水资源保护2026，Vol.42Issue(3)：72-80,9.DOI:10.3880/j.issn.1004-6933.2026.03.009
考虑水库调蓄影响的洪水预报智能校正方法研究
Research on intelligent correction methods for flood forecasting considering reservoir regulation impacts
摘要
Abstract
To improve basin-scale flood forecasting accuracy and support the integration of flood forecasting and reservoir operation,taking the Jialing River Basin as the study area,an intelligent correction framework for flood forecasting considering reservoir regulation impacts was developed.In the framework,the VIC distributed hydrological model was utilized to simulate the runoff generation and routing processes.The K-nearest neighbor(KNN)algorithm was employed for multi-step extrapolated discharge correction based on historical error similarity.A hierarchical nested long short-term memory(LSTM)model was introduced to predict reservoir outflow:LSTM1 characterized the basic inflow-outflow response,while LSTM2 incorporated water level-storage constraints and water balance principles.Dynamic correction of the entire process was achieved through stage-by-stage coupling across mainstreams,tributaries,and cascade reservoirs.The results show that the VIC model achieves an average NSE of approximately 0.70 and relative errors of 10%～15%at stations with minimal reservoir impact.The KNN correction yields NSE values mostly above 0.90 and relative errors below 10%for short lead times(≤12 h),with sustained improvements for longer lead times.Compared with inflow-outflow balance and parametric operation methods,the LSTM model better characterizes complex nonlinear regulation along the Tingzikou Reservoir-Caojie Station-Beibei sequence,significantly enhancing flood forecasting accuracy.This intelligent correction method significantly reduces simulation errors for both reservoir inflows and downstream control station discharge processes.关键词
VIC模型/洪水预报/长短期记忆网络/水库调度/嘉陵江流域Key words
VIC model/flood forecasting/long short-term memory/reservoir dispatching/the Jialing River Basin引用本文复制引用
陈顼,吴志勇,何海,刘杨合,李杨千,施怡然,孙昭敏..考虑水库调蓄影响的洪水预报智能校正方法研究[J].水资源保护,2026,42(3):72-80,9.基金项目
国家自然科学基金面上项目(52579007) （52579007）
国家自然科学基金联合基金重点项目(U2240225) （U2240225）
长江电力股份有限公司科技项目(Z242302050) （Z242302050）
