Simulating the impacts of climate change on rice (Oryza sativa L.) yield using the DSSAT-CERES Rice Model in Fogera Plain, Ethiopia

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Abstract Climate variability throughout the growing season is expected to have a significant impact on rice yield and crop model s are incredibly beneficial in a simulating crop and soil process in response to change in climate and crop management. So the objectives of the study were to consider calibrating and evaluating the effectiveness of the CERES-Rice model over the course of the growing seasons 2020 and 2021 in Fogera Plain. The varieties used were NERICA_4 and Foegera_1 as a high-yielding variety. The Meteorological Research Institute (MRI CGCM3) was chosen as an ensemble model to produce climate change scenarios for the 2021–2083 period, employing representative concentration pathways (RCP8.5 and 4.5). The model's results showed that the days to anthesis, maturity, and grain yield were all predicted correctly, with the normalized RMSEs for the cultivars NERICA_4 and Fogera_1 being 5.15 and 4.66, 2.98 and 3.19, and 3.55 and 7.14%, respectively. The predicted maximum and minimum temperatures under both RCP scenarios increased by 0.7 and 2.7 oC and 0.8 oC and 2.7 oC, respectively; however, rainfall decreased by 15% and increased by 11% in comparison to baseline. For the cultivars NERICA 4 and Fogera 1, the relative error in percentage between the baseline and the future climate scenario revealed a decrease in yield of 31.6% and 36.6%, respectively. Overall, the result showed the CERES-Rice model was capable of predicting how future climate change will impact rice productivity and assessing the requirement for long-term adaptation strategies for rain-fed rice production in the Fogera Plain.

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