paper print ; Estimates of flood discharge with various probabilities of exceedance are needed for a wide range of engineering problems: examples are culvert and bridge design and construction in major projects. At a site with long flow series, these estimates may be derived by statistical analysis of the measured floods. Alternatively the storm magnitude for an appropriate duration, areal coverage and return period may be converted into the flood of a given return period using a rainfall-runoff model. In order to derive the probability of occurrence of any flood event, the frequency distribution, which can best describe the past characteristics on the magnitude and the probability of occurrence of such floods, must be known. This involves the determination of the best flood frequency model, which can be fitted to the available historical record. The distributions used in this study include the Generalized Extreme Value (GEV) distributions, the Gumbel or Extreme Value type 1 (EV1) distribution, the lognormal distribution, the (log) Pearson type 3 distribution, among others. The fitting methods were based on parameter estimation techniques such as Method of Moments (MOM), Maximum Likelihood (ML) method and Probability Weighted Moments (PWM) method. Goodness-of-fit was evaluated by means of Chi-Square and Kolmogorov-Smirnov tests, as well as on the general tail behaviour of the extreme value distribution to be evaluated in quantile-quantile (Q-Q) plots. The focus of this paper is limited to the at-site analysis in the specific (semi-)humid climate region of the Equatorial Nile basins. The flow series were selected from the Equatorial Nile basin countries taking part in the FRIEND/Nile project, i.e. Kenya and Tanzania. The data used were annual maximum series with 12 stations in Tanzania and 16 stations in Kenya with periods ranging between 7-10 years and 27-45 years for Tanzania and Kenya respectively. ; status: published