Drought Risk Analysis in the Eastern Cape Province of South Africa: The Copula Lens

Abstract

<jats:p>This research study was carried out to investigate the characteristics of drought based on the joint distribution of two dependent variables, the duration and severity, in the Eastern Cape Province, South Africa. The drought variables were computed from the Standardized Precipitation Index for 6- and 12-month accumulation period (hereafter SPI-6 and SPI-12) time series calculated from the monthly rainfall data spanning the last five decades. In this context, the characteristics of climatological drought duration and severity were based on multivariate copula analysis. Five copula functions (from the Archimedean and Elliptical families) were selected and fitted to the drought duration and severity series in order to assess the dependency measure of the two variables. In addition, Joe and Gaussian copula functions were considered and fitted to the drought duration and severity to assess the joint return periods for the dual and cooperative cases. The results indicate that the dependency measure of drought duration and severity are best described by Tawn copula families. The dependence structure results suggest that the study area exhibited low probability of drought duration and high probability of drought severity. Furthermore, the multivariate return period for the dual case is found to be always longer across all the selected univariate return periods. Based on multivariate analysis, the study area (particularly Buffalo City, OR Tambo and Alfred Zoo regions) is determined to have higher/lower risks in terms of the conjunctive/cooperative multivariate drought risk (copula) probability index. The results of the present study could contribute towards policy and decision making through e.g., formulation of the forward-looking contingent plans for sustainable management of water resources and the consequent applications in the preparedness for and adaptation to the drought risks in the water-linked sectors of the economy.</jats:p>

Hydrological modelling for assessing spatio‐temporal groundwater recharge variations in the water‐stressed Amathole Water Supply System, Eastern Cape, South Africa

“…However, the natural water yield is predicted to fall behind the region's water requirement by the end of the current decade largely due to population and economic growth (DWS, 2016). Regional studies predict that increasing temperatures and a higher frequency or severity of extreme events such as droughts, are likely to further reduce the future reliability of the regional surface water availability (Botai et al, 2020; Dube et al, 2016; Mantel et al, 2015). Water levels in the dam reservoirs have been declining critically in recent years and Buffalo City was facing an acute Day‐Zero‐scenario in 2020 (Daily Dispatch, 2017; Department of Water and Sanitation, 2019; Global Africa Network, 2018).…”

Prediction of water reuse potential in South African water management areas: A linear regression and Bayesian network approach

“…In 2015-2016, South Africa's agricultural activities were threatened by a severe drought which was caused by an El Nino weather system that swept across southern Africa (Baudoin et al 2017). In 2020, Botai et al (2020) reported that five of the most economically active provinces of South Africa were recovering from the severe drought, which had caused negative socioeconomic impacts. The adverse climatic conditions resulted in the critical shortage of potable water and damages to crops, to the point that the North West Province was declared a state of disaster (Botai et al 2016).…”

Hydroclimatic Extremes in the Limpopo River Basin, South Africa, under Changing Climate

“…There are various ways in which climatological and hydrometric variables can be monitored. These include the use of integrated models to model interactions between natural and human processes [3], the assessment of trends in hydrological statistical parameters (e.g., annual mean, median, minimum and maximum) of the climate variables [21][22][23][24], General Extreme Value (GEV) analysis to determine the probability distribution and return periods of extreme events [25,26] and drought monitoring based on drought indices and drought monitoring indicators [27][28][29][30][31]. Research studies on monitoring of hydroclimatic variables are an essential supportive tool for policy makers in disaster preparedness, particularly in the most vulnerable communities, who are anticipated to always respond in earnest and continuously propose climate-related policies that support societal well-being, protection of infrastructure and all sectors of the economy.…”