South America Simulated River Discharge Dataset


Issues related to climate change and human impacts on water resources are currently a global concern. Even in South America (SA), known as the “continent of waters” (Stevaux et al., 2009) by contributing around 30% of the global runoff that reaches the oceans, the distribution of available water resources is quite heterogeneous and subject to many conflicts. In addition, many challenges arise in large basins such as Amazon, La Plata and Orinoco (> 50% of the SA territory) due to their complexity and transnational characteristic, that is, upstream-downstream relations in different countries with different policies that involve, for example, problems related to the quality and use of water and implementation of dams for energy production. Extreme events such as droughts and floods, on the other hand, do not always respect water dividers because they are connected to meteorological systems that may be smaller or larger in scope, which requires a broader view than simple topographic boundaries (e.g., headwaters of Paraná and São Francisco). Understanding and quantifying water resources in both space and time, on a consistent basis, is essential for planning and to develop adaptation strategies to modifications of the hydrological system, as well as to foster integrated management practices.

Product description

Here, we provide a dataset of simulated discharges for South America encompassing the period between 01-Jan-1990 and 31-Dec-2009. River discharges are estimated by running the MGB hydrologic-hydrodynamic model with daily time step forced with rainfall derived from gauge, satellite and reanalysis data. South America was discretized into 33,749 irregular computational elements (i.e., unit-catchments based on topography and river length), and the model computes a time series of discharge corresponding to the outlet of each of these unit-catchments. The data is free access and should be used only for research activities and other educational purposes. Authors are not responsible for the use of this dataset. It is worth mentioning that these estimates are part of a hydrological model run, assuming several hypotheses that must be understood before its use. The MGB continental model was manually calibrated and validated using different databases and remote sensing products. Below you will find a paper with a detailed description of methods, results and limitations of the initial version of the model:

Datasets used to build MGB model:

Preprocessing/Meteorological forcing

  • Bare-Earth SRTM, 500 m, O’Loughlin et al., 2016)
  • HydroSHEDS flow direction maps, 500 m (Lehner et al., 2008)
  • South America HRU map (Landcover + soil use) (Fan et al., 2015)
  • Multi-Source Weighted Ensemble Precipitation (Beck et al., 2017)
  • Climate Research Unit (CRU) 2.0 dataset (New et al., 2002)


  • Discharge gauge stations: ANA (Brazil), ONS (Reservoirs naturalized flows, Brazil), SENAMHI (Peru and Bolivia), IDEAM (Colombia), INA (Argentina), DGA (Chile), ORE-HyBam (Amazon basin/Orinoco), GRDC (Global).
  • Water Levels: ANA (in situ) e THEIA/HydroWEB (satellite altimetry);
  • Terrestrial water storage: GRACE JPL Mascon Solutions (Scanlon et al., 2016)
  • Evapotranspiration: Climate Data Record (Zhang et al., 2018)

Data access

In the link below, you will find a NetCDF file with river discharges simulated by the MGB model and also a Matlab code example for its reading. Data are arranged in a 7305 (rows) x 33,749 (columns) matrix with columns representing each unit-catchment and associated river reach and rows representing each simulation day (01-Jan-1990 to 31-Dec-2009).

Download South American River Discharge Dataset v1.0

The NetCDF file also provides the upstream drainage area and the centroid coordinates of each unit-catchment. There are many free softwares available on the internet that can also read NetCDF files. You can find a list of these softwares here: 

In the next link you can download the shapefiles of river networks and unit-catchments used by the MGB continental model. In the attribute table, the “UC” indicates the unit-catchment index that is related to columns of the discharge matrix (from NetCDF file), while the upstream drainage area to the outlet of unit-catchment is indicated by the “_Upstr_area” column.

Download shapefiles of river networks and unit-catchments for MGB South America


Please cite the following paper whenever you use this dataset:

Siqueira, V. A., Paiva, R. C. D., Fleischmann, A. S., Fan, F. M., Ruhoff, A. L., Pontes, P. R. M., Paris, A., Calmant, S., and Collischonn, W.: Toward continental hydrologic–hydrodynamic modeling in South America, Hydrol. Earth Syst. Sci., 22, 4815-4842,, 2018.

Other references

Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25º global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrology and Earth System Sciences, 21, 589-615, 10.5194/hess-21-589-2017, 2017.

Fan, F. M., Buarque, D. C., Pontes, P. R. M., and Collischonn, W.: Um mapa de unidades de resposta hidrológica para a América do Sul, XXI Simpósio Brasileiro de Recursos Hídricos, Brasilia, 2015, PAP019919,

Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from spaceborne elevation data, Eos, 89, 93-94, 10.1029/2008EO100001, 2008.

O’Loughlin, F. E., Paiva, R. C. D., Durand, M., Alsdorf, D. E., and Bates, P. D.: A multi-sensor approach towards a global vegetation corrected SRTM DEM product, Remote Sensing of Environment, 182, 49-59, 10.1016/j.rse.2016.04.018, 2016.

New, M., Lister, D., Hulme, M., and Makin, I.: A high-resolution data set of surface climate over global land areas, Climate Research, 21, 1-25, 2002.

Scanlon, B. R., Zhang, Z., Save, H., Wiese, D. N., Landerer, F. W., Long, D., Longuevergne, L., and Chen, J.: Global evaluation of new GRACE mascon products for hydrologic applications, Water Resources Research, 52, 9412-9429, 10.1002/2016wr019494, 2016.

Stevaux J.C., Latrubesse, E.M. Hermann, M.L.P., Aquino, S. Floods in urban Areas of Brazil. In Latrubesse, E. M.: Natural Hazards and Human-Exacerbated Disasters in Latin America, Special volumes of geomorphology. 2009. 550 p.

Zhang, Y., Pan, M., Sheffield, J., Siemann, A. L., Fisher, C. K., Liang, M., Beck, H. E., Wanders, N., MacCracken, R. F., Houser, P. R., Zhou, T., Lettenmaier, D. P., Pinker, R. T., Bytheway, J., Kummerow, C. D., and Wood, E. F.: A Climate Data Record (CDR) for the global terrestrial water budget: 1984–2010, Hydrology and Earth System Sciences, 22, 241-263, 10.5194/hess-22-241-2018, 2018.