Evaluation of the probability density function of unpredictable flood events in the Mngeni River basin, South Africa

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.

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Publication Details

Journal
Journal of Water and Climate Change
Published
2025-04-07
DOI
https://doi.org/10.2166/wcc.2025.566
Citations
2
Primary Topic
Hydrology and Drought Analysis
Type
article
Field-Weighted Citation Impact
2.21
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article

Evaluation of the probability density function of unpredictable flood events in the Mngeni River basin, South Africa

Rebecca Alowo, German Nkhonjera, Thabo Mphefu
2 citations
Journal of Water and Climate Change
Hydrology and Drought Analysis
2.21
article

Evaluation of the probability density function of unpredictable flood events in the Mngeni River basin, South Africa

Rebecca Alowo, German Nkhonjera, Thabo Mphefu
article en
2 citations

Abstract

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.

Journal of Water and Climate ChangeVol. 16(5)
University of Johannesburg (ZA)
Openalex Percentile: Top 14%
Hydrology and Drought Analysis
2.21
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Evaluation of the probability density function of unpredictable flood events in the Mngeni River basin, South Africa — Rebecca Alowo, German Nkhonjera, et al. · Journal of Water and Climate Change (2025) | TGRS Research Map | TGRS