Location: Soil and Water Management ResearchTitle: Development and testing of a dynamic CO2 input method in SWAT for simulating long-term climate change impacts across various climatic locations
|ZHANG, YINGQI - China Agricultural University|
|QI, JUNYU - University Of Maryland|
|PAN, DONGMEI - China Agricultural University|
|ZHANG, XUELIANG - China Agricultural University|
|FENG, PUYU - China Agricultural University|
|LIU, HAIPENG - China Agricultural University|
|LI, BAOGUI - China Agricultural University|
|DING, BEIBEI - China Agricultural University|
|SRINIVASAN, RAGHAVAN - Texas A&M University|
|CHEN, YONG - China Agricultural University|
Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/30/2022
Publication Date: 10/30/2022
Citation: Zhang, Y., Qi, J., Pan, D., Marek, G.W., Zhang, X., Feng, P., Liu, H., Li, B., Ding, B., Brauer, D.K., Srinivasan, R., Chen, Y. 2022. Development and testing of a dynamic CO2 input method in SWAT for simulating long-term climate change impacts across various climatic locations. Journal of Hydrology. 614(B). Article 128544. https://doi.org/10.1016/j.jhydrol.2022.128544.
Interpretive Summary: Finite groundwater resources are critical for sustaining irrigated agriculture in the Ogallala Aquifer region of U.S. Central Plains. Increased air temperature and atmospheric CO2 concentrations associated with climate change may impact the longevity of groundwater resources. Although the impacts of such increases are unknown, simulation modeling using global circulation models may provide insight into potential effects on future irrigation and crop yield. Researchers from USDA-ARS Bushland and university partners from the U.S. and China simulated the effects of climate change on corn production in Texas, Kansas, and Nebraska through the end of the 21st century and beyond. Simulations demonstrated significant differences between the static and dynamic CO2 input methods. However, overall results suggested that corn yield and irrigation requirements would decrease over time for all areas as a result of heat stress from increased air temperatures.
Technical Abstract: Water resources in semi-arid and arid regions are critical for sustainable agricultural development. Climate change imposes great challenges and brings about large uncertainties in water resources and crop yield predictions. In this study, the effects of future climate change on water cycle and corn production at three sites in the U.S. High Plains region were assessed using the Soil and Water Assessment (SWAT) model and four CMIP5 GCMs under RCP4.5 and 8.5 scenarios. A new method to dynamically input annual CO2 concentration into SWAT was developed to improves simulations. This method, along with the SWAT default CO2 input method (330 ppm), and the constant CO2 input method (average value for a simulation period) were compared for simulating hydrology and corn yield in 21st century (2031-2100). Results showed the default input method consistently simulated the greatest crop evapotranspiration (ETc) and irrigation values but with the lowest water yield and corn yield among three methods, under the RCP8.5 scenario. However, ETc and irrigation were greater for the dynamic input method before the mid-21st century and lower between mid- to late-21st century than the constant input method. These contrasting results were also found for the crop yield simulations. Additionally, the dynamic input method was applied to predict the changes in hydrology and crop yields for the three centuries (2031-2298) relative to the historical period (1970-1999). The results showed that the overall trend of future irrigation, ETc, and corn yield could decrease significantly at the three sites compared to the historical period. Water yield was relatively stable throughout the study period but increased markedly compared to the historical period. The study highlighted the necessity of considering the dynamic CO2 input method for the SWAT applications in climate change studies. Future projections of this study also inform and alert local producers for the risks of future climate change.