Rainfall and Temperature Trend Analysis using Mann-Kendall and Sen's Slope Estimator Test in Makueni County, Kenya

Abstract

This study sought to analyze annual, seasonal, and monthly rainfall and temperature (minimum and maximum) trends in Makueni County from 1991 to 2020 using the Mann–Kendall (MK) trend test and Theil-Sen’s slope estimator. Data analysis was done in R software. The findings revealed a declining trend in annual and seasonal (short and long rain seasons) rainfall, albeit statistically insignificant. Similarly, monthly rainfall exhibited a downward trend in nine of the twelve months. This decline, however, was only significant in June. The findings revealed a statistically significant upward trend in the county’s annual and seasonal minimum and maximum temperatures across the study period. Similarly, monthly analysis revealed a statistically significant increasing temperature (both minimum and maximum) trend in at least nine of the twelve months. When the data was analyzed by sub county, the results revealed differing trends in annual, seasonal and monthly rainfall patterns with some sub counties experiencing increased rainfall and others decreased rainfall. However, annual, seasonal and monthly temperature (minimum and maximum) analysis revealed an increasing trend in all the sub counties with the most of the observations being statistically significant. These patterns suggest that Makueni county is already experiencing climate change. The findings serve as a foundation for sound climate change policy decisions in the county. They also suggest the need for the development of climate change adaptation strategies targeted at mitigating risks and increasing resilience to climate shocks.