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Agent-Based Socio-Hydrological Hybrid Modeling for Water Resource Management

Author

Listed:
  • Joseph Bakarji

    (Stanford University)

  • Daniel O’Malley

    (Los Alamos National Laboratory)

  • Velimir V. Vesselinov

    (Los Alamos National Laboratory)

Abstract

Hybrid socio-hydrological modeling has become indispensable for managing water resources in an increasingly unstable ecology caused by human activity. Most work on the subject has been focused on either qualitative socio-political recommendations with an unbounded list of vague factors or complex sociological and hydrological models with many assumptions and specialized usability. In this paper, we propose a simple agent-based socio-hydrological decision modeling framework for coupling dynamics associated with social behavior and groundwater contamination. The study shows that using social health risk, instead of contaminant concentration, as an optimization variable improves water management decisions aimed at maximizing social wellbeing. The social models and computational framework are designed with enough flexibility and simplicity to encourage extensions to more general socio-hydrological dynamics without compromising either computability or complexity for better data-/model-driven environmental management.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:12:d:10.1007_s11269-017-1713-7
    DOI: 10.1007/s11269-017-1713-7
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    References listed on IDEAS

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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.
    2. Thomas Berger & Regina Birner & Nancy Mccarthy & JosÉ DíAz & Heidi Wittmer, 2007. "Capturing the complexity of water uses and water users within a multi-agent framework," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(1), pages 129-148, January.
    3. Ilke Borowski & Matt Hare, 2007. "Exploring the Gap Between Water Managers and Researchers: Difficulties of Model-Based Tools to Support Practical Water Management," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(7), pages 1049-1074, July.
    4. Xiao-Chen Yuan & Yi-Ming Wei & Su-Yan Pan & Ju-Liang Jin, 2014. "Urban Household Water Demand in Beijing by 2020: An Agent-Based Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(10), pages 2967-2980, August.
    5. 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.
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    2. 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.
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