PRECIPITATION VARIABILITY DETERMINANTS IN THE HIGHLANDS OF LESOTHO

The Southern Oscillation Index (SOI) and Sunspot Numbers (SSN) have long been recognized as key indicators of precipitation variability in various regions across the world. Understanding the influence of SOI and SSN on precipitation is crucial for effective water resource management, particularly in areas dependent on rainfall for their water supply. This study aimed at examining influences of SOI and SSN on precipitation variability in the highlands of Lesotho, a region that is particularly a source of country’s income and hydro energy. Key findings of this study showed a wide range of variability in SOI (M = -1,002; SD = 10,514) and SSN (M = 73,778; SD = 66,745) as well as in the dam precipitation measurements. A Mood test indicated a statistically significant difference in precipitation across the selected weather stations (U(3) = 9.685, p = 0.021). The Pettitt’s test for homogeneity showed no significant difference in the precipitation data for the four weather stations. The Dickey-Fuller test results showed strong evidence of stationarity in the precipitation data for the four stations. The Mann Kendall trend test showed a statistically significant trend in the SSN data (Kendall’s tau = -0.241, two-tailed p-value = or less than 0.0001) but not in the other data sets. The correlation analysis showed a weak positive relationship between SOI and precipitation in the dams (r = 0.083, p = 0.086 for Katse dam and r = 0.070, p = 0.146 for Mohale dam), while SSN had a strong negative correlation with precipitation in the dams (r = -0.025, p = 0.604). These results suggest that SOI and SSN play a significant role in the precipitation patterns in the dams and further studies are needed to explore their full extent and implications for water resources management. This study provides evidence of the significant influence of SOI and SSN on precipitation variability in the highlands of Lesotho, with a weak positive relationship between SOI and precipitation and a strong negative relationship between SSN and precipitation. Further research is necessary to understand the implications of these findings for water resources management in the region.