基于水文要素的闹德海水库入库沙量预测模型

针对水库调度需要,以闹德海水库为背景开展入库沙量预报研究。首先分析水库的入库水沙特性,以确定入库沙量的主要影响因素;进而研究建立基于水文要素的BP神经网络入库沙量预测模型,并利用历史场次洪水资料进行训练学习。结果表明所选择的产沙因子基本能够反映流域降雨-产沙-输沙过程的传递关系,模型可用于入库沙量预报,指导水库实时水沙调度决策。

Prediction model of inflow sediment in Naodehai reservoir based on hydrologic element

The prediction of reservoir sediment can be conducted by the background of Naodehai reservoir so as to meet the need of reservoir operation.The paper first aanalyzed the characteristics of water and sediment in reservoir so as to determine the main factors which affect the sediment storage volume;it further researched to establish sediment storage prediction model based on BP neural network of hydrological factors, and used historical flood data to train and learn. The results showed that the chosen sediment factor can basically reflect the transfer relationship of the processe of rainfall - sediment - sediment transport in the watershed.The model can be used to forecast sediment storage and guide the decision of real-time regulation of reservoir.