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Simulated responses of tile-drained agricultural systems to recent changes in ambient atmospheric gradients

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  • Jeong, Hanseok
  • Pittelkow, Cameron M.
  • Bhattarai, Rabin

Abstract

Agricultural systems in the U.S. Midwest have undergone rapid changes in atmospheric gradients of ambient nitrogen (N) deposition and carbon dioxide (CO2) concentration in recent decades. Despite potential impacts on soil-plant-atmospheric interactions, observed changes in these gradients have not been routinely considered in modeling studies, which could lead to biased results. This study evaluated the impacts of variation in nitrate concentration in rain water and ambient CO2 concentration on field-scale hydrology, nitrogen (N) dynamics, and crop yields in two tile-drained fields under a corn-soybean rotation in Illinois. A calibrated Root Zone Water Quality Model (RZWQM) coupled with Decision Support System for Agrotechnology Transfer (DSSAT) was used to simulate the impacts of ten scenarios over 10 years. Scenarios included a baseline with default values in RZWQM and each of the following three scenarios reflecting the actual changes for nitrate concentration (0.2, 0.3, and 0.4 mgN L−1), ambient CO2 concentration (360, 380, and 400 ppm), and combined effects (0.4 mgN L−1and 360 ppm, 0.3 mgN L−1and 380 ppm, and 0.2 mgN L−1and 400 ppm). Nitrate concentration in rain water demonstrated a moderate impact on N dynamics (e.g. nitrate losses to tile drainage increased up to 5.8% compared to the baseline scenario), while it had a small impact on field-scale hydrology and crop yield. In contrast, increasing ambient CO2 concentration showed a significant impact on cropping system N dynamics and soybean yields (e.g. biological N fixation and soybean yields increased up to 29.1% and 24.6%, respectively, compared to the baseline scenario), whereas it had little impact on hydrology and corn yields. The combined effects scenarios showed that decreased nitrate concentration in rain water may partially be related to the slight improvements in water quality in Illinois during the last decades. Considering the recent changes in both nitrate and CO2 concentrations, the overall annual nitrate losses through water (i.e., nitrate losses in runoff, seepage, and tile drainage) decreased by 0.1 kgN ha−1 and 1.3 kgN ha−1 at two tile-drained fields. This study highlights the importance of proper consideration of atmospheric gradients in agricultural systems modeling procedure for accurately estimating crop productivity and environmental performance in tile-drained agricultural landscapes.

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  • Jeong, Hanseok & Pittelkow, Cameron M. & Bhattarai, Rabin, 2019. "Simulated responses of tile-drained agricultural systems to recent changes in ambient atmospheric gradients," Agricultural Systems, Elsevier, vol. 168(C), pages 48-55.
    • Handle: RePEc:eee:agisys:v:168:y:2019:i:c:p:48-55
    DOI: 10.1016/j.agsy.2018.10.005
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    1. Li, Xiang & Takahashi, Taro & Suzuki, Nobuhiro & Kaiser, Harry M., 2011. "The impact of climate change on maize yields in the United States and China," Agricultural Systems, Elsevier, vol. 104(4), pages 348-353, April.
    2. Zhaozhi Wang & Zhiming Qi & Lulin Xue & Melissa Bukovsky & Matthew Helmers, 2015. "Modeling the impacts of climate change on nitrogen losses and crop yield in a subsurface drained field," Climatic Change, Springer, vol. 129(1), pages 323-335, March.
    3. Patricio Grassini & Kent M. Eskridge & Kenneth G. Cassman, 2013. "Distinguishing between yield advances and yield plateaus in historical crop production trends," Nature Communications, Nature, vol. 4(1), pages 1-11, December.
    4. Ma, L. & Hoogenboom, G. & Ahuja, L.R. & Ascough II, J.C. & Saseendran, S.A., 2006. "Evaluation of the RZWQM-CERES-Maize hybrid model for maize production," Agricultural Systems, Elsevier, vol. 87(3), pages 274-295, March.
    5. Richard A. Betts & Olivier Boucher & Matthew Collins & Peter M. Cox & Peter D. Falloon & Nicola Gedney & Deborah L. Hemming & Chris Huntingford & Chris D. Jones & David M. H. Sexton & Mark J. Webb, 2007. "Projected increase in continental runoff due to plant responses to increasing carbon dioxide," Nature, Nature, vol. 448(7157), pages 1037-1041, August.
    6. Fang, Q. & Ma, L. & Yu, Q. & Ahuja, L.R. & Malone, R.W. & Hoogenboom, G., 2010. "Irrigation strategies to improve the water use efficiency of wheat-maize double cropping systems in North China Plain," Agricultural Water Management, Elsevier, vol. 97(8), pages 1165-1174, August.
    7. Cameira, M.R. & Fernando, R.M. & Ahuja, L.R. & Ma, L., 2007. "Using RZWQM to simulate the fate of nitrogen in field soil-crop environment in the Mediterranean region," Agricultural Water Management, Elsevier, vol. 90(1-2), pages 121-136, May.
    8. Islam, Adlul & Ahuja, Lajpat R. & Garcia, Luis A. & Ma, Liwang & Saseendran, Anapalli S. & Trout, Thomas J., 2012. "Modeling the impacts of climate change on irrigated corn production in the Central Great Plains," Agricultural Water Management, Elsevier, vol. 110(C), pages 94-108.
    9. Ma, L. & Ahuja, L.R. & Islam, A. & Trout, T.J. & Saseendran, S.A. & Malone, R.W., 2017. "Modeling yield and biomass responses of maize cultivars to climate change under full and deficit irrigation," Agricultural Water Management, Elsevier, vol. 180(PA), pages 88-98.
    10. Kimball, B. A. & Idso, S. B., 1983. "Increasing atmospheric CO2: effects on crop yield, water use and climate," Agricultural Water Management, Elsevier, vol. 7(1-3), pages 55-72, September.
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    Cited by:

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    2. Gupta, Rishabh & Bhattarai, Rabin & Coppess, Jonathan W. & Jeong, Hanseok & Ruffatti, Michael & Armstrong, Shalamar D., 2022. "Modeling the impact of winter cover crop on tile drainage and nitrate loss using DSSAT model," Agricultural Water Management, Elsevier, vol. 272(C).

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