China Grid-level Natural Streamflow Estimates
(CHASE)
全国 1 km 分辨率天然径流估算数据集
(CHASE)
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This dataset is derived from model simulations, for research use only.
本数据集为模型模拟值，仅限用于学术研究。
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1 km
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1962-2024
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1,200+
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0.77
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{{ currentLang === 'en' ? 'CHASE at Gauges: Data & Accuracy' : '站点数据及其精度' }} Live
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- streamflow {{ t.var_flow }}
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{{ currentLang === 'en' ? 'Known Issues' : '已知问题' }}
- 2026-05-26: Due to non-negligible discrepancies between local gauges and CMFD2 precipitation forcing used for Taiwan, streamflow estimates are not reliable in Taiwan Province. This will be fixed in a future release.
- 2026-05-26：由于在台湾省使用的 CMFD2 降水驱动数据与当地雨量站观测之间存在不可忽略的差异，当前版本台湾省的天然径流估算结果不可信。该问题将在后续版本中修正。
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- 2025-10-27 (Version 1.0.0): First published.
- 2025-10-27（版本 1.0.0）：首次发布。
- 2026-06-16 (Version 1.0.3): We identified localized flood peak anomalies in the earlier CHASE release, caused by out-of-range values from the machine learning-based model parameter assignment. Click here to view the major affected regions. These issues have been corrected in Version 1.0.3. Users focusing on these areas are encouraged to use the latest release. Other regions are minimally affected.
- 2026-06-16（版本1.0.3）：我们发现早期 CHASE 版本中，基于机器学习的参数在少数河段出现超限值，导致局部洪峰过程存在异常偏多/偏少。点击此处查看受影响的主要区域。这些问题已在版本 1.0.3 中修正。建议研究区域涉及上述地区或其附近区域的用户使用最新版本。其他区域受影响很小。
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Ningpeng Dong* (董宁澎), Mingxiang Yang (杨明祥), Jianhui Wei (魏建辉), Shiqin Xu (徐世琴), Yong Zhao (赵勇), Xuejun Zhang (张学君), Bo Liu (刘博), Mengqi Wu (吴梦琪), Hao Wang (王浩), Harald Kunstmann. Reconstructing China's Natural Streamflow at 1 km resolution. Water Resources Research, 2026, 62(6), e2025WR042606. DOI: https://doi.org/10.1029/2025WR042606
{{ currentLang === 'en' ? 'Related publications on CLHMS' : 'CLHMS相关文献' }}
- Ningpeng Dong* (董宁澎), Mingxiang Yang (杨明祥), et al. Model estimates of China's terrestrial water storage variation due to reservoir operation. Water Resources Research, 2022, 58 (6), e2021WR031787.
- Ningpeng Dong* (董宁澎), Mingxiang Yang (杨明祥), et al. Toward improved parameterizations of reservoir operation in ungauged basins: A synergistic framework coupling satellite remote sensing, hydrologic modeling, and operation schemes. Water Resources Research, 2023, 59 (3), e2022WR033026.
- Haoran Hao (郝浩然), Ningpeng Dong* (董宁澎), et al. The changing hydrology of an irrigated and dammed Yangtze River: Streamflow, extremes, and lake hydrodynamics. Water Resources Research, 2024, 60 (10), e2024WR037841.
{{ t.contact }} Ningpeng Dong (ndong1993@163.com).