Kori, E.Muthige, M. S.Muzila, Fulufhelo Marvellous2025-11-072025-11-072025-09-05Muzila, F.M. 2025. Spatio-temporal analysis of extreme rainfall events in Limpopo Province. . .https://univendspace.univen.ac.za/handle/11602/3032MENVSCDepartment of Geography and Environmental SciencesThis research on the spatiotemporal analysis of extreme rainfall events in Limpopo Province is critical for understanding the changing rainfall patterns, intensity, and frequency, which have significant implications for water resources, agriculture, infrastructure, and disaster management. However, there is a lack of comprehensive and localized spatiotemporal analysis of extreme rainfall occurrences, particularly in Limpopo Province. The main aim of this study was to analyse spatial and temporal patterns of extreme rainfall in Limpopo province by identifying historical trends, frequency, intensity, and spatial distribution using statistical and geospatial techniques. This was undertaken using historical rainfall data obtained from the South African Weather Service (SAWS). The analysis involved using Geographic Information System (GIS) to examine trends in the frequency and intensity of extreme rainfall, analyse their spatial distribution, and analyse trends in extreme rainfall events using the Student's t-test, to determine the significance and Sen’s slope to assess the magnitude of those trends. Extreme precipitation indices developed by the World Meteorological Organization Expert Team on Climate Change Detection and Indices were used. The findings showed that the majority of Limpopo province saw an increase in the intensity of daily rainfall, aligning with global trends overall. A reduction in precipitation during the rainy period was observed in most regions of the east and northeast, while the eastern and southern sections near the slope received seasonal drought. Mara, Oudestad, and Tshivhasie tea Venda showed a strong upward trend in Consecutive Wet Days (CWD), R20mm, and R95p and a decline in Consecutive Dry Days (CDD) from the period of 1993-2023, showing that as the mean rainfall increases, so do extreme rainfall occurrences. In addition, the mean annual rainfall significantly influenced extreme precipitation indices in Limpopo Province. By assessing long-term trends and spatial variations, this study will assist decision-makers who emphasize climate resilience and sustainable development to properly allocate resources and establish areas that need attention in terms of managing impacts associated with droughts and floods, as well as enhancing local interpretation of rainfall and resource allocation to promote sustainability in the province.1 online resource (x, 87 leaves): color illustrations, color mapsenUniversity of VendaExtreme rainfallUCTDGISRainfall trendsSen slopeStudent t test551.5776825Rain and rainfall -- South Africa -- LimpopoRainfall frequencies -- South Africa -- LimpopoRainfall intensity duration frequencies -- South Africa -- LimpopoClimatic changes -- South Africa -- LimpopoDissertationMuzila FM. Spatio-temporal analysis of extreme rainfall events in Limpopo Province. []. , 2025 [cited yyyy month dd]. Available from:Muzila, F. M. (2025). <i>Spatio-temporal analysis of extreme rainfall events in Limpopo Province</i>. (). . Retrieved fromMuzila, Fulufhelo Marvellous. <i>"Spatio-temporal analysis of extreme rainfall events in Limpopo Province."</i> ., , 2025.TY - Dissertation AU - Muzila, Fulufhelo Marvellous AB - This research on the spatiotemporal analysis of extreme rainfall events in Limpopo Province is critical for understanding the changing rainfall patterns, intensity, and frequency, which have significant implications for water resources, agriculture, infrastructure, and disaster management. However, there is a lack of comprehensive and localized spatiotemporal analysis of extreme rainfall occurrences, particularly in Limpopo Province. The main aim of this study was to analyse spatial and temporal patterns of extreme rainfall in Limpopo province by identifying historical trends, frequency, intensity, and spatial distribution using statistical and geospatial techniques. This was undertaken using historical rainfall data obtained from the South African Weather Service (SAWS). The analysis involved using Geographic Information System (GIS) to examine trends in the frequency and intensity of extreme rainfall, analyse their spatial distribution, and analyse trends in extreme rainfall events using the Student's t-test, to determine the significance and Sen’s slope to assess the magnitude of those trends. Extreme precipitation indices developed by the World Meteorological Organization Expert Team on Climate Change Detection and Indices were used. The findings showed that the majority of Limpopo province saw an increase in the intensity of daily rainfall, aligning with global trends overall. A reduction in precipitation during the rainy period was observed in most regions of the east and northeast, while the eastern and southern sections near the slope received seasonal drought. Mara, Oudestad, and Tshivhasie tea Venda showed a strong upward trend in Consecutive Wet Days (CWD), R20mm, and R95p and a decline in Consecutive Dry Days (CDD) from the period of 1993-2023, showing that as the mean rainfall increases, so do extreme rainfall occurrences. In addition, the mean annual rainfall significantly influenced extreme precipitation indices in Limpopo Province. By assessing long-term trends and spatial variations, this study will assist decision-makers who emphasize climate resilience and sustainable development to properly allocate resources and establish areas that need attention in terms of managing impacts associated with droughts and floods, as well as enhancing local interpretation of rainfall and resource allocation to promote sustainability in the province. DA - 2025-09-05 DB - ResearchSpace DP - Univen KW - Extreme rainfall KW - GIS KW - Rainfall trends KW - Sen slope KW - Student t test LK - https://univendspace.univen.ac.za PY - 2025 T1 - Spatio-temporal analysis of extreme rainfall events in Limpopo Province TI - Spatio-temporal analysis of extreme rainfall events in Limpopo Province UR - ER -