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Updated: Dec 11, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Using mixed methods to construct and analyze a participatory agent-based model of a complex Zimbabwean agro-pastoral
M V Eitzel1, Jon Solera2, K B Wilson3
1Science and Justice Research Center, University of California, Santa Cruz, Santa Cruz, CA, United States of America.
This study developed an agent-based model for a Zimbabwean agro-pastoral system, finding that interventions smoothing rainfall variation improved sustainability. The model aids land-use planning and management strategies.
Area of Science:
- Social-ecological systems analysis
- Computational modeling
- Environmental management
Background:
- Social-ecological systems present complex challenges for study and management.
- Participatory modeling enhances stakeholder involvement in developing management strategies.
- Quantitative behavioral validation of simulation models is increasingly feasible with advanced data and models.
Purpose of the Study:
- To collaboratively develop and validate a novel agent-based model (ABM) for a Zimbabwean agro-pastoral system using extensive historical data.
- To assess the model's utility as a discussion tool for researchers and its effectiveness in informing land-use planning and management interventions.
- To investigate the impact of parameter assumptions, indigenous management, and rainfall variability on system dynamics and sustainability.
Main Methods:
- Creation of a novel agent-based model (ABM) using 35 years of data from the Muonde Trust in Zimbabwe.
- Qualitative structural validation through collaborative model calibration with stakeholders.
- Quantitative behavioral validation using community-based data, followed by sensitivity analysis.
Main Results:
- The ABM was successfully structurally validated and deemed a useful discussion tool for researchers.
- Behavioral validation was inconsistent, with some model variables aligning better with field data than others.
- Increasing rainfall variability and certain management interventions led to model system instability; interventions smoothing year-to-year variation enhanced sustainability.
Conclusions:
- The developed ABM provides a realistic and useful tool for exploring social-ecological system dynamics and informing management decisions.
- Management interventions that maintain system feedbacks and buffer against environmental variability are crucial for enhancing sustainability.
- The model facilitated successful advocacy for policy changes in land-use planning, demonstrating its practical application in real-world sustainability efforts.
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