Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5951-2021
https://doi.org/10.5194/hess-25-5951-2021
Research article
 | 
18 Nov 2021
Research article |  | 18 Nov 2021

AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment

Yuxue Guo, Xinting Yu, Yue-Ping Xu, Hao Chen, Haiting Gu, and Jingkai Xie

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Latest update: 13 Dec 2024
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Short summary
We developed an AI-based management methodology to assess forecast quality and forecast-informed reservoir operation performance together due to uncertain inflow forecasts. Results showed that higher forecast performance could lead to improved reservoir operation, while uncertain forecasts were more valuable than deterministic forecasts. Moreover, the relationship between the forecast horizon and reservoir operation was complex and depended on operating configurations and performance measures.