Abstract
In water resource management, assessing water resource allocation scenarios (WRASs) is an important multi-attribute decision making (MADM) problem. It involves spatially varied indicators, which interact with each other and impacts of the scenarios. These attributes are often simplified by using conventional Decision Support Systems (DSSs). In present research, a novel interactive spatial DSS for assessment of WRASs was developed. Effects of indicators type, decision matrix structures, and MADM models on priorities and ranks of scenarios were investigated in Aras basin. Sensitivity analysis of results showed that the interactive structure, comprising spatially distributed indicators and analytical network process (SANP), was the most stable model in terms of ranking. Providing more realistic results, the developed SDSS can be applied in other basins or for other MADM problems.
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Afshar A, Mariño MA, Saadatpour M, Afshar A (2011) Fuzzy TOPSIS multi-criteria decision analysis applied to Karun reservoirs system. Water Resour Manag 25(2):545–563. https://doi.org/10.1007/s11269-010-9713-x
Brirhet H, Benaabidate L (2016) Comparison of two hydrological models (lumped and distributed) over a pilot area of the Issen watershed in the Souss basin, Morocco. Eur Sci J 12(18):347. https://doi.org/10.19044/esj.2016.v12n18p347
Calizaya A, Meixner O, Bengtsson L, Berndtsson R (2010) Multi-criteria decision analysis (MCDA) for integrated water resources management (IWRM) in the Lake Poopo basin, Bolivia. Water Resour Manag 24(10):2267–2289. https://doi.org/10.1007/s11269-009-9551-x
Cenesta (2016) Participatory planning for comprehensive development of Moghan plain, report on the determination of the structure and tribal area of nomadic peoples (in Persian)
Cornell G, Morrison J (2008) Programming VB. Net: a guide for experienced programmers (.Net developer). http://www.aroundmyhouseconsignment.com
Dodge Y (2008) The concise encyclopedia of statistics. Springer Science and Business Media, Neuchatel
Fotovatikhah F, Herrera M, Shamshirband S et al (2018) Survey of computational intelligence as basis to big flood management: Challenges, research directions and future work. Eng Appl Comput Fluid Mech 12(1):411–437. https://doi.org/10.1080/19942060.2018.1448896
GWP (2009) A handbook for integrated water resources management in basins, Available at: www.gwpforum.org
Hajkowicz S, Higgins A (2008) A comparison of multiple criteria analysis techniques for water resource management. Eur J Oper Res 184(1):255–265. https://doi.org/10.1016/j.ejor.2006.10.045
Hawaiian Agronomics and Agronomic (1975) Master plan of Moghan region farm corporations project, executive summary, (1) :1-335
Kim Y, Chung ES (2014) An index-based robust decision making framework for watershed management in a changing climate. Sci Total Environ 473:88–102. https://doi.org/10.1016/j.scitotenv.2013.12.002
Labadie J (1995) MODSIM: river basin network flow model for conjunctive stream-aquifer management. Program User Manual and Documentation, Colorado State University
Liou JJ, Tzeng GH (2012) Comments on multiple criteria decision making (MCDM) methods in economics: an overview. Technol Econ Dev Econ 18(4):672–695. https://doi.org/10.3846/20294913.2012.753489
Liu P, Qian H, Wu J, Chen J (2013) Sensitivity analysis of TOPSIS method in water quality assessment I: sensitivity to the parameter weights. Environ Monit Assess 185(3):2453–2461. https://doi.org/10.1007/s10661-012-2723-9
Mahab Ghodss (2009) Comprehensive water plan of Khazar basin report (2385070.2050.23352): 1-123 (in Persian)
Malczewski J (2006) GIS-based multi-criteria decision analysis: a survey of the literature. Int J Geogr Inf Sci 20(7):703–726. https://doi.org/10.1080/13658810600661508
Montazar A, Snyder RL (2012) A multi-attribute preference model for optimal irrigated crop planning under water scarcity conditions. Span J Agric Res 10(3):826–837. https://doi.org/10.5424/sjar/2012103-484-11
Opricovic S (2011) Fuzzy VIKOR with an application to water resources planning. Expert Syst Appl 38(10):12983–12990. https://doi.org/10.1016/j.eswa.2011.04.097
Prodanovic P, Simonovic SP (2002) Comparison of fuzzy set ranking methods for implementation in water resources decision making. Can J Civ Eng 29(5):692–701. https://doi.org/10.1139/l02-063
Radmehr A, Araghinejad S (2014) Developing strategies for urban flood management of Tehran city using SMCDM and ANN. J Comput Civ Eng 28(6):05014006. https://doi.org/10.1061/(ASCE)CP.1943-5487.0000360
RazaviToosi SL, Samani JM (2016) Evaluating water management strategies in watersheds by new hybrid fuzzy analytical network process (FANP) methods. J Hydrol 534:364–376. https://doi.org/10.1016/j.jhydrol.2016.01.006
Saaty TL (1996) Decision making with dependence and feedback. the analytic network process. RWS Publication, Pittsburgh
Saaty TL (2012) Decision making for leaders: the analytic hierarchy process for decisions in a complex world, 3rd revised edition. RWS Publications, Pittsburgh
Simonovic SP (2002) A spatial fuzzy compromise programming for management of natural disasters. Institute for Catastrophic Loss Reduction, London
Taormina R, Chau KW, Sivakumar B (2015) Neural network river forecasting through baseflow separation and binary-coded swarm optimization. J Hydrol 529:1788–1797. https://doi.org/10.1016/j.jhydrol.2015.08.008
Tiwari DN, Loof R, Paudyal GN (1999) Environmental–economic decision making in lowland irrigated agriculture using multi-criteria analysis techniques. Agric Syst 60(2):99–112. https://doi.org/10.1016/S0308-521X(99)00021-9
Triantaphyllou E, Sanchez A (1997) A sensitivity analysis approach for some deterministic multi-criteria decision making methods. Decis Sci 28(1):151–194. https://doi.org/10.1111/j.1540-5915.1997.tb01306.x
UN-Water Activity Information System (2007) Kura-Aras river basin transboundary diagnostic analysis. RER/03/G41/A/1G/31. http://www.ais.unwater.org
Vafaei N, Ribeiro RA, Camarinha-Matos LM (2016) Normalization techniques for multi-criteria decision making: analytical hierarchy process case study. In doctoral conference on computing, electrical and industrial systems 261-269. https://doi.org/10.1007/978-3-319-31165-4_26
Wang WC, Xu DM, Chau KW et al (2013) Improved annual rainfall-runoff forecasting using PSO–SVM model based on EEMD. J Hydroinf 15(4):1377–1390. https://doi.org/10.2166/hydro.2013.134
Yang JS, Chung ES, Kim SU et al (2012) Prioritization of water management under climate change and urbanization using multi-criteria decision making methods. Hydrol Earth Syst Sci 6(3):801–814. https://doi.org/10.5194/hess-16-801-2012
Yilmaz B, Harmancioglu N (2010) Multi-criteria decision making for water resource management: a case study of the Gediz river basin, Turkey. Water SA 36(5). https://doi.org/10.4314/wsa.v36i5.61990
Zarghami M, Abrishamchi A, Ardakanian R (2008) Multi-criteria decision making for integrated urban water management. Water Resour Manag 22(8):1017–1029. https://doi.org/10.1007/s11269-007-9207-7
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Sarband, E.M., Araghinejad, S. & Attari, J. Developing an Interactive Spatial Multi-Attribute Decision Support System for Assessing Water Resources Allocation Scenarios. Water Resour Manage 34, 447–462 (2020). https://doi.org/10.1007/s11269-019-02291-y
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DOI: https://doi.org/10.1007/s11269-019-02291-y