Data-driven Hydrograph Modeling

Data-Driven Hydrograph Modeling is a hydrological modeling approach that belongs to the class of data-driven environmental simulation methods, distinguished by its reliance on empirical data and statistical or machine learning techniques to directly infer hydrograph dynamics without requiring explicit process-based representation of watershed physics.

9

Publications

312

Citations

42

Authors

13

Institutions

Publications per year

2017–2026

4

Authors

42

  1. YL
    Ying Lu

    Karolinska Institutet, Sweden

    1 publications · 31 citations

    1

    h-index

  2. WT
    Wen‐Ping Tsai

    National Taiwan University, Taiwan

    1 publications · 17 citations

    1

    h-index

  3. DH
    Dawei Han

    1 publications · 33 citations

    1

    h-index

  4. WZ
    Wentao Zhan

    Yangtze University, China

    1 publications · 21 citations

    1

    h-index

  5. HZ
    Hui Zhao

    Yangtze University, China

    1 publications · 21 citations

    1

    h-index

1–5 of 42

Venues

  1. Journal of Hydrology

    2 publications · 138 citations

    2

    h-index

  2. Journal of Petroleum Science and Engineering

    1 publications · 21 citations

    1

    h-index

  3. Water Resources Management

    1 publications · 17 citations

    1

    h-index

  4. Process Safety and Environmental Protection

    1 publications · 15 citations

    1

    h-index

  5. Journal of Environmental Management

    1 publications · 31 citations

    1

    h-index

1–5