"Modelling Risk Recurrence Intervals For Agricultural Projects From Theoretical Probability Distribution And Spi: Semonkong, Lesotho, South Africa"

Abstract

Drought events are major natural hazards that occur in various climate regimes with significant agricultural, environmental and socio-economic adverse impacts. These hazards are insidious, obstinate and slow-onset with creeping nature that lead to drought disasters mostly in agriculture dependent communities. In this study, the recurrence intervals of drought were studied from theoretical probability distribution and Standardised Precipitation Index (SPI) at Semonkong station in Lesotho. Firstly the spring (Sep, Oct and Nov) monthly precipitation data obtained from Lesotho Meteorological Services, was tested for outliers and homogeneity (2 tailed p-value = 0.286) for quality control purposes. Secondly, Mann Kendall trend test and probability distribution fitting were both determined by XLSTAT software. No significant trend was revealed. A normal probability distribution fitted well to the data using a Kolmogorov-Smirnov test (pvalue = 0.869) with a risk of 86.9% of rejecting the null hypothesis. DrinC software was then used to compute drought monitoring parameters at three months’ time scale (SPI-3) as shown in equation 1. The normal distribution parameters were then inputted in INSTAT software to determine exceedance probabilities and corresponding precipitation values. All precipitation values exhibited by INSTAT were matched with their SPI values. Given the focus of the current study, both recurrence intervals in years and non-exceedance probabilities were determined. The results showed that the study area is highly likely to experience moderate, severe and extreme or more drought events in 3.33, 5 and 10 years respectively at any given period. This is really a short period that these events will occur at any given year, therefore, the study recommends that authorities, Government, participating private and NGO’s put livelihood diversification measures in place given that over 80% of Lesotho population’s livelihood depends on rain-fed-agriculture.