期刊论文

Wan, QJ

英文

Water

2073-4441

2024

16

4

618-

10.3390/w16040618

This work was supported by the National Key Research and Development Program Youth Scientist Project of China, as part of a project entitled “Medium and Long-term Water Resource Prediction Technology for the Water Source Area of the Middle Route of the South-to-North Water Transfer Project” (2023YFC3210500); the Natural Science Foundation of Hubei Province (2021CFB151, 2022CFD027); the central research institutes of Basic Research and Public Service Special Operations (CKSF2021441/SZ); the Key Project of Chinese Water Resources Ministry (SKS-2022120); the National Natural Science Foundation of China (No. 42271044, No. 52109003, No. 52009005).

本校为通讯机构

Accurately predicting hydrological runoff is crucial for water resource allocation and power station scheduling. However, there is no perfect model that can accurately predict future runoff. In this paper, a daily runoff prediction method with a seasonal decomposition-based-deep gated-recurrent-unit (GRU) method (SD-GRU) is proposed. The raw data is preprocessed and then decomposed into trend, seasonal, and residual components using the seasonal decomposition algorithm. The deep GRU model is then used to predict each subcomponent, which is then...