![]() ![]() By assuming the current deforestation rates, we predicted a total water reduction of 23,653 m3/s by 2050, equivalent to a decrease of 33.9% of the river flows in the study region. Climate and land use and land cover changesĬombined were responsible for a total surface water reduction of −19,718 m3/s within the Cerrado watersheds. Most of the observed changes (56.7%) were due to land use and land cover changes and occurred in recent decades. We estimated an average decrease of 8.7% and 6.7% in the streamflow due to deforestation and climate changes, respectively. We observed that direct impacts by large-scale deforestation oriented to the production of irrigated agricultural commodities have more significantly impacted river flows than climate changes. Complementarily, we projected a future deforestation and climate scenario up to 2050 and predicted their impacts on surface water in the study area. In this study, we assessed the impacts of land use and climate changes on the river flows of 81 watersheds within the Cerrado biome, Brazil, based on a comprehensive analysis of field and secondary data acquired between 19. A Worrying Future for River Flows in the Brazilian Cerrado Provoked by Land Use and Climate Changes. This freely available gridded meteorological data set significantly advances the availability of climate data in Brazil.Ĭitation: Salmona, Y.B. Variations in the interpolation schemes across river basins are primarily attributed to differences in gauge or station network density. Forecasting capability was tested for precipitation only and performed adequately for the system state (wet or dry). ![]() ![]() The performance of the interpolation varies for different seasons for almost all variables. Performance of all methods was poorer prior to 1995 because of fewer stations and available data. The inverse distance weighting and angular distance weighting methods produced the best results. We also present the performance of the best interpolation for each climate variable at daily timescales and for river basins. We used a cross-validation approach that compares point observed data to point interpolated estimates to select the best interpolation scheme for each climate variable. The data were obtained from 3625 rain gauge and 735 weather stations for period of 1980–2013. We tested six different interpolation schemes to create the grids for these variables. These five variables are maximum and minimum temperature, solar radiation, relative humidity, and wind speed. The objective of this work was to develop high-resolution grids (0.25∘ × 0.25∘) of daily precipitation, evapotranspiration, and the five climate variables generally required to estimate evapostranspiration for Brazil. Basic meteorological data are essential for evaluating impacts of spatiotemporal variability in climate forcing on hydrology and agroecosystems. ![]()
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