Simulation of rainfall-underground outflow responses of a karstic watershed in Southwest China with an artificial neural network

查看全文 作　　者：Chen Xi Chen Cai Hao Qingqing Zhang Zhicai Shi [1]Peng

机构地区：[1]State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing210098, P. R. China

出　　处：《Water Science and Engineering》索引2008年第1卷第2期,共9页

基　　金：supported by the National Basic Research Program of China (973 Program, Grant No 2006CB403200);the National Natural Scientific Foundation of China (Grant No 50679025);the 111 Project of the Ministry of Education and the State Administration of Foreign Expert Affairs, China (Grant No. B08048) 摘　　要：Karstic aquifers in Southwest China are largely located in mountainous areas and groundwater level observation data are usually absent. Therefore, numerical groundwater models are inappropriate for simulation of groundwater flow and rainfall-underground outflow responses. In this study, an artificial neural network (ANN) model was developed to simulate underground stream discharge. The ANN model was applied to the Houzhai subterranean drainage in Guizhou Province of Southwest China, which is representative of karstic geomorphology in the humid areas of China. Correlation analysis between daily rainfall and the outflow series was used to determine the model inputs and time lags. The ANN model was trained using an error backpropagation algorithm and validated at three hydrological stations with different karstic features. Study results show that the ANN model performs well in the modeling of highly non-linear karstic aquifers. 关键词：人工神经网络模型中国西南部岩溶流域反应降雨岩溶含水层仿真水位观测资料

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Simulation of rainfall-underground outflow responses of a karstic watershed in Southwest China with an artificial neural network

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