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Quantitative Modeling of Human Responses to Changes in Water Resources Availability: A Review of Methods and Theories

Author

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  • Karen S. Meijer

    (Deltares, Boussinesqweg 1, 2629 HV Delft, The Netherlands)

  • Femke Schasfoort

    (Deltares, Boussinesqweg 1, 2629 HV Delft, The Netherlands)

  • Maike Bennema

    (Deltares, Boussinesqweg 1, 2629 HV Delft, The Netherlands)

Abstract

In rural areas in developing countries where livelihoods directly depend on agriculture, shortage of water can have severe socio-economic and humanitarian consequences and has been suggested to result in conflict and migration. Understanding such responses is important for the development of effective water management policies and other interventions. However, despite the availability of extensive knowledge on water-related human behavior, water resources planning studies do not always look beyond direct impacts. Therefore, this paper assesses literature on water-related human responses, the quantification and conceptualization methods and theories used, the scale at which models are applied, and the extent to which findings are used to make policy recommendations. We found system dynamics approaches mostly applied for policy evaluations, but often with a limited integration of human behavior beyond water use; agent-based models seem to be suited for policy analysis, but only limitedly applied for that purpose; and statistical studies to present the widest range of human responses and explanatory factors, but without making the behavioral mechanisms explicit. In fact, only a limited number of studies was based on behavioral theories. Based on these findings we recommend eight steps to facilitate quantification of human responses for water resources planning purposes.

Suggested Citation

  • Karen S. Meijer & Femke Schasfoort & Maike Bennema, 2021. "Quantitative Modeling of Human Responses to Changes in Water Resources Availability: A Review of Methods and Theories," Sustainability, MDPI, vol. 13(15), pages 1-17, August.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:15:p:8675-:d:607820
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