In recent years,flood disasters have occurred frequently,and flood forecasting is an important non-engineering way to effectively prevent and resist mountain torrent disasters,and provide vital decision-making basis for watershed flood warning. Real-time correction method can effectively improve the accuracy of flood forecasting. In this paper,three typical small and medium-sized watersheds in Hubei Province( Gaojiayan,Xiheyi,Yuyangguan) are used as research areas. Based on the Time Variant Gain Model,the model prediction results are corrected in real-time by recursive least square method with variable forgetting factor. The results show that the average Nash efficiency coefficient of flood forecasting in three watersheds is 0.78 before being corrected. After a real-time correction,the Nash efficiency coefficients of the three basins are all above 0.90,and the peak time forecast qualification rates and the peak flow forecast qualification rates are all up to Grade B or above. The forecast accuracy has been significantly improved.
China Rural Water and Hydropower
time variant gain model