This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash–Sutcliff efficiency (0.98) and percentage bias (4.4% and −8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.

The need for a detailed investigation of the Vea catchment water balance components cannot be overemphasized due to its accelerated land cover dynamics and the associated impacts on the hydrological processes. This study assessed the possible consequences of land-use change scenarios (i.e. business as usual, BAU, and afforestation for the year 2025) compared to the 2016 baseline on the Vea catchment's water balance components using the Soil and Water Assessment Tool (SWAT) model. The data used include daily climate and discharge, soil and land use/land cover maps. The results indicate that the mean annual water yield may increase by 9.1% under the BAU scenario but decrease by 2.7% under the afforestation scenario; actual evapotranspiration would decrease under BAU but increase under afforestation; and groundwater recharge may increase under both scenarios but would be more pronounced under the afforestation scenario. These outcomes highlight the significance of land cover dynamics in water resource management and planning at the catchment.

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