Abstract
Water supply operation of a reservoir group is a critical strategy for mitigating conflicts between water resource supply and demand in a basin. However, the uncertainty of runoff forecast presents significant challenges to this operation. To explore the risk laws of the complex water supply process, this study focuses on analyzing the three primary source streams and the main stream of the Tarim River, the largest inland river in China. Initially, a runoff forecast model is developed utilizing Long Short-Term Memory Artificial Neural Networks (LSTM-ANN) to generate runoff datasets. Subsequently, a theoretically optimal operation process for the reservoir group is derived through a long-series deterministic multi-objective operation, which establishes boundary constraints for water supply risk operation. Finally, the runoff forecast results are integrated into an uncertainty water supply risk operation model to assess the associated water supply risk. The results indicate that: 1) Due to varying guarantee rates and water supply priorities among different sectors, the risk of ecological water supply is the highest, followed by agriculture and then domestic-production. 2) Within an effective forecast range of 0% to 20%, the most significant increase occurs when the error ranges between 5 to 10%. 3) As the reservoir regulation capacity in mountainous areas increases, the average water supply risk value for agriculture decreases from 0.086 to 0.040, representing a 53.1% risk reduction. The research results are of great significance to the reservoir group risk operation and the water supply safety in the basin.
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Data Availability
The dataset on which this paper is based is too large to be retained or publicly archived with available resources. Documentation and data used to support this study are available from hydrological station data.
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Acknowledgements
This work was supported by the National Key R&D Program of China (2022YFC3202300), the National Natural Science Foundation of China (52179025, 51879213), the Basic Research Plan of Natural Science of Shaanxi Province of China (2019JLM-52, 2021JLM-44).
Funding
This research was funded by the following projects:
National Key R&D Program of China (2023YFC3206700).
National Natural Science Foundation of China (52179025).
National Natural Science Foundation of China (51879213).
Basic Research Plan of Natural Science of Shaanxi Province of China (2019JLM-52).
Basic Research Plan of Natural Science of Shaanxi Province of China (2021JLM-44).
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Tao Bai: Conceptualization, Methodology, Writing—original draft, Writing—review & editing, Project administration. Qianglong Feng: Conceptualization, Writing—original draft, Writing—review & editing. Dong Liu: Methodology, Writing—review & editing, Validation. Chi Ju: Investigation, Data curation, Software.
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Bai, T., Feng, Q., Liu, D. et al. Reservoir Risk Operation of 'Domestic-Production-Ecology' Water Supply Based on Runoff Forecast Uncertainty. Water Resour Manage (2024). https://doi.org/10.1007/s11269-024-03819-7
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DOI: https://doi.org/10.1007/s11269-024-03819-7