Modelling of Extremely High Rainfall in Limpopo Province of South Africa
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...
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MDPI AG
2022-02-01
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| Series: | Climate |
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| Online Access: | https://www.mdpi.com/2225-1154/10/3/33 |
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| author | Thendo Sikhwari Nthaduleni Nethengwe Caston Sigauke Hector Chikoore |
| author_facet | Thendo Sikhwari Nthaduleni Nethengwe Caston Sigauke Hector Chikoore |
| author_sort | Thendo Sikhwari |
| collection | DOAJ |
| description | 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 <i>r</i>-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<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mrow><mi>r</mi><mo>=</mo><mn>8</mn></mrow></msub></semantics></math></inline-formula>, 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. |
| first_indexed | 2024-03-09T19:59:06Z |
| format | Article |
| id | doaj.art-8d7fa04ad9dc412a8169d9f386ad36e8 |
| institution | Directory Open Access Journal |
| issn | 2225-1154 |
| language | English |
| last_indexed | 2024-03-09T19:59:06Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Climate |
| spelling | doaj.art-8d7fa04ad9dc412a8169d9f386ad36e82023-11-24T00:48:58ZengMDPI AGClimate2225-11542022-02-011033310.3390/cli10030033Modelling of Extremely High Rainfall in Limpopo Province of South AfricaThendo Sikhwari0Nthaduleni Nethengwe1Caston Sigauke2Hector Chikoore3Department of Geography and Geo-Information Sciences, School of Environmental Sciences, University of Venda, Thohoyandou 0950, South AfricaDepartment of Geography and Geo-Information Sciences, School of Environmental Sciences, University of Venda, Thohoyandou 0950, South AfricaDepartment of Mathematical and Computational Sciences, University of Venda, Private Bag X5050, Thohoyandou 0950, South AfricaUnit for Environmental Science and Management, North West University, Vanderbijlpark 1900, South AfricaExtreme 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 <i>r</i>-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<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msub><mrow></mrow><mrow><mi>r</mi><mo>=</mo><mn>8</mn></mrow></msub></semantics></math></inline-formula>, 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.https://www.mdpi.com/2225-1154/10/3/33extreme value theoryFréchet class of distributionmaximum rainfall<i>r</i>-largest order statistics |
| spellingShingle | Thendo Sikhwari Nthaduleni Nethengwe Caston Sigauke Hector Chikoore Modelling of Extremely High Rainfall in Limpopo Province of South Africa Climate extreme value theory Fréchet class of distribution maximum rainfall <i>r</i>-largest order statistics |
| title | Modelling of Extremely High Rainfall in Limpopo Province of South Africa |
| title_full | Modelling of Extremely High Rainfall in Limpopo Province of South Africa |
| title_fullStr | Modelling of Extremely High Rainfall in Limpopo Province of South Africa |
| title_full_unstemmed | Modelling of Extremely High Rainfall in Limpopo Province of South Africa |
| title_short | Modelling of Extremely High Rainfall in Limpopo Province of South Africa |
| title_sort | modelling of extremely high rainfall in limpopo province of south africa |
| topic | extreme value theory Fréchet class of distribution maximum rainfall <i>r</i>-largest order statistics |
| url | https://www.mdpi.com/2225-1154/10/3/33 |
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