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合理确定田间尺度土壤水力参数和溶质运移参数是保证农田土壤水盐动态模拟正确性的重要前提。本文开展了基于遗传算法(Genetic Algorithms,GA)与农田水文模型SWAP(Soil-Water-Atmosphere-Plant)耦合进行土壤水力参数和溶质运移参数优化的方法研究。在已有GA基础上引入了子体优生策略,并以完全嵌入方式耦合GA与SWAP模型。采用河套灌区曙光实验站的土壤剖面分层含水率(θi)和溶液浓度(cmli)、表土含水率(θsur)、实际腾发量(ETa)等观测资料,开展了田间尺度土壤水力参数和溶质运移参数优化的数值试验与相应分析。结果表明:(1)采用土壤分层信息(θi和cmli)作为观测数据,GA参数优化效果很好;(2)仅采用ETa作观测数据时,参数优化效果相对欠佳,需慎重使用,而结合ETa与θsur后可提高优化精度;(3)引入子体优生策略可提高GA的参数优化效率和精度。综上,结合GA与SWAP模型是优化田间尺度土壤水力参数和溶质运移参数的一种实用方法。
Reasonable determination of soil hydraulic parameters and solute transport parameters in field scales is an important prerequisite to ensure the correctness of soil-water dynamic simulation in farmland. In this paper, we studied the optimization of soil hydraulic parameters and solute transport parameters based on Genetic Algorithms (GA) and farmland hydrological model SWAP (Soil-Water-Atmosphere-Plant). Based on the existing GA, the eugenics strategy was introduced and the GA and SWAP models were coupled with complete embedding. Based on the observed data of stratified water cut (θi), solution concentration (cmli), surface soil moisture (θsur) and actual evapotranspiration (ETa) of Shuguang experimental station in Hetao Irrigation District, soil hydraulic parameters and solute Numerical Test and Corresponding Analysis on Optimization of Transportation Parameters. The results show that: (1) GA parameters are well optimized by using soil stratification information (θi and cmli) as observation data; (2) When ETa is used as observation data, the optimization results are relatively poor and need to be used with caution The combination of ETa and θsur can improve the precision of the optimization. (3) Introducing the eugenics strategy can improve the efficiency and precision of GA parameter optimization. In summary, combining GA with SWAP model is a practical method to optimize soil hydraulic parameters and solute transport parameters at field scale.