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A comprehensive, multisource database for hydrometeorological modeling of 14,425 North American watersheds.
- Source :
- Scientific Data; 7/20/2020, Vol. 7 Issue 1, p1-12, 12p
- Publication Year :
- 2020
-
Abstract
- The Hydrometeorological Sandbox - École de technologie supérieure (HYSETS) is a rich, comprehensive and large-scale database for hydrological modelling covering 14425 watersheds in North America. The database includes data covering the period 1950–2018 depending on the type and source of data. The data include a wide array of hydrometeorological data required to perform hydrological and climate change impact studies: (1) watershed properties including boundaries, area, elevation slope, land use and other physiographic information; (2) hydrometric gauging station discharge time-series; (3) precipitation, maximum and minimum daily air temperature time-series from weather station records and from (4) the SCDNA infilled gauge meteorological dataset; (5) the NRCan and Livneh gridded interpolated products' meteorological data; (6) ERA5 and ERA5-Land reanalysis data; and (7) the SNODAS and ERA5-Land snow water equivalent estimates. All data have been processed and averaged at the watershed scale, and provides a solid basis for hydrological modelling, climate change impact studies, model calibration assessment, regionalization method evaluation and essentially any study requiring access to large amounts of spatiotemporally varied hydrometeorological data. Measurement(s) elevation • temperature • hydrological precipitation process • Fluid Discharge • climate • physiographic feature Technology Type(s) digital curation Sample Characteristic - Environment watershed Sample Characteristic - Location North America Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12600281 [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 20524463
- Volume :
- 7
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Scientific Data
- Publication Type :
- Academic Journal
- Accession number :
- 144674617
- Full Text :
- https://doi.org/10.1038/s41597-020-00583-2