African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6862

Full Length Research Paper

Rainfall trend and variability analysis in Setema-Gatira area of Jimma, Southwestern Ethiopia

Girma Eshetu*
  • Girma Eshetu*
  • College of Agriculture and Veterinary Medicine, Jimma University, Jimma, Ethiopia.
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Tino Johansson
  • Tino Johansson
  • CHIESA Project Coordinator at International Insect Physiology and Ecology (ICIPE), Nairobi, Kenya.
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Wayessa Garedew
  • Wayessa Garedew
  • CHIESA Project Coordinator at International Insect Physiology and Ecology (ICIPE), Nairobi, Kenya.
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  •  Received: 14 July 2015
  •  Accepted: 15 October 2015
  •  Published: 11 August 2016


In this study, the trend and variability of rainfall were analyzed for Setema and Gatira meteorological stations. Daily rainfall data for two stations was obtained from National Meteorological Agency of Ethiopia. Mann-Kendall’s test was employed for a rainfall trend analysis. Standardized rainfall anomaly index, rainfall concentration index and coefficient of variation were used as descriptors of rainfall variability. The trend analysis revealed decreasing rainfall trend in Setema and increasing trend in Gatira. However, rainfall trends were not statistically significant (p < 0.05). The coefficient variation of the study area for Setema was (CV = 23%), while for Gatira it was (CV = 8%) which showed lower inter-annual variability. The rainfall concentration index revealed that 35% of years with values of PCI >16 in setema indicate poor monthly distribution. Monthly rainfall concentration range from moderate to high and total rainfall of the study area concentrated in ½ of the period. The standardized anomalies of annual rainfall revealed negative anomalies 42% at Setema and 50% of years at Gatira. All most in all stations annual rainfall has shown negative anomalies for much of the 1983/4 and 1994. Present study only showed local level rainfall trend and variability analysis, so future study should include watershed or regional levels.

Key words: Climate, rainfall trend, standard anomaly index, precipitation concentration index.