Spatiotemporal variability and time series trends of rainfall over northwestern parts of Ethiopia: the case of Horro Guduru Wollega Zone.

Abstract

This study examined the variability and trend of rainfall over Horro Guduru Wollega Zone. Studies such as this have paramount importance in countries and areas where rain-fed agriculture is predominant. Datasets for analysis were obtained from the National Meteorological Agency of Ethiopia (NMA) from 1987 to 2016 and Climate Hazard Group InfraRed Precipitation (CHIRPS) 1987-2019 with the station portal. Monthly rainfall with temporal variability ranging from 9.77 to 141.93% was observed. High variable (CV > 30%) and less variable (CV < 20%) rainfall was observed in the CHIRPS data records. Rainfall during most months of the last 30 and 33years showed a decreasing trend. Rainfalls with temporal variability ranging from 12.7 to 75.92% and from 8.11 to 43.45% were observed during the 3-month seasons, respectively. Rainfall over the 3-month seasons of the last 30 and 33years showed a decreasing trend. The average total rainfall ranging from 107.203 to 1016.82mm and from 122.8 to 1147.9mm, with variability from 9.163 to 55.7% and from 7.831 to 36.68% were observed during the Belg, Kiremt, and Bega seasons of the last 30 and 33years, respectively. A decrease in rainfall was tested over these three seasons of the last 30 and 33years. Significantly different (P < 0.05) and less variable (CV < 20%) annual total rainfall was recorded at 24 stations over 30years. Declining annual rainfall was observed over 30 and 33years. Non-significantly different (P < 0.05) and less variable (CV < 20%) average decadal rainfall ranging from 1342.6 to 1372.8mm was observed during the last 33years. The study area had experienced a rainfall with decreasing trends almost over all time scales. These might have been resulting in failure of agricultural production that necessitates developing and implementing systematic planning and management activities in the crop calendar under the face of changing rainfall patterns.