Remote sensing-based spatio-temporal rainfall variability analysis: the case of Addis Ababa City, Ethiopia

Abstract

Climate variability is a highly debated and unavoidable global environmental challenge that has adverse effects on Ethiopia, a developing country. Hence, the objective of this research is to examine the changes in rainfall patterns in Addis Ababa City, Ethiopia, from 1981 to 2018, considering both spatial and temporal aspects. The study utilized a time-series dataset of climate information, which had a spatial resolution of 4 × 4 km, obtained from the National Meteorological Agency of Ethiopia. Supplementary data was also acquired from the Ethiopian Space Science and Geospatial Institute. To examine the rainfall variability, statistical measures such as the coefficient of variation (CV) and standardized anomaly index (SAI) were employed. Geospatial technologies and “R” programming were also used to perform a non-parametric Mann-Kendall (MK) test and Sen’s slope estimator for the investigation of both the trend and magnitude of changes. The annual, Kiremt (main rainy), and Belg (spring) seasons rainfall exhibited low to moderate variability with CV < 20% and CV < 30%, respectively, and very high variability for the Belg season (CV > 30%). The Bega season’s variability was extreme (CV > 70%). In contrast, decadal rainfall variability was generally very low (CV < 10%). The months from October to March showed higher inter-monthly variability, with CV exceeding 100%. In contrast, the Kiremt season, July, and August, experienced lower inter-monthly variability (CV < 30%). The western, north-east, and southern parts of Addis Ababa demonstrated relatively higher rainfall variability, and the trends decreased in all seasons and months, except the Kiremt season and the months of May, June, and September. However, none of these seasonal and monthly changes were statistically significant (P > 0.05). The study identified 6 years (1982, 1984, 1997, 1999, 2014, and 2015) with varying degrees of drought. Consequently, the spatio-temporal variability of precipitation should be considered in development plans, disaster risk reduction strategies, and policy measures such as flood management.