Data

CABra: a novel large-sample dataset for Brazilian catchments 

The Catchments Attributes for Brazil (CABra) 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.  

The dataset is freely available at https://doi.org/10.5281/zenodo.4070146 and https://thecabradataset.shinyapps.io/CABra/ 

How to cite. 

Almagro, A., Oliveira, P. T. S., Meira Neto, A. A., Roy, T., and Troch, P.: CABra: a novel large-sample dataset for Brazilian catchments, Hydrol. Earth Syst. Sci., 25, 3105–3135, https://doi.org/10.5194/hess-25-3105-2021, 2021.

Weather station (online data)

Guariroba Watershed, Campo Grande, MS: https://www.hobolink.com/p/3ca304ccaf851a51169bc37320c4c808

Prosa Watershed, Campo Grande, MS:  https://hydronet.up.railway.app/

High-resolution soil erodibility map of Brazil:

We computed a high-resolution (250 m cell size) spatially explicit soil erodibility map across Brazil. To compute the K-factor, we applied the equations originally proposed in the USLE nomograph and EPIC, using the following soil properties, organic matter content, soil texture, soil structure, and permeability.

The dataset is freely available at doi:https://doi.org/10.5281/zenodo.4279869

How to cite. 

Godoi, R. F., Rodrigues, D.B.B., Borrelli, P., Oliveira, P.T.S. High-resolution soil erodibility map of Brazil. Science Of The Total Environment, v. xx, p. 146673, 2021. https://doi.org/10.1016/j.scitotenv.2021.146673

Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN):

We queried gridded global climate datasets (TerraClimate, ERA5, GPM-IMERG, and GLDAS) to estimate various 20-year climate statistics and obtain complete CLIGEN input parameter sets with coverage of the African and South American continents at 0.25 arc degree resolution. The estimation of CLIGEN precipitation parameters was informed by a ground-based dataset of >10,000 locations worldwide.

Data availability statement:

The data that support the findings of this study are openly available in Ag Data Commons at https://doi.org/10.15482/USDA.ADC/1524754.

How to cite. 

Fullhart, A., Ponce-Campos, G.E., Meles, M.B., Mcgehee, R.P., Armendariz, G., Oliveira, P.T.S., Almeida, C., De Araújo, J.C., Nel, W., Goodrich, D.C. Gridded 20-year climate parameterization of Africa and South America for a stochastic weather generator (CLIGEN). Big Earth Data, p. 1-26, 2022. https://doi.org/10.1080/20964471.2022.2136610