Enhancing Hydrological Modeling of Ungauged Watersheds through Machine Learning and Physical Similarity-based Regionalization of Calibration Parameters
L o a d i n g
Organization
United State Environmental Protection Agency - view all
Update frequencyunknown
Last updated3 days ago
OverviewAIHAWQSPUBSWATcalibrationstreamflow
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).
Additional Information
KeyValue
Dcat Modified2025-01-05
Dcat Publisher NameU.S. EPA Office of Research and Development (ORD)
Guidhttps://doi.org/10.23719/1531961
Harvest Object Idc38aa0f3-d044-4d2b-a4d2-5e6582bb5c52
Harvest Source Idb8e63f83-bbb9-45d3-a3de-09607cc9ff8a
Harvest Source TitleUSEPA Environmental Dataset Gateway
