Relationship Model Optimization Between Storage Capacity and Water Level of Cascade Reservoirs in Middle Reaches of Shule River

In order to study relationship between storage capacity and water level of cascade reservoir，multi-objective decision-making problem that reservoir was originally responsible for a single irrigation or power generation task has now become a multi-purpose reservoir.Three reservoirs（Changma Reservoir，Shuangta Reservoir and Chijinxia Reservoir）in the middle reaches of the Shule River Basin were selected as research objects.Relationship between reservoir water levels and reservoir capacity of three reservoirs was established using Gaussian function and two types of neural networks model.By comparing root mean square error（RMSE），relative root mean square error（RRMSE）and mean absolute percentage error（MAPE）predicted by different models，performance of the model was evaluated.Results showed that three models could better fit relationship between water level and capacity of three reservoirs.For Changma Reservoir and Shuangta Reservoir，performance of radial basis function neural network（RBF）was better than nonlinear regression model and feed forward back propagation neural network（FBNN）model.For Chijinxia Reservoir，performance of FBNN neural network was better than nonlinear regression and RBF neural network models.Compared with classical regression model，artificial neural network had advantages of high precision and scientific reliability in prediction of reservoir capacity.It was more suitable for determination of reservoir capacity.