The impact of rainfall variability and crop production on vertisols in the central highlands of Ethiopia

Abstract

Abstract Background Understanding the yearly, seasonal, monthly, and weekly rainfall variability is crucial for improved agricultural practice in Ethiopia, where agriculture depends on rainfall. In particular, knowledge of rainfall onset, withdrawal, amount, distribution, and the length of the crop growing period would protect farmers from crop damage due to climatic anomalies. This study collected and described 39 years of rainfall data using the Markov chain model. Based on the rainfall probability levels at different threshold values, the length of the dry and wet spells and the length of the growing period were determined. Results The study shows dependable rainfall at a 75% probability level commences in June. The chance of receiving greater than 10 mm at a 50% probability level starts in week 10 (5 March–11 March), with much discontinuity up to week 21st (21 May–27 May). The dependable weekly rainfall begins the week of 22 May (28th May–3rd June) with a probability of greater than 20 mm. The study revealed that the short rainy season rainfall (February to May) is unreliable for growing crops at Ghinchi as opposed to other highland areas of Ethiopia. The major crop growing season is therefore confined to periods of the long rainy season (weeks 22nd to 39th, or 28th May–30th September). The water balance for the study area indicates that the moisture availability index is greater than 0.5, and potential evapotranspiration is lower than precipitation during these months. Conclusions Climate change and rainfall variability is creating a problem with crop production constraints in the rain-fed agricultural production system in the highlands of Ethiopia. Physical properties of the soil coupled with the unfavorable soil-rainfall relationship limit increased crop production on vertisols. Improving the drainage system and capturing rainfall variability in agronomic-relevant terms is essential. Improving the physical limitations of the soil, adapting to rainfall variability, and practicing improved agronomic practices may help farmers overcome the production problem. This study provides critical information on rainfall variability concerning vertisol management and crop production. However, to overcome the problem, technological support is needed from researchers and policymakers.

Keywords

• Variability
• Probability
• Markov chain model
• Threshold
• Vertisol