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An Insurable Risk Analysis For Construction Projects And Industry Using Spi: Gauteng Province, South Africa

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dc.contributor.author Hlalele, Bernard, Moeketsi
dc.date.accessioned 2023-05-24T06:53:59Z
dc.date.available 2023-05-24T06:53:59Z
dc.date.issued 2020
dc.identifier.issn 2005-4238
dc.identifier.uri http://hdl.handle.net/11462/2491
dc.description Article en_US
dc.description.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. en_US
dc.language.iso en en_US
dc.publisher International Journal of Advanced Science and Technology Vol. 29, No. 7, (2020), pp. 13507 - 13525 en_US
dc.relation.ispartofseries International Journal of Advanced Science and Technology;Vol. 29, No. 7, (2020), pp. 13507 - 13525
dc.subject Drought en_US
dc.subject Project risk en_US
dc.subject Hazard en_US
dc.subject Construction business en_US
dc.subject SPI en_US
dc.subject Insurable risk en_US
dc.title An Insurable Risk Analysis For Construction Projects And Industry Using Spi: Gauteng Province, South Africa en_US
dc.type Article en_US


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