Modeling the Impact of Climate Change on Maize (Zea mays L.) Production and Choice of Adaptation Practices in Eastern Ethiopia

Abstract

Climate change poses challenges to maize production and productivity in eastern Ethiopia. Impact assessment using climate predictions is the prime step to design adaptation strategies. Crop Environment Resource Synthesis (CERES)-Maize model in DSSAT (Decision Support System for Agrotechnology Transfer) was calibrated using GenCalc software. The model was used to simulate change in maize yield in the baseline (1988–2017) and future climate periods (2030s and 2050s) under (Representative Concentration Pathways) RCP4.5 and RCP8.5 scenarios using 17 CMIP5 (Coupled Model Inter-comparison Project Phase Five) GCMs (Global Circulation Models). During calibration and evaluation of the model excellent agreement of measured and simulated anthesis, and days to physiological maturity for all the cultivars with normalized root mean square error (nRMSE) of less than 10% and R² value of 0.99 was obtained. The seasonal leaf area index (LAI) and top weight progressions were also predicted well by the model with d-index of 0.96 and 0.99, respectively. Excellent (nRMSE < 10) to good (nRMSE 10–20) predictions were also obtained for grain yield and tops weight. The average annual temperature would increase by (1.90 ± 0.36) ^oC, (2.45 ± 0.53) ^oC and rainfall would increase (8 ± 5) %, (12 ± 8) % under RCP 4.5 in 2030s and 2050s, respectively across GCMs compared to baseline in the study area. As a result in 2030s yield reduction, – 10.6% to – 15.4% and – 7.4% to – 9.3% in 2050s of maize cultivar was projected across GCMs. In 2030s and 2050s under RCP4.5 and RCP8.5 long maturing cultivars (BH661) on 15th May planting with 130.5 kg N ha^–1 application predicted the highest maize grain yield.