An insurable risk analysis for construction projects and industry using SPI: Gauteng Province, South Africa

Abstract

The South African construction sector accounts for 11% of the total employment, thus contributing approximately 4% of the country’s Gross Domestic Product (GDP). However, severe unpredictable weather patterns can send this sector’s costs skyrocketing and revenue spiralling. Construction industry is said to be a good indicator for economic growth. The aim of this current study was to assess rainfall variability in the current rapidly changing climate regime, to set an avenue for businesses’ opportunities and risk reduction adaptation measures in order to keep this industry in the market. Annual rainfall data sets from eight weather stations were collected from an online source for analysis. A non-parametric test, Pettitt’s homogeneity and Shapiro-Wilk tests for data stationarity and normality respectively were deployed. A further Mann Kendall’s trend test was used to detect if any monotonic trend patterns were existent in the data sets. The probability of non-exceedance and return level periods were computed for each station. ANOVA test revealed all stations statistically different in rainfall patterns. The major results for this study, was that (i) no statistically significant decreasing patterns were observed over all candidate stations (ii), for every 2 to 5-year return periods, all stations are to experience near-normal drought conditions as computed from Standardised Precipitation Index (SPI). Given the frequent and intense drought episodes in South Africa and other parts of the world, Gauteng province remains a relatively conducive environment for construction business projects.