Quantifying the influence of climate change on streamflow of Rietspruit sub-basin, South Africa

Abstract

This study integrated climate projections from five global climate models (GCMs) into the soil and water assessment tool to evaluate the potential impact of climate alterations on the Rietspruit River sub-basin under two representative concentration pathways (RCP4.5 and 8.5). The model's performance was evaluated based on the coefficient of determination (R2), percent bias (PBIAS), Nash–Sutcliffe efficiency (NSE), probability (P)-factor and correlation coefficient (R)-factor. Calibration results showed an R2 of 0.62, NSE of 0.60, PBIAS of 20, P-factor of 0.86 and R-factor of 0.91, while validation produced an R2 of 0.64, NSE of 0.61, PBIAS of 40, P-factor of 0.85 and R-factor of 1.22. Precipitation is predicted to increase under both RCPs. Maximum temperature is projected to increase under both RCPs, with a major increase in the winter months. Minimum temperatures are projected to decrease under RCP4.5 in the near (−0.99 °C) and mid (−0.23 °C) futures, while the far future is projected to experience an increase of 0.14 °C. Precipitation and temperature changes correspond to increases in streamflow by an average of 53% (RCP4.5) and 47% (RCP8.5). These results indicate a need for an integrated approach in catchment water resource management amid potential climate and land use variations. HIGHLIGHTS An ensemble of five best-performing GCMs (MiroC5, CanESM2, SHMI-ESM, CSIRO and NorESM2) was employed.; P-factor and R-factor were used to assess model uncertainty particularly due to anthropogenic land use changes.; During winter, maximum and minimum temperatures are projected to increase and decrease, respectively.; The projected increase in streamflow seems to be aggravated by continued land use changes.;

Keywords

• global climate models
• hydrological modelling
• land use
• representative concentration pathways
• swat model