Simulating the potential effects of elevated CO2 concentration and temperature coupled with storm intensification on crop yield, surface runoff, and soil loss based on 25 GCMs ensemble: A site-specific case study in Oklahoma

Authors: YUAN, LIFENG - University Of Oklahoma; Zhang, Xunchang; Busteed, Phillip; Flanagan, Dennis

Submitted to: Catena
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/24/2022
Publication Date: 3/30/2022
Citation: Yuan, L., Zhang, X.J., Busteed, P.R., Flanagan, D.C. 2022. Simulating the potential effects of elevated CO2 concentration and temperature coupled with storm intensification on crop yield, surface runoff, and soil loss based on 25 GCMs ensemble: A site-specific case study in Oklahoma. Catena. 214:106251. https://doi.org/10.1016/j.catena.2022.106251.
DOI: https://doi.org/10.1016/j.catena.2022.106251

Interpretive Summary: Storm intensification should be considered while predicting crop yield, surface runoff, and soil loss under climate change conditions. We developed a total of 100 climate scenarios coupled with storm intensification, which were based on 25 downscaled GCMs (General Circulation Model) projections under RCP4.5 and RCP8.5 (Representative Concentration Pathways) for two time periods of 2021-2050 and 2051-2080. The climate files were applied to a modified WEPP (Water Erosion Prediction Project) model to estimate crop yield, runoff, and soil loss under 29 combinations of cropping and tillage systems in central Oklahoma. The results showed that future extreme storm events (> 82.3 mm) would significantly increase (p < 0.01) during 2021-2080. Average monthly precipitation in summer would decrease by 12.5% in June and 10.8% in July, along with annual precipitation declines by 2.6%, leading to a decrease in crop yield in this rain fed agricultural region. The yields of soybean, sorghum, wheat, and canola averaged across two emission scenarios and two time periods would separately decrease by 19.2, 15.1, 9.7, and 5.7%, but the cotton yield would increase by 95% during 2021-2080. The amount of runoff (soil loss) from extreme storms would account for 45.9 (64.3%) of the total annual runoff (soil loss) when averaged across two time periods and two RCPs. The average annual runoff depth (soil loss amount) on crop rotation or double cropping would be 27.6 (78.1%) less than the corresponding values in a continuous monoculture cropping system. No-till and crop rotation with alfalfa are the best alternatives to mitigate soil erosion rates under future climate change. The analysis of variance indicated that the uncertainty contribution of annual precipitation reached 47.7% (p < 0.001) in annual runoff prediction, while carbon dioxide concentration (26.5%, p < 0.001) and annual precipitation (23.4%, p < 0.001) are the major uncertainty sources in annual soil loss simulations. This work provides useful information to soil and water conservationists to develop new conservation strategy to mitigate the adverse impact of climate change on agricultural production and sustainability.

Technical Abstract: Storm intensification should be considered while predicting crop yield, surface runoff, and soil loss under climate change conditions. We developed a total of 100 climate scenarios coupled with storm intensification, which were based on 25 downscaled GCMs (General Circulation Model) projections under RCP4.5 and RCP8.5 (Representative Concentration Pathways) for two time periods of 2021-2050 and 2051-2080. The climate files were applied to a modified WEPP (Water Erosion Prediction Project) model to estimate crop yield, runoff, and soil loss under 29 combinations of cropping and tillage systems. The results showed that future extreme storm events (> 82.3 mm) would significantly increase (p < 0.01) during 2021-2080. Average monthly precipitation in summer would decrease by 12.5% in June and 10.8% in July, along with annual precipitation declines by 2.6%, leading to a decrease in crop yield in this rain fed agricultural region. The yields of soybean, sorghum, wheat, and canola averaged across two emission scenarios and two time periods would separately decrease by 19.2, 15.1, 9.7, and 5.7%, but the cotton yield would increase by 95% during 2021-2080. The amount of runoff (soil loss) from extreme storms would account for 45.9 (64.3%) of the total annual runoff (soil loss) when averaged across two time periods and two RCPs. The average annual runoff depth (soil loss amount) on crop rotation or double cropping would be 27.6 (78.1%) less than the corresponding values in a continuous monoculture cropping system. No-till and crop rotation with alfalfa are the best alternatives to mitigate soil erosion rates under future climate change. The analysis of variance indicated that the uncertainty contribution of annual precipitation reached 47.7% (p < 0.001) in annual runoff prediction, while carbon dioxide concentration (26.5%, p < 0.001) and annual precipitation (23.4%, p < 0.001) are the major uncertainty sources in annual soil loss simulations.