Abstract
Nelspruit and its environs frequently experience extreme high annual maximum daily rainfall (AMDR) events resulting in flood hazards. These flood hazards have caused flood disasters that have resulted in loss of property and lives. The main objective of this study was to carry out statistical analysis of extreme high AMDR events that have caused flood hazards, which in turn have caused flood disasters in Nelspruit and its environs. Empirical continuous probability distribution functions (ECPDF) and theoretical continuous probability distribution functions (TCPDF) were applied to carry out the statistical analysis of the extreme high AMDR events. Annual maximum daily rainfall event of magnitude 100 mm was identified as a threshold. Events > 100 mm were considered as extreme high events resulting in flood disasters. The results of empirical frequency analysis showed that the return period of flood disasters was 10 years. The occurrence probability of flood disaster event at least once in 1, 2, 3, 4 and 5 years was 0.10, 0.19, 0.27, 0.34 and 0.41, respectively. Generalised logistic PDF was identified as the best-fit theoretical PDF for statistical analysis of the extreme high AMDR events in Nelspruit and its environs. The results of this study contributed to the understanding of frequency and magnitude of extreme high AMDR events that could lead to flood disasters. The results could be applied in developing flood disaster management strategies in Nelspruit and its environs.
Highlights
Extreme high annual maximum daily rainfall (AMDR) events are among environmental events that have caused the most disastrous consequences for human society (Kysely, Picek & Huth 2006)
The other objective of the study was the identification of the theoretical probability distribution function(s) (PDF) that best describe these extreme high AMDR events which cause flood hazards that result in flood disasters in Nelspruit and its environs
generalised logistic (GL), generalised extreme value (GEV) and Gumbel maximum (GM) theoretical PDFs were identified as the suitable candidate theoretical continuous probability distribution functions (TCPDF) for frequency analysis of maximum annual daily rainfall events of Nelspruit and its environs
Summary
Extreme high annual maximum daily rainfall (AMDR) events are among environmental events that have caused the most disastrous consequences for human society (Kysely, Picek & Huth 2006). Flood hazards caused by high extreme rainfall events have resulted in flood disasters that have accounted for 47% of all weather-related disasters affecting 2.3 billion people worldwide (Wahlstrom & Guha-Sair 2015). In 2007, floods killed 3300 people in India and Bangladesh alone; in 2010, floods killed 2100 people in Pakistan and 1900 people in China, whereas in 2013, 6500 people died because of floods in India (Wahlstrom & Guha-Sair 2015). These flood events have been attributed to effects of human-induced climate change (Komi, Amisigo & Diekkriiger 2016). In order to formulate and develop strategies to manage and reduce flood disaster risk, it is necessary to carry out statistical analysis of the AMDR events that cause these flood disasters
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