Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters
The study results and data used and produced in this study are available through the Texas Data Repository at https://doi.org/10.18738/T8/A9X5ET (Srinivasan et al., 2023). The data also includes the necessary information to reproduce the figures and tables presented in the study.
This dataset is associated with the following publication:
Bawa, A., K. Mendoza, R. Srinivasan, F. O'Donncha, D. Smith, K. Wolfe, R. Parmar, J. Johnston, and J. Corona. Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 186: 106335, (2025).
Complete Metadata
| accessLevel | public |
|---|---|
| bureauCode |
[
"020:00"
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| contactPoint |
{
"fn": "Rajbir Parmar",
"hasEmail": "mailto:parmar.rajbir@epa.gov"
}
|
| description | The study results and data used and produced in this study are available through the Texas Data Repository at https://doi.org/10.18738/T8/A9X5ET (Srinivasan et al., 2023). The data also includes the necessary information to reproduce the figures and tables presented in the study. This dataset is associated with the following publication: Bawa, A., K. Mendoza, R. Srinivasan, F. O'Donncha, D. Smith, K. Wolfe, R. Parmar, J. Johnston, and J. Corona. Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters. ENVIRONMENTAL MODELLING & SOFTWARE. Elsevier Science, New York, NY, 186: 106335, (2025). |
| distribution |
[
{
"title": "https://doi.org/10.18738/T8/A9X5ET",
"accessURL": "https://doi.org/10.18738/T8/A9X5ET"
}
]
|
| identifier | https://doi.org/10.23719/1531961 |
| keyword |
[
"AI",
"HAWQS",
"PUB",
"SWAT",
"calibration",
"streamflow"
]
|
| license | https://pasteur.epa.gov/license/sciencehub-license-non-epa-generated.html |
| modified | 2025-01-05 |
| programCode |
[
"020:000"
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| publisher |
{
"name": "U.S. EPA Office of Research and Development (ORD)",
"subOrganizationOf": {
"name": "U.S. Environmental Protection Agency",
"subOrganizationOf": {
"name": "U.S. Government"
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|
| references |
[
"https://doi.org/10.1016/j.envsoft.2025.106335"
]
|
| rights |
null
|
| title | Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters |
