This study assessed the impact of climate change on the hydrological regime of the Paraguaçu river basin, northeastern Brazil. Hydrological impact simulations were conducted using the Soil and Water Assessment Tool (SWAT) for 2020–2040. Precipitation and surface air temperature projections from two Regional Climate Models (Eta-HadGEM2-ES and Eta-MIROC5) based on IPCC5—RCP 4.5 and 8.5 scenarios were used as inputs after first applying two bias correction methods (linear scaling—LS and distribution mapping—DM). The analysis of the impact of climate change on streamflow was done by comparing the maximum, average and reference (Q90) flows of the simulated and observed streamflow records. This study found that both methods were able to correct the climate projection bias, but the DM method showed larger distortion when applied to future scenarios. Climate projections from the Eta-HadGEM2-ES (LS) model showed significant reductions of mean monthly streamflow for all time periods under both RCP 4.5 and 8.5. The Eta-MIROC5 (LS) model showed a lower reduction of the simulated mean monthly streamflow under RCP 4.5 and a decrease of streamflow under RCP 8.5, similar to the Eta-HadGEM2-ES model results. The results of this study provide information for guiding future water resource management in the Paraguaçu River Basin and show that the bias correction algorithm also plays a significant role when assessing climate model estimates and their applicability to hydrological modelling.
The Paraguaçu watershed in northeastern Brazil faces increasing water scarcity, with water resources unable to meet the increasing demand. Accurate assessment of water availability is thus essential for efficient planning and management of local resources. In this work, the potential of the SWAT model for predicting daily and monthly variability of the hydrologic regime of the Paraguaçu River was assessed. Model calibration/validation followed: (i) A hierarchical framework; (ii) the assessment of maximum, average and minimum streamflow based on paired t-test and linear regression analysis; and (iii) the definition of permanence curves for streamflow with a probability of occurrence of 90% (Q90) and 95% (Q95). The goodness-of-fit indicators revealed a “satisfactory” model performance (model efficiency ranged from 0.42 to 0.83) when predicting streamflow in monitored sub-basins using a unique set of parameters for wet and dry conditions. The flow duration curves also showed that the model underestimated higher flows resulting from extreme events but performed well for flows with exceedance probabilities of <90%. The regression analysis and paired t-test demonstrated that the SWAT model can be used for estimating maximum, average and minimum monthly streamflow in a region where information is insufficient to support water authorities in the decision-making process. The SWAT model can thus be considered adequate for simulating monthly streamflow in the Paraguaçu watershed.
Flow is one of the hydrological variables of greatest interest due to its connection with water availability and its multiple uses. However, in recent years this resource has been threatened by intense land use and climate change, affecting patterns previously considered to be stationary. The goal of this study was to evaluate trends in changes of patterns of flow, precipitation, and land use in a basin located in the Brazilian Cerrado. 33 years of rainfall, fluviometric, and land use data were used, covering the period of 1985 to 2018 on an annual scale. Mann-Kendall and Sen Slope’s nonparametric test was applied to evaluate the trends in temporal series, as well as the Spearman Rho and Pettit, which were used to analyze the correlations between variables and detect the point of change in the series, respectively. The results show statistically significant trends in flow reduction over time. At the same time, a considerable reduction in natural areas occurred, with an increase of +750% in agricultural areas. The results also show that although a tendency to reduce precipitation was detected, its magnitude was not significant, with land use changes being the main factor for the negative changes in the flow of the Rio Grande tributary.
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