Abstract
With constantly unpredictable floods in the eastern coastal areas of South Africa, e.g. Mngeni River basin, there is a need to evaluate the probability density function (PDF) of the flood records to determine the magnitude and frequency of floods. Four hydrological PDFs, namely, normal distributions, log-normal (LN), log-Pearson type III (LP3), and Gumbel Max, were used in this study to determine flood magnitude and their frequency. Eleven flow gauging stations were considered where flood magnitudes were estimated for 2-, 5-, 10-, 25-, 50-, 100-, and 200-year recurrence intervals. Goodness-of-fit tests for the four statistical distribution techniques, at a 5% significance level, were performed using Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared tests. For the Mngeni basin, LP3 was considered the most reliable hydrological PDF, seconded by LN. The study also showed that the probable maximum flood for the area is 1141.797 m3/s, and by interpolation, a flow discharge of 1,300 m3/s in the basin represents a 100-year flood value. As the scientific knowledge improves, and the development increases in the catchment, there is a need to incorporate predicted changes in flood risk from land use, climate change, and other alterations within the catchment.