Spatio-temporal variability and rainfall trend affects seasonal calendar of maize production in southern central Rift Valley of Ethiopia

Abstract

Understanding rainfall variability is important to establish crop calendar related agronomic decisions. To this end, we defined start and end of seasons, analyzed dry spell and evaluated conditional risks of alternative planting dates using a thirty years daily rainfall data across southern central rift valley of Ethiopia. Results showed that the probability of annual rainfall being greater than 1000 mm was 97, 24, 94, and 61%, in Dilla, Bilate, Shamana, and Hawassa clusters, respectively. The variability of annual total rainfall in the lowland areas of Dilla and Bilate was above 25%, whereas for Shamana and Hawassa was below 20%. Variability of seasonal rainfall during FMAM was 33.7%, which is higher than ONDJ (27.1%) and JJAS (27.9%), which could lead to maize plants suffering moisture stress during FMAM season. The onset of rains had variability of 29.2, 19.5, 17.5 and 26.5%, and also LGP showed variability of 22.8, 22.1, 21.2 and 20.3% in Shamana, Bilate, Hawassa, and Dilla clusters, respectively. Moreover Shamana, Bilate, Hawassa and Dilla clusters are hit by agricultural drought in one out of 2.61, 2.3, 2.5 and 2.5 years, respectively. Model based analysis of conditional risk of farmers planting dates also showed a success rate of less than 10, 7, 40 and 63% for maize variety in Shamana, Bilate, Hawassa and Dilla clusters, respectively. However, the success rate of risk taker farmers’ is higher than anticipated by the model. The farmers who take risk were encouraged in Shamana cluster by local edaphic, physiographic, socioeconomic and climatic differences. Hence, there is a need to seek real time local agrometrological advisory and follow the necessary tactical and strategic farming decisions. Moreover, there is also a need to incorporate local factors with modern climate models to obtain synchronized calendar estimates.