Trends and spatiotemporal patterns of meteorological drought incidence in North Wollo, northeastern highlands of Ethiopia

Abstract

The study was aimed at detecting and characterizing meteorological drought risk areas using remote sensing data in North Wollo, Ethiopia. The Climate Hazards Group InfraRed Precipitation with Stations (CHIRPS) rainfall dataset was used to compute the Z score index (ZSI) and depict droughts during the meher season (2000–2019). MOD11A2 from Moderate Resolution Imaging Spectroradiometer (MODIS) image datasets was also used to generate land surface temperature (LST) and investigate its association with ZSI and precipitation. To analyze the seasonal and annual rainfall trends, the Mann–Kendall test was applied, and Sen’s slope estimator was used to fix the magnitude of change. The Mann–Kendall test result revealed that an increasing trend of annual rainfall (0.24–10.7 mm/year) has been observed in many districts, while it was decreasing (−0.43 to −3.85 mm/year) in kiremt. However, the belg (1.64–5.13 mm) and bega (0.54–2.8 mm) seasons revealed a slightly increasing trend which was significant at p < 0.05 in one station for the former and three stations for the latter. The ZSI value confirmed that 2002, 2004, 2009, 2011, 2014, 2015, and 2019 were under a rainfall deficit with extreme drought events. Nevertheless, 2009 and 2015 were the driest years, with a Z score intensity of −2.01 to −2.84. Based on the correlation and regression results, ZSI showed a positive relationship (r = 0.93–0.99) with precipitation and negative (r = −0.1 to −0.52) with LST. Thus, ZSI revealed a significant increasing trend (at p < 0.0001) with rising precipitation and a decreasing with LST. In the last 20 years, every district encountered a rainfall deficit repeatedly (15–18 times), and thus, the area is categorized as an extremely high drought risk zone. Such spatiotemporal drought risk events have an imminent threat to the rain-fed agricultural activities, imposing an immense influence on the agro-based livelihoods of the local community. Therefore, it demands continuous drought monitoring and the application of effective early warning systems.