Improving hydrological modeling to close the gap between elevated CO2 concentration and crop response: implications for water resources

Authors: WEN, NA - China Agricultural University; HAN, YIWEN - China Agricultural University; QI, JUNYU - University Of Maryland; Marek, Gary; SUN, DANGFENG - China Agricultural University; FENG, PUYU - China Agricultural University; SRINIVASAN, RAGHAVAN - Texas A&M University; LIU, DE LI - Wagga Wagga Agricultural Institute; CHEN, YONG - China Agricultural University

Submitted to: Water Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/13/2024
Publication Date: 8/14/2024
Citation: Wen, N., Han, Y., Qi, J., Marek, G.W., Sun, D., Feng, P., Srinivasan, R., Liu, D., Chen, Y. 2024. Improving hydrological modeling to close the gap between elevated CO2 concentration and crop response: implications for water resources. Water Research. 265. Article 122279. https://doi.org/10.1016/j.watres.2024.122279.
DOI: https://doi.org/10.1016/j.watres.2024.122279

Interpretive Summary: The effects of increased atmospheric carbon dioxide concentration (CO2) on crop production and the hydrologic cycle are largely unknown and may pose a substantial risk to global food security and water availability in agricultural crop production regions such as the Upper Mississippi River Basin (UMRB). Maize is a major agricultural crop in the UMRB and while increased CO2 is expected to increase yield marginally, effects on the hydrologic cycle and sediment loss are largely unknown. Computer simulation modeling incorporating general circulation models and shared socioeconomic pathways may help identify interactions between CO2 and maize production. However, simulation of crop physiological responses to climate change are limited in hydrologic models such as the Soil and Water Assessment Tool (SWAT). SWAT is a widely used watershed scale model but only allows for a static CO2 concentration value. Researchers from USDA-ARS Bushland and university partners from the U.S., Australia, and China developed a modified SWAT model that included a dynamic CO2 module and associated functions that allow for simulation CO2 effects on stomatal conductance and leaf area index. Simulations of maize production under increased CO2 in the UMRB resulted in increased yields and crop water use. Surface runoff was also increased but sediment loss was not necessarily increased due to increased groundcover and leaf area index. Modifications to the SWAT model demonstrated sensitivity of crop and hydrologic outputs to CO2, likely improving the model’s efficacy for developing adaptation strategies for soil and water conservation and sustainable food production in the UMRB.

Technical Abstract: Rising atmospheric carbon dioxide concentrations (CO2) affect crop production and the associated hydrological cycle through physiological forcing, which is mainly regulated by reduced stomatal conductance (gs) and increased leaf area index (LAI). However, reduced gs and increased LAI can affect crop water consumption, and the overall effects need to be quantified under elevated (CO2). Here we develop a SWAT-gs-LAI model by incorporating a nonlinear gs-CO2 equation and an updated LAI-CO2 relationship to investigate the responses of maize water consumption, yield, and water and soil losses to elevated (CO2) in the Upper Mississippi River Basin (UMRB; 492,000 km2). Results exhibited a trend of enhanced maize production with decreased water consumption for increases in (CO2) from 495 ppm to 825 ppm during the historical period (1985-2014). Elevated (CO2) promoted surface runoff but suppressed sediment loss as the predominant impact of the LAI-CO2 model leading to enhanced surface cover. A comprehensive analysis of future climate change showed that maize water consumption increased in the future compared to the historical period as a result of the stronger impacts of climate change than for only elevated (CO2). Generally, future climate change promoted maize production in most regions of the UMRB for three Shared Socioeconomic Pathway (SSP) scenarios. Surface runoff was shown to increase generally in the future with sediment loss increasing by an average of 0.39, 0.42, and 0.66 ton per ha for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. This was due to negative climatic change effects largely surpassing the positive effect of elevated (CO2), particularly in zones near the middle and lower stream. Our findings highlight the importance of accurate model representation of crop physiological processes under elevated (CO2) for reliable projections of crop production and hydrological cycle.