Location: Soil and Water Management ResearchTitle: Assessing impacts of global climate change on water and food security in the black soil region of Northeast China using an improved SWAT-CO2 model
|ZHANG, YINGQI - China Agricultural University|
|LIU, HAIPENG - China Agricultural University|
|QI, JUNYU - University Of Maryland|
|FENG, PUYU - China Agricultural University|
|ZHANG, XUELIANG - China Agricultural University|
|LIU, DE LI - Wagga Wagga Agricultural Institute|
|SRINIVASAN, RAGHAVAN - Texas A&M University|
|CHEN, YONG - China Agricultural University|
Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/12/2022
Publication Date: 10/18/2022
Citation: Zhang, Y., Liu, H., Qi, J., Feng, P., Zhang, X., Liu, D., Marek, G.W., Srinivasan, R., Chen, Y. 2022. Assessing impacts of global climate change on water and food security in the black soil region of Northeast China using an improved SWAT-CO2 model. Science of the Total Environment. 857(2). Article 159482. https://doi.org/10.1016/j.scitotenv.2022.159482.
Interpretive Summary: The continuance of irrigated agriculture in the Ogallala Aquifer region of U.S. Central Plains is dependent on irrigation management strategies that work to extend finite groundwater resources. Climate change poses uncertainty for managing water resources in the future as changes in precipitation, solar radiation, air temperature, and atmospheric CO2 concentrations may impact crop growth and yield. However, simulation modeling using global circulation models can provide insight for understanding and addressing effects of climate change. Researchers from USDA-ARS Bushland and university partners from the U.S., Australia, and China simulated the effects of climate change on full, limited, and dryland corn production in the black soil region of northeastern China through the 21st century and beyond. Overall, simulations revealed a slight increase in corn yields despite projected increases in temperature and CO2 concentrations. These findings may also be relevant for similar black soil lands in the Mississippi River Plain.
Technical Abstract: Future climate change may have substantial impacts on both water resources and food security in China’s black soil region. The Liao River Basin (LRB; 220,000 km2) is representative of the main black soil area, making it ideal for studying climate change on black soil. In this study, the SWAT (Soil and Water Assessment Tool) model was first initialized for the LRB and divided into seven zones based on the natural flow distribution, irrigation conditions, and administrative divisions. Actual evapotranspiration (ETa) values calculated using the SEBS (Surface Energy Balance System) model and city-level yields were then used to calibrate and evaluate the SWAT model. Finally, the calibrated SWAT model was modified to accept dynamic CO2 input and used to explore the impacts of future climate change on water balance and crop water productivity (CWP) in the LRB. Simulation scenario design included 22 GCMs (General Circulation Models) and 4 SSP (Shared Socioeconomic Pathway) scenarios from the latest CMIP6 (Coupled Model Intercomparison Project 6) for two time periods of 2041-2070 and 2071-2100. The simulated results showed a significant (P less than 0.05) increase in mean annual air temperatures and precipitation in the LRB. In contrast, solar radiation decreased significantly and was most reduced for the SSP3-7.0 scenario. Reference Evapotranspiration (ETo), ETa, and soil evaporation significantly increased in future scenarios, while canopy interception and crop transpiration showed partial reductions. Corn yield varied considerably (P less than 0.05) among the different zones, with the largest increase of up to 200 percent in Zones 2, 3, 6, and 7 for the SSP5-8.5 scenario. Future changes in crop water productivity were similar to those for yield, with significant increases in the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios. These findings suggested climate change may have a positive impact on the sustainability of corn production in the LRB.