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A Fuzzy-Stochastic Modeling Approach for Multiple Criteria Decision Analysis of Coupled Groundwater-Agricultural Systems

Author

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  • Yohannes Hagos Subagadis

    (TU Dresden, Institute of Hydrology and Meteorology)

  • Niels Schütze

    (TU Dresden, Institute of Hydrology and Meteorology)

  • Jens Grundmann

    (TU Dresden, Institute of Hydrology and Meteorology)

Abstract

The complexity of water resources management increases when decisions about environmental and social issues are considered in addition to economic efficiency. Such complexities are further compounded by multiple uncertainties about the consequences of potential management decisions. In this paper, a new fuzzy-stochastic multiple criteria decision-making approach is proposed for water resources management in which a variety of criteria in terms of economic, environmental and social dimensions are identified and taken into account. The goal is to evaluate multiple conflicting criteria under uncertainties and to rank a set of management alternatives. The methodology uses a simulation-optimization water management model of a strongly interacting groundwater-agriculture system to enumerate criteria based on these bio-physical process interactions. Fuzzy and/or qualitative information regarding the decision-making process for which quantitative data is not available are evaluated in linguistic terms. Afterwards, Monte Carlo simulation is applied to combine these information and to generate a probabilistic decision matrix of management alternatives versus criteria in an uncertain environment. Based on this outcome, total performance values of the management alternatives are calculated using ordered weighted averaging. The proposed approach is applied to a real world example, where excessive groundwater withdrawal from the coastal aquifer for irrigated agriculture has resulted in saltwater intrusion, threatening the economical basis of farmers and associated societal impacts. The analysis has provided potential decision alternatives which can serve as a platform for negotiation and further exploration. Furthermore, sensitivity of different inputs to resulting rankings is investigated. It is found that decision makers’ risk aversion and risk taking attitude may yield different rankings. The presented approach suits to systematically quantify both probabilistic and fuzzy uncertainties associated with complex hydrosystems management.

Suggested Citation

  • Yohannes Hagos Subagadis & Niels Schütze & Jens Grundmann, 2016. "A Fuzzy-Stochastic Modeling Approach for Multiple Criteria Decision Analysis of Coupled Groundwater-Agricultural Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(6), pages 2075-2095, April.
  • Handle: RePEc:spr:waterr:v:30:y:2016:i:6:d:10.1007_s11269-016-1270-5
    DOI: 10.1007/s11269-016-1270-5
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    References listed on IDEAS

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    1. Yue-Ping Xu & Yeou-Koung Tung, 2008. "Decision-making in Water Management under Uncertainty," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(5), pages 535-550, May.
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    7. Ebrahim Ahmadisharaf & Alfred Kalyanapu & Eun-Sung Chung, 2015. "Evaluating the Effects of Inundation Duration and Velocity on Selection of Flood Management Alternatives Using Multi-Criteria Decision Making," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(8), pages 2543-2561, June.
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    2. Shamraiz Ahmad & Kuan Yew Wong & Babar Zaman, 2019. "A Comprehensive and Integrated Stochastic-Fuzzy Method for Sustainability Assessment in the Malaysian Food Manufacturing Industry," Sustainability, MDPI, vol. 11(4), pages 1-23, February.

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