Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters
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).
Resources
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Description |
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https://doi.org/10.18738/T8/A9X5ET |
Tags
- pub
- calibration
- hawqs
- streamflow
- ai
- swat