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Managing Water Resources Conflicts: Modelling Behavior in a Decision Tool

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  • Masih Akhbari
  • Neil Grigg

Abstract

While technical tools for analysis of water resources systems have advanced, the major issue in resolving problems focuses on the interaction of human and natural systems. Agent-based modeling (ABM) has recently been used as an effective tool to develop integrated human-environmental models. One of the main challenges of ABM application in water resources management is to identify and characterize key agents. We provided recommendations to characterize agents normally involved in water decisions, and developed a framework for a conflict management tool, comprised of three models: a watershed simulation, an optimization, and a behavioral simulation model. The optimization-simulation model determined tradeoffs between the objective functions. The behavioral simulation model, developed based on ABM, simulated stakeholders interactions and their reactions to water allocation decisions. This model evaluated the applicability of different management scenarios to achieve specific rates of reduction in agricultural water allocations, selected from the tradeoffs. To develop and adjust this model, key stakeholders were identified in the San Joaquin River (SJR) watershed, California, and a survey was administered. The proposed recommendations and framework provides a new and innovative way to identify institutional interconnections, formulate and simulate their interactions, and create a hydrologic-environmental-human interface to support powerful decision-support tools to manage conflicts and make informed, practical decisions in water resources. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Masih Akhbari & Neil Grigg, 2015. "Managing Water Resources Conflicts: Modelling Behavior in a Decision Tool," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5201-5216, November.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:14:p:5201-5216
    DOI: 10.1007/s11269-015-1113-9
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    1. Masih Akhbari & Neil Grigg, 2013. "A Framework for an Agent-Based Model to Manage Water Resources Conflicts," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(11), pages 4039-4052, September.
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    3. Joseph Bakarji & Daniel O’Malley & Velimir V. Vesselinov, 2017. "Agent-Based Socio-Hydrological Hybrid Modeling for Water Resource Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(12), pages 3881-3898, September.
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    5. Jiali Gu & Shikun Sun & Yubao Wang & Xiaojuan Li & Yali Yin & Jingxin Sun & Xinyu Qi, 2021. "Sociohydrology: An Effective Way to Reveal the Coupled Evolution of Human and Water Systems," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(14), pages 4995-5010, November.
    6. Farhadi, Saber & Nikoo, Mohammad Reza & Rakhshandehroo, Gholam Reza & Akhbari, Masih & Alizadeh, Mohammad Reza, 2016. "An agent-based-nash modeling framework for sustainable groundwater management: A case study," Agricultural Water Management, Elsevier, vol. 177(C), pages 348-358.
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    9. Nafiseh Bahrami & Mohammad Reza Nikoo & Ghazi Al-Rawas & Khalifa Al-Jabri & Amir H. Gandomi, 2023. "Optimal Treated Wastewater Allocation Among Stakeholders Based on an Agent-based Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 135-156, January.
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