  Citation: Sikhwari, T.; Nethengwe, N.; Sigauke, C.; Chikoore, H. Modelling of Extremely High Rainfall in Limpopo Province of South Africa. Climate 2022, 10, 33. https://doi.org/10.3390/cli10030033 Academic Editor: Salvatore Magazù Received: 24 January 2022 Accepted: 21 February 2022 Published: 28 February 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). climate Article Modelling of Extremely High Rainfall in Limpopo Province of South Africa Thendo Sikhwari 1,† , Nthaduleni Nethengwe 1 , Caston Sigauke 2, * ,† and Hector Chikoore 3 1 Department of Geography and Geo-Information Sciences, School of Environmental Sciences, University of Venda, Thohoyandou 0950, South Africa; sikhwarimushavhi@gmail.com (T.S.); nthaduleni.nethengwe@univen.ac.za (N.N.) 2 Department of Mathematical and Computational Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa 3 Unit for Environmental Science and Management, North West University, Vanderbijlpark 1900, South Africa; 32945280@nwu.ac.za * Correspondence: caston.sigauke@univen.ac.za † These authors contributed equally to this work. Abstract: Extreme value theory is a powerful method that is known to provide statistical models for events rarely observed. This paper presents a modelling framework for the maximum rainfall data recorded in Limpopo province, South Africa, from 1960 to 2020. Daily and monthly rainfall data were obtained from the South Africa Weather Service. In this work, the r-largest order statistics modelling approach is used. Yearly blocks were used in fitting a 61 years’ data set. The parameters of the developed models were estimated using the maximum likelihood method. After the suitable model for data was chosen, i.e., GEVD r=8 , the 50-year return level was estimated as 368 mm, which means a probability of 0.02 exceeding 368 mm in fifty years in the Thabazimbi area. This study helps decision-makers in government and non-profit organisations improve preparation strategies and build resilience in reducing disasters resulting from extreme weather events such as excessive rainfall. Keywords: extreme value theory; Fréchet class of distribution; maximum rainfall; r-largest order statistics 1. Introduction Climate extremes such as floods, droughts and heatwaves have become topical issues since they have triggered most natural disasters in recent decades that can potentially affect humans and the natural environment [1]. Climate extreme events are regular across the globe and impact society in various ways, leading to loss of lives, shortage of food, failure of crops, famine, mass migration and health issues [2]. The increased number, frequency and intensity of natural hazards such as floods, heatwaves and hurricanes are generally attributed to climate change [3–5]. In Africa, impacts of a changing climate vary significantly by region [6,7]. More than 90% of natural disasters in southern Africa are related to weather, climate and water. Understanding extreme climate events will help prepare and formulate mitigation strategies to cope with events associated with climate change. Modelling and predicting future extreme events become more relevant in commercial agriculture, to insurance companies, statisticians and meteorologists. Extreme climate and weather events such as floods, droughts and heatwaves negatively impact society, environment and resource management in developing countries [6,8,9]. In South Africa, anomalous cut-off lows, tropical cyclones and tropical storms are the major extreme rainfall producing systems affecting the Limpopo province, while the Botswana High becomes dominant during heatwaves and drought. Extreme weather events are common in Limpopo during summertime and often coincide with mature phases of the El Niño Southern Oscillation. In February 2000, about 700 people lost their lives and over a million residents were displaced in Mozambique due to flooding associated with tropical cyclone Eline [10,11]. In recent decades (1980–2015), southern Africa experienced Climate 2022, 10, 33. https://doi.org/10.3390/cli10030033 https://www.mdpi.com/journal/climate