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Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): Streamflow observations, forcing data and geospatial data for hydrologic studies across North America
Description: | This resource contains the CAMELS-SPAT data set. CAMELS-SPAT provides data that can support hydrologic modeling and analysis for 1426 streamflow measurement stations located across the United States and Canada. The area upstream of each station has been divided into various subbasins. The provided data include: (1) shapefiles outlining the location of each basin and its subbasins, (2) streamflow observations at daily and hourly resolution at the outlet of each basin, (3) meteorological data from 4 different data sets (RDRS, EM-Earth, ERA5, Daymet), at their native gridded resolution as well as averaged to the basin and subbasin level, (4) geospatial data from 11 different data at their native gridded resolution, and (5) statistical summaries (i.e. catchment attributes) calculated from the streamflow, meteorological and geospatial data at the basin and subbasin level. Data set structure is described in the README found in this repository. Data set development is described in Knoben et al (to be submitted). When using the CAMELS-SPAT data, please follow the attribution guidelines provided in Section 6 in this paper (briefly, individual attribution of any data set included in CAMELS-SPAT is requested if this data is used). BibTeX entries for the individual data sources aggregated in CAMELS-SPAT are provided in the citation.bib file found in this repository. Reference: Knoben, W. J. M., Keshavarz, K., Torres-Rojas, L., Thébault, C., Chaney, N. W., Pietroniro, A. & Clark, M. P. (to be submitted). Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): Streamflow observations, forcing data and geospatial data for hydrologic studies across North America. |
Authors: | Knoben, Wouter J. M.; University of Calgary; ![]() Keshavarz, Kasra; University of Calgary; ![]() Torres-Rojas, Laura; Princeton University; ![]() Thébault, Cyril; University of Calgary; ![]() Chaney, Nathaniel W.; Duke University; ![]() Pietroniro, Alain; University of Calgary; ![]() Clark, Martyn P.; University of Calgary |
Keywords: | large-sample hydrology meteorological data streamflow data geospatial data North America |
Field of Research: | Earth and related environmental sciences > Hydrology > Hydrology, not elsewhere classified
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Publication Date: | 2025-03-11 |
Publisher: | Federated Research Data Repository / dépôt fédéré de données de recherche |
Funder: | National Oceanic and Atmospheric Administration; NA22NWS4320003 |
URI: | https://doi.org/10.20383/103.01216 |
Related Identifiers: |
This dataset is derived from
This dataset is derived from
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This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
This dataset is derived from
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Geographic Coverage: | Place Name North America Country Canada Place Name North America Country United States |
Geolocation Box: | West Longitude -142.2745833333333394 East Longitude -52.8079166666666566 North Latitude 69.3579166666666680 South Latitude 26.9512499999999946 |
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Access to this dataset is subject to the following terms:
This dataset is made available under a custom license. Some of the files are available under variety of CC licenses, while others are either open or available under the Public domain, Open Government License, Copernicus Data License, and Environment and Climate Change Canada Data Server End-Use License.
Please see the LICENSE.txt for the full terms of use and data_citation.bib for data references in standard bibtex format.
Citation
Knoben, W., Keshavarz, K., Torres-Rojas, L., Thébault, C., Chaney, N., Pietroniro, A., Clark, M. (2025). Catchment Attributes and MEteorology for Large-Sample SPATially distributed analysis (CAMELS-SPAT): Streamflow observations, forcing data and geospatial data for hydrologic studies across North America. Federated Research Data Repository. https://doi.org/10.20383/103.01216