| Cite this article: | 张晓斌,李抗彬,郝改瑞,等.基于BP神经网络的新安江模型初始土壤蓄水量计算研究[J].灌溉排水学报,0,():-. |
| ZHANG Xiaobin,LI Kangbin,HAO Gairui,et al.基于BP神经网络的新安江模型初始土壤蓄水量计算研究[J].灌溉排水学报,0,():-. |
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| Study on Calculation Method of Initial Soil Water Storage of Xin'anjiang Model Based on BP Neural Network |
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ZHANG Xiaobin1, LI Kangbin2, HAO Gairui3, ZHANG Xiaopeng1
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1.Yuncheng University;2.Xi’an Land Water and Electricity Measurement and Control CO.LTD;3.Xi’an University of Technology
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| Abstract: |
| 【Objective】In order to overcome the shortcomings of traditional empirical reduction coefficient method in calculating the initial soil water storage of Xin'anjiang model, and to improve the application effect of Xin'anjiang Model in humid and semi humid areas. 【Methods】 Based on the influencing factors of the initial soil water storage and the characteristics of the neural network model, the calculation method of initial soil water storage of Xin'anjiang model based on BP neural network was proposed in the paper. 【Results】Under the combination of three input factors, when the hidden layer node of BP neural network is greater than 11, the application effect of the model in the simulation training period reaches the first-class level of the project accuracy evaluation index, and 9 samples in the prediction test period, all of which are more than 6 samples qualified; compared with the traditional empirical reduction coefficient method for calculating the initial soil water storage of Xin'anjiang model, the application effect of BP neural network model is obviously superior. 【Conclusion】① it is feasible and applicable to use BP neural network model to calculate the initial soil water storage of Xin'anjiang Model in humid and semi humid areas; ② when the selection of hidden layer nodes of BP neural network is reasonable, the application effect of the calculation method of initial soil water storage of Xin'anjiang model based on BP neural network is better than the traditional empirical reduction coefficient method. ③ In the process of application, this method can overcome the shortcomings of using the empirical reduction coefficient method to calculate the initial soil water storage, which needs to select a rainstorm or a long drought without rain in the basin to start the calculation and the calculation process can’t be interrupted. It provides a new reference method for the initial soil water storage of Xin'anjiang model when it is applied in the humid and semi humid areas. |
| Key words: Initial soil water storage; BP neural network; Xin 'anjiang model; Runoff simulation |
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