A multivariate analysis approach in determining potential hotspots of seasonal rainfall change over Uganda

Kevin John Oratungye, Oludhe C, Moses Mwangi Manene, Komutunga E. "A multivariate analysis approach in determining potential hotspots of seasonal rainfall change over Uganda." International Journal of Statistics and Applied Mathematics. 2017;2(1):31-41.


Evidence of climate change continues to emerge in Uganda as indicated by recent floods in Teso subregion and Kasese district, landslides in Bududa and long droughts experienced in Karamoja. The major objective of the study was to identify potential hotspots of rainfall change in Uganda during March-May and October-December seasons. Monthly rainfall data for the period extending from 1951 to 2010 were used in the study. ArcGIS, a geographic information system tool was used to determine geographical areas that have experienced changes in seasonal rainfall over the decades 1981-2010 relative to the longterm mean (1951-2010). Mbale, Mbarara and Moroto were identified as areas of potential rainfall change. The historical rainfall series for the identified areas were tested for inhomogeneities using Standard Normal Homogeneity and Pettitt tests and found to be homogenous. Multivariate two-sample Hotelling T2-test was used to generate evidence of rainfall change in the identified areas by comparing mean seasonal rainfall vectors between the sub-periods 1951-1980 and 1981-2010. Results indicated a significant simultaneous decrease in mean rainfall over Moroto and Mbarara areas across the March-May season with April having the highest decrease (11 mm and 18 mm respectively). Mean rainfall in Mbale was found to have increased simultaneously across both wet seasons with April and October experiencing the greatest increase (10 mm apiece). These changes have detrimental effects on crop and livestock farming as well as human lives. There is need for increased climate change adaptation and resilience action in the …


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