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Spatial and Temporal Variation of Rainfall and Streamflow in the Kikuletwa Catchment of Upper Pangani Basin, Tanzania
Abstract
Streamflow and rainfall records from 1980 to 2015 as a (common period for the analyzed stations) were used to analyze the variations of rainfall and streamflow in the Kikuletwa catchment. Also, the analysis of the longest time series available at each station up to 2015 (referred to as the whole series in this study) was conducted to relate past rainfall and streamflow changes, at the tributaries of Kikuletwa River located above the Rundugai natural springs as recommended from previous studies. Various methods such as simple statistics of the mean, standard deviation, coefficient of variance, and graphs were used to analyze intra-annual variations. Multi-year variability was analyzed by trends and change point tests using MannKendall and Pettitt tests respectively. The results of the study revealed the spatial variation of rainfall which was related to elevation differences. The streamflow amounts were found to vary from upstream to downstream. The whole time series analysis of annual rainfall and streamflow amounts revealed a decrease in rainfall and streamflow amounts for almost all stations though a significant decrease was only observed at two stations located on the upstream (for rainfall) and two stations located above the Rundugai natural springs (for streamflow). During 1980 – 2015, trends analysis indicated significant decreasing trends only in annual rainfall amounts at the two stations located on the upstream of the catchment with Z values of -3.20 and -2.68. In contrast, average annual flow trends analysis indicated significant decreasing trends at four stations out of five with Z values of -2.52, -2.28, -1.99 and -3.4 and, at one station insignificant decreasing trend was observed. The findings revealed the existence of other catchment influences to the streamflow changes other than rainfall during 1980-2015. The study provides very useful information that decides the necessity for separating the climate and human influences to the streamflow changes to find the most influencing factor.