Hydrological Processes and Climate Change in Hydrographic Regions of Brazil

  • Ribeiro Neto A
  • da Paz A
  • Marengo J
  • et al.
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Abstract

The objective of this work is to assess the impacts of IPCC AR5 climate change scenarios on water resources and hydrological processes across the entire Brazilian territory. Hydrological simulations are carried out in total drainage area of about 11,535,645 km 2 and average stream flow of about 272,460 m 3 /s. The study area consists of different climates and land covers such as the Amazon Forest, Northeast Se-miarid, Brazilian Savannah, Pantanal wetlands and temperate climate in the South. The atmospheric forcing to drive the large-scale hydrological model MGB-IPH is derived from the downscaling of two global climate models, HadGEM2-ES and MIROC5, by the Eta Regional Climate Model, at 20 km resolution. The Eta model provided the downscaling of the baseline (1961-1990) and three time-slices (2011-2040, 2041-2070 and 2071-2099). These projections adopted two emission scenarios, the RCP 4.5 and RCP 8.5. The change in the average and extremes of precipitation, evapotranspiration, rates of river discharge and soil moisture were assessed. The simulations showed the response of the hydrographic regions due to change of precipitation and potential evapotranspiration in the scenarios. Water availability decreases in almost the entire study area (exception for the South) and the major basins for hydroelectric power generation are affected. The Northwest, Amazon and a small area along the Northeast Atlantic coast exhibited intensification of the extremes discharges , where the anomaly is positive for high-flow (Q 10) and negative for low-flow (Q 95). The results highlight the most climatic sensitive regions in Brazil in terms of hydrological variables and water resources.

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APA

Ribeiro Neto, A., da Paz, A. R., Marengo, J. A., & Chou, S. C. (2016). Hydrological Processes and Climate Change in Hydrographic Regions of Brazil. Journal of Water Resource and Protection, 08(12), 1103–1127. https://doi.org/10.4236/jwarp.2016.812087

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