Geospatial Variabilities and Trends in Extreme Agroclimatic Indicators in the Jimma Zone, Southwest Ethiopia

Abstract

Abstract Floods, droughts, and heat waves are becoming more common in Ethiopia, inflicting havoc on the country's rain-fed agricultural productivity. The objective of the study was to investigate the patterns and volatility of the extreme agroclimatic indicator in the Jimma zone. Raw data of daily rainfall temperatures from ten weather stations recorded between 1991 and 2020 was processed using the Climate Impact version 2 (ClimPact2) tool to extract extreme agroclimatic indicators. A regression model and descriptive statistics were used, respectively, to examine the spatial and time-series patterns of the 12 significant extreme agroclimatic indicators that were selected from a total of 27. The geographic distribution of the variables was displayed using ArcMap. The results show that the coefficient of variation for the number of consecutive dry days, the number of days with heavy rain, very heavy rain, and extremely heavy rain is greater than 30%. The annual mean of consecutive dry days was 35 days per year, with a 44% coefficient of variation. The minimum and maximum values of the indicators were recorded at Gera (11 days per year) and Omo-Nada (77 days per year), respectively. The total annual average rainfall was extremely heavy (248.28 mm) and very heavy (59.80 mm), with very high coefficients of variation of 45 and 62%, respectively. The western and northeastern portions of the research area were eroded as a result of these rainfall extremes. The eastern portion of the research area was impacted mostly by the coldest day temperatures, the warmest day temperatures, and consecutive dry days. The number of cool nights and cool days both dropped significantly at all stations, while the number of warm nights, cold (TXn), and warm (TXx) daytime temperatures over the study area. There can be no dispute regarding the socio-economic effects of climate variability and change, which are increasingly being detected to harm residents because of a significant increase in agroclimatic extreme events. It is suggested that studies on the impacts of agroclimatic indicators on agriculture be conducted.