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

Publications

33

1–5 of 33

Authors

141

  1. BT
    Bernard T. Nolan

    United States Geological Survey, United States

    2 publications · 235 citations

    2

    h-index

  2. MK
    Madan K. Jha

    Indian Institute of Technology Kharagpur, India

    2 publications · 166 citations

    2

    h-index

  3. KV
    K. V. Deepesh Reddy

    Koneru Lakshmaiah Education Foundation, India

    1 publications · 12 citations

    1

    h-index

  4. BC
    Benyamin Chahkandi

    University of Tehran, Iran

    1 publications · 20 citations

    1

    h-index

  5. KK
    Kue‐Young Kim

    Korea Institute of Geoscience and Mineral Resources, South Korea

    1 publications · 67 citations

    1

    h-index

1–5 of 141

Venues

  1. Water Resources Management

    4 publications · 308 citations

    4

    h-index

  2. Journal of Hydrology

    3 publications · 148 citations

    3

    h-index

  3. Environmental Earth Sciences

    3 publications · 212 citations

    3

    h-index

  4. Water Resources Research

    2 publications · 62 citations

    2

    h-index

  5. Arabian Journal of Geosciences

    1 publications · 43 citations

    1

    h-index

1–5