Resumo As mudanças climáticas no século XXI é uma realidade inconteste. Diversos efeitos e impactos vêm sendo registrados em várias regiões do planeta. Este trabalho tem por objetivo avaliar a associação do modelo hidrológico MHD-INPE ao modelo atmosférico Eta/CPTEC, a fim de simular o impacto de mudanças climáticas na Bacia Hidrográfica do Ribeirão Jaguara, localizada no sul do estado de Minas Gerais. Para tal fim, foram utilizados dois cenários (RCP4.5 e RCP8.5) de três modelos globais (HadGEM2-ES, MIROC5 e CanESM2), regionalizados pelo modelo Eta. Os resultados da calibração e validação mostraram uma boa performance MHD-INPE em simular a vazão da BHRJ. Após a correção de viés, as saídas dos cenários foram usadas como entrada no MHD-INPE. As projeções climáticas corrigidas dos cenários resultaram em predominante redução da precipitação ao longo do século. Os resultados das projeções da temperatura mostraram aumento consensual por parte dos modelos climáticos, em ambos os cenários. As estatísticas da curva de permanência das vazões advindas das simulações climáticas mostraram um bom desempenho do MHD-INPE na simulação do clima presente.
Landform classification is important for representing soil physical properties varying continuously across the landscape and for understanding many hydrological processes in watersheds. Considering it, this study aims to use a geomorphology map (Geomorphons) as an input to a physically based hydrological model (Distributed Hydrology Soil Vegetation Model (DHSVM)) in a mountainous headwater watershed. A sensitivity analysis of five soil parameters was evaluated for streamflow simulation in each Geomorphons feature. As infiltration and saturation excess overland flow are important mechanisms for streamflow generation in complex terrain watersheds, the model’s input soil parameters were most sensitive in the “slope”, “hollow”, and “valley” features. Thus, the simulated streamflow was compared with observed data for calibration and validation. The model performance was satisfactory and equivalent to previous simulations in the same watershed using pedological survey and moisture zone maps. Therefore, the results from this study indicate that a geomorphologically based map is applicable and representative for spatially distributing hydrological parameters in the DHSVM.
Changes in precipitation and air temperature may produce different impacts on the hydrological regime, compromising water supply. This study focuses on climate change impacts in the Verde River Basin (VRB), a tropical headwater basin in southeast Brazil, located in the state of Minas Gerais. The Variable Infiltration Capacity model (VIC) was calibrated and validated in the Verde River Basin. The downscaling (Eta Regional Climate Model, at 20-km resolution) of three Global Circulation Models (CanESM2, HadGEM2-ES and MIROC5) were used to drive the VIC for a historical baseline (1961-2005) and three time-slices (2011-2040, 2041-2070 and 2071-2099), under RCPs 4.5 and 8.5 scenarios. The scenarios were used as input in the hydrological model after bias correction. The hydrological model (VIC) showed satisfactory statistical performance in calibration and validation, with CNS varying from 0.77 to 0.85 for daily and monthly discharges; however, it overestimated some peak flows and underestimated the recession flows. Multi-model ensemble means predict increases of the minimum and maximum monthly average temperature for the investigated area at the end of the century. The Eta-CanESM2 indicated greater warming, mainly for RCP8.5 at the end the century, whereas Eta-HadGEM2-ES showed higher reduction in the precipitation for RCP4.5 at the beginning of the century and for RCP8.5 at the end the century, negatively impacting the evapotranspiration and discharge. Among the Regional Climate Models (RCMs), the Eta-MIROC5 showed minor changes in the components of the hydrological cycle. This study suggests that Global Circulation Models represent an additional uncertainty, which should be accounted for in the climate change impact assessment. Keywords: climate changes, RCP4.5, RCP8.5, VIC model.
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