Spatiotemporal characteristics and trend analysis of rainfall and temperature in Sidama Regional State, Ethiopia

Abstract

This study aims to investigate spatiotemporal variability, trends, and anomaly in rainfall and temperature in the Sidama region, Ethiopia. The TerraClimate gridded dataset on a monthly time scale for 30 years (1991–2020) with a horizontal resolution of approximately 4 km was used for the study. Trends in annual and seasonal rainfall and temperature were assessed using a nonparametric test (Mann-Kendal test) and Sen’s slope, to test the statistical significance and magnitude of trends (increase/decrease), respectively. Our findings revealed that annual rainfall, summer (Hawado), and spring (Badhessa) rainfall have shown an increasing trend in most parts of the region, except for its northwest parts. We found a low annual rainfall variability (CV < 13%) over the southeastern and northwestern parts of the region. Rainfall variability revealed the difference in both time and space across the region. Six drought years (1999, 2001, 2002, 2003, 2012, and 2019) with different magnitudes were identified across the region. Annual average maximum (up to 0.4°C decade–1) and minimum (up to 0.25°C decade–1) temperatures revealed significantly increasing trends across the region. The standardized anomaly in the mean annual temperature indicated that the years in the recent decade (2011–2020) are getting warmer compared to the past two decades (1991–2010) due to climate change and other local and regional factors that cause weather extremes in the region. The results of this study for rainfall contradict the other studies in the rift valley part of the region. Therefore, we suggest the design and implementation of locally driven climate change adaptation strategies so that there is high rainfall and temperature variability across the region and between seasons.

Insights into varroa mite (Varroa destructor) infestation levels in local honeybee (Apis mellifera) colonies of Ethiopia

“…The differences in the prevalence of varroa mites observed across the country may be attributed to various regional factors, such as changes in environmental conditions, seasonal flora of the area, beekeeping management practices and variations in local honey bee subspecies (Giacobino et al, 2017; Hillayová et al, 2022). Although climatic data were lacking in this study, Ethiopia is known for its highly diverse topography, followed by variation in climatic factors (Cheung et al, 2008; Etana et al, 2020; Ware et al, 2023). Such spatial variability in climatic factors, between regions and even between seasons, can create opportunities for the spread of different pests and pathogens beyond their ecological niches if not regularly monitored.…”

“…Although climatic data were lacking in this study, Ethiopia is known for its highly diverse topography, followed by variation in climatic factors (Cheung et al, 2008;Etana et al, 2020;Ware et al, 2023).…”

Historical Trend Analysis and Future Projections of Rainfall in Amhara, Ethiopia

“…As rainfall is the most important meteorological element, it directly affects the socio-economic and food security conditions of a society depending on rain-fed agriculture. Because human-induced climate variability and change have detrimental effects on socio-economic activities such as livelihood, food security, and health (Budusa- Ware et al, 2023), the rainfall trend and projection information in the Amhara regional state of Ethiopia will be crucial for implementing climate change adaption and mitigation strategies in the region. Thus, documented spatiotemporal historical trends and future projections of the rainfall amount of the Amhara regional state of Ethiopia are useful information inputs in policy making and water resources planning and management.…”

Temporal Dynamics and Trend Analysis of Areal Rainfall in Muger Subwatershed, Upper Blue Nile, Ethiopia

“…Te CV was used to evaluate the seasonal and annual rainfall dynamics for the observation period [8,38,41]. According to Hare [3], the extent of rainfall dynamics is classifed as high (CV > 30), moderate (20 < CV < 30), and low (CV < 20).…”