The aim of the study is to analyze the spatio-temporal variability and projection of rainfall and temperature (2021-2040) in Suha watershed, North West highlands of Ethiopia. The study used 4 km × 4 km reconstructed (blended) monthly rainfall and temperature data from National Meteorological Agency of Ethiopia (NMAE) and Royal Netherlands Meteorological Institute (KNMI) of Cen Trends v1 (0.25° × 0.25°), respectively. Mann-Kendall test, Sen's slope estimator, coefficient of variation, autoregressive integrated model , and the inverse distance weighted tool were used to analysis the rainfall and temperature variability for different timescale and agroecology. The coefficient of variation showed the existence of high seasonal variability than the year-to-year in the watershed. Kiremt (main rainy season) rainfall showed substantial inter-annual variability throughout the time of observation (1990-2020). Besides, the Mann-Kendall test and the Sen's slope estimator detected that except, Belg (little rainy season) rainfall, all the others including the annual exhibited a nonsignificant increasing trend at p < 0.05. Spatially, the upper part of the watershed is wetter than the lower portion and a large portion of it (40%) received 930-1024 mm of rainfall per year. The minimum temperature showed a decreasing trend (0.01 °C per year), while the maximum temperature exhibited the opposite result (0.02 °C per year). The seasonal variability in both cases showed mixed outcomes. Forty-two percent of the watershed experiences a minimum temperature of 10.6-12.0 °C, whereas 45% experiences a maximum temperature between 24.1 and 26.0 °C. Meanwhile, the projected result showed that there is a decreasing trend for mean annual rainfall and an increasing trend for mean annual temperature from 2021 to 2040. Hence, policymakers have to give priority to the designing and application of area-specific adaptive strategies to curb the impact of climate variability. Rainwater harvesting and small-scale irrigation practice could be possible options.
Keywords: ARIMA, Agroecological zone; Climate variability; Suha watershed, Trends.
© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.