Abstract

Food insecurity is a recurrent feature of the Ethiopian drylands. The risk of food insecurity has been aggravated by climate variability, climate change, population pressure, and subsistence agricultural practices. In Ethiopia, common bean is the main source of protein for people who do not get access to animal protein. The national average yield in Ethiopia is 1600 kg ha−1 which is far below yield at research sites (3000 kg ha−1) mainly due to drought, low soil fertility and lack of improved agronomic practices. A simulation study was conducted with the objectives (1) to calibrate and evaluate the CROPGRO-dry bean model of DSSAT for simulating phenology, growth and yield of common bean (2) to assess impacts of future climate on phenology and yield (3) to explore climate adaptive strategies for common bean. Three sowing dates (early, normal and late) and two water regime (rainfed and irrigated) were evaluated as climate adaptive measures. Results of model calibration indicated that the crop genetic coefficients were properly estimated. The RMSE, R2 and d-index values for days to flowering in the model evaluation phase were 2.42 days, 0.76 and 0.82, respectively. The RMSE, R2 and d-index values for days to physiological maturity were 3.19 days, 0.70 and 0.87, respectively while the values for grain yield were 113.7 kg ha−1, 0.95 and 0.89 for the respective parameters. The impact analysis showed that both days to flowering and days to maturity may decrease in 2030s and 2050s at both sites and under both RCP4.5 and RCP8.5 scenarios as compared to the simulated values for the baseline period (1981–2010) but the decrease is not statistically significant. On the other hand, grain yield may significantly increase by 11% in 2030s under RCP8.5 scenario and by 9.2% and 21.1% in 2050s under RCP4.5 and RCP8.5 climate scenarios respectively. The highest significant increase in grain yield may be obtained from the early sowing (SSD − 15 days) combined with supplemental irrigation which may increase yield by 89%, 71% and 56% for the baseline period, 2030s and 2050s, respectively. However, the pattern of climate changes and the nature of crop stressors may change overtime. Thus, understanding the cumulative effects of these factors may help to develop climate resilient cropping systems in the study region.

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