Browsing by Person "Rettie, Fasil Mequanint"

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Reducing uncertainty in prediction of climate change impacts on crop production in Ethiopia
(2024) Rettie, Fasil Mequanint; Streck, Thilo
Ethiopia, with an economy heavily reliant on agriculture, is among the countries most vulnerable to climate change. It faces recurrent climate extreme events that result in devastating impacts and acute food shortages for millions of people. Studies that focus on their influence on agriculture, especially crop productivity, are of particular importance. However, only a few studies have been conducted in Ethiopia, and existing studies are spatially limited and show considerable spatial invariance in predicted impacts, as well as discrepancies in the sign and direction of impacts. Therefore, a robust, regionally focused, and multi-model assessment of climate change impacts is urgently needed. To guide policymaking and adaptation strategies, it is essential to quantify the impacts of climate change and distinguish the different sources of uncertainty. Against this backdrop, this study consisted of several key components. Using a multi-crop model ensemble, we began with a local climate change impact assessment on maize and wheat growth and yield across three sites in Ethiopia . We quantified the contributions of different sources of uncertainty in crop yield prediction. Our results projected a of 36 to 40% reduction in wheat grain yield by 2050, while the impact on maize was modest. A significant part of the uncertainty in the projected impact was attributed to differences in the crop growth models. Importantly, our study identified crop growth model-associated uncertainty as larger than the rest of the model components. Second, we produced a high-resolution daily projections database for rainfall and temperature to serve the requirement for impact modeling at regional and local levels using a statistical downscaling technique based on state-of-the-art GCMs under a range of emission scenarios called Shared Socioeconomic Pathways (SSPs). The evaluated results suggest that the downscaling strategy significantly reduced the biases between the GCM outputs and the observation data and minimized the errors in the projections. Third, we explored the magnitude and spatial patterns of trends in observed and projected changes in climate extremes indices based on downscaled high-resolution daily climate data to serve as a baseline for future national or regional-level impact assessment. Our results show largely significant and spatially consistent trends in temperature-derived extreme indices, while precipitation-related extreme indices are heterogeneous in terms of spatial distribution, magnitude, and statistical significance coverage. The projected changes in temperature-related indices are dominated by the uncertainties in the GCMs, followed by uncertainties in the SSPs. Unlike the temperature-related indices, the uncertainty from internal climate variability constitutes a considerable proportion of the total uncertainty in the projected trends. Fourth, we examined the regional-scale impact of climate change on maize and wheat yields by crop modeling, in which we calibrated and validated three process-based crop models to guide the design of national-level adaptation strategies in Ethiopia. Our analysis showed that under a high-emissions scenario, the national-level median wheat yield is expected to decrease by 4%, while maize yield is expected to increase by 2.5% by the end of the century. The CO2 fertilization effect on the crop simulations would offset the projected negative impact. Crop model spread followed by GCMs was identified as the largest contributor to overall uncertainty to the estimated yield changes. In summary, our study quantifies the impact of climate change and demonstrates the importance of a multi-model ensemble approach. We highlight the significant impacts of climate change on wheat yield in Ethiopia and the importance of crop model improvements to reduce overall uncertainty in the projected impact.
The role of crop management practices and adaptation options to minimize the impact of climate change on maize (Zea mays L.) production for Ethiopia
(2023) Feleke, Hirut Getachew; Savage, Michael J.; Fantaye, Kindie Tesfaye; Rettie, Fasil Mequanint
Climate change impact assessment along with adaptation measures are key for reducing the impact of climate change on crop production. The impact of current and future climate change on maize production was investigated, and the adaptation role of shifting planting dates, different levels of nitrogen fertilizer rates, and choice of maize cultivar as possible climate change adaptation strategies were assessed. The study was conducted in three environmentally contrasting sites in Ethiopia, namely: Ambo, Bako, and Melkassa. Future climate data were obtained from seven general circulation models (GCMs), namely: CanESM2, CNRM-CM5, CSIRO-MK3-6-0, EC-EARTH, HadGEM2-ES, IPSL-CM5A-MR, and MIROC5 for the highest representative concentration pathway (RCP 8.5). GCMs were bias-corrected at site level using a quantile-quantile mapping method. APSIM, AquaCrop, and DSSAT crop models were used to simulate the baseline (1995–2017) and 2030s (2021–2050) maize yields. The result indicated that the average monthly maximum air temperature in the 2030s could increase by 0.3–1.7 °C, 0.7–2.2 °C, and 0.8–1.8 °C in Ambo, Bako, and Melkassa, respectively. For the same sites, the projected increase in average monthly minimum air temperature was 0.6–1.7 °C, 0.8–2.3 °C, and 0.6–2.7 °C in that order. While monthly total precipitation for the Kiremt season (June to September) is projected to increase by up to 55% (365 mm) for Ambo and 75% (241 mm) for Bako respectively, whereas a significant decrease in monthly total precipitation is projected for Melkassa by 2030. Climate change would reduce maize yield by an average of 4% and 16% for Ambo and Melkassa respectively, while it would increase by 2% for Bako in 2030 if current maize cultivars were grown with the same crop management practice as the baseline under the future climate. At higher altitudes, early planting of maize cultivars between 15 May and 1 June would result in improved relative yields in the future climate. Fertilizer levels increment between 23 and 150 kg ha−1 would result in progressive improvement of yields for all maize cultivars when combined with early planting for Ambo. For a mid-altitude, planting after 15 May has either no or negative effect on maize yield. Early planting combined with a nitrogen fertilizer level of 23–100 kg ha−1 provided higher relative yields under the future climate. Delayed planting has a negative influence on maize production for Bako under the future climate. For lower altitudes, late planting would have lower relative yields compared to early planting. Higher fertilizer levels (100–150 kg ha−1) would reduce yield reductions under the future climate, but this varied among maize cultivars studied. Generally, the future climate is expected to have a negative impact on maize yield and changes in crop management practices can alleviate the impacts on yield.