Application of GAs and GIS in Xin’anjiang Model
首发时间:2009-10-16
Abstract:Generally, in Xin’anjiang model, the basin is divided into a set of sub-basins by Thiessen method so that the spatial distribution of rainfall can be taken account, which the same recession constants of runoff concentration are used in all sub-basins. It can be seen that topography is not taken account. However, it is well known that the runoff concentration behaviors of basin largely depended on topographic characteristic. And also it adopts a traditional method to make parameters calibration and optimization which takes on uncertain factor. The paper make use of GIS to carve up sub-basins and genetic algorithm to make parameters calibration and optimization, and the application results in Dapoling River Basin show that the number of flood with the qualified rate of error of peak-time increased to 100% from 90%, and excellent rate increased to 30% from 20%, and that with relative error of peak of less than 5% increased to 50% from 30%.
keywords: Xin’anjiang Model Genetic Algorithm DEM parameter optimization
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Application of GAs and GIS in Xin’anjiang Model
摘要:Generally, in Xin’anjiang model, the basin is divided into a set of sub-basins by Thiessen method so that the spatial distribution of rainfall can be taken account, which the same recession constants of runoff concentration are used in all sub-basins. It can be seen that topography is not taken account. However, it is well known that the runoff concentration behaviors of basin largely depended on topographic characteristic. And also it adopts a traditional method to make parameters calibration and optimization which takes on uncertain factor. The paper make use of GIS to carve up sub-basins and genetic algorithm to make parameters calibration and optimization, and the application results in Dapoling River Basin show that the number of flood with the qualified rate of error of peak-time increased to 100% from 90%, and excellent rate increased to 30% from 20%, and that with relative error of peak of less than 5% increased to 50% from 30%.
关键词: Xin’anjiang Model;Genetic Algorithm;DEM;parameter optimization
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No.3587621817312556****
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Application of GAs and GIS in Xin’anjiang Model
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