenditures exceeded pre-disaster expenditures on average (and almost year by year); and second,
pre-disaster investments remain stable over time or, if anything, display an increasing trend whereas
post-disaster investments are highly responsive to the occurrence of major disasters every year and are
therefore volatile (de la Fuente, 2009).
Limited data and robust information increases the uncertainty of costing when scaling up to higher
levels of government from a very limited (and often very local) evidence base. There are double
counting problems and issues of incompatibility between types of impacts in the process of multisectoral and cross-scale analyses, especially for the efforts to add both market and non-market values
such as ecosystem services (Downton and Pielke, 2005; Pielke et al., 2008; Parry et al., 2009). Moreover
the full impacts of weather and climate related extremes in developing countries are not fully
understood, and a lack of comprehensive studies on damage, adaptation, and residual costs indicates
that the full costs are underestimated (IPCC, 2012:274).
It is important to highlight that although quantifying the cost effectiveness of improved DRR-M including
effective climate information and EWS investments is difficult, and is therefore not regularly
undertaken, for example solid cost-benefit analyses of investments in improved climate monitoring and
effective EWSs are scarce (UNISDR, 2007). There is evidence that suggests that investment in prevention
is more cost-effective than spending on relief (Tsirkunov and Rogers, 2010; Hallegatte, 2012).
3.1.
Socio-economic impacts of climate hazards in South Africa
The impacts of disasters or extreme events have primary and secondary effects, with some impacts
easier to measure, for example damage to infrastructure, while others are difficult to measure and cost,
such as death and trauma related to the event. According to the UNISDR (2009) terminology, disaster
losses are traditionally classified as follows:
• Direct costs are the damage, including damage to the productive capital stock (industrial plants,
standing crops, stock, etc.), damage to economic infrastructure (transport, energy supply, etc.), and
damage to social infrastructure (housing, schools, etc.).
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3.1.1. Socio-economic impacts of different hazard types in South Africa
As evidenced by the frequency and intensity of extreme weather events in South Africa, the myriad of
socio-economic impacts as documented in section below indicate the need for pro-active costs and
investment in DDR-M activities to deal with disasters. This is essential given the escalating costs of
damage from disasters and the focus by most institutions on recovery and rehabilitation after a disaster
rather than DDR-M. The next section attempts to give a classification of the different hazard types
experienced in South Africa and the socio-economic impacts on the various economic sectors which
affect sustainable economic development in the country.
•
Indirect costs are secondary disorders that affect the supply of goods and services, such as reduced
performance due to destruction or damage of facilities or infrastructure, and loss of earnings due to
lower revenue opportunities. Cuts in basic services can have serious consequences, such as
disruption of telecommunications or a lack of drinking water. The indirect costs also include health
expenditures and lost productivity due to illness, disability and death. There are however positive
effects that could partially offset the gross indirect costs through rehabilitation and reconstruction
which revives the construction sector. Socio-economic studies have revealed that the secondary
effects and indirect costs of disasters have also long-term effects on societies, regardless of their
level of development (van Niekerk et al, 2009:1).
Side effects are the short and long-term impacts of a disaster throughout the economy and socioeconomic conditions. These include effects on, for instance, fiscal and monetary performance, the
amount of housing and the external debt, income distribution and the magnitude and incidence of
poverty, the consequences of removal or restructuring of certain elements of the economy and the
labour force.
Floods
Most floods are characterised as sudden or rapid-onset disasters, which could be at a local or wide scale
based on physical characteristics of the area. While there are man-made floods, in this report we focus
on climate related flooding, and although some floods can be predicted, flash floods are difficult to
predict. Harvey (2007) identifies three principal types of floods:
•
•
•
Rapid-onset floods: these include flash floods, tidal surges, floods provoked by cyclones or
accompanied by strong winds, high runoff from heavy rainfall, dam bursts and overtopping,
canals and rivers bursting their banks. Typically water rising to dangerous levels within 48
hours.
Slow-onset floods: prolonged rainfall causing low-lying areas to gradually become flooded over
a period of days or weeks.
Annual seasonal flooding: many communities around the world are flooded annually and may
be under water for some considerable time each year.
Floods were the most common hazard type with South Africa (figure 3), causing most damage and
resulting in escalated costs for response and recovery. The socio-economic impacts of floods affect a
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myriad of sectors pertinent to the country’s development and human wellbeing. Table 3.3 provides a
summary of the flood impacts on the different sectors, with some examples provided (where these were
available).
Figure 3: NDMC floods Hazard Map
(NDMC, 2014)
Table 1: Summary of flood impacts in South Africa
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Sector
Impact
Examples
Health (see
figure 4 for
public health
impacts of
floods).
 Destruction of sewers systems causing pollution.
 Water pollution diseases such as Typhoid, Cholera,
Malaria, Gastroenteritis, Conjunctivitis.
 Young, elderly, handicapped and HIV/AIDS affected
people most vulnerable.
After the Juksei River flooded in
Johannesburg’s Alexandra township in
1999 resulted in cholera outbreak.
Residents were moved to sanitary
conditions (UNEP 2000).
Human
settlements
 Inundation of homes and destruction of furniture.
 Homelessness in poor communities, having to
resettle or migrate.
 No accessibility to community services.
 Human occupancy of the floodplains and the
presence of floodwaters produce losses to
There are hundreds of thousands of
shack dwellers and backyarders in
Cape.
People left homeless after the
Laingsburg flood disaster of January,
1981, caused by a cut-off low weather
2
Table is compiled from different data sources as referenced in Annexure 1, including print media. More
references are provided within the table under impacts and examples.
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individuals and society (Cardoso et al, (n.d.):446).
 Compensation, resettlement and reconstruction
cost escalate, running out of flood relief funding.
 Dead and lost pets.
 Secondary impacts include trauma, depression and
grief due to continued loss after the disasters, with
detrimental impacts on community life and
economic activities.
Mortality
 Recovery and identification of bodies.
 Loss to the family.
 Traditional burials sometimes not possible.
Infrastructure




Water
resources
 Contamination of drinking water (Yande, 2009).
 Acid mine drainage (WRC 2011, DWAF 2010, IOL
2011).
Agriculture &
food security





Agriculture &
food security
 Loss of crops and livestock.
Houses damaged.
Water and sewerage, roads, bridges washed away.
Drainage systems blocked.
Dams, hospitals, schools, community centres,
housing and property damage.
 Learning is disrupted by inundated schools.
 No electricity supply.
 Heritage sites and icons destroyed.
Loss or damage to agricultural infrastructure.
Loss and damage of crops and livestock.
Loss of livelihoods.
Loss of income to subsistence families.
Isolation.
system (Grobler 2001).
The 1987 the KwaZulu-Natal flooding
left 68 000 people homeless (Grobler
2001).
Many people, especially children and
the elderly, become sick from the cold,
the wind and the rain. Their homes are
flooded every single winter destroying
all their furniture and displacing
families for weeks on end (Gugulethu
AEC, 2011).
The Laingsburg flood disaster of
January, 1981 resulted in 104 losses of
life. In 1987 the Kwazulu-Natal
Flooding left 388 people dead, some
buried under collapsed mud.
In 1987 the KwaZulu-Natal flooding
caused severe damages to thousands
of kilometres of roads, 14 bridges
washed away, all entrance routes to
Durban closed.
“Over 120 000 agricultural jobs are
threatened by the deteriorating water
quality. The Loskop Dam on the
Olifants River, for example, is heavily
polluted by mining in its headwaters,
which is affecting downstream
activities. This is compounded by the 5
906 abandoned and ownerless coal
mines in the country” (IOL 2011).
Successive floods of 1983, 1984 and
1985 resulted in food being imported
for the domestic market, loss of
livestock due to reduced grazing.
After cyclone Eline some reports
indicate crop losses valued at some
R70 million. Most affected crops are
pulses, maize and vegetables and
many villages remain isolated by
impassable roads and broken bridges
which hamper relief operations- food
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Tourism
 Infrastructure and accommodation damages.
 Transport closures.
 Loss of livelihood, including loss of employment.
Ecosystems











Coastal zones
Polluted water causing damage.
Washing away of flora and fauna.
Cope less with the next event.
Reduced and disappearing ecosystem services.
Flora & fauna extinctions.
River erosion.
More dams needed which impacts on ecosystems
change in the ecosystem services provided by the
floodplain vegetation communities, flood
attenuation & water purification of wetlands, and
decline in biodiversity (Turpie, 2010:III).
Alien plant invasion, alien plants being able to
germinate and establish quicker than indigenous
species after floods (Foxcroft and Richardson 2003).
Role and capacity of wetlands, floodplains, and
Coastal Ecosystems diminished in further regulating
of floods.
Landslides.
Acid mine drainage.
 All pollutants move and disperse during flood
plumes and contaminate marine ecosystems and
biodiversity, and produce algae on the reefs
(Schaffelke, 2013; ISRS (n.d.)).
parcels and medical equipment (FAO
2000).
Flooding in KwaZulu-Natal in
September 1987 resulted in all
entrances to Durban being closed
(Grobler 2001).
The Cape Mountain Pass
Meiringspoort closed for 4 years after
a serious flood in November 1996
(Ross 2001).
32 hikers had to be rescued after being
trapped by heavy rain on the Whale
Trail near Bredasdorp (Al Jazeera
2012).
Kruger – Alien plant invasion after
flood (Foxcroft and Richardson, 2003).
Riparian vegetation fulfils or influences
various important ecological functions
in relation to aquatic habitats,
including the provision of food,
moderation of stream water
temperature via evapotranspiration
and shading, providing a buffer zone
that filters sediments and controls
nutrients, and stabilization of stream
banks (Barling and Moore, 1994; Hood
and Naiman, 2000). It also provides a
corridor for the movement of biota
(Naiman and Décamps, 1997) and
serves many important roles for
humans (Kemper, 2001; Richardson et
al, 2007).
A positive of floods is that deposited
wood creates regeneration niches for
riparian vegetation on a semi-arid
Sabie River in Kruger NP (Pettit et al.,
2006).
Examples?
1
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Nelson Mandela Bay Metropolitan Municipality Case Study
The Disaster Management Centre of the Nelson Mandela Bay Metropolitan Municipality identified in
2010 the top rated risks as the following:





Floods, especially affecting informal settlements and infrastructure;
The effects of fire, explosions and spillage of hazardous materials;
Severe storms;
Human disease. This category includes diseases that can lead to rapid onset as well as slow
onset disasters. Diseases and conditions included under this category include HIV/AIDS,
tuberculosis, cholera, and asthma; and
Drought, as is evident from the 2010 experience (Nelson Mandela Bay Disaster Management
Centre, 2013).
The risk for the metropolitan area of floods and severe wind, has been categorised as very severe (Henry
Lansdown, Nelson Mandela Bay Disaster Management Centre, personal communication, 14 January
2014).
1
2
An EWS consisting of 29 CCTV cameras at strategic remote sites were installed to monitor potential
high-risk flooding areas in the metro. In partnership with SAWS, four fully automatic weather stations
were also installed at four existing CCTV sites. These four sites provide both images and weather
information at the surveillance centre. Surveillance is done at the Joint Operations Centre (in adverse
conditions a member of the local SAWS joins the centre) and runs on the wireless backbone
infrastructure of the metro but also has a fibre optic link with the local SAWS. Eight extra SAWS
automatic rain stations (funded by the NDMC) were installed across the metro as part of the Flash Flood
Guidance System and to enhance the capacity of the Port Elizabeth branch of the Weather Services to
predict flooding. This system detects and monitors adverse weather phenomena and issues warnings to
affected communities. Some rivers crossings are also fitted with an alarm system to alert users of any
risks (Nelson Mandela Bay Disaster Management Centre, 2013; Nelson Mandela Bay Disaster
Management Centre, n.d.). Communication or dissemination of the informations conducted through the
media and through various key institutions such as disaster management practitioners, NGOs, and
organs of state.
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Figure 4: Public health impacts
(WHO, (n.d.))
Storms
The classification of storms includes severe thunderstorms, cyclones, tornados, convective storms,
frontal systems and cut-off low events (OneWorld, 2010) which can cause flash floods. In this report we
include in the classification of storm, storm surges, hail storms, severe cold fronts including some
instances of snow. Storm surges are an irregular rise in sea level produced by a storm and characterised
by heavy rains and high winds (NOAA, 2014). It is important to note that storms result in similar socioeconomic impacts as flooding, but often with more destructive winds. While all the impacts in the
previous table apply to storms additional impacts are listed below (Table 2).
Table 2: Summary of storms impacts
Sector
Impact
Examples
Tourism




In January 2012 after Cyclone Dando,
hundreds of tourists and locals were left
stranded and at least 30 people had to be
airlifted after flash floods washed away
bridges and damaged numerous buildings
and roads (Wikipedia (n.d.)).
The ”Outeniqua Choo Tjoe” stopped
Destroyed tourism businesses and settlements.
Loss of income for the affected businesses.
Disappearing by storm surges.
Tidal surges destroy infrastructure, houses near
the coast, destroy protective sand dunes and
wash away beaches, recreational assets and
danger zone buffers (Southern District Plan,
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2012).
 Tourist private property (caravans, tents etc.)
damaged.
operating after heavy storms in 2006
caused major damage to the track
(Heritage Portal, 2013).
Infrastructure





Human
settlements
 Loss of homes.
 Damaged cars.
 A combination of sea level rise and storm surges
will potentially threaten low-lying areas of the
major coastal metropolitan centres of Cape
Town, Durban, Port Elizabeth and East London
(Mather, 2008).
Cyclone Eline in February 2000 resulted in
loss of life and damage to housing and
infrastructure (FAO 2000).
In 1985 a major hailstorm striking
Pretoria city centre and surroundings.
Roofs collapsed, windows of cars were
broken (Grobler 2001).
Tornado in Duduza - Some of the
buildings devastated by the tornado had
thick stone walls that may have added
significant structural strength, although
the overall construction of the area was
substandard (Extreme Planet, 2012).
Heavy seas disrupt train operations to
Port Elizabeth harbour (Ports & Ships
Maritime News, 2008).
Tornado in Duduza left hundreds
homeless and injured and 1 child dead.
Six people were arrested for looting
affected homes in the aftermath.
Ecosystems
 Increasing salinization of groundwater and
estuaries by storm surges may impact on
boreholes (which are particularly important for
water provision for smaller coastal settlements)
and on the many fish species that are dependent
on estuaries as breeding grounds (Petersen and
Holness, (n.d.):5).
 Sediments build up at the mouth increasing the
risk of back-flooding during storms (Sink et al,
2012).
 Loss of top soil impacts agriculture resulting in
low crop yields
 Siltation requires dredging of ports to allow
access to boats
Examples?
Coastal zones
 Damage on coastal infrastructure.
 Erosion of protective dunes.
 Damage to wetlands.
Examples?
Houses & roofs damaged or torn off.
Fallen trees on infrastructure and blocking roads.
Damage to sea walls, railway lines and harbours.
Coastal erosion events.
Impacts on rail and other transport.
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Droughts
Drought has become a permanent feature of the South African agricultural sector. This is usually
interspaced with flooding arguably due to climate variability. As a result, South Africa has a long history
of drought risk management (Ngaka, 2012b:36).
Wilhite and Glantz (1985) describe four basic categories or types of drought:
•
•
•
•
Meteorological drought: A reduction in rainfall supply compared with a specified average
condition over some specified period; defined as a period during which less than a certain
amount (e.g. 70 percent) of the normal precipitation is received over any large area for an
extended period.
Agricultural drought: A reduction in water availability below the optimal level required by a
crop during each different growth stage, resulting in impaired growth and reduced yields.
Agricultural drought relates to an imbalance in the water content of the soil during the
growing season, which although influenced by other variables such as the crop water
requirement, the water-holding capacity and degree of evaporation, is also largely dependent
upon rainfall amount and distribution.
Hydrological drought: The impact of a reduction in precipitation on natural and artificial
surface and subsurface water resources. It occurs when there is substantial deficit in surface
runoff below normal conditions or when there is a depletion of groundwater supplies.
Hydrological drought reduces the supply of water for irrigation, hydro-electrical power
generation, and other household and industrial uses.
Socio-economic drought: The impact of drought on human activities, including both indirect
and direct impacts. This relates to a meteorological anomaly or extreme event of intensity
and/or duration outside the normal range of events taken into account by enterprises and
public regulatory bodies in economic decision-making, thereby affecting production and the
wider economy (Wilhite and Glantz, 1985). Socio-economic drought occurs when demand for
freshwater exceeds supply.
Drought is an example of a slow-onset disaster. This is a period when there is very little or no rain, and
as a result much less water and crops than people need. This creeping disaster is one of the most severe
types of disaster because it affects a much larger number of people than other types of disasters.
Droughts affect social and economic activities resulting in loss of assets. Intervention in the event of a
drought includes emergency food relief which is often supported by large amounts of donated food aid.
Drought preparedness at government level can be done by creating food reserves mainly of the staple
food like maize which will be used to compensate for production shortfalls and provide for possible
emergency aid. Some of the general social economic impacts of droughts are shown below followed by
specific examples from South Africa (see Table 3)
.
30
1
Table 3: Summary of drought impacts in South Africa
Sector
Social economic impacts
Examples
Agriculture
and food
security
 Reduced income, food shortage,
reliance on shops, unemployment,
eviction through reduced crops, total
crop failure.
 Reduced health, food shortage, sales,
slaughter, reduced income through
weakened, disease, dead livestock.
 Increased food prices, loss of tenure,
food shortages, homelessness and
migrations through increased evictions,
closure of farms, food shortages.
 Livestock weakening, diseases, heat
stress and death, livestock sales and
slaughter, impounding, conflict, land
degradation through reduced grazing.
 Inadequate, poor land and
management thereof, often heighten
the impact of a drought.
 Veldfires.
In 1992/1993, undoubtedly one of the most
widespread droughts of the last 45 years, maize had
to be imported to South Africa (as well as the rest of
southern Africa). The knock-on effect of crop failure
could be seen in the population drift from rural areas
into the cities, farm labour lay-offs and farm closures
as well as an increasing indebtedness in the
agricultural sector (WeatherSA).
Backward and forward linkages to other sectors (e.g.
the purchase of goods such as fertilizers, chemicals
and implements as well as the supply of raw
materials to industry). According to the Reserve Bank
(Pretorius and Smal 1992) the loss of GDP during the
1992 drought was approximately 1.8 percent,
representing US $500 million which is a substantial
impact from a sector playing a relatively small role in
the economy (Mniki, 2009:34).
Health
 Human diseases (respiratory trouble,
poor hygiene & mental health issues),
human health, and deaths, crop failure
and loss, migrations through reduction,
contamination and absence of water.
Examples
Employment
 Loss of income, debts, food shortages,
increased unemployment, alcoholism,
migrations through layoffs, evictions.
Human
Settlements
 Migrations through reduction and
disruption of domestic activities,
conflict through contamination and
absence of water.
 Poor infrastructure and water supply in
an area.
 Pastoralists, poor women and children,
the elderly, the disabled, internally
displaced persons and their host
communities, people living with
HIV/AIDS and their families, and the
food-insecure living in urban areas are
vulnerable to drought (ALNAP, 2007).
Threatened shutdown of PetroSA’s petrochemical
refinery in Mossel Bay because of prolonged drought
in the Southern Cape region (Engineering News,
2010).
In the Eastern Cape, drought has resulted in delays in
the provision of low cost housing in certain coastal
towns because of the inability to secure reliable
water supplies (Petersen and Holness, (n.d.):4).
Water
 Loss of aquatic biodiversity as rivers
and dams dry up.
Water restrictions need to be put in place in the
Eden & Central Karoo areas (NDMC 2009 -2011
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 Water restrictions which affect
households and industry.
 Land degradation.
 Loss of flora and fauna/terrestrial
ecosystems.
 Increase in wild fires.
(Adapted from Cogta, 2004)
Ecosystems
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report). In 2004, 6 provinces experienced drought as
they has little or no rainfall -Northern Cape, NorthWest, KwaZulu-Natal, Eastern Cape, Mpumalanga
and Free State (Irin News, 2004).
Drought deaths in Fynbos vegetation in the south
will lead to dam siltation problems and a less
predictable water storage.
The Drought Hazard Index (DHI) map below (figure 5) shows the probability of crop failure combined
with the degree of rainfall variability from year to year. Statistical summaries of 35 years of data on the
Water Requirement Satisfaction Index were used. A very low DHI means that there is a low chance of
crop failure and a stable environment from year to year. A very high DHI means that there is a high
chance of crop failure and a large degree of rainfall and agricultural production variation from year to
year. Much of the Limpopo Basin faces a moderate to high drought hazard.
Figure 5: Drought Hazard Index Map for the Limpopo Basin
(Atlas for disaster preparedness and response in the Limpopo Basin, http://edmc1.dwaf.gov.za/library/limpopo/)
Veldfires
Most of South Africa has strong seasonal rainfall and a dry season which lasts for five or more months.
The eastern half of the country receives enough rainfall for the grasses to produce enough fuel to
support a fire every year or two. This means that veldfires are frequent and inevitable. Originally most
fires were caused by lightning but our ancestors learned to light and manage fires more than a million
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5
years ago, exploiting and augmenting the natural causes of fires to manage the vegetation for their own
purposes. Today, more than 90% of fires are lit by people, either deliberately or accidentally (Forsyth et
al., 2010) resulting in the sector impacts recorded below (see table 4).
Table 4: Summary of impacts of veldfires in South Africa
Sector
Social economic impacts
Examples
Agriculture
 Loss of crops, livestock, game and grazing land.
Forestry
 Loss of forests- timber.
 Loss of income.
Mortality
 People and animals may die.
Ecosystems
 Role of ecosystems in regulating fires
diminishes (Cardoso et al, (n.d.):445).
 Ecosystems, such as fynbos, that are vulnerable
to invasion by alien plant species after fire,
present a special case of veld fire vulnerability
(CSIR 2010).
 Too many fires have a negative impact on
biodiversity & changes in grazing regimes
which may further damage natural habitats
(Petersen and Holness, (n.d):5).
 Fire in the ecosystem is an ecological process
and part of our environment. It has a
fundamental role in sustaining biodiversity.
However, if fire is mistimed, occurs too
frequently or too seldom, or is too severe, it
In 1992 there were several huge fires which
destroyed thousands of hectares of grassland.
In one of the worst events, during August, at
least nine people perished (WeatherSA).
In Potchefstroom (North West) about 460
cattle, 160 calves and 300 sheep were burnt. 60
000ha were annihilated. In Amalia 640 head of
game were burnt in a game farm (Farmers
Weekly 2011).
During the period from January to August 2007,
61,700ha of plantation forest burnt in KwaZuluNatal and Mpumalanga, 2.9% and 9.5% of the
total area of plantations respectively in these
two provinces. ForestrySA estimated the value
of standing timber burnt amounted R1.33bn
(2007 prices), and that of this, 40% would be
unsalvageable (Forsyth et al, 2010).
July of 2002, Mpumalanga was devastated by
fires that destroyed 24,000 ha of pasture and
left four people dead and damages amounting
to more than R32 million.
In August 2011 - Five people were hurt and
several major roads closed due to veld fires
fuelled by strong winds in Bloemfontein.
In forestry the spread of alien invasive plants
continues in certain areas. The consequences
are diverse, since the effect on fuel varies with
the species that invades, and the density
reached. In some parts, where species of pine
have become dense, the potential for blow-up
fires may have increased (Forsyth et al., 2010).
33
may result in ecosystem degradation (CSIR,
2010).
GHG
 Vegetation fires do contribute to global
warming and climate change through the
release of CO². However, research has been
undertaken that suggests that CO² from veld
fires is less of an impact to global warming due
to the veld taking up more CO² again
afterwards than it lost due to the fire. Bush
encroachment from high co2 levels would
reverse this situation. (City of Cape Town, 2014
& Du Toit and Sguazzin, 1995).
Examples?
Health
 Air quality reduced & smoke pollution can
adversely affect the health of large groups of
people outside the immediate area of the
wildfire (City of Cape Town, 2014).
Industrial activity, veld fires, coal-fired stoves in
residential areas and vehicular emissions are
major contributors to deteriorating Air Quality
in the city (Climate Action in Joburg, 2014).
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3.1.2. Social impacts of climate hazards
The frequency of previous natural disaster events from 1980 to 2010, as well as the number of people
affected and number of people killed can be observed in Figures 6 to 9. It is important to note that
floods occurred most frequently and also killed the most people, whereas drought affected the most
people. Other extreme weather events that resulted in damages and loss of life are severe
thunderstorms as well as isolated incidences of meteorological phenomena including cyclones and
tornadoes. Table 5 highlight the number of disasters in the county between 1983 and 2013. Others
include veld and forest fires, locust infestations, and very rarely earthquakes and landslides following
heavy rainfall (Grobler, 2001).
Figure 7: Economic damages in US$
Figure 6: Occurrence (including Tsunamis)
34
Figure 8: Number of people affected
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4
COGTA reported the figures for disaster from 1983-2013, and reflects similar trends to EMDAT in their
country report.
Table 5: Disasters in South Africa 1983-2013
Type of disaster
Flood
Storm
Fire
Epidemic
Extreme temperature
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Figure 9: Number of people killed
(EMDAT, 2014)
Drought
Earthquake
Landslide
Total
(Pharoah et al, 2013)
No. events
No. killed
23
19
8
7
3
2
2
1
65
No. affected
473
154
123
336
17
34
1 137
483 965
140 945
7 380
112 385
53 663
15 300 000
104
16 098 442
It is important to note that CRED/EMDAT figures underestimate the scope and prevalence of hazard
events in South Africa. CRED only records data on events where ten or more people are reported killed,
100 or more people need to be evacuated, provided with humanitarian assistance or otherwise
affected; or states declare an emergency or call for international assistance. This conceals the diversity
of the hazard landscape in South Africa, which experiences a far broader range of small and everyday
hazards (Pharoah et al, 2013).
In addition to extreme weather events, there are also slow-onset recurring flood events which are not
included in the statistics. For example on Mitchells Plain in the Western Cape during winter, large parts
of the Khayelitsha (meaning ‘new home’), are flooded and at least once every year. The local
newspapers carry pictures of people wading knee-deep while using buckets to scoop water out of their
houses (capeflats.org.za).
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The maps below (figures 10, 11 and 12) highlight the extent of all extreme events as recorded by the
NDMC, beginning with the historic disaster (figure 10), the NDMC disaster situation report incidents (1990current) (figure 11) and the extreme weather events (figure 12).
Figure 10: NDMC historic disasters map for South Africa
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Figure 11: NDMC disaster situation report incidents (1990-current) map
Figure 12: Extreme weather events in South Africa
(CSIR/SARVA, 2014)
Economic impacts of climate hazards
There has been an increase in the frequency of disasters from 1981 to date, corresponding with the
increase in the direct costs of damage and recovery. The costing table (Table 6) and Figure 11 illustrate
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4
5
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7
this upward trend for the year with the highest frequency of disasters, especially for the flood hazard
type (figure 14). This increase in cost of disasters is not unique to South Africa, with a 15 fold global
increase noted. Climate change and development will exacerbate the situation, especially for middle and
low income countries like South Africa (OneWorld, 2010). Below is an example summary of direct
economic damage costs of disasters in South Africa, measured from 1981 to 2013.
Table 6: An example summary of direct damage costs of disasters by year and disaster type from 1981 to 2013
Year
Disaster
Type
1981
1984
1987
1990
1992
1997
1998
1996
2000
2004
2006
2006
2007
2007
2007
2008
2008
2009
2010
2010
2011
2011
2011
2012
2013
Flood
Storm
Flood
Storm
Drought
Flood
Flood
Flood (4)
Storm
Flood
Flood
Storm
Flood
Storm (2)
Fires
Flood
Fires
Flood
Flood
Drought (8)
Flood (3)
Storm
Fires (2)
Flood
Flood
TOTAL
Reported Costs
R 16 000 000
R 2 160 000
R 3 300 000 000
R 230 000 000
R 10 000 000
R 45 000 000
R 105 000 000
R 1 061 000 000
R 1 500 000 000
R 448 000
R 250 000 000
R 37 800 000
R 166 700 000
R 1 804 308 136
R 1 400 000 000
R 315 000 000
R 265 000 000
R 101 182 700 000
R 131 862 000
R 6 736 790 000
R 4 410 630 000
R 1 650 000
R 1 810 000 000
R 218 000 000
R 17 903
R 125 000 066
3
Deaths
104
400
17
30
173
34
34
6
8
806
8
3
This table is developed based on various data sources attached as annexure 1 of this document. The year 1981 is
used as a baseline due to the availability of the first reliable records and is also prompted by the Laingsburg
(Western Cape). Please use these figures with caution since figures for some years are missing.
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Figure 33: An upward trend in the disaster intensive years of documented direct damage costs from 1981 to 2013
Figure 14: A cost indication per hazard type from 1981- 2013
According to the NDMC Annual reports from 2006 to 2011, the municipal and district damage costs are
the areas of greatest financial need for post disaster response, compared to the national, provincial, and
municipal damage, rehabilitation and recovery costs and disaster risk reduction.
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Figure 15: All Hazard related costs recorded in the NDMC Annual reports from 2006-2011 broken down as damage,
recovery/rehabilitation and disaster risk reduction allocated NDMC funding
While the district and municipal budget allocations were substantial, (figure 15) the allocation for the
2010/2011 Eastern Cape drought emergency measures at a cost of R1596 billion, allocated by the
province for the cost of rehabilitation/recovery is the highest.
An optimal risk financing strategy is key for both pre- and post-disaster management at national and,
sectoral levels to support provincial and local levels. International case studies indicate that some roles,
functions and funding are best centralised, while others need to be decentralised. While
decentralisation has been done in South Africa, there is a big need to capacitate the institutions involved
in DDR-M.
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4. Disaster risk reduction and management in South Africa
DDR-M requires a myriad of activities and consequently many actors apart from government and subgovernment institutions are involved in the implementation of disaster risk measurements. This may
include vulnerability and risk assessment, capacity building, establishing social and economic
infrastructure as well as the utilisation of EWSs. These activities require technical expertise and other
skills which may not be found in government; hence collaboration between government, the private
sector and communities is necessary, since the impacts of disasters are felt at local level (SALGA, 2013).
The Hyogo Framework for Action (2005-2015) urges government support for disaster risk reduction,
with the application of DRR-M at local level being critical (van Niekerk, 2011). In this section, the legal
policy instruments as well as institutions governing DRR-M is discussed, including the nature of existing
DRR-M systems and the challenges faced.
4.1.
The Act and the Framework
In South Africa, DRR-M is the responsibility of the public sector, occurring at all level of government and
guided by the Disaster Management Act (RSA, 2001) and the National Disaster Management Framework
(RSA, 2005). The DMA consists of seven chapters dealing with several issues of disaster risk reduction,
for example, chapters 2-5 of the act discuss the inter-governmental structures and mandates; chapters
3, deals with national issues; chapter 4 focusses on provincial issues of disaster reduction and chapter 5
discuses local issues. Other chapters such as chapter 6, focuses on funding mechanisms for
rehabilitation and post- disaster recovery while chapters 1 and 7 provide information on the
interpretation of the Act.
The Act motivates for the formation of the NDMF. The Framework, which is divided into two parts, is
structured according to key performance areas (KPA) such as institutional capacity for disaster risk
reduction, disaster risk assessment, reduction and recovery. Enablers, which are components that need
to be in place to implement the KPA include: 1) information management and communication; 2)
education, training, public awareness and research; and 3) funding structures for disaster risk
management. However the implementation of both the DMA and the NDMF, has been fraught with
constraints and challenges. This may have led to the review of the Disaster Management Act, which is
currently on-going. Some of the sections of the DMA that may be reviewed include the roles and
responsibilities of municipal disaster management centres. The review includes the focus on good risk
assessments, mapping and the development of strategies and planning including budgeting. The review
will further look at the format and structure and capacity of the institutions and other issues such as the
validity and extent of by-laws, the issuing of directives and the issue of disaster management volunteers
at local level needing to be reviewed. DMISA (2014) also recommend the disaster framework be
reviewed, especially the terminology which is used incorrectly and has cause some confusion as well
aligning the frames to the amended act.
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The Act and the Framework provided a change from disaster response to disaster reduction, prevention
and mitigation. The objective of the DMA is to integrate and coordinate disaster management, mainly
preventing and reducing the risks of disasters, to alleviate the severity, emergency preparedness, timely
and effective response and post disaster recovery. The Act further facilitates the decentralisation of
responsibilities for DRR-M to all levels of government and within national government departments,
with a focus on disaster risk reduction as part of local government core business (van Niekerk, 2011).
With the three tiers of government (national, provincial and local) all play a role in disaster risk
management which is coordinated through the National Disaster Management Centre (NDMC).
Figure 16: Structures and responsibilities of disaster management across all spheres of governance in South Africa as
mandated in the Disaster Management Act
According to the DMA, disaster risk management should adopt an integrated, multi-sectoral and multidisciplinary method of decreasing risk associated with hazards and vulnerability, making it key in the
development planning process, especially for local government (van Niekerk and Visser, 2010). The DMA
further highlights the ideal structures essential to respond to DRR-M within the three levels of
government (figure 16) and the intention to include ‘at risk’ communities, as well as the private sector,
parastals entities such as the utilities companies, research and academic institutions, as well as NGOs
and traditional leadership (van Niekerk, 2011). In terms of decentralisation of disaster reduction
activities, the Act provides comprehensive information on the establishment of disaster risk
management centres and inter-governmental structures. Both the DMA and the NDMF place emphasis
on the creation of appropriate institutional structures of DRR-M to support the various actions and
actors that need to be involved. However the adoption of an integrated multi-sectoral approach has
been problematic, with a lack of understating of the core issues of DRR-M and poor coordination being
cited as challenges
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Other instruments addressing disaster risk reduction in mainly the agricultural sector include the
Agricultural Disaster Risk and Management Plan (ADRMP), the Agricultural Flood Management Plan,
Agricultural Cold Spells Management Plan and the Agricultural Veld Fire Management Plan. All these are
at different levels of development. The ADRMP is meant to provide a sector specific framework to
address disaster risk management in the agriculture, forestry and fisheries sectors, with a focus on
climate change (DEA, 2013). The plan seeks to reduce, prevent and mitigate disaster risk, while
strengthening capacity and preparedness for active disaster response. The plan further pays attention to
disaster risk reduction with economic loss and damage of property targeting mainly the agricultural
sector. One of the key objectives of this plan will be the development of adequate, reliable and easily
accessed EWSs, which will be part of DRR-M (DEA, 2013).
The Drought Management Plan of 2005 is another instrument addressing disaster risk reduction. The
plan identifies the physical and social vulnerabilities, as well as providing spatial information of drought,
rangelands and vegetation, for informed decision making by the farming communities. The plan acts as
an early warning for risk reduction, including preparedness, mitigation, response, recovery and
rehabilitation (DEA, 2013). The key performance areas for the drought plan have a key focus around
institutional arrangements for disaster management in all three tiers of government as well disasters
risk assessment and reduction. The plan also mentions the declaration of disasters and response and
recovery. The drought policy is still under development. Some of the legislative instruments do not
directly link to climate change or its impacts, but they do address issues pertaining to disasters risk
reduction and management and early warning.
4.2.
Mandate of the National Disaster Management Centre
At national government level, the National Disaster Management Centre (NDMC) has the mandate to
create the required institutional activities for integrated and coordinated disaster risk management,
focusing on prevention and mitigation at all levels of government including legislative functionaries,
other role-players involved in disaster management and communities. Other objectives include building
and enhancing capacity as well as accountability of provincial and local municipalities as they perform
their constitutional mandate according to the DMA as well as forestall and respond to disasters. The
NDMC’s mandate is to enhance the general resilience of communities and infrastructure to disaster risk
as well as reinforce the capacity of other levels of government, in disaster response.
A technical forum, the National Disaster Management Advisory Forum (NDMAF), which includes all the
players from government to communities involved in disaster risk management, was established in
2007. The forum has been instrumental in the establishment of the Technical Task Teams (TTTs), for
areas of work that need to be done on different types of hazards for example disaster response, fires,
and energy related disasters (NDMC, 2006). The forum is also plays a key role in disaster risk reduction,
in accordance with the Hyogo Framework, and facilitates the discussion of other cross cutting matters
regard DDR. In essence, the NDMC is responsible for guiding and developing frameworks for
government’s disaster risk management policy and legislation, facilitating and monitoring their
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implementation, and facilitating and guiding cross-functional and multidisciplinary disaster risk
management activities among the various organs of state (NDMC 2006).
Some of the established centres are reported to be fully functional and with disaster plans in place.
Further, other disaster management centres have been established at metropolitan and district
municipalities, while there are no clear guidelines of the establishment of centres at local municipalities
(van Niekerk and Visser, 2010). This decentralisation of disaster risk means that each municipal centre
should have in place, a disaster risk management policy framework, an advisory forum, and a disaster
risk management committee (van Niekerk and Visser, 2010). Municipal disaster risk management
centres develop or compile disaster risk management plans which are then integrated into the
Integrated Development Plan (IDP) for the municipality which is a very important statutory document.
This addresses calls within South Africa to mainstream DRR-M in local government planning, which will
also assist access to funding for DRR-M (SALGA, 2013). It is important to note however that some of
these disasters centres are usually poorly capacitated in many areas and are often dysfunctional.
4.3.
Existing DRR-M systems
South Africa has various DRR-M systems in place, which are supported by legislation and these include
the EWS available in the country (see chapter 5). While most of the systems are established at national
level, different district, local, metropolitan and communities have established or are carrying out DRR-M
activities in their respective places and some of these will be discussed below.
National Disaster Management Information System
To assist with its mandate of disaster risk reduction, the NDMC established the National Disaster
Management Information System (NDMIS). The system is meant to be all-encompassing IT solution that
relates to various aspects of hazard analysis, vulnerability assessment, contingency planning, reporting
systems as well as EWSs (NDMC, 2011). The main priorities of the NDMIS are related to:
 the establishment and improvement of EWS
 the subsequent dissemination of these warnings;
 the establishment of risk and vulnerability profiling, moving towards the establishment of a
National Indicative Risk Profile;
 building of a GIS Portal with the aim of disseminating relevant information to key stakeholders
are as required by the Act.
The NDMIS aspects related to communication, contacts management database, document
management, system work flow, event and incident reporting, and planning and resource management
are expected to be rolled-out to disaster management stakeholders end of 2012-2013 (NDMC, 2011).
There has been no indication from the NDMC whether this roll out has happened or if the information
system is functional.
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Working on Fire
The National Veld and Forest Fire Act, 1998 (Act 101 of 1998) provides a variety of mechanisms,
institutions, methods and practices for the prevention, combating and management of veld, forests and
mountain fires in South Africa. These include the formation of Fire Protection Associations, which are
voluntary organisations comprising of land owners responsible for the prevention, suppression and
management of veldfires in their areas of jurisdiction. Fire management entails 3 key activities:
•
•
•
Suppression of wild fires
Implementation of control burns
The preparation of firebreaks.
Working on Fire (WoF), a programme of the Department of Environmental Affairs is mandated to
implement integrated fire management in South Africa, which includes supporting the development of
the Fire Protection Association (FPA) structure under the National Veld and Forest Fire Act of 1998. WoF
also assists with the development of fire protection measures, reduction of fire hazards, improved
veldfire control, the implementation of appropriate veld management strategies and the empowerment
of communities affected by fire. It is an amalgamation of national, provisional and local governments
with the private sector. To date, the programme has trained over 5000 fire-fighters both in the
prevention and suppression of fires (www.workingonfire.org, 2014; Vosloo & Frost 2006).
City of Cape Town Disaster Management
EWS forms part of the DRR-M system and this occurs at various scales and different levels of
government and metropolitan areas (see chapter 5), for example the Cape Town metropolitan area’s
disaster risk information system. The Disaster Risk Management Centre (DRMC) is a branch of the City
Emergency Services Department which in turn is part of the Safety & Security Directorate of the City of
Cape Town. The Disaster Risk Management office website contains information on a myriad of natural
and man-made hazards affecting the province and the different disaster centres in the province and
collaborates with the different district municipalities which have their own systems in place. The centres
runs various awareness programs on disasters and keep the public informed through the website
(http://www.capetown.gov.za/en/DRM/Pages/default.aspx).
4.4.
Identified gaps and opportunities for DRR-M systems
4.4.1. Legislation
One of the key challenges noted in the implementation of DRR-M is the varied interpretation of both the
DMA and the NDMF, especially among the disaster risk management officials. This includes some of the
wording in the Act such as ‘may’ or ‘must’, which cause confusion on what is mandated and what is not
in terms of the decentralised centres. A study conducted on the Act and the Framework (van Niekerk
and Visser, 2011) indicates that the wording may result in different interpretations as well, with the
opinion that all the actions indicated as ‘may’ should actually be ‘must’ do actions. Further, the
understanding of especially the core principles of disaster risk reduction at both the lower level centres
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and the line national government departments have also been cited as a challenge affecting
implementation. This understanding is essential given the multi- sectorial nature of DRR-M.
Another gap identified in the study by van Niekerk and Visser (2011) is that the Act is not explicit on the
roles and responsibilities of local municipalities when compared to district and metropolitan
municipalities, leading to ineffective DRR-M. This adversely affects the implementation of DRR-M and
disaster response at local municipality level. At national level, not all essential government departments
have implemented the required disaster risk reduction activities and no focal points for DRR-M have
been identified, despite this being required by the NDMF. This does not only affect the functionality and
effectiveness of the National Disaster Management Advisory Committee, but all the advisory
committees at lower levels. Further, the DRR-M function at local level, including district and
metropolitan are not properly funded giving the impression that DRR-M does not receive the attention it
should both at the legislation and at local level, resulting in local municipalities neglecting their
responsibilities (van Niekerk, 2011). This may be exacerbated by the limited capacity and understanding
of DDR-M, which if could be improved, together with the improved mainstreaming of DDR-M activities
at local level and reassess the existing funding mechanisms could assist with access to funding for DDRM.
4.4.2. Institutional
The placing of the National Disaster Management centre in the Department of Cooperative Governance
is not a new debate in South Africa, with suggestion that the NDMC should be in a politically influencing
department to influence the effectiveness of the centre, especially given that the NDMC plays a
coordinating role across various sectors (van Niekerk and Visser, 2011). The line ministry in which NDMC
is placed restricts the centre to function effectively and carry out its mandate or enforce the DMA and
the NDMF, and it also affects the other centres at lower levels of government. Further, the centre does
not have authority over other government structures which are declared as semi-autonomous under the
Constitution, thus implementation is problematic. This makes monitoring, evaluation, accountability and
transparency difficult to assess (van Niekerk and Visser, 2011). For example, there is limited evidence of
the inclusion of disaster risk reduction in the municipal IDP documents, despite this required by the
DMA and the Municipal Systems Act, and the presence of guidelines on the integration, but neither the
NDMC nor the provincial centres can enforce or support this (van Niekerk and Visser, 2011).
In terms of institutional structure, both the Act and the Framework do not have a strong institutional
basis. Most of the structures outlined in the Act and the Framework are not present in the centres and
where they are present, their functionality, especially at provincial and district level is inadequate (van
Niekerk and Visser, 2011). As a result, many district municipalities have not established the required
systems for DRR-M, including disaster management centres, advisory forums, interdepartmental
committees for cross-sectoral collaboration and integration of DRR in planning. At the national
government level, some of the line ministries do not have focal points and in some cases disaster risk is
assigned to junior officers who do not have the capacity to make decisions. DRR-M duties are not
incentivised, thus there is reluctance or lack of interest to implement them at local and government
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level (van Niekerk and Visser, 2011). This issue is critical and will hopefully be addressed during the DMA
review process.
The provincial, municipal and local disaster management centres, which were created as a result of the
decentralisation process, have also faced various challenges. The lack of capacity hinder the
implementation of DRR-M, including the lack of capacity at national and provincial government levels
(FCC, 2011) as illustrated in Table 7. Most of the provinces are at different stages of development as
illustrated by figure 17 which provides a progress to date for some of the provincial centres. The
challenges include constraints faced in terms of capacity at the different centre levels.
Figure 17: Functioning of Disaster Risk Management structures per province (Limpopo, Gauteng, Mpumalanga, North-West
and Northern Cape) (SALGA, 2013)
Table 2: Capacity challenges faced by the Disasters Centres in terms of fulfilling their Mandate at different levels of
government according to DMA
Government
level
Mandates from Disaster Management Act
(Act 57 of 2002)
Capacity
National
Disaster
Management
Centre

The national office is functional but requires
more human capacity.
Objective of the NDMC is to promote an
integrated and co-ordinated system of
disaster management, with special
emphasis on prevention and mitigation by
national, provincial and municipal organs
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Provincial
Disaster
Management
Centre
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Municipal
Disaster
Management
Centre
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of state, statutory functionaries, other
role-players including affected
communities.
Section 17 (1) gives NDMC the directive to
create a repository of disasters and
disaster management information.
Subsection (2) stipulates that they develop
and maintain an electronic data base and
take necessary steps to disseminate such
information to communities that are
vulnerable to the identified disasters.
Promote and support provincial and
municipal disaster management centres.
Section 28: the provincial government
should develop a Disaster Management
Framework consistent with the provisions
of the Act and the NDMF. This should be an
integrated and coordinated process
involving provincial organs of state,
provincial legislative representatives, NGOs
and the private sector.
Section 29: each province must establish a
disaster management centre. It should also
promote disaster related research in the
province, build capacity of local
stakeholders to prepare and respond to
disasters.
By 2008, five fully functional provincial
disaster management centres had been
established in the Eastern and Western
Cape, Free State, Gauteng and Limpopo
provinces.
Functional in all provinces however some
provinces such as the Western Cape and
KwaZulu Natal have advanced systems and
officials who also work with sector
departments.
Provincial centres require more human
capacity, technical equipment and funding
for training, capacity building and community
volunteer projects.
Section 42: every metropolitan and district
municipality must establish and implement
a Disaster Management Framework that
integrates all stakeholders in that district/
metropolis.
Section 43: all metropolitan and district
municipality’s must establish in its
administration a disaster management
centre for its municipal area.
Section 51: a municipal disaster risk
management advisory forum.
Section 53: A municipal disaster risk
management plan to be integrated as part
Functional in most metropolitans and district
municipalities. Require more human capacity
to ensure efficiency as well as funding and
training of disaster officials.
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community
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of the municipality's integrated
development plan (also noted in Municipal
Systems Act 32 of 2000, Section 26(g)).
Amendments to the Act propose that the
disaster management plans should include
disaster risk assessments, GIS mapping of
risk and reporting of disaster occurrence,
expenditure on response and recovery. It
also seeks to provide measures aimed at
risk reduction through climate change
adaptation and development of EWS at
local level. The amended bill seeks to
strengthen policy implementation at local,
district and metropolitan municipality.
Section 58: members of the community
who meet the prescribed minimum
requirements can apply to enrol as a
volunteer in the unit of volunteers of a
relevant municipality.
Local government authorities need to work
with stakeholders to establish a strategic
and operational partnership (including
communities at risk (NDMC, 2011).
Amendments to the act provide
regulations for education and training. It
also provides for the South African
National Defence Force and South African
Police Services to assist disaster
management structures.
All provinces have trained some community
members to be volunteers as stipulated in
the Disaster Management Act however these
numbers are often fewer than what would
be required per community/local
municipality. However a SALGA report
showed that in 2011, 72% of local
municipalities and 50% of district
municipalities did not have volunteer units in
place.
Apart from the lack of capacity in the disaster centres at the different level of government, other
essential skills such as engineers are limited and this consequently leads to delays in the implementation
of disaster focused projects.
Botha et al., (2011) found that in 2011, 50% of local municipalities in South Africa lacked disaster
management structures, while 68% of local and 25% of district municipalities did not have disaster
management advisory forums. The individual challenges faced in each of the provinces are summarised
in table 8. In these cases disaster management roles were often assigned to civil defence structures in
local municipalities resulting in the fire and police services becoming overburdened (Botha et al., 2011).
This could be attributed to the perception of some provinces and municipalities that they have no legal
standing in terms of the act and thus do not prioritise disaster management. Furthermore, the disaster
management function is not seen as a funded mandate (NDMC, 2011).
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Table 8: Challenges experienced by local, district and provincial municipalities with regard to disaster management
Province
Challenges
Eastern Cape
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Inadequate funding
Non-availability of a budget for disaster mitigation
Poor participation of stakeholders and communities due to the lack of coordination
of activities
Non-prioritisation of disaster management
Non-existence of disaster management units in sector departments
Guidelines for incorporating disaster management programmes and initiatives into
current activities has not been developed and implemented due to the poor
awareness of the impacts of climate change impacts
Disaster management focal points have not been identified
Risk-related information has not been incorporated into spatial development
frameworks
Free State


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
Limited financial resources
Municipalities do not budget for disaster risk reduction programmes
Local municipalities do not appoint dedicated disaster management officials
Lack of an Integrated Information Management and Communication system
Gauteng
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Lack of funding
Lack of budgets for disaster management
Lack of cooperation with local municipalities to establish and maintain advisory
forums
Lack of training of officials and councillors in basic disaster management
KwaZulu Natal
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Disaster management plans are not aligned with the IDPs
Municipalities do not plan and allocate enough resources for disaster management
Limpopo
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Incapacity of sector departments to deal with disasters when they occur
Lack of communication between stakeholders
Lack of funding
Lack of cooperation and commitment from local municipalities
Mpumalanga
No information available
North West
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
Northern Cape
Western Cape
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Lack of funding
Shortage of capacity with regard to monitoring, reporting and evaluation
Municipal IDP project do not address vulnerability indicators
Poor participation of key stakeholders during disasters
Lack of budgeting by sector departments
No sector departments disaster risk management plans have been submitted to the
PDMC
Poor reporting systems
Limited political leadership

Establishment of coordination forums
Establishment of an inter-departmental Disaster Management Committee which
could be addressed by creating more nodes for DRR-M
Identification of Disaster management focal points

Lack of capacity and funding
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Formalities, procedures and legislation delays post-disaster recovery
Lack of communication between NDMC, PDMCs and MDMCs
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4.4.3. Funding mechanisms for DRR-M
Investment in disaster reduction has not received adequate attention, not only in South Africa but
internationally, with most of the focus being put on disaster risk response and recovery. However, the
increasingly huge costs of disasters, the huge losses covered by insurance companies and the pressure
put on governments when dealing with post disaster recovery urges governments to reconsider risk
reduction (FCC, 2011). A study by the Fiscal & Finance Commission submission (FCC, 2012) on
alternative financing mechanisms for disaster management in the South Africa, found that since 2005
the funding focus has disproportionately been on post-disasters rather than on integrating funding into
development initiatives that reduce the risk of disasters happening. Thus funding disaster risk reduction
is becoming an important issue, especially integration into developmental programmes, for example the
municipal IDPs in South Africa. Earlier studies on disaster risk reduction in South Africa found that there
was no specific funding for DRR-M at local government level, and where they did exist, they were
reserved for disaster recovery (FCC, 2011).
The issue of poor funding has also been raised as a constraint in the implementation of DRR-M at local
and provincial level. DRR-M funding encompasses start-up costs for municipalities, disaster response
and recovery as well as continuous disaster risk reduction activities. According to van Niekerk and Visser
(2011), access to funding for DDR-M is a critical challenge for municipalities. Despite the availability of
funding mechanisms for various levels of government and the various DDR-M activities as outlined in
the framework (FCC, 2011), the funds have not been accessed or used. This could be possibly be
attributed to the confusion about the different mechanisms or probably due to a lack of knowledge
about the funding instruments available and how to access them. This confusion has been attributed to
a lack of clarity in the Act on funding mechanisms. Further, sector funding for DDR-M needs better
planning, including the development of good sector plans with implementation actions and timelines.
Further, given other priorities in the municipality such as service delivery, DRR is not considered a
priority, often getting minimum attention and budget allocation in terms of municipal budgets. In
addition, sectors need to access funds that are already allocated but understood as DRR funding. This
however, needs to be accompanied by good expenditure reporting. Therefore, the challenge of funding
in the implementation of the NDM Framework needs to be addressed.
Other identified gaps include:
 The lack of political will at mainly provincial and local government, with most emphasis being
put on disaster response and recovery instead of reduction.

The classification and the declaration of disasters as mandated in the DMA and the NDMF has also been
identified as a challenge. This lack of clarify affects even the declaration and classification of a disaster
when one occurs, often leading to duplication of efforts. Therefore there is a need to develop clear
guidelines for classification and declaration of disasters as well clear guidelines for funding mechanisms.
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The classification and understanding of what DRR means to each sector, and all levels, i.e. provincial and
local municipality needs to be made more explicit and discussed within sectors and advisory forums.

Both the Act and the Framework highlight the need for the development of uniform guidelines
for the assessment of disasters, but this has not happened (van Niekerk and Visser, 2011). This
renders the classification and declaration of disasters ambiguous. This sometimes results in
duplication of efforts between line ministries such as the Department of Social Development,
through its Fund Raising Act (No. 107 of 1978), and this sometimes results in duplication of
efforts, when both acts are used to respond to a disaster. Under the Fund Raising Act, a national
disaster can only be declared by the president, particularly where the affected communities
cannot cope. This highlights the need to align the DMA and the Fund Raising Act (van Niekerk
and Visser, 2011).
The development of national indicative disaster risk profiles as required by the framework using
a multidisciplinary and multi-sectoral approach has not been done. This hinders the
understanding of disasters, the planning and the budgeting for disaster risk reduction (FCC,
2011).
The involvement of the private sector in the financing disaster risk reduction, especially the
insurance industry has been limited. It has to be noted that the many requirements for Public
Private Partnerships (PPP) are costly for municipalities, hindering the cooperation with the
private sector.
Long lead times in transferring of funds when a disaster occurs, including the Municipal
Infrastructure Grant (MIG). Stringent conditions need to be met before the funding can be
channelled from the national budget to COGTA and eventually to the MIG fund. Further, the fact
that the MIG and other conditional grants do not explicitly fund DDR needs to be reviewed by
treasury. These funds could assist in the access of additional funding. In addition, the guidelines
for funding mechanisms at national and local level could assist in better access to funds such as
the green fund.




There is a general lack of capacity in critical areas such as engineering and other professional
skills. This may have an impact on the type of solutions devised for example at local level,
project focus has been on engineered solution rather than softer innovative solutions such as
ecological infrastructure that are not well-known or well-funded.
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4.4.4. Opportunities
Let’s Respond Toolkit
In terms of the legislation and policy instruments, opportunities do exist to amend the existing DMA, not
only to address the issues that have been raised over the years on the gaps to implement the Act, but to
also align the DMA with other sectoral legislative instruments that are under development. This would
assist in the removing or reducing of duplication of roles and responsibilities for disaster risk in the
different sectors as well to incorporate climate change adaptation. This is currently being addressed in
the amendment bill.
The Let’s Respond Toolkit (Figure 18) is a tool that is designed to assist local government to integrate
climate change response in the development process through the Integrated Development Plans (IPDs).
The Let’s Respond Toolkit was developed in collaboration with DEA, SALGA and COGTA and supported
by Sustainability Energy Africa and funded by GIZ. The toolkit presents municipal managers with
opportunities to include climate change in their everyday activities.
Figure 4: Let’s Respond Toolkit
The toolkit provides a step by step guide for climate change response which is aligned to the IDP process
(see figure 19), includes the integrative steps needed and the expected outputs. The Let’s Respond
Toolkit aims to align local level climate response with existing environmental and development
challenges, and develop knowledge flows by engaging with research institutes. The step by step
approach ensures that climate change planning is conducted at all levels of IDP planning, and at spatial,
sector and departmental levels, and to improve cross sector integration (SALGA, 2010).
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Figure 5: Step by step approach to integrate climate change in the IDP process
The first and second steps of the toolkit which involve the preparation and the analysis include capacity
building of municipal staff on climate change and its impacts and the identification of key focal people in
the municipality to lead the process. The analysis phase includes the preparation of climate change
vulnerability assessment and disaster management plans. These two aspects of the toolkit are beneficial
for disaster risk reduction, by not only identifying communities at risk but helping them and the local
government prepare for disasters. However, the roll out of the Let’s Respond Toolkit has been slow, and
the outreach is on a small scale to date. Despite this, the Lets Respond Toolkit presents an opportunity
to align DDR-M and adaptation activities, in addition to planning for climate change, in terms of the
institutional mechanisms already in place for the climate change and IDP processes being adapted for
DDR-M activities at all levels of government.
Working on Fire
Another opportunity for the improvement of DDR-M activities is presented by the Working on Fire
(WoF) programme mentioned above as an existing DDR-M system. WoF, which was established 10 year
ago employs more than 5000 young men and women, who have been fully trained as forest fire fighters
and are posted in approximately 200 teams across the country. While the focus on WoF is the
prevention of and control of wild land fire, with the aim of improving sustainability and protection of
life, property and the environment through Integrated Fire Management (IFM) practices. At least 24% of
the total budget for WOF is devoted to training. WOF already plays an important part in the reduction of
disasters from veldt fires, and an opportunity exists to utilise the institutional mechanism in place to
extend disaster risk activities to other weather related events.
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Figure 20: Some of the over 5000 youths employed by Working on Fire
There is also an opportunity to adopt what seems to be a successful business model for WoF to DDR
activities, with the involvement of all levels of government, and especially the involvement of the
private sector dealing with disasters risk reduction, for example insurance companies. Part of the
success of the WoF seems to be the involvement of the private sector and as noted on their website
they have many partners including National Disaster Management Centre.
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5. Climate information and Early Warning Systems in South Africa
South Africa has adopted the Multi Hazard Early Warning System (MHEWS) which makes use of multiple
monitoring systems and uses meteorological, hydrological and climate information to prepare and
respond to the multiple hazards. Hazards included in this system are floods, heavy rain, wild fires, storm
surges and wind storms (SAWS, 2012). The NDMC is mandated in the National Disaster Management
Framework to be the custodian of MHEWS. Extreme weather events challenge the ability of
governments to meet their development objectives as some hazards often result in fatalities,
displacement of communities, severe disruption and infrastructure damage (Twigg, 2004). Therefore
MHEWS requires collaboration between disaster management structures at all levels of governance i.e.
national, provincial and local level to plan and respond together. Weather advisories, watches and
warnings from the EWS inform stakeholders at different levels of government, NGOs and the
communities at risk to prepare for impending hazards.
Poolman (2012) noted that generally there is a good relationship developing on coordination and
dissemination of early warnings between SAWS which is the custodian of weather and climate
information, the National, Provincial and Municipal/Metropolitan Disaster Management Centres. This is
illustrated by the effort that SAWS has put in palce to ensure that the disaster management centres are
provided with severe weather warnings and advisories ahead of time, so that they can plan and respond
accordingly.
5.1.
Existing Weather and Climate Information and Early Warning Systems
The responsibility of producing weather and climate information as well as giving early warning
information alerts is the responsibility of SAWS, as stipulated in the Weather Service Act (RSA, 2001).
SAWS is the main source of early warning information, feeding information to various metropolitan
municipalities and other government sectors. SAWS is mandated by law to earn income for the provision
of commercial services and thus has both a public and private role in producing and disseminating
weather forecasts and warnings. SAWS is likewise the custodian of the South African climate databank
and the Severe Weather Warning System which forms part of MHEWS (SAWS, 2012; Makuleni, 2011).
SAWS EWS is based on international best practices and maintains the standards of the World
Meteorological Organisation and International Weather Services (Poolman, 2012).
SAWS collects weather and climate information from the following:
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20 Regional weather offices
130 Automatic weather stations
112 Climate stations
1512 Rainfall stations (Makuleni, 2011)
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SAWS produces different types of forecasts as illustrated in figure 21, which also shows the different
sectors that make use or could benefit from the forecasts and the tools used to get these forecasts.
Seasonal forecasts, if carefully targeted, can be a useful tool for reducing the risks related to seasonal
climate extremes such as floods and droughts (Mason 1998; Ropelewsky & Halpert 1989). The
Standardised Precipitation Index (SPI) has been successfully used as an indicator of drought conditions.
The SPI is also used to assess the severity of a drought – the higher the negative number the more
severe the drought (McKee et al. 1993). The Drought Monitoring Desk at SAWS provides information on
long range seasonal forecasts, observed rainfall as well as maps of SPI. Predicting extreme climate
anomalies in advance for the coming season, offers disaster management authorities the ability to
prepare and respond in time. In southern Africa, seasonal rainfall forecasts have been made for almost
two decades and these forecasts were developed to improve the ability of users to cope with
fluctuations in rainfall on a seasonal time scale.
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Benefits
Tools
Products
Tools
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Figure 21: SAWS forecasting system (SAWS CEO Dr Makuleni, 2011)
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5.2.
Interpretation, Disseminations and Packaging
As previously mentioned, SAWS feeds information to the disasters centres, different government
departments, including the communities in need of this information as highlighted in figure 22 which
outlines how early waning information is disseminated from SAWS to disaster centres, municipalities
and the public. The advisories, watches and warnings are issued by SAWS through the web, or the
printed or electronic media or are sent by SMS to disaster managers. This includes climate information
such as seasonal weather forecasts.
Figure 22: Flow of information from SAWS to DMC at the national, provincial and municipal levels; and the public through
the web and media channels (SAWS CEO Dr Makuleni, 2011)
5.2.1. Institutional Collaboration
SAWS also work with other institutions, both government, private, community and research to produce,
interpret, package and disseminate climate information and advisories for different hazards and
extreme weather events to the affected and interested stakeholders. Table 9 shows the research
institutions (mainly CSIR) and the type of early warning information they generate.
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Table 9: Research institutions involved in interpretation, packaging and dissemination of early warning and climate
information
Institution/Programme
Hazard
Interpretation and packaging
Means of dissemination
CSIR Meraka InstituteAdvanced Fire Information
System
Fire
The fire monitoring is used to
locate fires in near-real time over
southern Africa and prevent loss
of exposed human life,
biodiversity, settlements and
infrastructure.
CSIR Meraka Institute Wide Area Monitoring
Information System
Fire,
floods
and
drought
Seasonal Forecasts (CSIR
and SAWS)
Floods
and
drought
Interpret fire, flood, and drought
information collected from
satellite-based information
services. They provide near realtime monitoring and mapping
capabilities of natural events in
Southern Africa.
The most commonly used way to
visualise seasonal forecasts is to
display them on maps that show
the likelihood of predicted rainfall
and temperature anomalies
exceeding certain predetermined
thresholds. These thresholds are
th
typically terciles values or the 15
th
and 85 percentile values of the
climatological record. The latter
thresholds are being used to
predict whether or not a coming
season will be extreme.
Fire maps are broadcast to the
public weekly as part of the
television weather bulletin on
SABC channels (Frost, 2011). Fire
location information from AFIS is
also distributed through email,
Twitter, XMPP (e.g. Google Talk,
jabber.org, etc.) and cell phone
text messages worldwide (CSIR
AFIS, 2012).
WAMIS data portal that displays
and makes available some MODIS
products. For example one can
download the burned area data,
the active fire text files as well as
download the true and false
colour composites in GEOtiff.
Forecasts are usually issued for a
period of six months and suggest
the total amount of rainfall
expected over that period, but
not the distribution of rainfall
within that period or the
initiation of the rainy season
(Landman et al. 2011). Forecasts
are issued by SAWS and through
the annual SARCOF meeting as
well as posted on the South
African Risk and Vulnerability
Atlas Portal.
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Western Cape Province Case Study
The Western Cape Province is prone to numerous natural hazards such as floods, wildfires and droughts (Raju
and Van Niekerk, 2013). The climate is expected to change to the extent that the annual average temperature
will increase by 1°C by 2050; rainfall is likely to decline with a resultant decrease in available water sources and
soil moisture; the frequency and intensity of extreme weather events will possible increase; and the risk of
wildfires will increase as well. These will negatively impact on crops, infrastructure, the coastline, the built
environment, tourism, etc. (Western Cape Province, 2008).
As a coordinating function, Western Cape Disaster Management maintains an early warnings database and
disseminates warnings to relevant stakeholders (i.e. district heads of centres and other relevant provincial
departments) via email and/or SMS. These warnings are largely for weather related hazards received from the
South African Weather Services via email and/or SMS. The informed officials are required to disseminate the
warning where applicable, prepare and act accordingly. The Western Cape also makes use of fire and flash
floods EWSs, but no details about these systems were made available (Nicole Wagner, Western Cape Provincial
Government, personal communication, 14 January 2014).
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5.2.2. Links with other government departments
The National Disaster Management Centre also collaborates with other national and provincial
departments that have programmes and projects aimed at early warning and assisting victims of hazards
with recovery when a hazard occur (table 10). The next section looks the different national and
provincial departments and their roles. It is important to note that while most of the government
departments, with the exception of DWA, Department of Energy and Department of Science and
Technology, do not produce any early warning information , that use early warning information in ther
operations.
Table 10: Government department linkages with DDR-M and Early Warning Systems
Government
Department/institution
Mandate
National Agro Meteorology
Committee
National Agricultural Disaster
Management Forum (NADMF
National Drought Task team
National Agricultural Disaster
Risk Management Committee
Department of Water Affairs
Interpret data on early warning for the agricultural sector
Department of Agriculture,
Forestry and Fisheries
Department of Health
Has three policy documents i.e. Agricultural Disaster Risk Management Plan,
Climate Change Sector Plan and the Drought Management Plan (NDMC, 2009)
The Emergency Medical Services and Disaster Management Directorate – focus
Advise and decide on disaster intervention strategies and procedures.
Advise the NADMF on drought related issues
Advise the national department on disaster risk management.
Responsible for the flood management of the Vaal and Orange River Systems
(Maswuma 2011). Real time flow data is collected and disseminated by the
Department.
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Department of Energy
Department of Human
Settlements
Emergency Housing Policy which assists victims of disasters by providing them
with temporary shelter, providing access to land and basic municipal engineering
services by providing grants to affected municipalities. Provincial Disaster
Management Centres together with Provincial Human Settlement departments
manage the provincial disaster response (NDMC, 2011).
Department of Public Works
Though not weather or climate related the department focuses on dolomite
disaster. They have a Dolomite Risk Management Strategy and conduct
awareness raising workshops for vulnerable stakeholders that occupy dolomitic
land (NDMC Annual Report, 2011).
Department of
Communication
Department of Science and
Technology
DST & DGLG
Supports ICT on weather and EWS, response and recovery
The South African Earth
Observation Strategy
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Use of early warning information as power supply often affected by extreme
weather events such as floods, storms and strong winds.
Have an EWS for nuclear power and the Radiological Emergency Monitoring
Working Group responsible for monitoring and development of an action plan to
prevent any radioactive contamination.
Financially support a number of students to enrol for a post-graduate course in
Disaster Risk Management at the Free State University. The course curriculum
includes EWS and disaster management
Captures South Africa’s response to the Global Earth Observation Systems of
Systems (GEOSS) coordinates the collection, assimilation and dissemination of
earth observation data to support planning, decision making in South Africa
(NDMC, 2008).
South African Risk and
Vulnerability Atlas
Has a portal that provides the public with free access to a large collection of
scientific data and knowledge in about global and climate change related
vulnerability, risks and impact. The project has a dedicated climate and weather
information theme page where climate information ranging from weather, to
seasonal forecasts, to dynamically-downscaled climate projections from SAWS is
interpreted.
Department of Safety and
Security
The South African Police Service (SAPS) has developed a disaster management
strategy, disaster management policy and a contingency plan in line with the
DMA and the NDMF. SAPS Disaster Management Strategy will be rolled out to all
provinces(NDMC, 2009).
5.2.3. Community response
The NDMC is mandated in the DMA Section15 (1) (g) and (h) “to promote the recruitment, training and
participation of volunteers in disaster management and promote disaster management capacity
building, training and education throughout the Republic, including in schools” (RSA, 2002).
Coordination between local institutions needs to be strengthened so as to reduce the vulnerability of at-
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risk communities. Various government departments at national, provincial and local level engage in
different community outreach activities which include the following:
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The Extended Public Works Programme Working on Fire which encourages public participation
in responding to fires and provides local community members with fire management training,
firefighting and record keeping.
Department of Agriculture, Forestry and Fisheries (DAFF) conducts a myriad of awareness
programmes targeted at farming communities to provide farmers with knowledge on their risks,
disaster preparedness and response strategies when an alert or warning is given.
Western Cape: the City of Cape Town is proactive in disaster risk reduction and is working
together with neighbouring municipalities, private sector, organs of state and communities
through mutual assistance agreements on early warnings, response and recovery. Community
members are encouraged to inform authorities of any imminent threats such as blocked drains
and storm water systems. Community awareness includes providing residents at risk with
pamphlets in IsiXhosa, English and Afrikaans with tips on how to raise their floor levels, divert
flood water and reduce health hazards that result from stagnant water (Hweshe, 2012).
Swartland Municipality has developed an EWS which is shared with the City of Cape Town as
heavy rains in the municipality can result in the flooding of the Diep River and affect residents of
the Du Noon’s Doornbach informal settlement (Hweshe, 2012).
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Eden District Municipality case study
Eden District is plagued by both floods and droughts. These events have a severe impact on the economy,
tourism, the environment and local development, and the district has been declared a disaster area at numerous
occasions (Raju and Van Niekerk, 2013).
Eden Municipality subscribes to the SAWS EWS and receives all its information about weather watch and severe
weather events from this system. Combined with information received from automatic rain stations, and
information about the flow of the rivers and the level of dams, action is taken by die District and warnings and
alerts are sent out to the public, councils and councillors. An early warning display system, designed by the Eden
Municipality and funded by SANTAM, was installed to warn and alert the public of severe weather. It may also be
used for brief notifications of community meetings or other public alerts. This LED display system is linked to the
Eden Disaster Management Centre in George from where information is uploaded on the early warning display
units (Eden District Municipality Disaster Management Centre, n.d.).).
As part of the EWS, the Eden District Municipality also sends bulk
SMS warnings about severe weather to the various municipal
disaster management advisory forums as well as to councillors of
the affected wards. Such councillors are in the best positions to
ensure the warnings reach citizens (Gerhard Otto, Eden District
Disaster Management Centre, personal communication, 14
January 2014Eden Municipality also subscribes to the Advanced
Fire Information System (AFIS), an EWS that alert users of any risk
of wildfires (Gerhard Otto, Eden District Disaster Management
Centre, personal communication, 14 January 2014).
Photo depicting an early warning display sign in George that says “22 Aug, Thu 16:23, Severe weather warning
display”
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Community response also includes the uptake of weather and climate information by the public and
using it together with their indigenous knowledge to increase the resilience and diversity of their
livelihoods by engaging in appropriate community adaptation projects. The Department of Agriculture
Forestry and Fisheries has been working on improving uptake of weather and climate information by
packaging and translating the information into easy understandable messages for the communities.
Other known initiatives include:
 The City of Tshwane developed a disaster management primary school guide pack to raise
awareness in schools.
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5.3.
Disaster Mitigation for Sustainable Livelihoods based at the University of Stellenbosch engages
in community risk reduction work that can be used by local authorities to plan and respond to
disasters.
Climate advisories and Early Warning Systems to support DRR-M
SAWS Severe Weather System covers potentially damaging weather events (e.g. heavy rain, heat waves
and cold weather) that are common in the country and can result in severe impacts. National warnings
and advisories are compiled and issued with the longest possible lead-time. SAWS operate a MultiHazard EWS (MHEWS) which requires closer cooperation with disaster management structures at
national, provincial and local level. Severe weather hazards include extremely hot conditions, heat
waves, very cold conditions, snow, heavy rain, flash floods, destructive coastal waves, veldfire danger
rating, gale force winds and stronger, and severe thunderstorms. The weather alerts, which form part of
SAWS Multi-Hazard EWS (MHEWS), are based on 4 levels (see Figure 23):
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No alert: no hazard is expected.
Advisory: a potential hazard may occur in the next 2 to 6 days.
Watch: hazardous weather is likely to occur in the next 1 to 3 days.
Warning: hazardous conditions are occurring or are about to occur in the next 1 to 24 hours
(SAWS 2010).
These alerts are issued by SAWS and are used by Disaster Management Centres in preparation and
readiness for emergency actions such as evacuation in the face of the hazard. The alerts are also issued
directly to the public through the media, internet and cellphone service providers.
Figure 6: South African Weather Service Severe Weather Alerts
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Floods
SAWS is primarily responsible for the forecasting of flood producing rainfall, which is based on
mathematical weather models, geostationary satellite images and radar observation stations (Du Plessis
2004). EWSs for flash floods were initially based on the projected impact of heavy rain over a wide area
but these warnings were not sufficient for high risk areas such as small river basins. Consequently, SAWS
and the NDMC developed the South African Flash Flood Guidance (SAFFG) system (Coning & Poolman
2010) which provides guidance on potential flash flood watches and warnings within 1 to 6 hours. It
models the likely hydrologic response of small river basins to rainfall and estimates how much rainfall is
needed to cause flooding. The Flash Flood Guidance System was utilised to inform warnings on the
Gauteng flash floods which occurred in 2010 (See Box 1 and Figure 24). Warnings were issued to the
NDMC, including an hourly breakdown (Figure 25). Other decision-support tools include the Severe
Weather Forecasting Demonstration Project, which forecasts the intensity and movement of rainfall
events and severe winds across southern Africa (Poolman et al. 2008). It is important to add that DWA
uses river flow gauges and river flow measurements in combination with rainfall information from SAWS
to determine the timing of the opening of dam gates to release water during high rainfall events. There
is collaboration between NDMC and DWA in dealing and handling disasters related to water issues.
Box 1: Gauteng flash floods 15-16 December 2010
Over 133 mm of rain fell overnight in Gauteng and severe flash flooding occurred, which resulted in a few
fatalities, people being displaced and severe disruption and infrastructure damage. Forecasters issued flash
flood warnings throughout the night initially for southern Gauteng and later central and northern Gauteng.
Warnings were disseminated by SMS to disaster managers in the relevant municipalities and metropolitan
areas.
Figure 7: Snapshot at 06 hr SA time of basins where flooding were expected
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Figure 8: Hourly breakdown issues by SAWS for the floods
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Droughts
An Agricultural Drought Management Plan was drafted in 2005 and seeks to reduce the impacts of
droughts by providing information management, monitoring and evaluating systems for the early
warning of droughts (DEA 2013). Another example of a drought EWS is the Umlindi system developed by
the Agricultural Research Council (ARC) which provides information on drought conditions based on the
interpretation of satellite and climate data. This information is translated and packaged and by DAFF
into monthly newsletters with understandable key messages. The information is also used for crop
estimation by the National Crop Estimate Committee (NCEC) and is also disseminated through the
provincial departments, the National Agro-meteorological Committee (NAC) and subsequently to the
farming community. Experimental work is also currently under way through a partnership between ARC,
CSIR and the University of Pretoria which will start adding a suite of tailored forecasts for livestock.
Fires
The National Veld and Forest Fire Act provides for the prevention of fires through the development of a
National Fire Danger Rating System (NFDRS), launched in 2005. The NFDRS is an early warning system
for predicting conditions conducive to occurrences of veldfires. This tool is aimed at increasing the
capacity of Fire Protection Association’s, veldfire managers and municipalities to manage veldfires
appropriately by being aware of the likelihood of fires occurring beforehand (Willis et al., 2001). The
system gives out the fire danger index by taking into account variables such as the weather and fuel
factors. When predictions indicate that the fire danger rating will be high or extreme, a warning will be
issued to the Fire Protection Associations and Disaster Management Centres and to the public through
television, radio and local newspapers. SAW is responsible for issuing the warnings.
In partnership with Eskom, the University of Maryland and NASA, the CSIR developed the Advanced Fire
Information System (AFIS) to locate fires in near-real time over southern Africa (Frost and Annegarn
2007; Davies et al., 2008).
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Australian case studies
1
Australia is home to a diverse number of climatic regions, and thus experiences various extreme weather
events such as drought, prolonged periods of extreme temperatures (heat waves), bushfire, cyclones and
floods. It is projected that the severity of these events will increase in future as a result of climate change with
huge damage to infrastructure and the economy. Australia has therefore implemented a number of early
warning systems, of which two are described below (Chhetri et al., 2012).
The Early Warning Network (EWN)
The Australian Early Warning Network (EWN) provides geographically targeted early warning services,
technology and systems for all severe weather and natural hazards. The system monitors potentially
dangerous incidents and alerting people directly in danger of severe weather such as hail, flash floods,
damaging winds, fires, and tsunamis. It is based on a person’s registered or physical location at the time and is
communicated via email, SMS, landline, fax, web, twitter, facebook and desktopALERT™. Only subscribers in
the area at risk are warned, based on the longitude and latitude of their mobile phone at that time, or
otherwise their registered physical address (The Early Warning Network, n.d.).
The Wildfire Management Overlay (WMO)
Bushfires have a significant impact on lives, income, human settlements, the economy, transport and
infrastructure in southern Australia. The total direct cost of bushfires has been estimated at $AUD 4 billion
with infrastructure and the economy taking months to normalise. As the climate changes, the frequency and
intensity of wildfires in Australia are growing. The Wildfire Management Overlay identifies areas as Bushfire
Protection Areas and Bushfire Prone Areas, and formulates Bushfire Risk Management Plans at local
government level. In its prevention and preparedness campaign, WMO ensures that buildings in in the
Bushfire Prone Areas include appropriate fire protection measures and does not significantly increase the
threat to life and property from wildfire (Chhetri, et al., 2012; Hughes and Mercer, 2009).
The WMO also detects areas where the risk for wildfires is most considerable and can cause danger to life and
assets and alert people. The ‘stay or go’ policy was revised to a ‘prepare, stay & defend, or leave early’ policy
and social media is used more often as early warning tools (Chhetri, et al., 2012; Hughes and Mercer, 2009).
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Storm surges
As part of the National Storm Surge Workshop held in Knysna in 2011 “Guidelines for a storm surge EWS
for South Africa” (Stander 2011) were developed. This document sets out key elements in the design of
a new National Storm Surge EWS dealing with the necessary monitoring for an operational warning
system, and the dissemination of the appropriate alerts to vulnerable communities. These guidelines are
utilised by the NDMC and local municipalities when dealing with the extreme climate events in coastal
zones. The storm surge alert process for South Africa is outlined in Figure 26.
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Figure 9: Storm surge alert process (Stander 2011)
Real time observations of the state of the marine environment (e.g. wind and wave data) are provided
through the activities of the South African Navy Hydrographic Office (SANHO), the CSIR for the National
Ports Authority, and the Marine Office of the South African Weather Service, which include the
Automated Weather Stations (AWS), the drifting weather buoy programme, Ships of Opportunity (VOS),
as well as related information from satellites and numerical models. These observations enable the
forecast of extreme conditions at sea and along the coastline of South Africa and provide information
for the issuing of storm surge alerts (Rossouw et al., 2011). Additional maritime weather is available
from international weather institutes such as the National Weather Service of USA.
SANHO is responsible for the installation and maintenance of tide gauges in the principal harbours of
South Africa as well as the acquisition, processing, archiving and dissemination of sea level data from
these tide gauges (Rossouw et al., 2011). The CSIR Coastal Systems is responsible for the installation and
maintenance of wave recorders as well as the collection of the data. Numerical wave models (e.g.
SWAN) are used to provide wave information for locations where no buoys are located (Booij et al.,
1999). The SAWS Coastal Network System provides weather and warning forecast services for the
Southern African oceans (Rossouw et al., 2011). As previously mentioned, SAWS is responsible for the
dissemination of weather alerts to all the primary role players outlined in Figure 21.
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5.4.
Identified gaps and opportunities in current climate information and EWSs
This section will highlight key challenges which need to be addressed in order to improve adaptive
management as well as the opportunities that exist.
5.4.1. Legislative, institutional and mandate issues
Challenges faced at the national, provincial and local government level
There are currently significant challenges in disaster risk reduction at the local and provincial
government level (see chapter 4) (Botha et al., 2011; Zuma et al., 2012) and the approach to disasters
still remains a very reactive process (Du Plessis, 2004). Despite the existence of the DMA and the NDMF,
evidence from various parts of the country shows that the implementation and uptake of early warning
information remains slow. Provincial offices of DAFF remain incapacitated and constrained because of
the lack of structure and defined roles of individuals (NDMC, 2011).
Effective dissemination of warnings to all levels of society remains a challenge and requires support and
participation with the local disaster management structures and the media (SAWS, 2011). Currently,
extension services do not play a significant role in the dissemination of warnings. A study conducted by
Ngaka (2012a) found that only 11% of the people interviewed accessed information from the extension
officers compared with radio at 70%. Extension officers have huge potential to play an integral part in
disaster risk management but this requires sustained effort by local and provincial government and
continuous training and support. Another area of concern is the lack of communication materials to
raise awareness and mainstream disaster risk reduction at the local level (SALGA, 2013). This is
something that is often being addressed by NGOs but needs serious up-scaling across all municipalities.
The Let’s Respond Toolkit currently being mainstreamed in the country seeks to integrate climate
change into an existing planning process (IDPs) rather than create a separate process altogether, given
the human capital and financial constraints at municipal level. The toolkit is also raising awareness at the
local municipality level of adaptation responses.
Another key challenge facing disaster response is the lack of communication between various
governments departments involved with disaster management (Raju and Van Niekerk 2013). One of the
primary reasons for this is that disaster risk reduction is not seen as a priority for local planning and
development. Neither the NDMC, nor the SAWS can provide any information on the extent their EWSs
are being used by other spheres of government. They admit that they make their EWSs and data
available, but do not know the impact of their systems on provincial and local government and are
therefore somewhat removed from what happens in practice. The NDMC is in the process of doing
studies to determine the impact of the EWSs on disaster risk reduction (Eugene Poolman, SAWS,
personal communication, 9 January 2014; Mark van Staden, NDMC, personal communication, 13
January 2014).
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Lack coordination and collaboration between institutions
There is currently insufficient communication and collaboration between organisations that provide
climate services and EWSs. Competitive groups exist in the country for providing these services and the
legal framework, and do not provide the means for local or international informal systems to feed into
the framework. Information sharing between institutions needs to be strengthened in order to facilitate
early action to severe weather events. Furthermore, the modelling, monitoring and predicting capacities
at institutions across the country have the potential to contribute to advances in EWSs but this is often
limited by the limited by the translation of information into DRR-M strategies.
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5.4.2. Technical issues
False alarms
As EWSs and advisories grow and develop, so does the number of false alarms. High incidences of false
alarms can lead to community mistrust and could impact the credibility and effectiveness of future
warnings. This emphasises the need for increasing community awareness and the ability of communities
to interpret climate information and warnings. In addition, the inclusion of reliable local hazard
indicators such as vegetation changes could verify the scientific warnings and thereby increase
community trust, as well as increase effective response
Seasonal forecasts
A key problem identified with seasonal forecasts is that there are large uncertainties in the predictions.
For example, weather forecasts for the next day may be predicted correctly nine out of ten consecutive
days, but for seasonal timescales, even during the mid-summer season of highest predictability, forecast
are typically correct only about three out of five summer seasons. There are also currently difficulties in
understanding forecast implications. For example, most of the seasonal rainfall forecasts are typically
presented in rainfall categories representing probabilities for the highest, middle and lowest third of
seasonal values to occur. Even when seasonal predictions are understood properly, it may not be
obvious how to use them since the uncertainty in the predictions is very high and the predicted variable
may not be immediately relevant to an impact or decision. This notion does not imply that seasonal
forecasts cannot be useful. These problems simply emphasise the need for the development of tools
that can translate such information to quantities directly relevant to end-users, and thus for better
communication between modelling centres and end-users. Delivery and uptake of seasonal forecast
information is thus as substantial a challenge as the actual production of skilful seasonal forecasts
(Landman et al., 2011).
Many of the more widespread disasters (e.g. floods and droughts) are only simulated to a limited degree
by the coarse resolution GCMs, suggesting improvements may come through downscaling, running the
GCMs at a higher resolution (to capture the influence of topography) and improvements to the
simulated interactions between the land, ocean and atmosphere. Specifically for droughts, the
development of an effective early warning system is often challenging since droughts are slow-onset
disasters. The changing climate (through increases in anthropogenic emissions) needs to be
incorporated into seasonal forecast schemes as the baseline climate state is constantly changing.
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Modellers in the region are contributing to the international effort of improving models. Such modelling
efforts are also trying to address the prediction for time scales between that for weather forecasts
(typically seven days ahead) and seasonal forecasts, and between seasonal forecasts and multi-decadal
climate change projections (Landman et al., 2011).
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5.4.3. Social issues
Dissemination and interpretation of warnings
Effective dissemination of warnings to all levels of society remains a problem and needs significant
support and participation with other structures, including disaster management, media and other role
players. Even when warnings are disseminated effectively, there is still a lack of awareness in local
communities on the EWS and how to respond to these warnings (Du Plessis, 2004). This can be
attributed to the challenges faced with the interpretation and translation of climate information and
warnings at the local level. Approaches for combining traditional and indigenous knowledge with
scientific knowledge to strengthen climate information and warnings have been suggested in the
literature to increase community response (for example Stigter et al., 2005; Shaw et al., 2009). This
would increase acceptance, ownership and the long term sustainability of EWSs. There is currently no
mechanism in the country to integrate local knowledge and practises with those of the scientific
community. Mercer et al. (2010) propose a framework that could be used to successfully combine local
knowledge and scientific information for EWSs (Figure 27).
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Figure 10: Framework for integrating local knowledge and scientific information on early warning
(Mercer et al. 2010)
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Human capacity challenges
SALGA has identified areas within disaster risk management where skills are lacking (Table 11). For
example, there is a shortage of fire risk and firefighting skills in many municipalities which is currently
constraining Municipal Disaster Management Framework Enabler number 2 on education, training,
public awareness and research (SALGA, 2013).
Table 31: Identified areas of skills shortage
(Botha et al, 2011)
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6. Recommendations for enhancing climate information and early
warning systems to support DRR_M for building climate resilience
In this section, we distinguish between operational recommendations, institutional recommendations
and policy recommendations to enhance climate information and early warning systems for building
climate resilience. These are based on the literature reviews as well as on the gaps and opportunities as
identified in this document and by other institutions (such as NDMC’s own reporting, and analyses, for
example, of SAWS’s mandate and functioning).
6.1.
Operational recommendations
The purpose of operational recommendations is to propose changes or alternatives to the practical ways
in which disaster risk is approached, implemented and managed in South Africa. Essentially, some
recommendations may require a departure from traditional approaches to strategic and operational
DRM in South Africa, given a changing physical and social environment. It is clear, in fact, that a sea
change in thinking may be required in a number of sectors addressed by LTAS – disaster management is
by no means unique. Some of the recommendations are as follows:
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R&D support for forecasting and tailored forecasting has seen a decline in recent years, for a
variety of reasons not to be detailed here. We recommend that R&D support for initiatives in
these areas be substantively increased, to address some (if not all) of the technical issues
identified in section 4.3.
In addition, the gap analysis undertaken in this report has not focused specifically on gaps in
R&D in forecasting and tailored forecasting, and we recommend that a specific audit in this area
be undertaken, by an independent stakeholder; including a comprehensive updated user needs
assessment. The latter task, in particular, has been lacking in recent years.
Additional actors be enabled to join both R&D and operational prediction/forecasting, in
addition to those who currently have mandate (Figure 21). Archer van Garderen (2013) provides
more specifics here, particularly in the context of supporting innovation in forecasting and
prediction; including providing an enabling environment to private forecasting and tailored
forecasting, perhaps drawing learning from the model of US mixed stakeholder forecasting.
We recommend that opportunities to extend the Cape Town metropolitan area’s disaster risk
information system for the whole country be examined (see chapter 5 for details on system),
including partnerships with new partners, such as the Risk and Vulnerability Atlas and the Risk
and Vulnerability Assessment Centres (RAVAC) (including capacitation).
For local government to plan for climate change it should: 1) translate national and international
disaster risk reduction requirements into local initiatives with a concrete agenda and budget
allocation for implementation; 2) conduct local disaster risk assessments to determine the
present and future threats from climate change, and formulating specific, contextualised
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adaptation strategies to be integrated with the strategic development plans; 3) monitor and
report on climate change initiatives, to prevent it being pushed from the agenda by more
pressing developmental issues; and 4) reduce local government’s operational impact on the
environment (Visser & Van Niekerk, 2009). It should be noted that mainstreaming DRR into
existing IDP processes is also essential, in an explicit and well planned manner. This would
include strategic assessment of existing projects, likely impacts by disaster and climate risk, and
appropriate adaptation options.
Other recommended response actions to support adaptation in the DRR sector include the development
of risk and vulnerability science centres at academic institutions so that they can support local
municipalities, and maintaining, updating and improving the South Africa Risk and Vulnerability Atlas
(SARVA) as tool for local government to advice climate change adaptation. The increased use of climate
seasonal forecasts, for the agriculture and water sector, development of micro-insurance to assist the
poor recover from the effects of disasters, and the encouragement of region wide collaboration on early
warning systems, as well collaboration with community organisations, NGOS, women’s and farmer
organisations are also suggested response actions; as is enhanced design and use of the
aforementioned Let’s Respond toolkit. Over and above the listed actions, detailed ex-post studies of
severe storms and related flood events need to be conducted to provide critical awareness on risk
factors for purposive adjustments and useful potential adaptive strategies (LTAS, 2013a).
Figure 11: Meteorological station, Northern Cape (part of community based climate risk adaptation and response capacity
building initiatives in the area)
6.2.
Institutional and process recommendations
The purpose of institutional and process recommendations is to propose changes or alternatives to the
institutional set-up of the disaster risk management function in South Africa.
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As indicated in the gap analysis presented in this report, the challenge of funding in the
implementation of the NDMF needs to be addressed. Funding strategy here may not be limited
to mere increased provision of funding, but to further finding solutions to the fundamental fact
that the function of DRM is not seen as a funded mandate by some provinces and/or
municipalities. This comprises a priority area for engagement.
Secondly, DRR-M as linked to climate adaptation does not currently comprise a Key
Performance Area (KPA) for municipal managers – providing a clear disincentive to address.
KPAs may further be linked to incentives (including non-financial incentives); showing improved
performance in DRR as part of local management.
Further support must be provided to the inclusion of risk assessments, mapping of vulnerable
areas (people and ecosystems), measures to adapt to climate change and development of early
warning mechanisms into the DM framework and enactment of the amendment bill. Again, we
recommend here local and district municipalities expanding their partnerships with the SARVA
programme and the RAVACs, to include a capacity building dimension.
Linked to recommendation #2 above, findings of risk assessments and vulnerability levels need
to be integrated from the start into programme and project design (this is occurring, as
mentioned previously, to a highly variable extent in the provinces).
Further, such analyses need to be integrated into the appraisal process, and the way in which
such considerations are integrated must be explicit. Standardised guidelines and operational
procedures are essential. Beyond a focus on design and operational implementation, capacity
building of the relevant stakeholders requires critical attention (see, for example,
recommendation 2 above).
Linked to recommendations regarding a funded mandate earlier, as well as capacity building,
disaster management structures need to be established and capacitated where lacking (e.g. in
municipalities outside of metropolitan and well capacitated district municipalities where we
tend to see a tendency to a lack of disaster management advisory fora; Disaster Risk Units (with
no or limited operation); and to improve response capacity and relieve the pressure on civil
defence structures. Again, this is likely to be both a ‘funded mandate’ (whether a real or
perceived barrier) and a capacity issue (this further links to the role that RAVACs, for example,
may have to play in capacitation). Attention needs to be paid to the difficulty in obtaining
verified assessment reports in cost damages. It is clear that this challenge is not simply a
capacity issue, but links further to the challenge of the perception of funded versus non-funded
mandates described above. Capacity in cost assessment, as well as a focus on standardised
approaches, comprises a critical priority, however. Capacitation of DAFF at the provincial level
needs priority attention, particularly in vulnerable provinces. There are, however, existing
initiatives in this regard – care should be taken to avoid duplication, and to align and support
existing efforts (for example, initiatives in Limpopo Province around prediction and response in
the agricultural sector).
As mentioned earlier, it is commonly accepted that extension services comprise a key point of
local support in adaptation and responding to DRR. Increased utility of early warning
information to extension services (not simply dissemination, but also capacity to incorporate
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6.3.
and respond) needs to be a priority, with recognition that different extension focal points
throughout the country may have different capacity and/or needs.
As further indicated in the gap analysis earlier, communication and coordination between
government departments in the area of disaster response remains a critical need. Robust needs
assessments and gap analyses needs to be undertaken in this regard, including (as mentioned
above) KPAs linked to effective DRR (thus incentivizing communication and coordination). The
recommendation regarding establishment of disaster management units in sector departments
where there are currently none should further help in this regard.
In addition, municipalities need to provide reports on the costing of the damages caused by
each disaster that has occurred. Some require longer term focus, while some may be doable in
the short term, with a low resource realignment, or refined focus.
Finally, as shown in the gap analysis, and as mentioned earlier, the non-existence of disaster
management units in sector departments remains a critical gap. Addressing this need would
have co-benefits with a number of recommendations made here, were it well coordinated.
Policy recommendations
The constitution of the mandatory disaster management structures must be made a priority by
provincial and national governments. Furthermore, disaster management advisory forums and
volunteer units should be established and made operational. There is an opportunity here for local
governments to work closely with the private sector and civil society (e.g. Fire Protection Associations).
In addition, at the national level, Treasury can and should play a critical role in guiding policy and
strategy around DM, and strategic access and engagements with regard to finance. Recommendations
regarding KPAs and incentives made above further apply here. Treasury can play a strategic role in
helping in incentivizing access to certain funds for local government to support innovation and climate
resilience.
Further support must be provided to the inclusion of risk assessments, mapping of vulnerable areas,
measures to adapt to climate change and development of early warning mechanisms into the DM
framework and to ensure implementation of these assessments and strategies and mechanisms as part
of the DM amendment bill. The importance of disaster risk reduction and not only disaster response as
outlined in the bill needs to be further emphasised in all sectors and levels of government and
implemented.
Vulnerability to weather hazards is not evenly distributed and a key task of local municipalities is to map
the vulnerability of communities to all the weather related hazards. For example, Conservation South
Africa has a longstanding capacity building engagement in Namakwa District Municipality to map key
vulnerabilities to climate change as part of a participatory adaptation planning process to assist in
mainstreaming into integrated development plans.
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7. Conclusion
The impacts of climate change on extreme weather events and natural disasters, especially the increase
in frequency and intensity of these events has been acknowledged, both at international and local level.
International organisations have called for the integration of disaster risk reduction management and
climate change adaptation to address the continued increase in the current and projected changes and
impacts as a result of climate and disaster risk. Given that both these practises aim to reduce
vulnerability and enhance coping capacity of affected communities and systems the integration would
increase the resilience of the affected. South Africa has adopted a proactive approach by adopting
legislation and various strategies that promote effective disaster prevention, mitigation and
preparedness through the Disaster Management Act and Disaster Management Framework (SALGA,
2013). This is however, not an easy task as this is juxtaposed against social pressures such as the service
delivery backlogs. National, provincial, district and local level governments have the responsibility of
facilitating social, economic and environment needs in pursuit of sustainable development. Climate
change is likely to challenge their ability to meet these development objectives as some hazards often
result in fatalities, displacement of communities, severe disruption and infrastructure damage (Twigg,
2004).
The escalation in the damage costs from disasters is an indication that disaster risk reduction will
continue to be a key development issue in the country, with the impacts being increasingly felt by the
poor who have no means to recover or cope with these events, as well as the various economic sectors
in the country, making disaster risk reduction a cause of concern for everyone. As indicated in chapter 3,
an escalation in damage costs from disasters continues to rise, with the socio-economic impacts being
wide ranging, from agriculture and food security to health, and other costs which are not measureable
such as mortality and trauma of the affected. While South Africa as a country has the legislation,
statutory instruments and infrastructure in place for effective disaster risk reduction and management
as well climate change adaptation, several challenges have deterred the realisation of the benefits of
these frameworks. While the decentralisation of disaster risk management in the government structures
is seen as a positive and necessary move, improving even the funding structures for disaster risk at local
municipality, the success of decentralisation still needs to be realised.
Disaster risk reduction management systems put in place, through legislation and institutional
mechanisms within the NDMC and other line ministries, as well as the South African Weather Services
who are the providers of early warning and climate information, are at the forefront of the risk
reduction system in the country. These systems have however faced similar challenges, especially a lack
of human capacity at the national, provincial and local government structures that has caused problems
in understanding the core principles of DRR, interpretation of both the Disaster Management Act, and
the National Disaster Management Framework and the South Africa Weather Act, hindering effective
implementation of disaster risk reduction and management. Further, the need for packaging climate and
early warning information has been highlighted as an area of need, for increased uptake of early
warning information especially in vulnerable communities. This includes the dissemination of the early
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warning information to the people who needs it, as illustrated by the Eden case study, where early
warning information is posted on display units and SMSes are sent to the councillors of the affected
wards and the public. While this is one of the good examples of cooperation between local government
and the private sector, generally, private sector involvement in disaster risk reduction as well as
community involvement has been rather limited. Other issues of concern include opening up the sector
and acknowledging independent early warning information producers such as community farmers. The
issue of competition among the different information producers as well the high costs of data from
SAWS were also highlighted as areas of concern.
Some issues raised regarding the poor implementation of the disaster risk reduction in the country stem
from the legislation, where the Disaster Management Act has been criticised for its lack of clarity on
operational, institutional and financial mechanisms. The poor implementation of the DMA has also been
attributed to the lack of capacity and the poor understanding of the Act itself in the different sector
departments and levels of government. While the Disaster Management Act is currently under review, it
is acknowledged that there is a need to align the Act to other statutory instruments and across
government sectors. It is also clear that the country still has a long way to go in getting the
implementation of disaster risk reduction and climate change adaptation right at all levels of
government, across government departments, in the private sectors and vulnerable communities in
need. For this to happen, climate change adaptation measures need to be integrated with disaster risk
reduction measures, which need to be embedded in the policy and development agenda of
Government. Given the importance of climate information and early warning systems for supporting
disaster risk reduction and management in South Africa, the LTAS process, phase 2 will be a crucial
instrument to begin to address some of these issues, especially for the development of adaption
scenarios under the different future climates. This will be crucial given the wide-spread impacts of
disasters in the country, and the multi-sectorial nature of disaster risk reduction and climate change
adaption and the importance of cross sectoral planning and implementation in order to build climate
resilience nationally.
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