Abstract
High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization, which makes global studies difficult. This paper introduces a dataset called Caravan (a series of CAMELS) that standardizes and aggregates seven existing large-sample hydrology datasets. Caravan includes meteorological forcing data, streamflow data, and static catchment attributes (e.g., geophysical, sociological, climatological) for 6830 catchments. Most importantly, Caravan is both a dataset and open-source software that allows members of the hydrology community to extend the dataset to new locations by extracting forcing data and catchment attributes in the cloud. Our vision is for Caravan to democratize the creation and use of globally-standardized large-sample hydrology datasets. Caravan is a truly global open-source community resource.
| Original language | English |
|---|---|
| Article number | 61 |
| Journal | Scientific data |
| Volume | 10 |
| Issue number | 1 |
| DOIs | |
| State | Published - Dec 2023 |
| Externally published | Yes |
Bibliographical note
Funding Information:Frederik Kratzert was partially supported by a Google Faculty Research Award (PI: Sepp Hochreiter, JKU Linz). Daniel Klotz was partially supported by Verbund AG. Martin Gauch was supported by the Linz Institute of Technology DeepFlood project. We would like to thank Shaun Harrigan and Ervin Zsoter at ECMWF for help the ERA5-Land data product. We would also like to thank Kurt Schwehr with the Google Earth Engine team for helping facilitate public access to the HydroATLAS dataset. Additionally, we would like to thank Jon Schwenk, who reported a problem with how we derived some of the attributes and helped finding a solution. This work is a contribution to the large-sample hydrology working group of the Panta Rhei research initiative of the International Association of Hydrological Sciences (IAHS).
Funding Information:
Frederik Kratzert was partially supported by a Google Faculty Research Award (PI: Sepp Hochreiter, JKU Linz). Daniel Klotz was partially supported by Verbund AG. Martin Gauch was supported by the Linz Institute of Technology DeepFlood project. We would like to thank Shaun Harrigan and Ervin Zsoter at ECMWF for help the ERA5-Land data product. We would also like to thank Kurt Schwehr with the Google Earth Engine team for helping facilitate public access to the HydroATLAS dataset. Additionally, we would like to thank Jon Schwenk, who reported a problem with how we derived some of the attributes and helped finding a solution. This work is a contribution to the large-sample hydrology working group of the Panta Rhei research initiative of the International Association of Hydrological Sciences (IAHS).
Publisher Copyright:
© 2023, The Author(s).