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Climate Change Indicators Trace for Identification of Climat | 84627

Zeitschrift für Klimatologie und Wettervorhersage

ISSN - 2332-2594

Abstrakt

Climate Change Indicators Trace for Identification of Climate Change Vulnerability in Salale Zone, Oromia Region, Ethiopia.

Mengistu Tilahun, Megersa Tefesa, Tade Girma, Misganawu Milkiyas, Hana Tamirat

Droughts and floods have major environmental, social and economic repercussions. Climate change leads to recurrent droughts and floods in different parts of Ethiopia. Therefore, this study was aimed to characterize trends of climate change indicators (temperature, rainfall, drought, and flood). The study was conducted in the Salale zone, Oromia region Ethiopia. 30 years of climate data (maximum temperature, minimum temperature, and rainfall) from 1990-2019 was used to forecast climate variables. The precipitation/evaporation index was used to identify droughtprone areas. The flood-prone areas were identified using slope and rainfall distribution over main rivers. R statistical software, T-R, and Arc Map were used for data analysis. Accordingly, Sululta will receive higher annual rainfall, which is 1232.82 mm explicitly during the end term (2070-2099). The lowest annual rainfall will be scored at Sheno which is 594.04 mm during the near term (2020-2039). The projection of maximum temperature showed that there will be an increase of maximum temperature by 3.83°C and minimum temperature by 4.27°C in the future up to 2099. The highest maximum temperature will be scored at Ghatsion station, which will be 29.6°C in the end term and the lowest minimum temperature will be recorded at Sheno station which will be 8.1℃ in the near term. Areas with low rainfall and high temperature were identified as prone to drought, which indicates high evaporation after low precipitation/rainfall specifically low precipitation/evaporation (P/E) index. Areas found around flat land with main rivers and receive high rainfall are more prone to flooding occurrences.

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert