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<p>Increasing pressures on water resources, exacerbated by ecological, social, and economic challenges, necessitate innovative management strategies, particularly in systems prone to water use conflicts and vulnerability. To address these complexities, innovative modeling techniques that can capture dynamic interactions and support informed decision-making are needed. Fuzzy Cognitive Maps (FCMs) offer a promising approach by integrating stakeholder perspectives to identify and quantify causal relationships among key system factors, enabling “what-if” simulations to endorse changing conditions in favor of risk mitigation. This paper introduces the Quasi-Nonlinear FCM (q-FCM)-based methodology for Water Resources Management (WRM), incorporating stakeholder input to model cause-effect relationships and simulate scenarios. In rural Lissos River basin, representatives from all stakeholder groups collaboratively designed a causal graph encoded into an interconnection matrix. Using the q-FCM approach, three distinct demand and supply scenarios were then modeled by initializing system factors accordingly. The results provide critical insights into the basin’s dynamic behavior, identifying the system balance under different conditions. Simulations consistently showed a shift toward more human-centered trends, with increased water demand resulting in significant environmental impacts. These findings underscore the potential of q-FCM methodology as a valuable decision-support tool for WRM, particularly in complex and conflict-prone basins.</p>

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Participatory Modeling and Scenario Analysis for Managing Mediterranean River Basins Using Quasi-nonlinear Fuzzy Cognitive Maps

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月15日

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  • Christopher Papadopoulos,
  • Thomas Bakas,
  • Marios Tyrovolas,
  • Dionissis Latinopoulos,
  • Ifigenia Kagalou,
  • Mike Spiliotis,
  • Chrysostomos Stylios

摘要

Increasing pressures on water resources, exacerbated by ecological, social, and economic challenges, necessitate innovative management strategies, particularly in systems prone to water use conflicts and vulnerability. To address these complexities, innovative modeling techniques that can capture dynamic interactions and support informed decision-making are needed. Fuzzy Cognitive Maps (FCMs) offer a promising approach by integrating stakeholder perspectives to identify and quantify causal relationships among key system factors, enabling “what-if” simulations to endorse changing conditions in favor of risk mitigation. This paper introduces the Quasi-Nonlinear FCM (q-FCM)-based methodology for Water Resources Management (WRM), incorporating stakeholder input to model cause-effect relationships and simulate scenarios. In rural Lissos River basin, representatives from all stakeholder groups collaboratively designed a causal graph encoded into an interconnection matrix. Using the q-FCM approach, three distinct demand and supply scenarios were then modeled by initializing system factors accordingly. The results provide critical insights into the basin’s dynamic behavior, identifying the system balance under different conditions. Simulations consistently showed a shift toward more human-centered trends, with increased water demand resulting in significant environmental impacts. These findings underscore the potential of q-FCM methodology as a valuable decision-support tool for WRM, particularly in complex and conflict-prone basins.