CAMELS-BR: Hydrometeorological time series and landscape attributes for 897 catchments in Brazil

Abstract. We introduce a new catchment dataset for large-sample hydrological studies in Brazil. This dataset encompasses daily time series of observed streamflow from 3713 gauges, as well as meteorological forcing (precipitation, evapotranspiration and temperature) for 897 selected catchments. It also includes 63 attributes covering a range of topographic, climatic, hydrologic, land cover, geologic, soil and human intervention variables, as well as data quality indicators. This paper describes how the hydrometeorological time series and attributes were produced, their primary limitations and their main spatial features. To facilitate comparisons with catchments from other countries, the data follow the same standards as the previous CAMELS (Catchment Attributes and MEteorology for Large-sample Studies) datasets for the United States, Chile and Great Britain. CAMELS-BR complements the other CAMELS datasets by providing data for hundreds of catchments in the tropics and in the Amazon rainforest. Importantly, precipitation and evapotranspiration uncertainties are assessed using several gridded products and quantitative estimates of water consumption are provided to characterize human impacts on water resources. By extracting and combining data from these different data products and making CAMELS-BR publicly available, we aim to create new opportunities for hydrological research in Brazil and to facilitate the inclusion of Brazilian basins in continental to global large-sample studies. We envision that this dataset will enable the community to gain new insights into the drivers of hydrological behavior, better characterize extreme hydroclimatic events, and explore the impacts of climate change and human activities on water resources in Brazil. The CAMELS-BR dataset is freely available at https://doi.org/10.5281/zenodo.3709338 (Chagas et al., 2020).