Parameters optimization on DHSVM model based on a genetic algorithm |
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| Authors: | Changqing Yao and Zhifeng Yang |
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| Institution: | (1) Institute of Scientific and Technical Information of China, Beijing, 100038, China;(2) State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China |
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| Abstract: | Due to the multiplicity of factors including weather, the underlying surface and human activities, the complexity of parameter
optimization for a distributed hydrological model of a watershed land surface goes far beyond the capability of traditional
optimization methods. The genetic algorithm is a new attempt to find a solution to this problem. A genetic algorithm design
on the Distributed-Hydrology-Soil-Vegetation model (DHSVM) parameter optimization is illustrated in this paper by defining
the encoding method, designing the fitness value function, devising the genetic operators, selecting the arithmetic parameters
and identifying the arithmetic termination conditions. Finally, a case study of the optimization method is implemented on
the Lushi Watershed of the Yellow River Basin and achieves satisfactory results of parameter estimation. The result shows
that the genetic algorithm is feasible in optimizing parameters of the DHSVM model. |
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| Keywords: | genetic algorithm DHSVM parameters Optimization Yellow River Basin |
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