Statistical Streamflow Models is a type of hydrological prediction model that employs statistical methods to estimate streamflow by identifying empirical relationships between observed hydrological variables and streamflow, distinguished from deterministic or physically-based models by its reliance on data-driven rather than process-based representations of watershed behavior.
200
Publications
9.7K
Citations
638
Authors
294
Institutions
Publications per year
2017–2026
69
Parents
Publications
200
1–5 of 200
Authors
638
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1–5 of 638
Institutions
294
United States Geological Survey
Reston, United States
15 h-index
43 publications
2.9K citations
University of Regina
Regina, Canada
5 h-index
13 publications
579 citations
Hohai University
Nanjing, China
4 h-index
16 publications
448 citations
Texas A&M University
College Station, United States
4 h-index
6 publications
300 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
4 publications
155 citations
University of Padua
Padua, Italy
4 h-index
5 publications
107 citations
China Institute of Water Resources and Hydropower Research
Beijing, China
4 h-index
5 publications
159 citations
University of Chinese Academy of Sciences
Beijing, China
4 h-index
5 publications
145 citations
1–8 of 294
Venues
- Water Resources Research
31 publications · 2K citations
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- Journal of Hydrology
19 publications · 717 citations
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- JAWRA Journal of the American Water Resources Association
11 publications · 686 citations
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- Antarctica A Keystone in a Changing World
8 publications · 278 citations
8
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- Hydrology and earth system sciences
7 publications · 396 citations
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