ASSESSING IMPACTS OF CLIMATE VARIABILITY ON SORGHUM YIELD IN CHIRO DISTRICT, EASTERN ETHIOPIA

Ethiopia is one of the countries where agricultural production is highly vulnerable to climate change and variability. An understanding of the impacts of climate variability on agricultural production at a local level is essential to devise context-specific adaptations. In view of this, this study was carried out to assess the impact of climate variability on sorghum yield in Chiro district. To achieve this objective, historical time series climate data and sorghum yield data from 2000 to 2020, were collected from the National Meteorological Agency (NMA) of Ethiopia and the Chiro district Agricultural Office, respectively. After checking for quality, data analysis was carried out using INSTAT+ v.3.36 and XLSTAT 2014. The long-term annual and kiremt rainfall showed moderate variability with a coefficient of variation (CV) of 22% and 24%, respectively. Bega and belg showed high variability with a CV of 73.4% and 38.6%, respectively. The average onset and end dates of belg were on April 05 and May 09, respectively, while the average onset and end dates of kiremt were on July 13 and September 20, respectively. The length of growing period for belg and kiremt seasons were 34 and 69 days, respectively. The mean NRDs of annual, belg and kiremt seasons of the study area during the study period, were 116, 37 and 65 days with CV values of 12.6%, 13.9% and 24.1%, respectively. The dry spell probability curve reached a minimum point around April for the belg season and around August for the kiremt season and reaches a maximum point during the growing season and maturity of sorghum. The mean sorghum yield recorded was 17 qt/ha with moderate variability (CV=25.7%). The recorded sorghum yield was below sorghum yield in the West Hararghe zone, Oromia region and the national estimates. Pearson’s correlation analysis revealed that annual rainfall (r = 0.90), belg and kiremt rainfall (r = 0.74) rainfall, had a very strong and moderate positive relationship with sorghum yield, respectively. Additionally, rainfall variables such as end date (r = 0.61), LGP (r = 0.55), and NRDs (r = 0.60) of belg season, and LGP (r = 0.58) of kiremt season had a moderate positive association with sorghum yield. However, the onset date of belg (r = -0.36) and kiremt (r = -0.46) seasons had a weak and moderate negative correlation with sorghum yield, respectively. Multiple regression analysis showed that the coefficient of determination (R2) was 0.884, this means that about 88.4% of the variation is explained by the fitted model and hence the model is good for the data set to go for the linear regression analysis. The regression model explain by adjusted R square 76.8% of the total variation in the sorghum yield by climatic parameters jointly. In general, climate variability has a considerable negative influence on sorghum yield in the district. Further studies are needed on extended weather forecasting to minimize the effect of climate variability on yield decline.