An assessment of the impacts of climate change on the hydrology of Upper Manyame Sub-Catchment, Zimbabwe.
Climate change has caused devastating impacts worldwide. The impacts include erratic rainfall, prolonged droughts and increase in mean temperatures. Inthe Upper Manyame sub-catchment (UMSC) in Zimbabwe, no impact assessment study has been conducted despite the strategic importance of the sub-basin in providing water to over 2 million people. The aim of this study was to assess the impacts of climate change on the hydrology of the UMSC. The study specifically assessed the historical trends in precipitation and temperature, downscaled the projected climate variables (temperature and precipitation) for the 2030s (2021-2050) and 2060s (2051-2080)for the UMSC and estimated the impacts of the projected variables on runoff. In assessing historical precipitation and temperature trends, the Mann-Kendall trend and Wilcoxon signed rank tests were used. The Statistical DownScaling Model was used to downscale the projected global precipitation and temperature for the 2030s and 2060s using data from two General Circulation Models (GCMs), Hadley Center Coupled Model, version 3 (HadCM3) and Canadian Earth System Model (second generation) (CanESM2). Simulation of the changes in runoff and reservoir inflows was done using theHydrologic Engineering Centre-Hydrological Modeling System(HEC-HMS) model. Results for both the Mann Kendall and Wilcoxon signed rank tests showed a declining trend in precipitation and a statistically significant rising trend in maximum and minimum temperature. The projected temperature analysisthrough the HadCM3A2a scenario showed that the maximum temperature will increase by about 0.39°C and 0.64°C for the 2030s and 2060s respectively as compared to an increase by 0.35°C and 0.51°C for the same time periods using the HadCM3B2a scenario. The minimum temperature will generally increase by 0.15°C and 0.25°C for the 2030s and 2060s respectively for HadCM3A2a scenario as compared to an increase by approximately 0.11°C and 0.2°C for the same periods respectively in the HadCM3B2a scenario.The downscaled CanESM2 data showed that maximum temperature will increase by 0.5°C to 0.9°C for the two extreme Representative Concentration Pathways, RCP2.6 and RCP8.5. The minimum temperature will increase by around 0.3°C to 0.8°C for the two RCPs. The projected monthly potential evaporation will on average increase by 1.2 % (HadCM3A2a) and 0.97 % (HadCM3B2a) whereas for CanESM2 it will increase by 1.9 % (RCP2.6) and 2.3 % (RCP8.5) for the two projected periods.According to projections for HadCM3, the amount of precipitation will decrease in October and generally increase in November and December. In January and March the amount of precipitation will also decrease and increase in February. Average monthly precipitation will decrease by 8 - 28% and 9 - 37% for the 2030s and 2060s respectively for HadCM3A2a. For the HadCM3B2a scenario, the precipitation will drop by upto 23% and 26% for the 2030s and 2060s respectively. The decline in precipitation for RCP2.6 will range from 20% to 40% whilst for RCP8.5 it will drop by as high as upto 50%. Calibration of the HEC-HMS model for a period from 2000 to 2010 in the Mukuvisi and Marimba basins revealed satisfactory model efficiencies of 4.3% (RVE) and 0.1(Bias) and 9.5%(RVE) and 0.15(Bias) respectively. HEC-HMS model simulations revealed that runoff for the UMSC will decrease by approximately 7 - 27 % for HadCM3 for the 10 micro-catchments. Specifically, Mukuvisi and Marimba micro-catchments will experience decline in runoff ranging from 7.4-13.5 % and 7.4 - 16.2 % respectively for HadCM3. For CanESM2 runoff will decrease by 2- 35 % for the 10 micro-catchments and specifically for the key micro-catchments Mukuvisi and Marimba, the runoff will drop by 4.5 -30.3 % and 2.5 - 26 % respectively.The reservoir inflows for Lake Chivero and Lake Manyame will decrease by 10- 18% for HadCM3 and by upto 34 % for the CanESM2.The results are very important for forecasting, planningand coming up with informed decisions for integrated water resources management in the context of climate change.