Analysis of observed and projected spatiotemporal patterns of rainfall and temperature changes over lake kyoga basin
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The changes in climate manifest as prolonged hotter and drier seasons, changes in the length of seasons, and more frequent to severe droughts. In order to understand these changes, this study was conducted with the main objective as examining the spatiotemporal patterns of observed and projected rainfall and temperature. Lake Kyoga Basin was used as the case study. The study analyzed rainfall and air temperature observations for the period 1990 to 2020 and projections for the period 2021 to 2060. It analyzed the rainfall and sea surface temperatures teleconnection signals over the period 1990 to 2020. Various methods including homogeneity test, interpolation, Mann-Kendall trend test (MK-test), Standard Precipitation Index (SPI)1 , derivation of climate indices, spatial and statistical correlation, and simple linear regression were used. The study found that the Lake Kyoga Basin has a bimodal rainfall regime with peaks in April (average rainfall of 184.9mm) and October (average rainfall of 157.6mm). SPI showed that Buginyanya and Namulonge had the highest wet periods while Kotido, Lira and Apac had the highest incidences of dry periods. The MK-tests presented an insignificant reduction of the March to May (MAM) and December to February (DJF) rainfall at 95% confidence interval with z= -0.63, z=-0.50 and p-values of 0.53 and 0.62 respectively. The study further noted an insignificant increase in rainfall during the June to August (JJA) and September to November (SON) season, according to the positive z and the Sen’s slope values; although, the p-values for JJA (0.09) and for SON (0.48) are not significant at 95% confidence interval. The models, CNRM-CM6-1 and CanESM5 indicated a significant rise in both temperature and rainfall across the Lake Kyoga Basin. Further analysis of Consecutive Dry Days (CDD) and Consecutive Wet Days (CWD) using historical rainfall from 1990 to 2020 showed that Apac had comparatively more CDD (p-value: 0.05) whereas Buginyanya had comparatively more CWD (p-value: 0.02). Analysis of projected rainfall (2021 to 2061) revealed that Karamoja region, mostly Kotido is projected to have more CDD reaching up to 76 days per year compared to Kituuza, Jinja and Namulonge with about 65 CDD days per year. Tororo, and Buginyanya The MAM and JJA seasons are projected to have a reduction in the rainfall percentage changes of CNRM_CM6_1 model for both SSP4342 (26.2% and 46.5%), SSP585 (12.1% and 12.1%) respectively. The SON and DJF seasons exhibits a positive percentage change of (22.9% and 10.7%) for CanESM5 SSP434. The DJF season exhibits an increment of 10.7% and 31.6% for both SSP434 in both models and a negative change of 65.4% and 36.6% for the SSP585 in both models. The study further found a significant correlation for annual average rainfall (r = 0.44, p-value 0.01) and SON seasonal rainfall (r=0.51, p-value 0.003) for the and over the Lake Kyoga Basin with Western Indian Ocean Dipole (WIOD) at 95% confidence intervals. Additional analysis using simple linear regression to examine the predictability of rainfall using WIOD showed that annual average rainfall and SON regression models were considered basing on the model goodness of fit R-square values. (r 2 = 0.35, and r=0.48). The Model output showed that given the slope and X-intercept, Y-intercept (average SON, DJF rainfall) can be successfully predicted. The study recommends that wetter areas like Buginyanya, Tororo, Kituuza, Jinja, and Namulonge always to clear drainage channels, establish early warning systems and pay attention to the timely weather and climate information disseminated via different channels in order to initiate early action and reduce vulnerability. Drier areas like Kotido, Apac, Soroti should advocate for water harvesting tools like tarpaulin, and irrigation schemes. Practice tree planting and introduction of new resistant crop varieties to cope with changing rainfall and temperatures.