Multiple criteria decision making and decision support systems for flood risk management. (English) Zbl 1120.90343

Summary: Multiple criteria decision making (MCDM) is a collection of methodologies to compare, select, or rank multiple alternatives that typically involve incommensurate attributes. MCDM is well-suited for eliciting and modeling the flood preferences of stakeholders and for improving the coordination among flood agencies, organizations and affected citizens. A flood decision support system (DSS) architecture is put forth that integrates the latest advances in MCDM, remote sensing, GIS, hydrologic models, and real-time flood information systems. The analytic network process (ANP) is discussed with application to short-term flood management options for the middle reaches of the Yangtze River. It is shown that DSS and MCDM can improve flood risk planning and management under uncertainty by providing data displays, analytical results, and model output to summarize critical flood information.


90B50 Management decision making, including multiple objectives
86A05 Hydrology, hydrography, oceanography


Full Text: DOI


[1] Al-Sabhan W, Mulligan M, Blackburn GA (2003) A real-time hydrological model for flood prediction using GIS and the WWW. Comput Environ Urban Syst 27:9-32
[2] Barton I, Bathols J (1989) Monitoring floods with AVHRR. Int J Remote Sensing 10:1873-1892
[3] Brans JP, Vincke P, Mareschal B (1986) How to select and how to rank projects: the PROMETHEE method. Manage Sci 31:647-656 · Zbl 0576.90056
[4] Carlsson C, Turban E (2002) DSS: directions for the next decade. Decis Support Syst 33:105-110
[5] Casale R, Samuels PG (1998) Hydrological risks: analysis of recent results from EC research and technological development actions. Directorate-General Science, Research and Development, Environment and Climate Programme, European Commission
[6] Clark MJ (1998) Putting water in its place: a perspective on GIS in hydrology and water management. Hydrol Processes 12:823-834
[7] Deutsch M, Ruggles F, Guss P, Yost E (1973) Mapping the 1973 Mississippi floods from the Earth Resource Technology satellites. In: Proceedings of international symposium on remote sensing and water resource management, (Burlington, American Water Resources Association Ontario)
[8] Dingfei L, Stewart TJ (2004) Object-oriented decision support system modelling for multicriteria decision making in natural resource management. Comput Oper Res 31:985-999 · Zbl 1046.90534
[9] Easterling DR, Evans JL, Groisman PY, Karl TR, Kunkil KE, Ambenjen P (1999) Observed variability and trends in severe weather climate events: a brief review. Bull Amer Meteor Soc 81:417-425
[10] Eom SB (1999) Decision support systems research: current state and trends. Ind Manage Data Syst 5:213-220
[11] Feldman AD (1981) HEC Models for Water Resources System Simulation: Theory and Experience. Advances in hydroscience, vol 12. Academic, New York, pp 297-423
[12] Frank, AU; Medyckyj-Scott, D. (ed.); Hearnshaw, H. (ed.), The use of geographical information system: the user interface is the system (1993), London
[13] Haimes YY, Hall WA (1974) Multi-objectives in water resources systems analysis: the surrogate worth trade-off method. Water Resources Res 10:615-624
[14] Hipel KW (1992) Multiple objective decision making in water resources. Water Resource Bull 28(1):1-8
[15] Hwang CL, Yoon K (1981) Multiple attribute decision making methods and applications. Springer, Berlin Heidelberg New York
[16] Islam MM, Sadu K (2002) Development of priority map remote sensing data for flood counter measures by Geographic Information System. J Hydrol Eng 7:346-355
[17] Kingston S, Carver S, Evans A, Turton I (2000) Web-based public participation geographical information systems: an aid to local environment decision-making. Comput Environ Urban Syst 24:109-122
[18] Labadie JW, Sullivan CH (1986) Computerized Decision Support Systems for Water Managers. J Water Resource Plan Manage ASCE 112:299-307
[19] Lekuthai A, Vongvisessomjai S (2001) Intangible flood damage quantification. Water Resource Manage 15:343-362
[20] Loucks DP (1996) Developing and implementing decision support systems: a critique and challenge. Water Resource Bull 31:571-582
[21] Loucks DP, da Costa JR (eds) (1991) Decision support systems: water resources planning, NATO ASI series. Springer, Berlin Heidelberg New York, pp 87-96
[22] Miller RC, Guertin DP, Heilman P (2004) Information technology in watershed management decision making. J Am Water Resource Assoc 40:347-358
[23] Mysiak J, Giupponib C, Rosatoc P (2005) Towards the development of a decision support system for water resource management. Environ Model Softw 20:203-214
[24] Plate EJ (2002) Flood risk and flood management. J Hydrol 267:2-11
[25] Raju KS, Pillai CRS (1999) Multicriterion decision making in river basin planning and development. Eur J Oper Res 112:249-257 · Zbl 0937.90058
[26] Rango A, Anderson AT (1974) Flood hazard studies in the Mississippi River Basin using remote sensing. Water Resource Bull 10:1060-1081
[27] Roy B (1968) Classement et choix en presence de points de vue multiples, la methode ELECTRE. RIRO 2:57-75
[28] Saaty TL (1980) The analytic hieararchy process. McGraw-Hill, New York
[29] Saaty TL (2000) The fundamentals of decision making and priority theory with the analytic hierarchy process, vol VI, AHP Series. RWS Publications, Pittsburgh
[30] Saaty TL (2001) The analytic network process: decision making with dependence and feedback. RWS Publications, Pittsburgh
[31] Saaty TL (2004) Decision making—the analytic hierarchy and network processes (AHP/ANP). J Syst Sci Syst Eng 13:1-35
[32] Sanyal J, Lu X (2004) Application of remote sensing in flood management with special reference to monsoon asia: a review. Nat Hazards 33:283-301
[33] Schielen RMJ, Gijsbers PJA (2003) DSS-large rivers: developing a DSS under changing societal requirements. Phys Chem Earth 28:635-645
[34] Simonovic SP, Ahmad S (2005) Computer-based model for flood evacuation emergency planning. Nat Hazards 34:25-51
[35] Smith LC (1997) Satellite remote sensing of river inundation area, stage and discharge: a review. Hydrol Processes 11:1427-1439
[36] Soscini-Sessa R, Castelletti A, Weber EA (2003) DSS for planning and managing water reservoir systems. Environ Model Softw 18:395-404
[37] Sprague R (1983) A framework for the development of decision support systems, decision support systems: a data based, model-oriented, user-developed discipline. Petrocelli, Princeton
[38] Stam A, Kazimierz AS, Aronson JE (1998) An interactive reservoir management system for Lake Kariba. Eur J Oper Res IO7:119-136 · Zbl 0943.90593
[39] Todini E (1999) An operational decision support system for flood risk mapping, forecasting and management. Urban Water 1:131-143
[40] Todini E, Marsigli M, Pani G, Vignoli R (1997). Operational UNDRO, 1991. Office of the United Nations Disaster Relief Coordinator: Mitigating natural disasters: phenomena, effects and options. A Manual for Policy Makers and Planners, United Nations, New York
[41] US Army Corps of Engineers (1990) Flood damage analysis package on the microcomputer-installation and user’s guide, TD-31, CEIWR-Hydraulic Engineering Center, Davis
[42] US Army Corps of Engineers (1982) HEC-5 simulation of flood control and conservation systems, user’s manual. CPD-5A, Hydrologic Engineering Center, Davis
[43] US Army Corps of Engineers (1985) Reservoir Systems analysis for Conservation HEC-3 User’s Manual. CPD-3A, Hydrologic Engineering Center, Davis
[44] US Army Corps of Engineers (1986) HEC-5(Q) simulation of flood control and conservation systems; appendix, water quality analysis. Hydrologic Engineering Center, Davis
[45] US Army Corps of Engineers (1987) HEC-DSS user’s guide and utility program manual. Hydrologic Engineering Center, Davis, CA, USA
[46] US Army Corps of Engineers (1997) HEC-FDA flood damage reduction analysis, user’s manual, CPD-72. CEIWR-HEC, Davis
[47] Vermieren JC, Watson CC (2001) New technology for improved storm risk assessment in the Caribbean. Disaster Manage 6:191-196
[48] Wang Y, Colby JD, Mulcahy KA (2002) An efficient method for mapping flood extent in a coastal flood plain using Landsat TM and DEM data. Int J Remote Sensing 23:3681-3696
[49] Wierzbicki AP (2000) Decision support methods and applications: the cross-sections of economics and engineering or environmental issues. Annu Rev Control 24:9-19
[50] Willet K, Sharda R (1991) Using the analytic hierarchy process in water resources planning: selection of flood control projects. Socio-Econ Plan Sci 25:103-112
[51] Wu R, Hu ZZ, Kirtman BP (2003) Evolution of ENSO-related rainfall anomalies in East Asia. J Climate 16:3742-3758
[52] Zeleny M (1982) Multiple criteria decision making. McGraw-Hill, New York · Zbl 0588.90019
[53] Zerger A, Wealands S (2004) Beyond modelling: linking models with GIS for flood risk management. Nat Hazards 33:191-208
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