Dry spell length analysis for crop production using Markov-Chain model in Eastern Hararghe, Ethiopia
DOI:
https://doi.org/10.15243/jdmlm.2017.044.891Keywords:
crop production, dry spells, Markov-chain model, EthiopiaAbstract
The information on the length of dry spells could be used for deciding a particular crop or variety, supplementary irrigation water demand and for others agricultural activities. The study was conducted in three districts: Babile, Haramaya and Kersa, eastern Hararghe, Ethiopia. The aim of the study was to analyze dry spell lengths and its implications on crop production in eastern Hararghe, so as to minimize unexpected damage due to long dry spells and to have effective and efficient planning for farming communities. Thirty years of rainfall data for each district were collected form National Meteorological Agency of Ethiopia. Data quality control has been done prior to analysis. Markov-Chain model were employed to analyze the collected data. The result of the study revealed that dry spells were highly hitting Babile district comparing to the other two districts. The probability of dry spell lengths of 5 and 7 days in Babile district was found to be about 99 and 80%, respectively. Whereas, in Haramaya district, the probability of dry spell length of 5 days was found to be 80% during 181(Days of the Year) DOY, then it falls to below 50 % by 221DOY. Moreover, the probability of the occurrences of dry spells of 10, 15, and 20 days were below 5% in Haramaya district during the main rainy season. The study also investigated that in Kersa district, the probability of occurrences of the dry spell lengths of 5, 7, 10, 15, and 20 days were estimated to fall below 30%, showing that the area was better in crop production as compared to the rest districts. The annual rainfalls in all the districts were decreasing as per the trend line and variable in all the districts: Babile, Haramaya and Kersa districts, having the CV values of, 41, 34 and 31%, respectively. Information regarding dry spell length analysis has to be well understood at grass root levels to ensure food security via lifesaving irrigation schemes or any other options.Â
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