Abstract

Climate change impact drivers includes increased rainfall variability, increased extreme events, and changes in the mean behaviour of hydro-meteorological variables such as air temperature, rainfall, and runoff. As such, this study assessed the potential impacts of climate change on surface water resources in a semi-arid Tugwi Mukosi catchment of Zimbabwe. The Mann-Kendall trend analysis, climate change downscaling and streamflow modelling were used as the primary methodology. The analysis of historical hydro-climatic data trends were performed using the Mann-Kendall trend test and Sen's slope method. Equally, observed daily rainfall was extended using bias-corrected CHIRPS satellite rainfall. Thus, a total of 9 Global Climate Models including (CCCma-CanESM2, Miroc Miroc 5, MOHCHadGEM2, MPI-M-MPI-ESM-LR, and NCCNorESM1-M) on the Sveriges Meteorologiska och Hydrologiska Institut (SMHI) Rosby Centre Atmosphere model version 4 (RCA4) RCM under the Representative Concentrated Pathways 4.5 and 8.5 were extracted and analysed for the 2030s (2021–2050) and 2060s (2051–2080) period. The results show significant (p<0.05) decreasing rainfall trends at the analysed stations, as well as significant decrease in rainfall for the 2030s and the 2060s under GCMs CCCma-CanESM 2 model. The Hydrologic Engineering Centre-Hydrological modeling System (HECHMS) (1997–1999) was calibrated and validated for the period 1981–2016. Calibration results on gauged catchment runoff and peak flows are satisfactory (Ngezi observed peak discharge and simulated peak discharge at 42.4 m3/s and 34.8 m3/s respectively, NSE 62.8%, Upper Muzhwi 30 m3/s and 19.5 m3/s, NSE 53.55%, Musogwezi 18.7 m3/,s and 16.5 m3/s, NSE 58.4%). The GCM-CanESM RCP 4.5 model showed a decrease in the runoff predicted of above 17% in both the 2030s and a significant decrease in the 2060s of 28.41% and 5% respectively. The combination of climate downscaling and water resources modelling is paramount to the management of water resources in a semi-arid area. Hydrological modelling and climate downscaling techniques gives important insights for water resources planning and development to support the water sector adaptation to climate change. The methodology applies to other data-scarce and semi-arid areas whose climate change impacts require further investigation.

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