ASSESSING CLIMATE CHANGE IMPACTS ON WHEAT [TRITICUM AESTIVUM (L.)] AND BARLEY [HORDEUM VULGARE (L.)] PRODUCTION AND POTENTIAL ADAPTATION OPTIONS IN CENTRAL ETHIOPIA

Abstract

Climate change affects crop productivity in most parts of the world, particularly in Sub-Saharan Africa. This challenge is expected as a major threat to crop production in central Ethiopia. The major purpose of the study was to assess the current and future impacts of climate change on wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.) production in central Ethiopia and identify adaptation options. In order to achieve these objectives, the study combined climate analysis, field experimentation and crop modeling (DSSAT cropping system model) methodologies. The modeling work was supplemented by assessment of farmers’ perception of climate change and determinants of adaptation. Historical and future climate trends of 10 meteorological stations were analyzed using Mann-Kendall test. Rainfall variability was tested by rainfall anomaly and concentration indices. Implications of climate variables on wheat and barley yield were evaluated using bivariate correlation analysis. A household survey was conducted using 120 randomly selected households in 2017. The multinomial logit model was used to examine determinants of climate change adaptation. DSSAT crop model was calibrated with field experimental data of Kulumsa and Bokoji in 2016. The performance of the model was evaluated with experimental data of Holeta, Fitche, and Ambo stations in the same year. Wheat and barley yields were simulated for 1984-2014 and 2040-2069. Yield responses of two wheat and barley varieties were simulated for three planting dates combined with four levels of nitrogen. Mann-Kendall trend test results showed significantly (P <0.01) increasing trend of annual and seasonal rainfall for the baseline (1980 -2016) and mid-century (2040-2069) periods. Rainfall concentration and anomaly indices indicated high variability with the largest anomalies that occurred in 1987 (driest) and 1996 (wettest). The annual and seasonal temperatures showed significantly (P < 0.01) increasing trends for baseline and mid-century. Extremely low-temperature events exhibited a significant (P < 0.05) decreasing trend while extremely high-temperature events showed a significant (P < 0.05) increasing trend for both periods. The magnitude of high temperature events is expected to be greater in the mid-century compared to the baseline period. Seasonal rainfall amount had xvii a significant (P < 0.05) positive correlation with the yields of wheat and barley at Debre Berhan while it had a significant (P < 0.01) negative correlation at Holeta and Ambo. Seasonal rainfall amount explained 21-51% and 35-65% of the variability in wheat and barley yields, respectively. The yields of wheat and barley varieties showed a significant (P < 0.05) negative correlation with maximum and minimum temperatures although the level of correlation varied among sites and the varieties. Farmers perceived that temperatures had increased which agreed with the analyzed temperature trend while contradicted with rainfall. Analysis with Multinomial Logistic regression model indicated that demographic and socio-institutional variables had a significant (P < 0.05) impact on choice of climate change adaptation options. The CERES-Wheat and CERES-Barley models simulated the phenological, growth, and grain yield of wheat and barley with very good accuracy. The projected climate is expected to decrease wheat and barley yields under both the farmers’ practices and research recommendations. Increase in the level of ambient CO2 (380 ppm to 571 ppm) is expected to increase simulated wheat and barley yields. Planting between 20 to 30 June is expected to minimize the impact of climate change for medium-duration varieties of the two crops. Likewise, increasing the rate of nitrogen from 92 to 138 kg N ha-1 is projected to offset the negative impacts of future climate on the two crops. The combinations of adaptation measures (changing cultivars, changing planting dates and increasing rate of nitrogen) are expected to reduce the adverse effects of climate change. From the study, it can be concluded that, for better climate change impacts and adaptation assessment, integrated use of crop models, climate models, representative concentration pathways, and projection periods is imperative. Further studies are suggested on quantifying uncertainties associated with crop models and climate scenarios for developing rigorous adaptation measures