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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #401480
Research Project: Enhancing Agricultural Management and Conservation Practices by Advancing Measurement Techniques and Improving Modeling Across Scales

Location: Hydrology and Remote Sensing Laboratory

Title: Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model

Author
item LIANG, KIANG - University Of Maryland
item Zhang, Xuesong
item LIANG, XIN-ZHONG - George Mason University
item Jin, Virginia
item Birru, Girma
item Schmer, Marty
item ROBERTSON, PHILIP - Michigan State University
item McCarty, Gregory
item Moglen, Glenn

Submitted to: Science of the Total Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/12/2023
Publication Date: 3/17/2023
Citation: Liang, K., Zhang, X., Liang, X., Jin, V.L., Birru, G.A., Schmer, M.R., Robertson, P.G., McCarty, G.W., Moglen, G.E. 2023. Simulating agroecosystem soil inorganic nitrogen dynamics under long-term management with an improved SWAT-C model. Science of the Total Environment. 879. Article 162906. https://doi.org/10.1016/j.scitotenv.2023.162906.
DOI: https://doi.org/10.1016/j.scitotenv.2023.162906

Interpretive Summary: Agroecosystem models are widely used to support optimal soil nitrogen management to achieve high crop yields and minimize negative environmental impacts. Here, we added multiple new algorithms into the Soil and Water Assessment Tool – Carbon (SWAT-C) model to better represent the nitrification and denitrification processes. Model evaluation against field data shows that those improvements help to achieve much improved simulation of soil inorganic nitrogen (nitrate and ammonium) than using the original methods in the SWAT-C model. In addition, SWAT-C achieved comparable or even better performance as compared to multiple agroecosystem models that have been tested for simulating soil inorganic nitrogen. Overall, the improved SWAT-C model is able to provide more credible predictions to inform agroecosystem management decisions related to fertilization and related water quality impacts.

Technical Abstract: Agroecosystem models have been widely used to simulate the dynamics of soil inorganic nitrogen (SIN) and support optimal crop management to ensure productivity while minimizing negative environmental impacts. Here, we improved and evaluated the Soil and Water Assessment Tool – Carbon (SWAT-C) model for simulating long-term (1984-2020) dynamics of SIN for 40 cropping system treatments in the U.S. Midwest. Model improvements included adding one nitrification and two denitrification algorithms to the default SWAT version. The six combinations of the available two nitrification and three denitrification options exhibited a wide range of performance for simulating SIN. The optimal combination achieved R, NSE, PBIAS, and RMSE of 0.63, 0.29, -4.7%, and 16.0 kg N ha-1, respectively. In general, the performance of the revised SWAT-C model is comparable to or better than other agroecosystem models tested in previous studies for assessing the availability of SIN for plant growth in different cropping systems. Sensitivity analysis showed that parameters that control soil organic matter decomposition, nitrification, and denitrification were most sensitive for SIN simulation. Using SWAT-C with improved prediction of plant-available SIN is expected to better inform agroecosystem management decisions to ensure crop productivity while minimizing the negative environmental impacts caused by fertilizer application.