Data-driven Hydrograph Modeling
Data-Driven Hydrograph Modeling is a hydrological modeling approach that belongs to the class of data-driven environmental simulation methods, distinguished by its reliance on empirical data and statistical or machine learning techniques to directly infer hydrograph dynamics without requiring explicit process-based representation of watershed physics.
9
Publications
312
Citations
42
Authors
13
Institutions
Publications per year
2017–2026
4
Parents
9
1–5 of 9
42
1
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1
h-index
1 publications · 33 citations
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1–5 of 42
13

McMaster University
Hamilton, Canada
1 h-index
2 publications
30 citations

National Taiwan University
Taipei, Taiwan
1 h-index
3 publications
51 citations
Imperial Oil (Canada)
Calgary, Canada
1 h-index
1 publications
15 citations
Purdue University West Lafayette
West Lafayette, United States
1 h-index
2 publications
36 citations
Yunnan University
Kunming, China
1 h-index
9 publications
279 citations
Université du Québec à Chicoutimi
Saguenay, Canada
1 h-index
2 publications
78 citations

Zhejiang University
Hangzhou, China
1 h-index
1 publications
17 citations
University of Miami
Coral Gables, United States
1 h-index
1 publications
120 citations
1–8 of 13
2 publications · 138 citations
2
h-index
1 publications · 21 citations
1
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1 publications · 17 citations
1
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1 publications · 15 citations
1
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1 publications · 31 citations
1
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1–5