From individual Fuzzy Cognitive Maps to Agent Based Models: Modeling multi-factorial and multi-stakeholder...

Area of Science:

• Social-Ecological Systems (SESs)
• Environmental Policy
• Agricultural Management

Background:

• Policy making for complex Social-Ecological Systems (SESs) requires integrated approaches to account for system behavior and stakeholder interventions.
• Water scarcity in Rafsanjan, Iran, poses significant challenges to the local farming community.

Purpose of the Study:

• To simulate the impacts of different policy options on a farming community facing water scarcity.
• To develop and apply an integrated modeling methodology for policy analysis in SESs.

Main Methods:

• Combined Agent-Based Modeling (ABM) with Fuzzy Cognitive Mapping (FCM) to capture farmer behavior and environmental causalities.
• Utilized both qualitative (farmers' knowledge) and quantitative (empirical data) for FCM development.
• Simulated policy impacts on groundwater use and farmer emigration against a baseline scenario.

Main Results:

• A policy promoting farmers' participation in groundwater management led to the greatest reduction in water use.
• This participatory policy also helped secure the long-term viability of farming activities in the region.
• The integrated approach effectively addressed causal relationships, feedback mechanisms, social-spatial heterogeneity, and temporal dynamics.

Conclusions:

• Integrated modeling using ABM and FCM provides a robust framework for ex-ante policy analysis in SESs.
• Empowering farmers in water resource management is a critical policy intervention for arid agricultural communities.
• The study highlights the effectiveness of participatory approaches in mitigating water scarcity impacts.