Abstract. We introduce a new catchment dataset for large-sample
hydrological studies in Brazil. This dataset encompasses daily time series
of observed streamflow from 3679 gauges, as well as meteorological forcing
(precipitation, evapotranspiration, and temperature) for 897 selected
catchments. It also includes 65 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 (Brazil)
complements the other CAMELS datasets by providing data for hundreds of
catchments in the tropics and 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 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.3709337 (Chagas et al., 2020).