Abstract
Recognizing that, over the last several years, extreme rainfall has led to hazardous stress in humans, animals, plants, and even infrastructure, in the present study, we aimed to investigate the characteristics of droughts over the Free State (FS) Province of South Africa in order to determine the future likelihood of reoccurrences of precipitation extremes using the generalized extreme value distribution (GEV) and extreme frequency analysis (EFA). In this regard, daily rainfall datasets from nine South African weather service homogenous climatic districts, spanning from 1980 to 2019, were used to compute: (a) the total annual rainfall, (b) the Effective Drought Index (EDI), and (c) the Standard Precipitation Index (SPI). The SPI was calculated for 3, 6, and 12 month accumulation periods (hereafter SPI-3, SPI-6, and SPI-12, respectively). The trend analysis results of the EDI and SPI-3, -6, and -12 showed that the Free State Province is generally negative, illustrating persistent drought. An analysis of the GEV parameters across the EDI and SPI-3, -6, and -12 values illustrated that the location, scale, and shape parameters exhibited a noticeable spatial variability across the Free State Province with the location parameter largely negative, the scale parameter largely positive, while the shape parameter pointed to an inherent Type III (Weibull) GEV distribution. In addition, the return levels for the drought/wet duration and severity of the EDI and SPI-3, -6, and -12 values generally showed increasing patterns across the corresponding return periods; the spatial contrasts were only noticeable in the return levels derived from the wet/drought duration and severity derived from SPI-3, -6, and -12 values (and not in the EDI). Further, the EFA results pointed to a noticeable spatial contrast in the return periods derived from the EDI and SPI-3, -6, and -12 values for each of the extreme precipitation categories: moderately wet, severely wet, extremely wet to moderately dry, and severely dry. Over four decades, the FS Province has generally experienced a suite of extreme precipitation categories ranging from moderately wet, severely wet, extremely wet to moderately dry, severely dry, and extremely dry conditions. Overall, the present study contributes towards implementation of effective drought early warning systems and can be used to enhance drought related policy and decision making in support of water resource management and planning in the FS Province.
Highlights
Extreme weather patterns can be viewed as complex spatiotemporal physical and societal processes that act as a cascade of events, causing major impacts that transcend many environmental, socioeconomic, and political regimes
The results indicate that 1992, 1994, 2003, and 2015 were dry years illustrated in Figure The results indicate that of the normal period
The results presented in this study suggest that the Free State Province has continued to experience prolonged drought conditions over the period 1980–2019
Summary
Extreme weather patterns can be viewed as complex spatiotemporal physical and societal processes that act as a cascade of events, causing major impacts that transcend many environmental, socioeconomic, and political regimes. Extreme weather events include heatwaves, droughts, floods, wildfires, concurrent wind, and intense rainfall. Climate change has exacerbated the frequency, intensity, severity, and duration of droughts at all geographical scales. This phenomenon can be detrimental, often leading to loss of lives and destruction of properties [1,2,3,4,5,6,7,8,9]. It has been observed that extreme rainfall has a detrimental consequence on food and water security, creating unrest and prompting migrations, among other factors [10]. It is projected that climate change will alter the pattern of occurrence of wet/dry months in the future with severe consequences for agricultural production and food security [11]. Drought is one of the most destructive natural phenomena because its effects extend over a large area and last for a long time, albeit slowly [13]
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