Browsing by Author "Ally, Karim S."

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    Regional flood frequency analysis for Pangani and Rufiji basins in Tanzania
    (University of Dar es Salaam, 1999) Ally, Karim S.
    Regional Flood Frequency Analysis (RFFA) is one of the practical means of providing flood information at sites with little, unreliable or no local data. RFFA makes use of data pooled together from a number of gauging sites from a hydrologically homogeneous region. In this study, an attempt has been made to delineate Pangani and Rufiji basins into hydrologically homogeneous region. The methodology involved the following steps: data analysis, regionalization of the basins into homogeneous regions, testing of regional homogeneity, identification of the underlying statistical distributions of flood flows, selection of appropriate frequency estimation procedures and development of relationship to predict mean annual floods (MAF) or index floods. The data for the analysis comprised of annual maximum discharge series from the two basins. These data were screened for auto-correlation, discordance, and cross correlation. All the stations that were found to be discordant and auto-correlated were excluded from further analysis. The process to delineate basins into homogeneous regions was subjective one based on catchment boundaries, topography map, mean annual rainfall map, location of gauging stations and flood statistics. Three statistics were used to check for regional homogeneity for the delineated regions. These are the coefficient of variation (CC), the heterogeneity measures (H), and the graphical plot test. Once a homogeneous region was established, the next step was to search for a suitable frequency distribution to model flood flows for that particular region. Two approaches, i.e., the regional behaviour of statistics and the L-moment ratio diagram were used to check for suitable statistical distribution. For identifying the best flood estimation, predictive ability tests indicators ie. Bias, the standard error of estimate, the root mean square error, and the expected probability of exceedance were used to assess the performance of various procedures. The results of predictive ability tests were then used to select the most robust flood estimation procedures for the delineated regions. P3/PWM was selected for Pangani basin and LP3/MOM was selected for Rufiji basin. Lastly, for each identified region, using the chosen robust procedure, regional frequency curves were constructed. Regression models were also developed to predict MAF from catchment characteristics. These relationships were developed to predict MAF to allow transfer of information from gauged to ungauged catchments