Geospatial-based climate variability analysis, in Central Ethiopia Rift Valley

• Published in: Theoretical and applied climatology 2023-04, Vol.152 (1-2), p.151-165
• Main Authors: Mekonnen, Esubalew Nebebe, Liou, Yuei-An, Damene, Shimeles, Gebremariam, Ephrem, Mulualem, Getachew Mehabie
• Format: Article
• Language: English
• Subjects: Analysis; Annual rainfall; Annual variations; Aquatic Pollution; Atmospheric Protection/Air Quality Control/Air Pollution; Atmospheric Sciences; CAD; Climate; Climate change; Climate science; Climate variability; Climatic analysis; Climatology; Computer aided design; Correlation; Crop production; Data analysis; Developing countries; Drought; Earth and Environmental Science; Earth Sciences; Ground stations; Hydrologic data; Information management; LDCs; Maximum temperatures; Mean; Mean annual precipitation; Minimum temperatures; Normalized difference vegetative index; Original Paper; Precipitation; Precipitation variability; Rain; Rain and rainfall; Rainfall; Rainfall data; Rainy season; Remote sensing; Rift valleys; Spring; Spring (season); Statistical analysis; Statistical correlation; Statistical methods; Surveys; Temperature; Temperature rise; Valleys; Variability; Vegetation; Vegetation index; Waste Water Technology; Water Management; Water Pollution Control; Wet season
• ISSN: 0177-798X; 1434-4483
• DOI: 10.1007/s00704-023-04376-6

Climate variability has been a crosscutting issue across the globe, where the effect is more adverse in developing countries such as Ethiopia. The study aimed at investigating climate variability of Ziway Dugda and Dodota Woredas, Central Rift Valley, Ethiopia. The study has used 1983–2012, time series gridded data, field survey, and normalized difference vegetation index (NDVI) data. The data were thoroughly processed and analyzed using combination of Geospatial technologies and descriptive statistics. Long-term (1983–2012) rainfall data analysis result revealed an increasing trend, with an overall mounting rate of 78.5 mm in three decades period and it is also characterized by inter-annual fluctuation. The mean maximum total rainfall analysis of the same period divulges a consistent pattern, distinctively featured by late-onset and early cessation of rainfall. It is found that the maximum temperature increased by 0.23 °C per decade with an overall rise of 0.7 °C in the 30-year period of concern, while the minimum temperature remains constant. The statistical correlation result signposted a linear positive correlation between NDVI and mean annual and spring season rainfall with r 2 value of 0.3467 and P value of 0.0342, and r 2 of 0.715 and P value of 0.0003, respectively. Indisputably, variability of rainfall, and minimum and maximum temperatures was observed. The analysis also stipulated that climate variability is pervasive particularly in the spring rainy season, substantially dwindled in its amount and distribution, and eventually afflicts the vegetation condition and crop production in the milieu. Therefore, as climate variability has been highly manifested in the study area, appropriate policy and strategic measures are required to reduce and mitigate the consequent impacts.