Statistical Groundwater Forecasting
Statistical Groundwater Forecasting is a methodology in hydrological science that employs statistical models to predict future groundwater levels by analyzing historical observational data, distinguished from physical or hybrid approaches by its reliance solely on data-driven correlations and stochastic relationships rather than mechanistic representations of hydrogeological processes.
33
Publications
1.8K
Citations
141
Authors
83
Institutions
Publications per year
2017–2026
22
33
Katherine M. Ransom, Bernard T. Nolan, Jonathan A. Traum et al. · The Science of The Total Environment · 2017 · 190 citations · Full text
Natural Resources, Earth Sciences, Water Resources Management +17
Aissam Gaagai, Hani Amir Aouissi, Selma Bencedira et al. · Water · 2023 · 145 citations · Full text
Natural Resources, Earth Sciences, Water Resources Management +17
Mouigni Baraka Nafouanti, Junxia Li, Nasiru Abba Mustapha et al. · Applied Geochemistry · 2021 · 110 citations
1–5 of 33
141
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2
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1
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Korea Institute of Geoscience and Mineral Resources, South Korea
1 publications · 67 citations
1
h-index
1–5 of 141
83

University of Tehran
Tehran, Iran
4 h-index
5 publications
314 citations
Chang'an University
Xi'an, China
2 h-index
8 publications
220 citations

University of Birjand
Birjand, Iran
2 h-index
6 publications
84 citations
Indian Institute of Technology Kharagpur
Kharagpur, India
2 h-index
3 publications
199 citations
United States Geological Survey
Reston, United States
2 h-index
13 publications
1.9K citations
Quality Research
San Antonio, United States
1 h-index
1 publications
190 citations
Yonsei University
Seoul, South Korea
1 h-index
1 publications
67 citations

University of Bologna
Bologna, Italy
1 h-index
2 publications
32 citations
1–8 of 83
4 publications · 308 citations
4
h-index
3 publications · 148 citations
3
h-index
3 publications · 212 citations
3
h-index
2 publications · 62 citations
2
h-index
1 publications · 43 citations
1
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1–5