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Updated: Dec 23, 2025

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Optimize the spatial distribution of crop water consumption based on a cellular automata model: A case study of the
Liuyue He1, Jianxia Bao2, Andre Daccache3
1Center for Agricultural Water Research in China, China Agricultural University, Beijing 100083, China; Department of Biological and Agricultural Engineering, University of California Davis, California 95616, USA.
Abstract:
Globally, agriculture is by far the largest water consuming sector and in areas where water is scarce, the spatial optimization of crop water consumption used to improve irrigation benefits becomes critical for regional water management. The spatial heterogeneity of environmental parameters brings great challenge to spatial optimization. Therefore, cellular automaton (CA), crop suitability (CS), spatial distributed crop water consumption model and optimization model were integrated and applied on the middle reaches of Heihe River basin, northwest of China. The cellular automata based Water Consumption Optimization (CA-WCSO) model is not only a spatial dynamic optimization model for crop water consumption, but also a decision support tool that reflects the interaction between water consumption at field level and management regulations at regional level. Six optimization paths: i) forward progressive (FP), ii) forward interlacing (F-IL), iii) forward interpolation (F-IP), iv) reverse progressive (R-P), v) reverse interlacing (R-IL) and vi) reverse interpolation (R-IP) of crop water consumption for the baseline year and the planning year were applied on the study site. Results for baseline year (2015) demonstrate that the six optimization paths can slightly reduce the water consumption (>1.4%) but significantly improve the irrigation benefits of the region by 20.56%. Using CA-WCSO model, decision makers can modify model's constraints and select appropriate optimization path to get the optimized crop planting patterns and make future regional water allocation plans.
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