Abstract

Projections of future climate change are plagued with uncertainties from global climate models and emission scenarios, causing difficulties for impact assessments and for planners taking decisions on adaptation measure. Here, we developed an approach to deal with the uncertainties and to project the changes of maize productivity and water use in China using a process-based crop model, against a global mean temperature (GMT) increase scale relative to 1961-1990 values. From 20 climate scenarios output from the Intergovernmental Panel on Climate Change Data Distribution Centre, we adopted the median values of projected changes in monthly mean climate variables for representative stations and driven the CERES-Maize model to simulate maize production under baseline and future climate scenarios. Adaptation options such as automatic planting, automatic application of irrigation and fertilization were considered, although cultivars were assumed constant over the baseline and future. After assessing representative stations across China, we projected changes in maize yield, growing period, evapotranspiration, and irrigation-water use for GMT changes of 1A degrees C, 2A degrees C, and 3A degrees C, respectively. Results indicated that median values of projected decreases in the yields of irrigated maize without (with) consideration of CO(2)-fertilization effects ranged from 1.4% to 10.9% (1.6% to 7.8%), 9.8% to 21.7% (10.2% to 16.4%), and 4.3% to 32.1% (3.9% to 26.6%) for GMT changes of 1A degrees C, 2A degrees C, and 3A degrees C, respectively. Median values of projected changes in irrigation-water use without (with) consideration of CO(2)-fertilization effects ranged from -1.3% to 2.5% (-18.8% to 0.0%), -43.6% to 2.4% (-56.1% to -18.9%), and -19.6% to 2.2% (-50.6% to -34.3%), which were ascribed to rising CO(2) concentration, increased precipitation, as well as reduced growing period with GMT increasing. For rainfed maize, median values of projected changes in yields without (with) consideration of CO(2)-fertilization effects ranged from -22.2% to -1.0% (-10.8% to 0.7%), -27.6% to -7.9% (-18.1% to -5.6%), and -33.7% to -4.6% (-25.9% to -1.6%). Approximate comparisons showed that projected maize yield losses were larger than previous estimates, particularly for rainfed maize. Our study presents an approach to project maize productivity and water use with GMT increases using process-based crop models and multiple climate scenarios. The resultant impact function is fundamental for identifying which climate change level is dangerous for food security.

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