Probabilistic Flood Modeling

Probabilistic Flood Modeling is a hydrologic modeling approach that quantifies flood risks and uncertainties by assigning probabilities to various flood scenarios, distinguishing itself from deterministic methods through its incorporation of stochastic processes and statistical distributions to represent the inherent variability and unpredictability of hydroclimatic extremes.

553

Publications

30.3K

Citations

1.5K

Authors

597

Institutions

Publications per year

2017–2026

213

Authors

1.5K

  1. BM
    Bruno Merz

    GFZ Helmholtz Centre for Geosciences, Germany

    14 publications · 1.7K citations

    14

    h-index

  2. PB
    Paul Bates

    University of Bristol, United Kingdom

    11 publications · 1.3K citations

    11

    h-index

  3. GB
    Günter Blöschl

    TU Wien, Austria

    9 publications · 1K citations

    9

    h-index

  4. AS
    Andreas Schumann

    Ruhr University Bochum, Germany

    7 publications · 360 citations

    7

    h-index

  5. SG
    Shenglian Guo

    Wuhan University, China

    7 publications · 291 citations

    7

    h-index

1–5 of 1.5K

Venues

  1. Water Resources Research

    80 publications · 5.2K citations

    43

    h-index

  2. Journal of Hydrology

    67 publications · 4.4K citations

    40

    h-index

  3. Hydrological Sciences Journal

    20 publications · 944 citations

    18

    h-index

  4. Natural hazards and earth system sciences

    19 publications · 898 citations

    17

    h-index

  5. Hydrology and earth system sciences

    17 publications · 1.4K citations

    17

    h-index

1–5