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Updated: Jan 31, 2026

Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
Development of a model to simulate soil heavy metals lateral migration quantity based on SWAT in Huanjiang watershed,
Pengwei Qiao1, Mei Lei2, Sucai Yang3
1Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China; Beijing Key Laboratory of Remediation of Industrial Pollution Sites, Environmental Protection Research Institute of Light Industry, Beijing 100089, China.
Abstract:
Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity of heavy metals. A model for heavy metal migration simulation was developed based on the SWAT (Soil and Water Assessment Tool) model. This model took into consideration the influence of soil pH value, soil particle size, runoff volume, sediment amount, concentration of water-soluble heavy metals dissolved in runoff and insoluble absorbed to the soil particles. This model was reasonable in Huanjiang watershed, Guangxi Zhuang Autonomous Region, south China, covering an area of 273 km2. The optimal drainage area threshold was determined by analyzing the effects of watershed subdivision on the simulation results to ensure the simulation accuracy. The main conclusions of this paper were: (1) watershed subdivision could affect simulation migration quantity of heavy metals; (2) the quantity of heavy metals transported by sediment accounted for 97%-99% of the total migration quantity in the study watershed. Therefore, sediment played the most important role in heavy metal migration; (3) the optimal drainage area threshold percentage to ensure high simulation accuracy was determined to be 2.01% of the total watershed; (4) with the optimal threshold percentage, this model could simulate the migration quantity of As, Pb and Cd accurately at the total watershed and sub-watershed level. The results of this paper were useful for identifying the key regions with heavy metal migration.
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