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Updated: Sep 17, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Optimizing rainfed cropping patterns for economic and environmental sustainability in East Lorestan Iran using GIS
Zahra Marzban1, Mohamamd Reza Asgharipour2
1Unit of Agroecology, Department of Agronomy, Faculty of Agriculture, University of Zabol, Zabol, Iran.
Abstract:
Under the dual objectives of economic viability and environmental sustainability, sustainable agriculture requires allocating production factors to diverse agricultural activities. The already precarious and unstable position of Iranian agriculture has been exacerbated by excessive reliance on nonrenewable energy and pollution. This study addresses the challenge of unsustainable practices in Iranian rainfed agriculture by recommending a suitable cropping pattern for East Lorestan Province. We integrate Life Cycle Assessment (LCA), Multi-Objective Programming (MOP), and Geographic Information System (GIS) with spatial design to maximize net profit while minimizing environmental impact. The results indicate that the MOP cultivation pattern reduces the global warming potential of the region's rainfed farmlands by 5,980 kg of CO2. Additionally, it increases the net profit by $203,000 while decreasing environmental impacts on human health and ecosystem quality by 9% and 11%, respectively, compared to the current scenario. Land suitability assessment revealed that Doroud has farmlands ecologically suited for diverse crops, while Aligudarz is moderately suitable for most crops. The study emphasizes the importance of integrating environmental considerations into agricultural practices for sustainable regional development. Policymakers can use these results to develop policies that promote sustainable agricultural practices while practitioners can adopt these methods to optimize their cultivation patterns and reduce their environmental impact.
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