CAMELS-FR dataset: a large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking

Abstract. Over the last decade, large-sample approaches, i.e., based on large catchment sets, have become increasingly popular in hydrological studies. Efforts were made to assemble and disseminate national catchment datasets. This article aims to make a contribution to the construction of a large international database of catchments by proposing the CAMELS-FR dataset, a contribution to the CAMELS (Catchment Attributes and MEteorology for Large-sample Studies) initiative. The first version presented here gathers hydroclimatic data and physical attributes for a set of 654 catchments in France. These catchments cover a wide spectrum of hydroclimatic conditions (from oceanic to continental, mountainous, or Mediterranean conditions) and are considered to have limited human influence. Data include time series of daily streamflow (with at least 30 years over the 1970–2021 period, also aggregated to monthly and yearly time steps) and of 11 catchment-scale daily climate variables (including precipitation, potential evaporation, and air temperature), as well as a total of 255 catchment attributes organized into 10 classes (e.g., geology, soil, land cover). River flow time series were quality-checked. Along with the database itself, two graphical tools are proposed, namely dynamic graphs to visualize time series and graphical fact sheets to summarize the main catchment characteristics. Care was taken to provide as many metadata as possible to help users interpret their results based on this dataset. We intend to update the database regularly to include new available data and account for end users' feedback. CAMELS-FR (Delaigue et al., 2024c) is available at https://doi.org/10.57745/WH7FJR.