| 欧阳文宇,张弛,马昊然,叶磊,王泽,吕恒.人工智能驱动水文预报与水库调度研究的探索与思考[J].水利学报,2025,56(9):1119-1131 |
| 人工智能驱动水文预报与水库调度研究的探索与思考 |
| Exploration and consideration of AI-driven hydrological forecasting and reservoir operation |
| 投稿时间：2025-01-24 修订日期：2025-05-23 |
| DOI：10.13243/j.cnki.slxb.20250049 |
| 中文关键词: 人工智能 水文预报 水库调度 算法 算力 |
| 英文关键词: artificial intelligence hydrological forecasting reservoir operation algorithm computing power |
| 基金项目:国家杰出青年科学基金项目（51925902）； 国家自然科学基金项目（52322901，52309010） |
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| 中文摘要: |
| 人工智能技术的快速发展为水文预报与水库调度研究带来了新机遇。本文以流域水文过程规律挖掘与水库防洪调度决策制定为切入点，概述了人工智能的应用案例研究，分析了其在发现流域水文复杂共性规律以及学习水库调度现实经验支持未来决策方面的优点，并讨论了当前AI应用中面临的数据尚不足以描述水文共性规律和调度中对现实情况的数字描述不够真实等挑战。基于此，进一步提出了提升数据完备性、强化算法能力和促进实际工程应用的算据、算法、算力协同发展路径，重点涵盖遥感大数据和地面观测体系的整合、领域知识与AI算法的深度融合，以及平台化软件产品的研发与应用，以期为相关领域的研究与实践提供参考。 |
| 英文摘要: |
| The rapid development of artificial intelligence（AI）technology has brought new opportunities to hydrological forecasting and reservoir operation research. This paper focuses on the mining of watershed hydrological process regularities and the decision-making in reservoir flood control scheduling as entry points. It provides an overview of AI application case studies，analyzing the advantages of AI in identifying complex common patterns in watershed hydrology and in learning from real-world reservoir operation experiences to support future decision-making. Furthermore，the paper discusses current challenges in AI applications，such as the insufficiency of data to describe common hydrological patterns and the inadequate digital representation of real-world conditions in scheduling. Based on this，a pathway for the collaborative development of data，algorithm and computing power is proposed to enhance data com pleteness，strengthen algorithm capabilities，and promote practical engineering applications，highlighting the integration of remote sensing big data with ground observation systems，the deep integration of domain knowledge with AI algorithms，and the research and application of platform-based software products. This aims to provide references for research and practice in related fields. |
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