Extreme rainfall indices and their consequences on the local farming crop calendar: An agro-climatic zone based study

Abstract

<p>The goal of this study is to investigate the extreme rainfall indices and their consequences on the local farming crop calendar among agro-climatic zones (ACZs) of the Abiya watershed. Climate Hazards Group Infrared Precipitation (CHIRPS) provided long-term (1981–2019) rainfall data for 50 sample grid points with a spatial resolution of 5 × 5 km. Different crops are affected differently by the same extreme rainfall event depending on when it occurred and how extreme it was; this means crop calendars for a specific time may be properly governed by extreme climatic conditions. There hasn’t been a sufficient published study on extreme rainfall indices and their consequences on crop calendars by considering various ACZ in Ethiopia. The study defined local crop calendar timing and the consequences of the extreme rainfall indices through focus group discussions. INSTAT+ software was applied to calculate eight extreme rainfall indices. The indices were evaluated using Mann-Kendall’s (MK) and Sen’s slope techniques to identify trends and determine variations in the magnitude, respectively. Increase and decrease indications for various crop calendars were found in each ACZ. Further, going-up signals were seen in the highlands, midlands, and all ACZs for land preparation time (LPT), sowing and management time (SaMT), and harvesting and threshing time (HaTP), respectively. While HaTT was found to be uniform in all ACZs, some of the declining trends in the indices were detected for LPT and SaMT in the cold-highland and highland zones. The perceived trend in indices across the whole ACZ will have direct and unintended consequences for watershed crop production. The findings imply that to reduce the unfavourable consequences of these extreme rainfall indices occurrences in the agricultural sector, it is necessary to develop suitable crop varieties and drought-tolerant crops, as well as an effective early warning system.</p>