Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5951-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5951-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Nov 2021
Research article |
| 18 Nov 2021
| 18 Nov 2021
AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment
Yuxue Guo
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Xinting Yu
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Haiting Gu
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Jingkai Xie
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
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Cited
14 citations as recorded by crossref.
- Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data J. Xie et al. 10.5194/hess-26-5933-2022
- A dynamic classification-based long short-term memory network model for daily streamflow forecasting in different climate regions H. Chu et al. 10.1016/j.ecolind.2023.110092
- Monthly streamflow prediction using hybrid extreme learning machine optimized by bat algorithm: a case study of Cheliff watershed, Algeria S. Difi et al. 10.1080/02626667.2022.2149334
- Improving long-term streamflow prediction in a poorly gauged basin using geo-spatiotemporal mesoscale data and attention-based deep learning: A comparative study F. Ghobadi & D. Kang 10.1016/j.jhydrol.2022.128608
- A spatiotemporal graph convolution-based model for daily runoff prediction in a river network with non-Euclidean topological structure L. Deng et al. 10.1007/s00477-022-02352-6
- Multi-objective robust optimization of reservoir operation for real-time flood control under forecasting uncertainty X. Yu et al. 10.1016/j.jhydrol.2023.129421
- Predictive simulation and optimal allocation of surface water resources in reservoir basins under climate change Q. Rong et al. 10.1016/j.iswcr.2023.08.003
- Multi-objective operation of cascade reservoirs based on short-term ensemble streamflow prediction S. He et al. 10.1016/j.jhydrol.2022.127936
- Multi-Step-Ahead Monthly Streamflow Forecasting Using Convolutional Neural Networks X. Shu et al. 10.1007/s11269-022-03165-6
- A parallel approximate evaluation-based model for multi-objective operation optimization of reservoir group D. Liu et al. 10.1016/j.swevo.2023.101288
- Comparison of strategies for multistep-ahead lake water level forecasting using deep learning models G. Li et al. 10.1016/j.jclepro.2024.141228
- Optimization of Reservoir Level Scheduling Based on InSAR-LSTM Deformation Prediction Model for Rockfill Dams Z. Fang et al. 10.3390/w15193384
- State-of-the-art review: Operation of multi-purpose reservoirs during flood season S. Jain et al. 10.1016/j.jhydrol.2023.129165
- Time-varying Decision-making Method for Multi-objective Regulation of Water Resources Z. Dong et al. 10.1007/s11269-021-02901-8
13 citations as recorded by crossref.
- Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data J. Xie et al. 10.5194/hess-26-5933-2022
- A dynamic classification-based long short-term memory network model for daily streamflow forecasting in different climate regions H. Chu et al. 10.1016/j.ecolind.2023.110092
- Monthly streamflow prediction using hybrid extreme learning machine optimized by bat algorithm: a case study of Cheliff watershed, Algeria S. Difi et al. 10.1080/02626667.2022.2149334
- Improving long-term streamflow prediction in a poorly gauged basin using geo-spatiotemporal mesoscale data and attention-based deep learning: A comparative study F. Ghobadi & D. Kang 10.1016/j.jhydrol.2022.128608
- A spatiotemporal graph convolution-based model for daily runoff prediction in a river network with non-Euclidean topological structure L. Deng et al. 10.1007/s00477-022-02352-6
- Multi-objective robust optimization of reservoir operation for real-time flood control under forecasting uncertainty X. Yu et al. 10.1016/j.jhydrol.2023.129421
- Predictive simulation and optimal allocation of surface water resources in reservoir basins under climate change Q. Rong et al. 10.1016/j.iswcr.2023.08.003
- Multi-objective operation of cascade reservoirs based on short-term ensemble streamflow prediction S. He et al. 10.1016/j.jhydrol.2022.127936
- Multi-Step-Ahead Monthly Streamflow Forecasting Using Convolutional Neural Networks X. Shu et al. 10.1007/s11269-022-03165-6
- A parallel approximate evaluation-based model for multi-objective operation optimization of reservoir group D. Liu et al. 10.1016/j.swevo.2023.101288
- Comparison of strategies for multistep-ahead lake water level forecasting using deep learning models G. Li et al. 10.1016/j.jclepro.2024.141228
- Optimization of Reservoir Level Scheduling Based on InSAR-LSTM Deformation Prediction Model for Rockfill Dams Z. Fang et al. 10.3390/w15193384
- State-of-the-art review: Operation of multi-purpose reservoirs during flood season S. Jain et al. 10.1016/j.jhydrol.2023.129165
1 citations as recorded by crossref.
Latest update: 23 Apr 2024
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.
We developed an AI-based management methodology to assess forecast quality and forecast-informed...
