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

Knoben, Wouter J. M.; Thébault, Cyril; Keshavarz, Kasra; Torres-Rojas, Laura; Chaney, Nathaniel W.; Pietroniro, Alain; Clark, Martyn P.

doi:https://doi.org/10.5194/hess-29-5791-2025

Articles | Volume 29, issue 20

https://doi.org/10.5194/hess-29-5791-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-29-5791-2025

© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 29, issue 20

Research article

|

28 Oct 2025

Research article |

| 28 Oct 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

Wouter J. M. Knoben, Cyril Thébault, Kasra Keshavarz, Laura Torres-Rojas, Nathaniel W. Chaney, Alain Pietroniro, and Martyn P. Clark

Supplement

https://doi.org/10.5194/hess-29-5791-2025-supplement

Data sets

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 Wouter Knoben et al. https://doi.org/10.20383/103.01306

EM-Earth: The Ensemble Meteorological Dataset for Planet Earth G. Tang et al. https://doi.org/10.20383/102.0547

A large-sample watershed-scale hydrometeorological dataset for the contiguous USA A. Newman et al. https://doi.org/10.5065/D6MW2F4D

MODIS/Terra+Aqua Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061 R. Myneni et al. https://doi.org/10.5067/MODIS/MCD15A2H.061

Landsat-Derived Global Rainfed and Irrigated-Cropland Product 30 m V001 P. Teluguntla et al. https://doi.org/10.5067/COMMUNITY/LGRIP/LGRIP30.001

MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V061 M. Friedl and D. Sulla-Menashe https://doi.org/10.5067/MODIS/MCD12Q1.061

GLobal HYdrogeology MaPS (GLHYMPS) of permeability and porosity T. Gleeson https://doi.org/10.5683/SP2/DLGXYO

Model code and software

Code used to create and update CAMELS-SPAT database Wouter Knoben https://doi.org/10.5281/zenodo.16751492

Short summary

Many existing datasets for hydrologic analysis tend to treat catchments as single spatially homogeneous units focusing on daily data and typically do not support more complex models. This paper introduces a dataset that goes beyond this set-up by (1) providing data at a higher spatial and temporal resolution, (2) specifically considering the data requirements of all common hydrologic model types, and (3) using statistical summaries of the data aimed at quantifying spatial and temporal heterogeneity.