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Analysis of spatiotemporal distribution, variability, and trends of rainfall in Wollo area, Northeastern Ethiopia

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  • Asnake Adane
  • Birhanu Asmerom

Abstract

Ethiopia’s agriculture is mostly dependent on rain, though the rainfall distribution and amount are varied in spatiotemporal context. The study was conducted to analyze the distribution, trends, and variability of monthly, seasonal, and annual rainfall data over the Wollo area from 1981 to 2022. To accomplish this, the study utilized the Climate Hazards Group Infrared Precipitation with Stations version two (CHIRPS-v2) data. Standard Rainfall Anomaly Index (SRA) and Coefficient of Variation (CV) were employed to examine rainfall variability and develop drought indices over southern Ethiopia. The Modified Mann Kendall (MMK) test, Sen’s slope estimator and the innovative trend analysis (ITA) were employed to detect temporal changes in rainfall trends over the study period. The study found that the area experienced considerable rainfall variability and change, resulting in extended drought and flood events within the study period. Results from SRA and CV revealed interannual and seasonal rainfall variability, with the proportions of years below and above the long-term mean being estimated at 56% and 44%, respectively. The MMK test showed that the annual rainfall during the Kiremt (summer-main rainy season) had an increasing trend. On the other hand, rainfall for the Belg (short rain season for the study area) season and the Bega (winter) season showed a significantly decreasing trend (p

Suggested Citation

  • Asnake Adane & Birhanu Asmerom, 2025. "Analysis of spatiotemporal distribution, variability, and trends of rainfall in Wollo area, Northeastern Ethiopia," PLOS ONE, Public Library of Science, vol. 20(1), pages 1-29, January.
    • Handle: RePEc:plo:pone00:0312889
    DOI: 10.1371/journal.pone.0312889
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    References listed on IDEAS

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    1. Parkes, Ben & Higginbottom, Thomas P. & Hufkens, Koen & Ceballos, Francisco & Kramer, Berber & Foster, Timothy, 2019. "Weather dataset choice introduces uncertainty to estimates of crop yield responses to climate variability and change," IFPRI discussion papers 1870, International Food Policy Research Institute (IFPRI).
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