TY - JOUR
T1 - CABra
T2 - A novel large-sample dataset for Brazilian catchments
AU - Almagro, André
AU - Oliveira, Paulo Tarso S.
AU - Meira Neto, Antônio Alves
AU - Roy, Tirthankar
AU - Troch, Peter
N1 - Publisher Copyright:
© 2021 André Almagro et al.
PY - 2021/6/9
Y1 - 2021/6/9
N2 - In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980-2010) of data and less than 10% of missing records were included. Catchment areas range from 9 to 4 800 000 km2, and the mean daily streamflow varies from 0.02 to 9mmd-1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed, along with the limitations for each of our multiple data sources. CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continentalscale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/(last access: 7 June 2021).
AB - In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow, groundwater, geology, soil, topography, land cover, and hydrologic disturbance). We have collected and synthesized data from multiple sources (ground stations, remote sensing, and gridded datasets). To prepare the dataset, we delineated all the catchments using the Multi-Error-Removed Improved-Terrain Digital Elevation Model (MERIT DEM) and the coordinates of the streamflow stations provided by the Brazilian Water Agency, where only the stations with 30 years (1980-2010) of data and less than 10% of missing records were included. Catchment areas range from 9 to 4 800 000 km2, and the mean daily streamflow varies from 0.02 to 9mmd-1. Several signatures and indices were calculated based on the climate and streamflow data. Additionally, our dataset includes boundary shapefiles, geographic coordinates, and drainage area for each catchment, aside from more than 100 attributes within the attribute classes. The collection and processing methods are discussed, along with the limitations for each of our multiple data sources. CABra intends to improve the hydrology-related data collection in Brazil and pave the way for a better understanding of different hydrologic drivers related to climate, landscape, and hydrology, which is particularly important in Brazil, having continentalscale river basins and widely heterogeneous landscape characteristics. In addition to benefitting catchment hydrology investigations, CABra will expand the exploration of novel hydrologic hypotheses and thereby advance our understanding of Brazilian catchments' behavior. The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/(last access: 7 June 2021).
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U2 - 10.5194/hess-25-3105-2021
DO - 10.5194/hess-25-3105-2021
M3 - Article
AN - SCOPUS:85107765356
SN - 1027-5606
VL - 25
SP - 3105
EP - 3135
JO - Hydrology and Earth System Sciences
JF - Hydrology and Earth System Sciences
IS - 6
ER -