A comprehensive, multisource database for hydrometeorological modeling of 14,425 North American watersheds.

Sci Data

Hydrology, Climate and Climate Change Laboratory, École de technologie supérieure, 1100 Notre-Dame West st., Montreal, Quebec, H3C 1K3, Canada.

Published: July 2020

AI Article Synopsis

  • The Hydrometeorological Sandbox (HYSETS) is a comprehensive database with hydrological data covering 14,425 watersheds in North America from 1950 to 2018.
  • The database includes diverse data types such as watershed properties, hydrometric discharge time-series, and various meteorological datasets including temperature, precipitation, and snow water equivalent.
  • It serves as a robust platform for hydrological modeling, climate change studies, model calibration, and other research needing extensive hydrometeorological data.

Article 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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7371877PMC
http://dx.doi.org/10.1038/s41597-020-00583-2DOI Listing

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