Advertisement

Multiple Criteria Decision Making for Flood Risk Management

  • Karin Hansson
  • Mats Danielson
  • Love Ekenberg
  • Joost Buurman
Chapter
Part of the Advances in Natural and Technological Hazards Research book series (NTHR, volume 32)

Abstract

This paper describes a framework for multiple criteria decision making (MCDM) for flood risk management. To date, most models assessing flood impacts and coping strategies focus on economic impacts and neglect environmental and social considerations. In this paper, we develop and test an ex-ante framework for flood damage assessment, which includes a flood simulation model, a decision tool, and suggested policy strategies. Environmental and social criteria are introduced into the framework, and soft evaluations are performed in order to demonstrate the usability of the framework. The Bac Hung Hai polder in northern Vietnam serves as a case study. Results show that it is useful to add a multi-criteria perspective to flood management decisions to account for differing views and preferences. Furthermore, such a framework enables stakeholder participation in consequence analyses as well as in formulating more elaborated criteria weights.

Keywords

Decision support tool Flood risk management Case study Multi-criteria perspective Simulation tool 

Notes

Acknowledgements

This work was supported by the Swedish international development cooperation agency (Sida). Many thanks to Dr. Lars Asker for discussions regarding Matlab methods.

References

  1. ADRC (2005) Total disaster risk management: good practices. Asian Disaster Reduction Centre, KobeGoogle Scholar
  2. AHC (2002) Protecting local heritage places: a guide for communities. Australian Heritage Commission, Canberra, Australia. ISBN 0642305382Google Scholar
  3. Ahern M, Kovats RS, Wilkinson P, Few R, Matthies F (2005) Global health impacts of floods: epidemiologic evidence. Epidemiol Rev 27:36–46CrossRefGoogle Scholar
  4. Arriens WL (2004) Participatory processes in IWRM, first training program on IWRM and strengthening of River Basin Committees (RBC). Bangkok and Chiang Mai, Thailand, 26 July–6 AugustGoogle Scholar
  5. Bana e Costa CA, Soares de Oliveira R (2004) A multicriteria model for portfolio management. Eur J Financ 10(3):198–211CrossRefGoogle Scholar
  6. Black MC, Williams PL (2001) Preliminary assessment of metal toxicity in the Middle Tisza River (Hungary) flood plain. J Soil Sediment 1(4):203–206CrossRefGoogle Scholar
  7. Brouwers L, Riabacke M (2012) Consensus by simulation: a flood model for participatory policy. In: Amendola A, Ermolieva T, Linnerooth-Bayer J, Mechler R (eds) Integrated catastrophe risk modeling: supporting policy processes. Springer, Dordrecent, NetherlandsGoogle Scholar
  8. Brouwers L, Hansson K, Ekenberg L (2002) Simulation of three competing flood management strategies – a case study. In: Ubertini L (eds) Proceedings of applied simulation and modelling (ASM). Applied Simulation and Modelling (ASM 2002), Crete, Greece, 25–28 JuneGoogle Scholar
  9. Brouwers L, Danielson M, Ekenberg L, Hansson K (2004) Multi-criteria decision-making of policy strategies with public-private re-insurance systems. J Risk Decis Policy 9:23–45CrossRefGoogle Scholar
  10. CCFSC (2009) Implementation plan of the national strategy for natural disaster prevention, response and mitigation to 2020. N. 20090929, The Central Committee of Flood and Storm Control Office 6, HanoiGoogle Scholar
  11. Cornwall A, Jewkes R (1995) What is participatory research? Soc Sci Med 41(12):1667–1676CrossRefGoogle Scholar
  12. Danielson M, Ekenberg L (1998) A framework for analysing decisions under risk. Eur J Oper Res 104(3):474–484CrossRefGoogle Scholar
  13. Danielson M, Ekenberg L (2012) A risk-based decision analytic approach to assessing multi-stakeholder policy problems. In: Amendola A, Ermolieva T, Linnerooth-Bayer J, Mechler R (eds) Integrated catastrophe risk modeling: supporting policy processes. Springer, Dordrecent, NetherlandsGoogle Scholar
  14. Danielson M, Ekenberg L, Hansson K, Idefeldt, J, Larsson A, Påhlman M, Riabacke A, Sundgren, D (2006) Cross-disciplinary research in analytic decision support systems. In: Proceedings of the 28th international conference on information technology interfaces, IEEE ITI. Cavtatm, DubrovnikGoogle Scholar
  15. Danielson M, Ekenberg L, Larsson A (2007) Distribution of expected utility in decision trees. Int J Approx Reason 46(2):387–407CrossRefGoogle Scholar
  16. De Silva N (2003) Preparedness and response for cultural heritage disasters in developing countries. In: International symposium proceedings of cultural heritage disaster preparedness and response, Hyderabad, India, 23–27 November, pp 223–226Google Scholar
  17. Ekenberg L, Brouwers L, Danielson M, Hansson K, Johansson J, Riabacke A, Vári A (2003) Flood risk management policy in the upper Tisza Basin: a system analytical approach – simulation and analysis of three flood management strategies. International Institute for Applied Systems Analysis, Interim report IR-03-003, Laxenburg, AustriaGoogle Scholar
  18. French JG, Holt KW (1989) Floods. In: Gregg MB (ed) The public health consequences of disasters. US Department of Health and Human Services, Public Health Service, CDC, Atlanta, pp 69–78Google Scholar
  19. Ghesquiere F, Mahul O (2007) Sovereign natural disaster insurance for developing countries: a paradigm shift in catastrophe risk financing. Hazard Risk Management Unit, Working paper 4345, The World Bank, Washington, DCGoogle Scholar
  20. GlobalAgRisk (2009) Designing agricultural index insurance in developing countries: a GlobalAgRisk market. Development model handbook for policy and decision makers, Lexington, KYGoogle Scholar
  21. GSO (2005) Statistics documentation centre. General Statistics Office of Vietnam, HanoiGoogle Scholar
  22. Hansson K, Ekenberg E (2002) Flood mitigation strategies for the Red River Delta. In: Proceedings of the international conference on environmental engineering, Niagara Falls, CanadaGoogle Scholar
  23. Hansson K, Ekenberg L, Danielson M (2006) Implementation of a decision theoretical framework: a case study of the Red River Delta in Vietnam. In: Proceedings of the 19th international Florida AI research society conference. AAAI Press, Menlo ParkGoogle Scholar
  24. Hansson K, Danielson M, Ekenberg L (2008) A framework for evaluation of flood management strategies. J Environ Manage 86(3):465–480CrossRefGoogle Scholar
  25. Hosking A (2004) The principles of stakeholder engagement and consultation in flood and coastal erosion risk management. Halcrow Group Limited and Flood Management Division, DERFA. http://www.defra.gov.uk/environ/fcd/policy/strategy/staking.pdf. Accessed 11 June 2006
  26. Huq S (2004) Bangladesh floods: rich nations ‘Must Share the Blame’, science and development network, 9 August. http://www.scidev.net/Editorials/index.cfm?fuseaction=readEditorials&itemid=125&language=1. Accessed 2 Aug 2006
  27. ICOLD (1997) The international commission on large dams. Position paper on dams and environment. http://www.icold-cigb.net/chartean.html. Accessed 1 Aug 2006
  28. IMECH/NIAPP (2005) Report 4. Case study of ECLAC’s methodology (Draft). In: Roundtable workshop on assessing socio-economic impact of flood in Vietnam Institute of Mechanics and National Institute for Agricultural Policy and Planning, HanoiGoogle Scholar
  29. Johnson C (2005) Neurological channelopathy in chronic fatigue syndrome (ME/CFS). http://phoenix-cfs.org/NeurologicalChannelopathy.htm. Accessed 3 Mar 2009
  30. Kondo H, Seo N, Yasuda T, Hasizume M, Koido Y, Ninomiya N, Yamamoto Y (2002) Post flood – infectious diseases in Mozambique. Prehosp Disaster Med 17:126–133Google Scholar
  31. Larsson A, Johansson J, Ekenberg L, Danielson M (2005) Decision analysis with multiple objectives in a framework for evaluating imprecision. Int J Uncertain Fuzz Knowl-Based Syst 13(5):495–509CrossRefGoogle Scholar
  32. Lee SL, Krishnapillay B (2003) Forest genetic resources conservation and management. In: Luoma-aho T et al (eds) Proceedings of the Asia Pacific forest genetic resources programme (APFORGEN) inception workshop. IPGRI-APO, Kepong, Kuala Lumpur, Malaysia, 15–18 JulyGoogle Scholar
  33. Linkov I, Satterstrom FK, Kiker G, Seager TP, Bridges TS, Gardner KH, Rogers SH, Meyer A (2006) Multicriteria decision analysis: a comprehensive decision approach for management of contaminated sediments. Risk Anal 26(1):61–78CrossRefGoogle Scholar
  34. Linnerooth-Bayer J, Vári A, Brouwers L (2012) Designing a flood management and insurance system in Hungary: a model-based stakeholder approach. In: Amendola A, Ermolieva T, Linnerooth-Bayer J, Mechler R (eds) Integrated catastrophe risk modeling: supporting policy processes. Springer, Dordrecent, NetherlandsGoogle Scholar
  35. Linnerooth-Bayer, J., Ermoliev, Y., Ermolieva, T., Galambos, I. Flood risk management in Hungary’s Upper Tiszabasin: the potential use of a flood catastrophe model. American Geophysical Union, Spring meeting (2001).Google Scholar
  36. Matsatsinis NF, Samaras AP (2001) MCDA and preference disaggregation in group decision support systems. Eur J Oper Res 130(2):414–429CrossRefGoogle Scholar
  37. Miao Z, Trevisan M, Capri E, Padovani L, Del Re AA (2004) Uncertainty assessment of the model RICEWQ in Northern Italy. J Environ Qual 33(6):2217–2228CrossRefGoogle Scholar
  38. MMWR (2003) Morbidity and mortality weekly report. Public health for consequences of a flood disaster 42(34):653–656. http://www.cdc.gov/mmwr/index.html. Accessed 20 May 2006
  39. Phillips L (2002) Creating more effective research and development portfolios. London School of Economics and Political Science. http://www.catalyze.co.uk/R&D%20Portfolios.pdf. Accessed 2 Aug 2006
  40. Riabacke M, Danielson M, Ekenberg L, Larsson A (2009) A prescriptive approach for eliciting imprecise weight statements in an MCDA process. In: Proceedings of 1st international conference on algorithmic decision theory. Venice, ItalyGoogle Scholar
  41. Rice J (1994) Mathematical statistics and data analysis, 2nd edn. Duxbury, Belmont Calif., USAGoogle Scholar
  42. Shaman J, Day JF (2005) Achieving operational hydrologic monitoring of mosquitoborne disease. Emerg Infect Dis [serial on the internet]. http://www.cdc.gov/ncidod/EID/vol11no09/05-0340.htm. Accessed 1 Aug 2006
  43. SWECO/WL (2005) Flood risk assessment for Bac Hung Hai Polder. 2nd RedRiver basinsector project. Report part a: water resources management. Project number 30292-03. Asian development bank (ADB),Viet NamGoogle Scholar
  44. UN United Nations Viet Nam (2010) Annual report. Hoan Kiem, Ha Noi, Vietnam, JuneGoogle Scholar
  45. UNDP (1998) Support to the disaster management system in Vietnam. United Nations Development Programme, HanoiGoogle Scholar
  46. UNDP (2002) UNDP’s statement on the international disaster reduction day: on disaster reduction for sustainable mountain development. J Ryan. United Nations Development Programme, HanoiGoogle Scholar
  47. US Environmental Protection Agency (2006) Mosquitoes and the diseases they can carry. Last updated on Tuesday, May 2nd. http://www.epa.gov/pesticides/health/mosquitoes/about_mosquitoes.htm. Accessed 20 June 2006
  48. Valcárcel V (2004) Job opportunities arise from Colombia’s floodwaters. International federation of Red Cross and Red Crescent societies. 16 November. http://www.ifrc.org/docs/news/04/04111601/. Accessed 22 July 2006
  49. van Ogtrop F, Hoekstra F, Arjen Y, van der Meulen F (2005) Flood management in the lower Incomati river basin,Mozambique, two alternatives. J Am Water Resour Assoc 41(3):607–619CrossRefGoogle Scholar
  50. Vári A, Linnerooth-Bayer J, Ferencz Z (2003) Stakeholder views on flood risk management inHungary’s upperTiszabasin. Risk Anal 23(3):585–600CrossRefGoogle Scholar
  51. Viljoen MF, du Plessis LA, Booysen HJ (2001) Extending flood damage assessment methodology to include sociological and environmental dimensions. J Water SA 27(4):517–522Google Scholar
  52. Vituki Plc (2000) Summary of cyanide contamination on the Tisza River. http://www.tiszariver.com/index.php?s=results. Accessed 20 Jan 2009
  53. Virola RA, Estrella V, Domingo EV, Amoranto GV, Lopez-Dee EP (2008) Gearing a national statistical system, towards the measurement of the Impact of climate change: the case of the Philippines. Conference on climate change and official statistics. Norway, 14–16 AprilGoogle Scholar
  54. VUFO-NGO (2006) Resource centre Vietnam. Climate change working group/disaster management working group coordinator. http://www.ngocentre.org.vn. Accessed 16 Nov 2011
  55. Watson-Smyth K (2000) Red Cross aims to reunite shattered families. Wednesday, 30 August 2000 in the independent. independent.co.uk. Accessed 2 Apr 2009Google Scholar
  56. West B, Jacobs K, Breazeale L (2006) Disaster relief. Minimizing wildlife problems after a flood. Forest and wildlife research center. Mississippistate university, information sheets, IS1786Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Karin Hansson
    • 1
  • Mats Danielson
    • 1
  • Love Ekenberg
    • 1
  • Joost Buurman
    • 2
  1. 1.Department of Computer and Systems SciencesStockholm UniversityStockholmSweden
  2. 2.Singapore-Delft Water AllianceNational University of SingaporeSingaporeSingapore

Personalised recommendations