Real-time Streamflow Forecasting
Real-Time Streamflow Forecasting is a hydrological prediction methodology that enables the continuous estimation of instantaneous river discharge values as observational and meteorological data become available, distinguishing itself from offline or retrospective approaches by requiring immediate model execution and output delivery to support time-sensitive water resource and flood management decisions.
279
Publications
22.7K
Citations
847
Authors
399
Institutions
Publications per year
2017–2026
149
Parents
279
Zaher Mundher Yaseen, Sadeq Oleiwi Sulaiman, Ravinesh C. Deo et al. · Journal of Hydrology · 2018 · 694 citations · Full text
Natural Resources, Hydrology, Water Resources Management +17
Monthly runoff forecasting based on LSTM–ALO model
Xiaohui Yuan, Chen Chen, Xiaohui Lei et al. · Stochastic Environmental Research and Risk Assessment · 2018 · 343 citations
1–5 of 279
847
19
h-index
15
h-index
Ton Duc Thang University, Vietnam
13 publications · 2.7K citations
13
h-index
8
h-index
7
h-index
1–5 of 847
399
University of Malaya
Kuala Lumpur, Malaysia
14 h-index
23 publications
2.7K citations

Ilia State University
Tbilisi, Georgia
12 h-index
12 publications
1.5K citations

Huazhong University of Science and Technology
Wuhan, China
10 h-index
23 publications
3.2K citations

National University of Malaysia
Bangi, Malaysia
9 h-index
24 publications
5.3K citations

Hohai University
Nanjing, China
9 h-index
30 publications
2K citations
Xi'an University of Technology
Xi'an, China
8 h-index
32 publications
5.2K citations

University of Southern Queensland
Toowoomba, Australia
7 h-index
13 publications
2.7K citations

Universiti Tenaga Nasional
Kuala Selangor, Malaysia
7 h-index
8 publications
604 citations
1–8 of 399
84 publications · 10.7K citations
56
h-index
35 publications · 2.6K citations
27
h-index
10 publications · 646 citations
10
h-index
9 publications · 862 citations
9
h-index
8 publications · 432 citations
8
h-index
1–5