Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
College of Earth and Planetary Sciences, University of Chinese Academy of Sciences, Beijing, China
Siyu Cai
State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, China
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3,264
1,159
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4,545
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PDF: 1,159
XML: 122
Total: 4,545
BibTeX: 156
EndNote: 166
Views and downloads (calculated since 10 Jul 2023)
Cumulative views and downloads
(calculated since 10 Jul 2023)
Total article views: 2,665 (including HTML, PDF, and XML)
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2,198
392
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2,665
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HTML: 2,198
PDF: 392
XML: 75
Total: 2,665
BibTeX: 113
EndNote: 134
Views and downloads (calculated since 25 Mar 2024)
Cumulative views and downloads
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Total article views: 1,880 (including HTML, PDF, and XML)
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1,066
767
47
1,880
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HTML: 1,066
PDF: 767
XML: 47
Total: 1,880
BibTeX: 43
EndNote: 32
Views and downloads (calculated since 10 Jul 2023)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 4,545 (including HTML, PDF, and XML)
Thereof 4,403 with geography defined
and 142 with unknown origin.
Total article views: 2,665 (including HTML, PDF, and XML)
Thereof 2,552 with geography defined
and 113 with unknown origin.
Total article views: 1,880 (including HTML, PDF, and XML)
Thereof 1,851 with geography defined
and 29 with unknown origin.
Large-sample hydrology (LSH) datasets have been the backbone of hydrological model parameter estimation and data-driven machine learning models for hydrological processes. This study complements existing LSH studies by creating a dataset with improved sample coverage, uncertainty estimates, and dynamic descriptions of human activities, which are all crucial to hydrological understanding and modeling.
Large-sample hydrology (LSH) datasets have been the backbone of hydrological model parameter...
