CABra: a novel large-sample dataset for Brazilian catchments
Open Access
- 9 June 2021
- journal article
- research article
- Published by Copernicus GmbH in Hydrology and Earth System Sciences
- Vol. 25 (6), 3105-3135
- https://doi.org/10.5194/hess-25-3105-2021
Abstract
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 9 mm d−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 continental-scale 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).Keywords
This publication has 95 references indexed in Scilit:
- The Global Precipitation Measurement MissionBulletin of the American Meteorological Society, 2014
- Height Above the Nearest Drainage – a hydrologically relevant new terrain modelJournal of Hydrology, 2011
- Tropical forests were the primary sources of new agricultural land in the 1980s and 1990sProceedings of the National Academy of Sciences of the United States of America, 2010
- Improving parameter estimation and water table depth simulation in a land surface model using GRACE water storage and estimated base flow dataWater Resources Research, 2010
- Hydrologic disturbance reduces biological integrity in urban streamsEnvironmental Monitoring and Assessment, 2010
- Can texture‐based classification optimally classify soils with respect to soil hydraulics?Water Resources Research, 2010
- Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshopsJournal of Hydrology, 2006
- Relating BTOPMC model parameters to physical features of MOPEX basinsJournal of Hydrology, 2006
- Changes in Lena River streamflow hydrology: Human impacts versus natural variationsWater Resources Research, 2003
- Red and photographic infrared linear combinations for monitoring vegetationRemote Sensing of Environment, 1979