Disaster Mitigation Saves

Please reference this document as:Kelman, I. and C.M. Shreve (ed.). 2014. Disaster Mitigation Saves. Version 6, 13 November

2014 (Version 1 was 30 October 2002). Downloaded fromhttp://www.ilankelman.org/miscellany/MitigationSaves.doc

The work in this document up until 2013 was published in the freely downloadable paper:Shreve, C.M. and I. Kelman. 2014. "Does mitigation save? Reviewing cost-benefit analyses of

disaster risk reduction". International Journal of Disaster Risk Reduction, vol. 10, part A, pp. 213-235, free to download at http://www.sciencedirect.com/science/article/pii/S2212420914000661

Purpose:People, especially donors, often ask for proof that disaster risk reduction works. This document compiles quantitative studies of disaster risk reduction projects, namely disaster mitigation, indicating the savings obtained for the investment. Only studies with such numbers are included. For instance, studies only describing methods are listed only under “Useful References Without Ratios”.

Suggestions to:Ilan Kelmanhttp://www.ilankelman.org/contact.html

Thanks to:Bob AlexanderCharles SetchellCharlotte BensonChris NewhallDaniel KullDavid CrichtonJames LewisJohn TwiggKate HawleyMarcus MoenchReinhard MechlerSteve BenderTerry JeggleTricia Wachtendorf

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Contents

Contents................................................................................................................................................2The Infamous 7:1 Ratio........................................................................................................................4Acronyms and Abbreviations...............................................................................................................4Summary Table of Case Studies..........................................................................................................5Case Studies.........................................................................................................................................8

Australia...........................................................................................................................................8Australia...........................................................................................................................................8Austria..............................................................................................................................................8Bangladesh.......................................................................................................................................9Bangladesh.....................................................................................................................................10Belarus............................................................................................................................................10Canada, Ontario..............................................................................................................................10China..............................................................................................................................................10Costa Rica, Limón..........................................................................................................................10Croatia............................................................................................................................................11Dominica........................................................................................................................................11DRC, Kinshasa...............................................................................................................................11Fiji, Navua......................................................................................................................................12Georgia...........................................................................................................................................12Germany.........................................................................................................................................12Germany.........................................................................................................................................13India................................................................................................................................................13India................................................................................................................................................14India, Rohini River Basin, Northeast Uttar Pradesh......................................................................14Indonesia........................................................................................................................................14Iran, Dez and Karun catchments....................................................................................................14Jamaica...........................................................................................................................................15Kazakhstan.....................................................................................................................................15Malawi, Mzimba District...............................................................................................................15Maldives: Gaaf Dhaal Atoll Thinadhoo, Gaaf Alif Atoll Villigili, and Thaa Atoll Vilufushi.......15Mozambique...................................................................................................................................16Nepal..............................................................................................................................................16Nepal..............................................................................................................................................17Nepal, Kailali.................................................................................................................................17Nepal, Kathmandu Valley..............................................................................................................18Netherlands.....................................................................................................................................18Pakistan, Lai Floodplain.................................................................................................................18Pakistan, Lai River.........................................................................................................................18Peru.................................................................................................................................................19Philippines......................................................................................................................................19Philippines......................................................................................................................................19Philippines......................................................................................................................................19Philippines......................................................................................................................................20Samoa.............................................................................................................................................20Sudan, Red Sea State......................................................................................................................20U.S.A..............................................................................................................................................21U.S.A..............................................................................................................................................21U.S.A..............................................................................................................................................22U.S.A..............................................................................................................................................22Vietnam..........................................................................................................................................22

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Vietnam..........................................................................................................................................23Vietnam..........................................................................................................................................23Vietnam, Da Nang Province...........................................................................................................23World, 35 Developing Countries...................................................................................................23

Case Studies to Investigate Further....................................................................................................25U.S.A., FEMA’s Project Impact....................................................................................................25U.S.A., Washington, Seattle: Medic One.......................................................................................25World, Community teams related to disaster risk reduction..........................................................25

Useful References Without Ratios.....................................................................................................26

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The Infamous 7:1 Ratio

Many continue to quote the World Bank as having calculated that disaster risk reduction saves $7 (sometimes $4-7) for every $1 invested, even though the World Bank no longer promotes that specific statement and recommends that the ratio not be used. With help from many colleagues, the earliest source for these numbers found so far is:

Dilley, M. and B.N. Heyman. 1995. “ENSO and Disaster: Droughts, Floods and El Nino Southern Oscillation Warm Events”. Disasters, vol. 19, no. 3, pp. 181-193.

This paper states (p. 183):

“The World Bank and U. S. Geological Survey calculate that a predicted $400 billion in economic losses from natural disasters over the 1990s could be reduced by $280 billion with a $40 billion investment in prevention, mitigation and preparedness strategies”.

No citation is given. It is strongly recommended to avoid using these numbers while investigations continue regarding:

1. Checking if the 7:1 ratio originates from the $280 billion / $40 billion figures or other calculations.

2. Finding the original study and calculations with either the $280 billion / $40 billion numbers or the 7:1 ratio.

Acronyms and Abbreviations

BCR, B:C Benefit to Cost RatioCBA Cost-Benefit AnalysisDRM Disaster Risk ManagementDRR Disaster Risk ReductionEWS Early Warning SystemFRB Flood Retention BasinIFRC International Federation of Red Cross and Red Crescent SocietiesNPV Net Present Value

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Summary Table of Case Studies This table summarises all the case studies in this document.

Reference Location Hazard Vulnerability Benefit:Cost RatioBrown et al., 1997 Canada, Ontario Flood Economic, direct Losses were 0.5%

what they might have been.

BTRE, 2002 Australia Flood Infrastructure Given as savings, not ratios.

Brouwer and van Ek, 2004

Netherlands Flood Economic, Social, Ecological

Given as costs and benefits of different land use scenarios compared to a baseline.

Burton and Venton, 2009

Philippines Flood Mobility disruption and property damage

0.7 to 31

Chowdhury et al., 1993 Bangladesh Cyclone People US$80 per death averted.

Dedeurwaerdere, 1998 Philippines Floods, lahars

Economic 3.5 to 30

DES, c. 2001 Australia All Economic and social

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EWASE, 2008 Germany Flood Economic 2.6 to 9Förster et al., 2005 Germany Flood Agriculture, road

networks, buildings, fishery

2.2 to 5.8

Ganderton et al., 2006Godschalk et al., 2009MMC, 2005Rose et al., 2007

U.S.A. All Disaster losses and repairs

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Gocht, 2003

Germany Flood Economic 0.80 (mean, insurance deliverables); 0.90 (derivatives)

Gocht, 2004 Germany Flood Economic 0.10 (mean, Polder invest)

Guocai and Wang, 2003 China All Economic Reported as cost-benefit (1:35, 1:40)

Healy and Malhotra, 2009

U.S.A. All Disaster damage 15

Heidari, 2009 Iran, Dez and Karun catchments

Flood Property and land damage

0.29-1.03 (levees);0.78-1.34 (dams)

Holland, 2008 Fiji, Navua Flood Property and livelihoods losses

3.7 to 7.3

Holub and Fuchs. 2008 Carinthia, Austria near the border to Slovenia

Flood, mass movement (especially shallow landslides)

Property damage, building stability, infrastructure damage, possible river blockage

1.67 and 1.21

IFRC, 2002 Vietnam Typhoons Infrastructure, economic

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IFRC, 2009 Philippines Flood Economic 2 of 3 interventions successful: 4.9-24

IFRC, 2011 Vietnam Flood Economic, ecological

3-68 (excluding ecological benefits)

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28-104 (with ecological benefits, yet to be materialized)

IFRC, 2012 Bangladesh Cyclones, Flood

Social, ecological, economic

1.18-3.043.05-4.90 (over a 15-yr time frame)

Khan et al., 2008 Pakistan Flood Economic 1-25 Khan et al., 2012 Vietnam

NepalEconomic 3.5 for boat winch

system, Vietnam;2 for straw-bale housing, Nepal

Khogali and Zewdu, 2009

Red Sea State, Sudan

Drought Food, water, agriculture, and livestock

2.4 to 1,800

Kilma et al., 2011 U.S.A.: Florida Tropical Cyclones

Economic loss from property damage

Model compares economic loss using wave pumps to lower SST (hypothetical) vs. adding shutters to houses (hardening); values reported in direct economic loss.

Kilma et al., 2013 U.S.A.: Florida Tropical Cyclones

Economic loss from property damage

Similar to Kilma et al., 2011 but investigates storm surge and wind damage; values reported in net economic loss

Kull et al., 2008 India: Rohini River Basin Uttar Pradesh

Flood Economic 2-2.5

Kull et al., 2013 Pakistan, Lai River Flood Direct and indirect damage

1.3 to 25.0

Kunreuther and Michel-Kerjan, 2012

Global: 35 developing countries

Earthquake, Flood

Economic, lives lost

> 1 retrofitting schools to be earthquake resistant; ave. 60 for one-meter wall around houses in flood areas, 14.5 for elevating houses

La Trobe and Venton, 2003

Mozambique Flood Damage and emergency response

The post-disaster aid request was 203 times the unfulfilled pre-disaster aid request.

Lazo and Chestnut, 2002 U.S.A. All Economic value of weather forecasts

4.4

Lewis, 2007 Vietnam Cyclone Housing damage > 4Mechler, 2005 Piura, Peru Flood Social, economic 3.8Mechler, 2005 Semerang,

IndonesiaFlood Economic 2.5

Mechler et al., 2008 Uttar Pradesh, India Drought Economic loss > 1 to 3.5

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Mertz and Gocht, 2001 Germany Flood Economic 0.5 (Flood Retention Basins) to 5.2 (local measures)

Nepal Red Cross 2008 Nepal Flood Social, economic 2 to 20.8Newhall et al., 1997 Philippines Volcano Property loss and

deaths> 9

PAHO, 1998 Costa Rica, Limón Earthquake Water and sewage system

Given as savings, not ratios.

Perrels, 2011 Nepal Drought Agriculture From 2013-2030, average is 9.

Setchell, 2008 DRC, Kinshasa Flood Economic, direct > 45Venton and Venton, 2004

Bihar and Andhra Pradesh, India

Flood Social, economic 0.67-57.8

Venton and Venton, 2009

Maldives Flood, tsunami, heavy rainfall, swell waves

Economic losses 0.28-3.65

Venton et al., 2010 Malawi, Mzimba District

Drought mainly

Food At least 24.

Vermeiren et al., 2004 Dominica Hurricane Infrastructure > 3Vermeiren et al., 2004 Jamaica Hurricane Infrastructure > 6White and Rorick, 2010 Nepal Flood Social, economic 3.49Woodruff, 2008 Samoa, Apia, lower

Vaisigano catchment area

Flood Damages 1.72 to 44(0.01 to 0.64 for structural measures)

World Bank, 2008 Belarus, Georgia, Kazakhstan

All Economic, infrastructure

Belarus (3.3), Georgia (5.7), Kazakhstan (3.1)

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Case Studies

Australia

DES (c. 2001):“Research has shown that every $1 spent on disaster mitigation saves at least $3 in economic and social recovery costs”.

DES. c. 2001. Disaster Mitigation. Fact Sheet 3, Disaster Mitigation Unit, DES (Department of Emergency Services), Queensland Government, Brisbane, Australia.

Australia

BTRE (2002):“In each of the five case studies, there is evidence that the estimated benefits of the various flood mitigation measures in terms of tangible savings are substantial.

0. Land use planning in Katherine is estimated to have reduced the AAD by around $0.6 million. In a 1 per cent AEP flood, the planning decision is estimated to save around $29 million in direct and indirect costs.

1. Voluntary purchase (VP) in the Kelso area of Bathurst is estimated to have saved $0.7 million in the 1998 flood. If all properties had been purchased before that 1998 event, savings would have been in the order of $1.2 million. When complete, the scheme will save approximately $1.8 million in a 1 per cent AEP event.

2. Building controls (minimum floor levels) in Thuringowa appear to have had an effect in reducing the extent of inundation (and therefore internal damage) in the 1998 flood. Given that individuals can pay off the higher construction costs over the life of a mortgage, building design measures enforced through building controls can be a cost-effective and affordable form of mitigation.

3. Investment in bitumen-sealed roads (which are more flood-resistant) in the Waggamba Shire is estimated to be economically justified. Analysis suggests that the minimum of 32 trucks per day required to break even is comfortably exceeded in the Waggamba Shire.

4. A levee proposed for the Tamworth industrial area would significantly reduce flood damage (the cost of the November 2000 flood is estimated at close to half a million dollars). It is also estimated that the existing CBD levee would avoid at least $5.36 million potential direct damage in a 100-year average recurrence interval (ARI) flood.

These savings typically refer only to direct and indirect costs avoided. Intangible savings (such as reduced stress and ill health) are discussed in the appendices (appendices I to V), but not quantified. The figures therefore underestimate the full benefit of implementing flood mitigation.”

BTRE. 2002. Benefits of Flood Mitigation in Australia (Report 106). BTRE (Bureau of Transport and Regional Economics), DoTaRS (Department of Transport and Remedial Services, Commonwealth of Australia, Canberra, Australia.

Austria

Holub and Fuchs (2008) performed a standardised cost-benefit analysis examining the risk-minimising effects of local structural measures for an Apline catchment in Carinthia, Austria with respect to flash flood events with fluvial bed load transport. Results show that mitigation concepts

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utilizing local structures, detailed below (LSM and LSM+), offer a better cost-to-benefit ratio of 1.67 and 1.21 compared to conventional measures (e.g. CMM; 0.36, detailed below).

Over the past few decades, the test site has undergone static and dynamic floods, ‘extraordinary’ surface runoff, accompanied by the transport of solids, which has resulted in endangering the stability of buildings. ‘Two fundamentally different concepts of mitigation were compared in this study, (i) a concept of conventional mitigation based on the implementation of torrential structures and (ii) a concept of local structural protection for buildings located in the endangered areas’. The benefit was defined as ‘prevented damage to buildings in the test site’.

Three scenarios had been defined according to the requirements of the responsible decision maker, (i) conventional mitigation measures aiming to avoid future design events, (ii) local structural measures neglecting that they could not fully avoid losses due to design events, and (iii) local structural measures taking into account these possible losses on the cost side of the mitigation concept.

a. Scenario 1: CMMConventional mitigation measures are implemented; protection for allelements at risk in red and yellow hazard zones (HZ).

b. Scenario 2: LSMLocal structural protection measures; protection for objects inside the yellowhazard zone to a deposition height and/or flow depth < 0.7 m (yellow HZ);no protection for detached garages.

c. Scenario 3: LSM+Local structural protection measures; additional costs (equals a reduction ofbenefit) due to arising losses from those buildings that are not equipped withlocal structural protection in red and yellow hazard zones; protection forobjects inside the yellow hazard zone to a deposition height and/or flowdepth < 0.7 m (yellow HZ); no protection for detached garages.

The results of this study are very case-sensitive and not transferable to other regions. Whether or not the test site is considered and open or closed systems in terms of a sub-catchment within a river network will impact the different benefit-cost ratios. Local structural measures generally fit better into the landscape, strengthen individual awareness and offer promising, cost-saving approach in mitigating natural hazards.

Holub, M. and S. Fuchs. 2008. “Benefits of local structural protection to mitigate torrent-related hazards”. In C.A. Brebbia and E. Beritatos (eds.), Risk Analysis VI, WIT Transactions on Information and Communication Technologies, vol. 39, WIT Press, Southampton, U.K., pp. 401-411.

Bangladesh

Regarding the 29-30 April 1991 cyclone which killed approximately 139,000 people, Chowdhury et al. (1993) write “the cost of averting a death through the construction of formal cyclone shelters was Taka 3,023 or US$ 80 per death averted (BRAC, 1991b)”.

Chowdhury, A., R. Mushtaque, A.U. Bhuyia, A.Y. Choudhury, and R. Sen. 1993. “The Bangladesh Cyclone of 1991: Why So Many People Died.” Disasters, vol. 17, no. 4, pp. 291-304.

Their reference to BRAC, 1991b is:

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BRAC (1991b) Cyclone ‘91: a study of epidemiology. Bangladesh Rural Advancement Committee, Dhaka.

Bangladesh

IFRC (2012) shows the results from an evaluation of the community-based Disaster Risk Reduction Programme implemented by the Bangladesh Red Crescent Society between 2005-2011. Benefit-cost ratios ranged from “1.18 - 3.04 across communities. If future protective benefits are included (a time frame of 15 years was chosen), BCRs are identified to be between 3.05 and 4.90. Since many benefits had to be excluded from the calculation, the ‘real’ benefit-cost ratios are certain to be significantly higher”.

IFRC. 2012. The long road to resilience: Impact and cost-benefit analysis of community-based disaster risk reduction in Bangladesh. IFRC (International Federation of Red Cross and Red Crescent Societies), Geneva, Switzerland.

Belarus

World Bank (2008) evaluates the cost-benefit of modernization of certain elements of the National Meteorological and Hydrological Service (NHMS). BCR reported for proposed modernizations for Belarus was 3.3.

World Bank, 2008. Weather and Climate Services in Europe and Central Asia. A regional review. Working Paper 151. The World Bank, Washington, D.C., U.S.A.

Canada, Ontario

Brown et al. (1997) examined similar 1986 floods in comparable locations in Michigan and Ontario. Ontario, with a sustainable approach to floodplain management since the Hurricane Hazel disaster in 1954, incurred economic losses less than 0.5% of Michigan’s losses.

Brown, D.W., Moin, S.M.A., and Nicolson, M.L. 1997. “A Comparison of Flooding in Michigan and Ontario: ‘Soft’ Data to Support ‘Soft’ Water Management Approaches.” Canadian Water Resources Journal, vol. 22, no. 2, pp. 125-139.

China

Guocai and Wang (2003) reported cost-benefit ratios of 1:35 and 1:40 from a nationwide study carried out in China between 1994-1996 by the China Meteorological Administration. The study evaluated the economic benefits of meteorological services and focused on macro-economic benefits.

Costa Rica, Limón

PAHO (1998) conducted a study on the impact of the 1991 earthquake on water and sewage systems. “The study concludes that had mitigation measures been applied to the water system in Limón, there would have been a savings of some US$4 million in repairs to the system following the 1991 event, and much of the impact on thousands of people would have been lessened.”

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PAHO. 1998. Natural Disaster Mitigation in Drinking Water and Sewerage Systems: Guidelines for Vulnerability Analysis. PAHO (Pan American Health Organization), Washington, D.C.

Croatia

Leviäkangas et al (2007) write “If we assume that the annual budget of DHMZ (Croatian Hydrological and Meteorological Service) is about 8 million € per year, we can estimate that the services delivered by DHMZ pay themselves back at least 3-fold each year, this estimate being a conservative one. Taking into account all the excluded sectors, the authors’ conclusion is that DHMZ’s services generate today an annual benefit which is about five times its budget. By improving the services, especially their deliverance, the potential ratio between annual costs and benefits is about 4–5 looking only at analyzed sectors, and correspondingly we can expect that with a full range of services (i.e. including all beneficiary sectors) the future benefit potential could lie somewhere in the range of 6–10.”

Pekka Leviäkangas et al., 2007. Benefits of Meteorological services in Croatia. Finnish Meteorological Institute. VTT Technical Research Centre of Finland, Vuorimiehentie 3, P.O.Box 1000, FI-02044 VTT, Finland.

Dominica

In 1979, one year after it had been constructed, Dominica’s deepwater port suffered damage from Category 4 Hurricane David, the reconstruction costs of which equaled 41% of the original construction cost: “Strengthening the facilities to withstand the forces from Hurricane David would have increased the original project cost by 10 to 15%.” (Vermeiren et al., 2004). Knowing the cost to withstand stronger hurricanes would be useful too.

Vermeiren, J., S. Stichter, and A. Wason. 2004. “Costs and Benefits of Hazard Mitigation for Building and Infrastructure Development: A Case Study in Small Island Developing States”. Downloaded from http://www.oas.org/en/cdmp/document/papers/tiems.htm on 23 February 2004.

(Also cited in) IADB, IMF, OAS, and the World Bank. 2005 (August). The Economics of Disaster Mitigation in the Caribbean Quantifying the Benefits and Costs of Mitigating Natural Hazard Losses. IADB (Inter-American Development Bank), IMF (International Monetary Fund), OAS (Organization of American States), and the World Bank, Washington, D.C.

DRC, Kinshasa

Following floods in Kinshasa in 1999, Setchell (2008) completed an economic analysis and concluded that “By adopting conservative assumptions -- and only accounting for direct economic losses -- one dollar of OFDA ‘investment’ in disaster risk reduction in 1998 resulted in a ‘savings’ of at least $45.58 during the 1999 rainy season. Furthermore, this ‘savings’ has occurred up to the present time, thereby compounding the initial benefit several times over.”

Further comments from the analysis:

“100,000 project beneficiaries did not have to again incur direct economic losses amounting to $7.1

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million, or $71.06 each, in 1999 because of the OFDA ‘investment’ of $1.56 per beneficiary in 1998. On a per-family basis, OFDA-supported disaster risk reduction measures resulted in a ‘savings’ of $426, or the equivalent of nearly 54 percent of average annual income, thereby enabling families to purchase the food, clothing, medicine, and other essential items that they may have had to forego in the event of a flood reoccurrence. Again, these benefits have continued to accrue over time because there has not been a repeat of the flooding that occurred in 1998.”

“This success was repeated in another commune of Kinshasa in 2000-2001. Torrential rains in late 1999 generated similar damage to the housing, possessions, and livelihoods of 50,000 residents. Adopting measures used in the earlier project, CRS received a $45,000 grant from OFDA to support additional mitigation activities, beginning in early 2000. As a result, the commune has not flooded since 2000, proving yet again that small investments in disaster risk reduction can result in large benefits for vulnerable people.”

“A 2002 study by the DRC Ministry of Health indicated that project risk reduction measures, together with the public health education component of the project, combined to improve commune environmental conditions to such an extent that the incidence of cholera was reduced by over 90 percent when compared to pre-flood conditions.”

Setchell, C.A. 2008 (May). Flood Hazard Mitigation in Kinshasa, DRC: A Disaster Risk Reduction Success Story. USAID (United States Agency for International Development), Washington, D.C., U.S.A.

Fiji, Navua

For the twenty years of lifetime of a flood warning system in Navua, Fiji, “overall investment returns from the warning system would then most likely be a minimum of between 3.7 to 1 to as high as 7.3 to 1” (Holland, 2008).

Holland, P. 2008 (October). An economic analysis of flood warning in Navua, Fiji. EU EDF 8 – SOPAC Project Report 122, Reducing Vulnerability of Pacific ACP States, Fiji Technical Report. SOPAC (Pacific Islands Applied Geosciences Commission), Suva, Fiji.

Georgia

World Bank (2008) evaluates the cost-benefit of modernization of certain elements of the National Meteorological and Hydrological Service (NHMS). BCR reported for proposed modernizations for Georgia was 5.7.

World Bank, 2008. Weather and Climate Services in Europe and Central Asia. A regional review. Working Paper 151. The World Bank, Washington, D.C., U.S.A.

Germany

Förster and Kneis (2005) provide a cost-benefit analysis of the use of retention areas for providing flood protection for downstream riparian areas in the Elbe River, Germany (2.2 to 5.8). The retention area consists of 6 larger Polders. Controlled flooding of the retention area was simulated using a conceptual model and assessed economically for 2 flood scenarios. In the cost-benefit

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analysis, damage to agriculture, roads, buildings and fishery was assessed. Results suggest the use of retention area for flood protection is highly cost-effective in economic terms.

Förster, S. and Kneis, 2005. Flood Risk Reduction by Use of Detention Areas at the Elbe River. Journal of River Basin Management, 3(1): 21-19.

Germany

EWASE (2008): Compares the cost-benefit of structural and non-structural flood reduction strategies, including Early Warning Systems (EWS), in the Odra and Elbe River basins. Results show 2.6 to 9 benefit-cost ratio using EWS. Results from Förster and Kneis (2005; Polder use 2.2-5.8), Mertz and Gocht (2001; FRB 0.5, local measures 5.2), Gocht (2003; insurance 0.8, derivatives 0.9) and Gocht (2004; Polder invest 0.10) are also cited.

EWASE 2008. CRUE Research Report No I-5: Effectiveness and Efficiency of Early Warning Systems For Flash Floods (EWASE). First CRUE ERA-Net Common Call Effectiveness and Efficiency of Non-structural Flood Risk Management Measures. (http://www.crue-eranet.net/partner_area/documents/EWASE_final_report.pdf).

Förster, S. and Kneis, 2005. Flood Risk Reduction by Use of Detention Areas at the Elbe River. Journal of River Basin Management, 3(1): 21-19.

Gocht, M. 2003. Weather Derivatives as Flood Protection Schemes. Design of Precipitation Derivativesand Application on Corporate and Municipal Level. MBA Master Thesis, Anglia Polytechnic University Cambridge, Berlin School of Economics.

Gocht, M. 2004. Schadenpotentialanalyse fur die Unterlieger, Nutzen-Kosten-Analyse, Handlungsoptionen. In: Bronstert, A.: (Hrsg.): Möglichkeiten zur Minderung des Hochwasserrisikos durch Nutzung von Flutpoldern an Havel und Oder. Brandenburgische Umweltberichte, Universität Potsdam.

Merz, B., Gocht, M. 2001. Risikoanalyse Seckach-Kirnau.: Er-mittlung von Schadenpotentialen, Nutzen-Kosten-Analyse. Gutachten im Auftrag des Zweckverbandes Hochwasser-schutz Einzugsbereich Seckach/Kirnau, unveröffentlicht, GeoForschungsZentrum Potsdam.

India

Venton and Venton (2004) provide a cost benefit analysis of two disaster mitigation and preparedness (DMP) interventions in India.

Bihar Baseline scenario (utilizing the cost benefit ratio as well as the net present value of the DMP

intervention): 4.58 Raised hand pumps: (repairing damaged pumps) 3.20 Modeling potential future initiatives: 0.67 Low-interest loans: 57.80

Khammam District, Andhra Pradesh Baseline scenario (utilizing the cost benefit ratio as well as the net present value of the DMP

intervention): 13.38 to 20.05

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Venton, C.C. and P. Venton. 2004. Disaster preparedness programmes in India: A cost benefit analysis. Network Paper Number 49, Humanitarian Practice Network, Overseas Development Institute, London, U.K.

India

Mechler et al (2008) provides a cost-benefit analysis of utilizing irrigation and insurance to mitigate drought impacts in the Rohini Basin of India. B:C ratios are reported along a continuum of financial intervention, reported as “discount rate %” for irrigation only, insurance only, and irrigation plus insurance, under constant climate and climate change scenarios. A combined approach yields the best benefits for both climate scenarios (B:C > 1 for all scenarios and discount rates; approximate range 1-3.5 for 0% discount rate, drops to about half above 5% discount rate).

Mechler R, et al. 2008. ‘The Risk to Resilience Study Team (2008). Uttar Pradesh Drought Cost- Benefit Analysis’, From Risk to Resilience Working Paper No. 5. Moench M, Caspari E, Pokhrel A (ed) ISET, ISET-Nepal and ProVention, Kathmandu, Nepal, 32 pp.

India, Rohini River Basin, Northeast Uttar Pradesh

Kull et al (2008) present a case study of alternatives to traditional embankment construction to mitigate flood risk in India. ‘People-centered’ drought mitigation strategies on rural livelihoods in Uttar Pradesh are evaluated. Benefit-cost ratios reported were:

future embankment construction < 1 investing in proper maintenance of embankments ~2.0 2-2.5 under both current and future climate change scenarios for "people-centered"

resilience-driven flood risk reduction

Kull, D., Singh, P., Chopde, S., S. Wajih and The Risk to Resilience Study Team, (2008): Evaluating Costs and Benefits of Flood Reduction under Changing Climatic Conditions : Case of the Rohini River Basin, India, From Risk to Resilience Working Paper No. 4, eds. Moench, M., Caspari, E. & A. Pokhrel, ISET, ISET-Nepal and ProVention, Kathmandu, Nepal.

Indonesia

Mechler (2005) provides a cost-benefit analysis of integrated water management and flood protection scheme for Semarang, Indonesia. Benefit to cost ratio was reported as 2.5 for reducing direct and indirect economic impacts of flooding.

Mechler, 2005. Cost-benefit Analysis of Natural Disaster Risk Management in Developing Countries. Working paper for sector project ‘Disaster Risk Management in Development Cooperation’, GTZ, 2005.

Iran, Dez and Karun catchments

From Heidari (2009) presents a master plan for damage-reduction in the floodplain areas of the Dez Karun rivers. A B:C ratio for levee construction is found to be 0.29-1.03 depending on location and

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for detention dams, 0.78 and 1.34 for single and double-dams, respectively.

Heidari, A. 2009. “Structural master plan of flood mitigation measures”. Natural Hazards and Earth System Sciences, vol. 9, pp. 61-75.

Jamaica

The Norman Manley Law School, University of the West Indies, Jamaica was damaged by Hurricane Gilbert on 12 September 1988: “The cost of the reconstruction was given as US$90,000 but the University took the opportunity to carry out some deferred maintenance, so the cost of repair due to the hurricane damage may have been somewhat overstated.” (Vermeiren et al., 2004). US$13,000 of investment would have prevented the hurricane damage.

Vermeiren, J., S. Stichter, and A. Wason. 2004. “Costs and Benefits of Hazard Mitigation for Building and Infrastructure Development: A Case Study in Small Island Developing States”. Downloaded from http://www.oas.org/en/cdmp/document/papers/tiems.htm on 23 February 2004.

Kazakhstan

World Bank (2008) evaluates the cost-benefit of modernization of certain elements of the National Meteorological and Hydrological Service (NHMS). BCR reported for proposed modernizations for Kazakhstan was 3.1.

World Bank, 2008. Weather and Climate Services in Europe and Central Asia. A regional review. Working Paper 151. The World Bank, Washington, D.C., U.S.A.

Malawi, Mzimba District

For a disaster risk reduction and food security programme in Malawi, Venton et al. (2010) report “for every US$1 invested, the project activities delivered US$24 of net benefits for the communities to help them overcome food insecurity while building their resilience to drought and erratic weather. This is a conservative estimate and the true figure could be as much as US$36.”

Venton, C.C., J. Siedenburg, J. Faleiro, and J. Khinmaung. 2010. Investing In Communities: The benefits and costs of building resilience for food security in Malawi. Tearfund, London, U.K.

Maldives: Gaaf Dhaal Atoll Thinadhoo, Gaaf Alif Atoll Villigili, and Thaa Atoll Vilufushi

Venton and Venton (2009) conduct a cost-benefit analysis for Disaster Risk Reduction (DRR) for two scenarios: 1) hazards and their impacts on communities “without any DRR measures” and 2) the reduction in hazard impacts “with” DRR measures. The benefits accrued from hazard reduction (e.g. reduction in lost assets) are offset against the costs of implementing protection measures to generate the benefit-cost ratios. Estimated losses for each island from tsunami, swell wave and storm surge, and rainfall flooding losses are calculated for each island.

BCR Scenarios: Min. hazard occurrence, Max. hazard occurrence, Max. hazard & climate change, respectively.

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Thinadhoo Safe Island Protection: 0.39, 1.35, 1.40 Selected Safe Island Protection: 0.52, 1.79, 1.85 Limited Protection: 1.13, 3.54, 3.65 All scenarios come out positive once the estimate for intangible losses is added in, yielding

BCRs ranging between 1.07 and 3.43.

Villigili Safe Island Protection: 0.28, 0.93, 1.00 Selected Safe Island Protection: 0.29, 0.89, 0.86 Limited Protection: 0.42, 1.23, 1.33

Vilufushi Safe Island Protection: 0.50, 1.65, 1.95 The findings indicate that, under current conditions, there is not a financial justification for

the measures undertaken on Vilufushi. The projections under climate change are positive, though the probability of hazard events will have to be very high to justify the expenditures on this basis.

The findings are mostly positive under the sensitivity testing.

Venton, C.C., P. Venton, and A. Shaig. 2009 (September) / 2010. Cost Benefit Study of Disaster Risk Mitigation Measures in Three Islands in the Maldives. United Nations Development Programme Maldives and Government of Maldives, Department of Housing, Transport and Environment, Malé, The Maldives.

Mozambique

Quoting Terry Jeggle, a study by Latrobe and Venton (2003) report “about six months before the Mozambique floods occurred, the meteorological authority indicated that the country was likely to experience heavier than usual rainfall. Mozambique put out an appeal to the international community for US$2.7 million worth of anticipatory measures. However, it received less than half this amount. Once the floods eventually materialised, Mozambique received US$100 million in emergency assistance. Then, at a subsequent conference, a further US$450 million was pledged by the international donor community for rehabilitation costs.”

It might be unfair to assume that no emergency assistance would have been needed if the “US$2.7 million worth of anticipatory measures” was implemented. The figures nonetheless illustrate the difference in cost between prevention and response.

La Trobe, S. and P. Venton. 2003 (July). Natural Disaster Risk Reduction: The policy and practice of selected institutional donors. A Tearfund Research Project. Tearfund, London, U.K.

Nepal

Nepal Red Cross (2008) conducted a study on the cost benefit of a Disaster Risk Reduction (DRR) programme. Benefit-cost ratios ranged from 2 to 20.8, depending on elements of the DRR programme included or excluded from the analysis:

4.8 (skills training) 18.6 (entire DRR programme)

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20.8 (check dams; 14.8 for sensitivity analysis including check dams) 2 (not including check dams)

Nepal Red Cross. 2008. Cost Benefit Analysis of a Nepal Red Cross Society Disaster Risk Reduction Programme. Nepal Red Cross, Kathmandu, Nepal.

Nepal

Agriculture is an important part of Nepal’s economy. Studies have shown that improving farmer’s knowledge and accessibility to meteorological data reduces economic loss. Perrels (2011) performs a cost-benefit analysis to ascertain the social and ecological benefits of improving weather services in Nepal.

A simple cost-benefit calculation is made for the period 2013 – 2030 assuming: modernisation of 81 weather observation stations (either through complete replacement or

through significant upgrade), on average about 10 stations per year upgraded from 2013 to 2021 use of radiosonde twice a day year round, with gradual scaling up of the operation in the first

two years installation of 3 Doppler double polarization weather radars up to 2020. The first two radars are

supposed to be replaced after 11 years of service (i.e. within the time horizon of this CBA). Funding of the investments is spread out over 10 years, starting at the year of installation, while a 4% real interest rate is applied.

Maintenance and data handling costs are supposed to depend on the number of observation stations and radars, but with noticeable economies of scale (i.e. growing less than proportionally compared to the growth of the modernised observation network).

‘Taken over the entire period 2013-2030, the benefit-cost ratio is rated at approximately 9. It rises from 6~7 in the first years to almost 11 to the end of the period. As a result of the assumptions made in chapter 4 the bulk of the benefits is generated in the agricultural sector (about 90%)’.

Perrels, A. 2011 (May 5). Social economic benefits of enhanced weather services in Nepal. Finnish Meteorological Institute, Helsinki, Finland.

Nepal, Kailali

White and Rorick (2010) conducted a cost-benefit analysis of the Disaster Risk Reduction project sponsored by Mercy Corps and the Nepali Red Cross in Kailali, Nepal. The primary aim of the programme is to assist riverside communities in the far western Kailali District and the project components include the development of Early Warning Systems, small scale mitigation works, and to support young rescuers clubs in schools that are devoted to learning about and passing on knowledge of disaster risk management. BCRs considering economic impacts ranged from 1.49-2.79. BCRS considering impacts to social and economical capital ranged from 1.55-5.81. White and Rorick (2010) write “It is our belief that the B:C ratio of 3.49, which was determined assuming a 10 year benefit duration, a 12% discount rate, best estimates for costs and benefits, and the inclusion of some social benefits, is the most accurate assessment of the KDRRI project. A B:C ratio of 3.49 indicates that for every Euro spent on DRR, we expect that 3.49 Euros will be saved by the community or the aid organization responding to the community’s post-disaster needs.

White, B.A. and M.M. Rorick. 2010. Cost-Benefit Analysis for Community-Based Disaster Risk Reduction in Kailali, Nepal. Mercy Corps Nepal, Lalitpur, Nepal.

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Nepal, Kathmandu Valley

Khan et al. (2012) conducted a cost-benefit analysis of using a straw-bale construction instead of brick or cement-mortar in Nepal to reduce earthquake damage. The CBA yielded a BCR of 2 for making a house with straw-bales instead of bricks, using a 12% social discount rate and project period of 30 years.

Khan, F., M. Moench, S.O. Reed, A. Dixit, S. Shrestha, and K. Dixit. 2012. Understanding the Costs and Benefits of Disaster Risk Reduction Under Changing Climate Conditions Case Study Results and Underlying Principles. ISET (Institute for Social and Environmental Transition-International), Boulder, Colorado, U.S.A.

Netherlands

Brouwer and van Ek (2004) investigate the integrated ecological, social and economic impacts of alternative flood control policies in the Netherlands. They find that traditional flood control policy, e.g. building higher and stronger dikes, is cost-effective. However, investment in alternative flood control policy, e.g. land use changes and floodplain restoration, is justifiable on the basis of a cost-benefit analysis and a multi-criteria analysis when including the longer-term (next 100 years) social and ecological benefits. Results are reported in present value (in millions) of costs and benefits of proposed land use and flood plain restoration compared to a ‘do nothing’ baseline scenario.

Brouwer, R. and R. van Ek. 2004. Integrated ecological, economic and social impact assessment of alternative flood control policies in the Netherlands. Ecological Economics, vol. 50, pp. 1- 21.

Pakistan, Lai Floodplain

Khan et al (2008) combine social science (CBA) and natural sciences (hydrologic and climate models) to investigate the cost-benefit of proactive flood mitigation measures in the Lai floodplain, Pakistan. Benefit-cost ratios ranged from 1-25:

Early warning: 0.96 Relocation/restoration: 1.34 Expressway/channel: 1.88 JICA options (community pond, river improvement): 8.55, 25

Khan, F., Mustafa, D., D., Kull and The Risk to Resilience Study Team, (2008): Evaluating the Costs and Benefits of Disaster Risk Reduction under Changing Climatic Conditions: A Pakistan Case Study, From Risk to Resilience Working Paper No. 7, eds. Moench, M., Caspari, E. & A. Pokhrel, ISET, ISET-Nepal and ProVention, Kathmandu, Nepal, 24 pp.

Pakistan, Lai River

Kull et al (2013) write ‘we introduce quantitative, stochastic CBA frameworks and apply them in case studies of flood and drought risk reduction in India and Pakistan, also incorporating climate change impact projections. DRM interventions are shown to be economically efficient with integrated approaches more cost effective and robust under climatic changes’. In the Lai River study site the following B:C ratios were given for flood management interventions:

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Expressway: 1.9 Retention pond: 9.3 River improvement: 8.6 Combined pond & river improvement: 25.0 Early Warning System: 1.6 Floodplain relocation: 1.3

Kull, D., R. Mechler, and S. Hochrainer. 2013. “Probabilistic Cost-Benefit Analysis of Disaster Risk Management in a Development Context”. Disasters, forthcoming.

Peru

Mechler (2005) provides a prefeasibility study of the reduction of flood hazards using Polders in Piura, Peru. Benefit to cost ratio was reported as 3.8 for reducing direct social and economic impacts of flooding.

Mechler, 2005. Cost-benefit Analysis of Natural Disaster Risk Management in Developing Countries. Working paper for sector project ‘Disaster Risk Management in Development Cooperation’, GTZ, Berlin.

Philippines

Regarding the 1991 eruption of Mount Pinatubo volcano in the Philippines, numbers given by Newhall et al. (1997) put the monitoring and response costs at US$56.5 million while the amount of property damage averted as a result of the monitoring and response is estimated at a minimum US$500 million not including over 5,000 lives saved.

Newhall, C., J.W. Hendley II, and P.H. Stauffer. 1997. Reducing the Risk from Volcano Hazards: Benefits of Volcano Monitoring Far Outweigh Costs —The Case of Mount Pinatubo. U.S. Geological Survey Fact Sheet 115-97, Vancouver, Washington, U.S.A.

Philippines

Dedeurwaerdere (1998) estimated the benefits of different prevention measures undertaken against floods and lahars in the Philippines. Results showed calculated benefits of 3.5 to 30 times the projects’ costs.

Dedeurwaerdere, A. 1998. Cost-benefit Analysis for Natural Disaster Management - A Case-study in the Philippines. Brussels: CRED.

Philippines

The project undertook a Quality Impact Assessment and Cost Benefit Analysis, to understand the impacts of disaster risk reduction activities being carried out in the Philippines by the Red Cross.

Two of three interventions are cost effective, benefit-cost ratio results: Hanging footbridge: 24 Sea wall: BCR = 4.9

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Dyke: BCR = 0.67

IFRC (2009). “Assessing Quality and Cost Benefit: A Philippines Case Study.”

Philippines

To avoid mobility disruption due to floods—which were preventing children from going to school and taking crops to market—“A CBA process was carried out for structural measures in three barangays – a hanging footbridge, a dyke and a sea wall…The analysis resulted in a range of Benefit to Cost Ratios, from 24 in the case of the footbridge and 4.9 in the case of the sea wall (positive returns), to 0.7 in the case of the dyke (negative return).” For the footbridge, “A sensitivity analysis of the discount rate leads to a BCR ranging from 19 (discount rate of 15%) to 31 (discount rate 5%).”

Burton, C. and C.C. Venton. 2009 (7 December). Case Study of the Philippines National Red Cross: Community Based Disaster Risk Management Programming. IFRC (International Federation of Red Cross and Red Crescent Societies), Geneva, Switzerland.

Samoa

For flooding in the lower Vaisigano catchment of Apia, Samoa, Woodruff (2008) describes various measures:

“In the case of an improved forecasting system, the ratio of benefits to costs was estimated to range from 1.92 to 1.72, depending on the choice of discount rate used to carry out the analysis.

“The most significant economic pay-off from investing in flood management options is found to be from constructing homes with raised floors. For new homes, the benefit cost ratio is found to range from 4 to 44 for wooden homes, and from 2 to 28 for cement block homes.”

“Structural measures, on the other hand, were found not to be economically viable. In the case of floodwalls, the benefit-cost ratios ranged from 0.11 to 0.64 depending on the choice of floodwall design and discount rate used in the analysis. For the construction of a diversion channel, the benefit-cost ratios ranged from 0.01 to 0.09. Although, it is likely that many of the indirect or non-monetary benefits not captured in the analysis such as avoided health costs or trauma suffered by residents during flooding, or reduced flood damages to households and businesses in nearby districts, would raise the benefit-cost ratios, it is unlikely that they would be significant enough to raise benefit-cost ratios above one.”

Woodruff, A. 2008 (February). Samoa Technical Report – Economic Analysis of Flood Risk Reduction Measures for the Lower Vaisigano Catchment Area. EU EDF – SOPAC Project Report 69g Reducing Vulnerability of Pacific ACP States. SOPAC (Pacific Islands Applied Geosciences Commission), Suva, Fiji.

Sudan, Red Sea State

Drought risk reduction measures were implemented in the Red Sea State of Sudan with the following results calculated by Khogali and Zewdu (2009):

“terraces were found to have a cost to benefit ratio of 1:61”. “earthdams/ embankments were found to have a cost to benefit ratio of 1:2.4”.

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“communal gardens were found to have a cost to benefit ratio of 1:1800”. A Hafir is “a large whole dug out in the ground that holds runoff water” and Hafirs “were

found to have a cost to benefit ratio of 1:2.7”.

Khogali, H. and D. Zewdu. 2009. Impact and Cost Benefit Analysis: A Case Study of Disaster Risk Reduction Programming in Red Sea State Sudan. Sudanese Red Crescent Society, Khartoum, Sudan.

U.S.A.

Lazo and Chestnut (2002) conducted a cost-benefit analysis of current and improved weather forecasts in the US. The study elicited values from individuals in nine different cities chosen from the nine regions defined by the National Climate Data Center for climate summaries: San Diego (California), Portland (Oregon), Denver (Colorado), Billings (Montana), Oklahoma City (Oklahoma), Madison (Wisconsin), Columbus (Ohio), Albany (New York), and Miami (Florida). ‘Historical data on weather forecasts and observed weather conditions were used to create indicesof weather variability and forecast accuracy for each city. These indices were used to explorehow individuals’ perceptions of and values for improved forecasts and current forecast servicesrelate to local weather variability (e.g., persistence) and the quality of forecasts currentlyavailable to the respondents.’

Lazo and Chestnut (2002) write:

“The median household value for current weather forecasts for all weather conditions isabout $109 a year. With about 105 million U.S. households, taking the median value asan estimate of the average household value, aggregate national values for all currentweather forecast services are $11.4 billion a year. With total federal spending on weatherforecasting services about $25 a year per household (Hooke and Pielke, 2000), this studysuggests a benefit-cost ratio of 4.4 to 1.”

Lazo, J.K. and L.G. Chestnut. 2002. Economic value of Current and Improved Weather Forecasts in the US Household Sector: Report prepared for the National Oceanic and Atmospheric Administration. Stratus Consulting Inc., Boulder, CO.

U.S.A.

Based on the findings of MMC (2005) and also referring to Ganderton et al. (2006) and Rose et al. (2007), Godschalk et al. (2009) summarise “each dollar spent on mitigation grants saves society an average of $4 in real resource costs. As expected, benefit-cost ratios varied across hazards, reflecting individual hazard characteristics and local mitigation priorities.” Rose et al. (2007) highlight “the overall benefit-cost ratio for FEMA mitigation grants is about 4:1, though the ratio varies from 1.5 for earthquake mitigation to 5.1 for flood mitigation. Sensitivity analysis was conducted and shows these estimates to be quite robust”. Woodworth (2008) repeats these figures.

Ganderton, P.T., L. Bourque, N. Dash, R. Eguchi, D. Godschalk, C. Heider, E. Mittler, K. Porter, A. Rose, L.T. Tobin, and C. Taylor. 2006. “Mitigation generates savings of four to one and enhances community resilience: MMC releases independent study on savings from natural hazard mitigation”. Natural Hazards Observer, vol. 30, no. 4, pp. 1-3.

Godschalk, D.R., A. Rose, E. Mittler, K. Porter, and C.T. West. 2009. “Estimating the value of

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foresight: aggregate analysis of natural hazard mitigation benefits and costs”. Journal of Environmental Planning and Management, vol. 52, no. 6, pp. 739-756.

Millerd, F., Dufournaud, C. M., & Schaefer, K. (1994). Canada–Ontario Flood Damage Reduction Program: case studies. Canadian Water Resources Journal, 19(1), 17–26.

MMC. 2005. Natural Hazard Mitigation Saves: An Independent Study to Assess the Future Savings from Mitigation Activities. Volume 1 – Findings, Conclusions, and Recommendations. Volume 2 – Study Documentation. Appendices. MMC (Multihazard Mitigation Council). National Institute of Building Sciences, Washington, D.C.

Rose, A., K. Porter, N. Dash, J. Bouabid, C. Huyck, J. Whitehead, D. Shaw, R. Eguchi, C. Taylor, T. McLane, L.T. Tobin, P.T. Ganderton, D. Godschalk, A.S. Kiremidjian, K. Tierney, and C.T. West. 2007. “Benefit-Cost Analysis of FEMA Hazard Mitigation Grants”. Natural Hazards Review, vol. 8, no. 4, pp. 97-111.

Woodworth, B. 2008 (April 30). Questions for the Record from the April 30, 2008, Pre-Disaster Mitigation Hearing: Responses provided by Brent Woodworth on behalf of the Multihazard Mitigation Council of the National Institute of Building Sciences. Unpublished.

U.S.A.

Healy and Malhotra (2009) write “Assuming a 4% annual interest rate and a 6% depreciation rate for preparedness investments, we estimate the NPV [Net Present Value] of $1 of disaster preparedness to be about $15.14.” over eight years.

Healy, A. and N. Malhotra. 2009. “Myopic Voters and Natural Disaster Policy”. American Political Science Review, vol. 103, no. 3, pp. 387-406.

U.S.A.

Kilma et al. (2011) examines whether it is potentially cost-effective to lower the wind speed of tropical cyclones (TCs) by reducing the sea surface temperature (SST) using wave pumps in South Florida. The FEMA HAZUS-MH MR3 damage model and census data on the value of property at risk are used to estimate expected economic losses. Wind damages after storm modification with damages after implementing hardening strategies protecting buildings. Results suggest ‘modification could reduce net losses from an intense storm more than hardening structures. However, hardening provides “fail safe” protection for average storms that might not be achieved if the only option were modification. The effect of natural variability is larger than that of either strategy’. Economic losses are reported in USD in the supplementary materials accompanying the article.

Klima, K., M. Granger Morgan, I. Grossmann, and K. Emanuel. 2011. “Does It Make Sense To Modify Tropical Cyclones? A Decision-Analytic Assessment”. Environmental Science and Technology, vol. 45, pp. 4242-4248.

Vietnam

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IFRC (2002): Planting of mangroves along coastline in Vietnam results in a benefit-cost ratio of 52 from 1994-2001 period. Mangroves promote savings in reduced cost of dyke maintenance.

IFRC 2002, World Disasters Report 2002. Geneva: International Federation of Red Cross and Red Crescent Societies.

Vietnam

With respect to housing in Vietnam, “Although every house has different needs, the average cost of strengthening is about 25 per cent of the house value. Access to credit and financial encouragement is part of the package...in October 2006, the hundreds of buildings that had been strengthened under the DWF programme [see http://www.dwf.org/en] withstood the impact of Typhoon Xangsane that destroyed 20,000 other houses and unroofed 250,000 more in the three central provinces.”

Lewis, J. 2007. “Disaster Reduction Measures for Typhoons and Floods”. Tiempo Climate Newswatch, http://www.tiempocyberclimate.org/newswatch/feature071101.htm and “Typhoons and floods in Vietnam: Measures for disaster reduction in contexts of climate change”. Radix, http://www.radixonline.org/resources/Lewis-Floods&typhoonsinVietnam.doc

Vietnam

IFRC (2011) evaluates the cost-benefit of “Community-based Mangrove Reforestation and Disaster Preparedness Programme” in Vietnam, sponsored by the IFRC. IFRC concludes that the mangrove afforestation programmes in Vietnam have been very economically, ecologically and socially successful. However, it warns that mangroves are difficult to plant, requiring suitable environmental conditions (soil type), local expertise and community capacity, so planting in less suitable regions will be more expensive.

The report provides two BCR: BCR 1 (excludes ecological benefits): 3-68 BCR 2 (including ecological benefits, yet to be materialized): 28-104

Vietnam, Da Nang Province

Khan et al. (2012) conducted a CBA of the use of a new boat winch system in Da Nang Province, Vietnam. Existing winch systems are unable to pull all the boats to shore and cannot pull boats larger than 30 CV. Benefits for this study are calculated by estimating the number of additional boats that could be pulled in with the new winch. A BCR of 3.5 was calculated using a 12% social discount rate and a 30-year project period.

Khan, F., M. Moench, S.O. Reed, A. Dixit, S. Shrestha, and K. Dixit. 2012. Understanding the Costs and Benefits of Disaster Risk Reduction Under Changing Climate Conditions Case Study Results and Underlying Principles. ISET (Institute for Social and Environmental Transition-International), Boulder, Colorado, U.S.A.

World, 35 Developing Countries

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Kunreuther and Michel-Kerjan (2012) conduct a cost-benefit analysis in 35 developing countries for: (1) retrofitting schools in seismically active countries so that they are earthquake resistant and (2) reducing losses from severe flooding by either (a) building a one-meter wall around houses in flood prone regions and (b) elevating houses in the same region. With regards to retrofitting schools Kunreuther and Michel-Kerjan (2012) write “it would cost ~ $300 billion to retrofit all these schools in the 35 most exposed countries, saving lives of 250,000 individuals over the next 50 yrs.” Regarding flood mitigation measures, a BCR of 60 was calculated for erecting a one-meter wall and 14.5 for elevating houses. Further regarding flood mitigation Kunreuther and Michel-Kerjan (2012) write ‘We find that it would cost nearly $940 billion to undertake the community-based disaster risk reduction measure of building walls around the affected communities and $5.2 trillion to elevate all houses exposed to floods in the 34 most exposed countries. Undertaking either of these measures will save 61,000 lives over the next 50 years. If one invested $75 billion in building one-meter high walls surrounding communities, the estimated benefits would be $4.5 trillion with an average BCR= 60. Elevating homes would yield estimated benefits of $1.1 trillion and an average BCR= 14.5 for {d=.03 VoL=$40,000}.’

Kunreuther H. and E. Michel-Kerjan. 2012 (April 12). Challenge Paper: Natural Disasters. Policy Options for Reducing Losses from Natural Disasters: Allocating $75 billion. Revised version for Copenhagen Consensus. Center for Risk Management and Decision Processes, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, U.S.A.

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Case Studies to Investigate Further

The case studies here would be useful projects for aiming to calculate costs and benefits through verifiable numbers and calculations.

U.S.A., FEMA’s Project Impact

FEMA has written plenty of documents on Project Impact. Do any provide benefit-cost ratios? FEMA (1997, 1998) as referenced in the next section do not include such ratios.

U.S.A., Washington, Seattle: Medic One

A long-term programme to train most members of the public in basic first aid. Any information on costs and benefits?

World, Community teams related to disaster risk reduction

See http://www.riskred.org/fav/cst.pdf for more information on these teams.

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Useful References Without Ratios

Anderson, M.B. 1990. Analyzing the Costs and Benefits of Natural Disaster Responses in the Context of Development. Environment Working Paper no. 29. The World Bank, Washington, D.C., U.S.A.

Annand, J. 2008 (June 20). SMGS PDF CRCS Evaluating the environmental losses and benefits from flooding. RMIT (Royal Melbourne Institute of Technology), Melbourne, Australia, http://mams.rmit.edu.au/kse6lzj09fet.pdf

Brinkhuis-Jak, M., S.R. Holterman, M. Kok, and S.N. Jonkman. 2003. “Cost benefit analysis and flood damage mitigation in the Netherlands”. In T. Bedford and P.H.A.J.M. van Gelder (eds.), Safety and Reliability: Proceedings of the ESREL 2003 Conference, Maastricht, the Netherlands, 15-18 June 2003, Routledge, London, pp. 261-270.

Clarke, D.J. and R.V. Hill. 2012 (5 June). Cost-Benefit Analysis of the African Risk Capacity Facility. World Food Programme, Rome, Italy.

CSSC. 1999. Earthquake Risk Management Mitigation Success Stories. CSSC (California Seismic Safety Commission, Sacramento, California.

de Loë and D. Wojtanowski. 2001. “Associated benefits and costs of the Canadian Flood Damage Reduction Program”. Applied Geography, vol. 21, pp. 1-21.

Dixit, A., Pokhrel, A., M. Moench and The Risk to Resilience Study Team, (2008): Costs and Benefits of Flood Mitigation in the Lower Bagmati Basin: Case of Nepal Tarai and North Bihar, From Risk to Resilience Working Paper No. 5, eds. Moench, M., Caspari, E. & A. Pokhrel, ISET, ISET-Nepal and ProVention, Kathmandu, Nepal, 34 pp.

FEMA. 1997 (April). Report on Costs and Benefits of Natural Hazard Mitigation. FEMA (Federal Emergency Management Agency), Washington, D.C., and developed under the Hazard Mitigation Technical Assistance Program (HMTAP) Contract Number 132 with Woodward-Clyde Federal Services, Gaithersburg, Maryland.

FEMA. 1998 (August). Protecting Business Operations: Second Report on Costs and Benefits of Natural Hazard Mitigation. FEMA (Federal Emergency Management Agency), Washington, D.C., and developed by the Mitigation Directorateís Program Assessment and Outreach Division under the Hazard Mitigation Technical Assistance Program (HMTAP) contract with Woodward-Clyde Federal Services, Gaithersburg, Maryland.

Ganderton, P.T. 2005. “‘Benefit-Cost Analysis’ of Disaster Mitigation: Application as a Policy and Decision-Making Tool”. Mitigation and Adaptation Strategies for Global Change, vol. 10, pp. 445-465.

IIED. 2010 (June). Beyond cost-benefit: developing a complete toolkit for adaptation decisions. IIED (International Institute for Environment and Development), London, U.K.

Jensen, J. 2011 (11 August). Preparedness: A Principled Approach to Return on Investment. Version 1.0. International Association of Emergency Managers. Falls Church, Virginia, U.S.A.

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Jonkman, S.N., M. Brinkhuis-Jak, and M. Kok. 2004. Cost benefit analysis and flood damage mitigation in the Netherlands. HERON, vol. 49, no. 1, pp. 95-111.

Kirkpatrick, S. 2011-2012. The Economic Value of Natural and Built Coastal Assets. Part 1: Natural Coastal Assets (2011 June 27) and Part 2: Built Coastal Assets (2012 March 28). ACCARNSI Discussion Paper – Node 1 Coastal Settlements, ACCARNSI (Australian Climate Change Adaptation Research Network for Settlements and Infrastructure), University of New South Wales, Sydney, Australia.

Mechler, R. 2003. “Natural Disaster Risk and Cost-Benefit Analysis”. Chapter 3, pp. 45-55 in Kreimer, A., M. Arnold, and A. Carlin (eds.), Building Safer Cities: The Future of Disaster Risk. Disaster Risk Management Series No. 3, The World Bank, Washington, D.C., U.S.A.

Olsen, J.R., P.A. Beling, J.H. Lambert and Y.Y. Haimes. 1997. “Input-Output Economic Evaluation of System of Levees”. Journal of Water Resources Planning and Management, vol. 124, no.5, pp. 237-245.

SDC. 2010. Disaster Risk Reduction in International Cooperation: Switzerland‘s Contribution to the Protection of Lives and Livelihoods. SDC (Swiss Agency for Development and Cooperation), Bern, Switzerland.

Walker, W., Abrahamse, A., Bolten, J., Kahan, J.P., Van de Riet, O., Kok, M. & Den Braber, M., 1994. A Policy Analysis of Dutch River Dike Improvements: Trading off safety, cost and environmental impacts. Operations Research (42), 5, 823-836. See Table III.

World Bank (2007). Project Appraisal Document. “Western Kenya Community Driven Development and Flood Mitigation Project”.

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