Effect Of Urbanization On Rainfall Over Kilimanjaro Region
Precipitation is a key link in the global water cycle and a proxy for changing climate. This study sought to assess the effects of urbanization on precipitation in Kilimanjaro region based on observed rainfall and population data between the period 1982 and 2012. Graphical analysis was used to determine space time variability of rainfall amount, frequency and intensity while the relationship between urbanization and rainfall was achieved through correlation and regression analysis. The slope of regression line showed that trend of total rainfall over urban areas (Moshi) was decreasing more than rural areas (Kia and Same) with increasing frequencies of rainy days. Annual rainfall showed highest peak in April and November with the number of rainy days reducing with increasing threshold value of rainfall category. Graphical analysis indicated a bimodal rainfall distribution over the region with highest peak during April –May –June and lowest peak in November –December -January while the slopes of regression line were all noted to be quite small with values of less than 0.3. Regression analysis indicated a positive relationship between rainfall and population over all stations except same with coefficient of determination (R2) values less than 9% and thus little influence of population on the amount of rainfall received over Kilimanjaro region. Correlation analysis showed that rainfall and population were negatively related over Lyamungu Moshi and Kia with correlation coefficient values of -0.23, -0.16 and -0.30 respectively. At 95% significance level, the student t test showed that these correlations were not significantly related to population as all values of t computed were less than t tabulated. Over Kilimanjaro region changes in population had little influence on rainfall amount, intensity, and frequency over Kilimanjaro region. However, the slight modification in rainfall over urbanized environment would necessitate convenient approaches and planning to help prevent modification of rainfall and thus urban climate. Therefore, this information will form basis of urban policy formulation towards limiting further changes in urban environment.