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Forecasting extreme hourly rainfall in South Africa for disaster risk reduction: thresholds and return periods


Jan H. Vermeulen
David W. Hedding
Nthabiseng Letsatsi

Abstract

Highest and percentile values determined for daily, hourly and 5-min rainfall data (July 1994 to June 2021) from 64 automatic weather  stations across South Africa were used to define extreme hourly and 5-min rainfall intensity. Internationally, 99.9th and 99.99th  percentiles are typically considered as thresholds for hourly and sub-hourly extreme rainfall when forecasting for disaster risk reduction  assessments. In South Africa (SA), the average of the 99.9th percentile for hourly rainfall values is 29.9 mm/h. This represents a good  indicator of extreme hourly rainfall in SA and is a useful threshold for forecasting flash floods. The average highest of the hourly rainfalls  for SA, 53.9 mm/h, should be a good indicator of more extreme hourly rainfalls for the country. The average of the 99.99th percentile for  5-min rainfall values is 12.8 mm/5 min, which equates to 2.6 mm/min. Significantly, the 5-min rainfall data is used to establish South  African categories based on rainfall intensity and total rainfall, whereby an event can be classified as a cloudburst, downpour or shower.  Using the newly established local categories, the severe thunderstorm of 4 April 2000 at Hoedspruit that produced 132.2 mm in 25 min  from an intensifying upper air trough system was classified as a cloudburst. Interestingly, the 66.2 mm recorded in 5 min during this  event makes it the world record holder for all-time highest 5-min rainfall, passing the previous world 5-min rainfall record of 63.0 mm in 5  min recorded at Porto Bello, Panama, on 29 November 1911. Return periods of expected maximum daily, hourly and 5-min rainfall,  based on yearly highest values, were also calculated for South Africa. This study presents expected maximums for 5-min rainfall in return   periods of 10, 25, 50 and 100 years, a first for South Africa, which can inform strategies for disaster risk reduction.


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eISSN: 1816-7950
print ISSN: 0378-4738