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DRAINMOD–DSSAT model for simulating hydrology, soil carbon and nitrogen dynamics, and crop growth for drained crop land

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  • Negm, L.M.
  • Youssef, M.A.
  • Skaggs, R.W.
  • Chescheir, G.M.
  • Jones, J.

Abstract

Integrated agricultural systems modeling represents an effective research tool to meet the evolving challenges facing agricultural production and environmental quality. An integrated, process-based model was developed to simulate the impacts of the changing environment and different water and farming management practices on the hydrology, water quality, and crop growth and yield for artificially drained cropping systems. The new model; named DRAINMOD–DSSAT, was developed by integrating three different process based models: the hydrological model, DRAINMOD; the soil carbon and nitrogen (N) dynamics model; DRAINMOD-NII, and selected crop modules of the DSSAT–CSM model; CROPGRO and CERES-Maize. The integration of the three component models is implemented at the source code level and allows for daily interactions and feedback among simulated climatic conditions, soil water and nitrogen, and crop growth. DRAINMOD–DSSAT performance was evaluated using a 10-yr dataset collected from a corn–soybean production system on a subsurface drained field in Iowa, with corn receiving low, medium, and high N fertilization rates. The model was calibrated using the data collected from the high-N treatment, and validated for the other two treatments. Annual and monthly subsurface drainage outflows were predicted with modeling efficiencies (NSE) of 0.95 and 0.83, respectively. The NSE's for annual and monthly NO3–N mass losses were 0.87 and 0.70 for the high N-treatment, 0.93 and 0.86 for the medium N-treatment, 0.94 and 0.67 for the low N-treatment, respectively. Predicted and measured crop yields were accurately predicted with an absolute percent error less than 8% in 27 of the 30 simulated plot-years (3 plots×10yrs). Nitrogen removal in crop grain was reasonably predicted. This first model application suggested the potential capability of DRAINMOD–DSSAT of simulating the hydrology, water quality, and crop growth and yield for corn and soybean production on artificially drained fields in response to varying climatic conditions and nutrient management practices. Further research, using more intense field measurements, is needed to validate the model for its intended use.

Suggested Citation

  • Negm, L.M. & Youssef, M.A. & Skaggs, R.W. & Chescheir, G.M. & Jones, J., 2014. "DRAINMOD–DSSAT model for simulating hydrology, soil carbon and nitrogen dynamics, and crop growth for drained crop land," Agricultural Water Management, Elsevier, vol. 137(C), pages 30-45.
  • Handle: RePEc:eee:agiwat:v:137:y:2014:i:c:p:30-45
    DOI: 10.1016/j.agwat.2014.02.001
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    2. Mariusz Sojka & Michał Kozłowski & Rafał Stasik & Michał Napierała & Barbara Kęsicka & Rafał Wróżyński & Joanna Jaskuła & Daniel Liberacki & Jerzy Bykowski, 2019. "Sustainable Water Management in Agriculture—The Impact of Drainage Water Management on Groundwater Table Dynamics and Subsurface Outflow," Sustainability, MDPI, Open Access Journal, vol. 11(15), pages 1-18, August.
    3. Youssef, Mohamed A. & Abdelbaki, Ahmed M. & Negm, Lamyaa M. & Skaggs, R.Wayne & Thorp, Kelly R. & Jaynes, Dan B., 2018. "DRAINMOD-simulated performance of controlled drainage across the U.S. Midwest," Agricultural Water Management, Elsevier, vol. 197(C), pages 54-66.
    4. Negm, L.M. & Youssef, M.A. & Chescheir, G.M. & Skaggs, R.W., 2016. "DRAINMOD-based tools for quantifying reductions in annual drainage flow and nitrate losses resulting from drainage water management on croplands in eastern North Carolina," Agricultural Water Management, Elsevier, vol. 166(C), pages 86-100.
    5. Zhong, Honglin & Sun, Laixiang & Fischer, Günther & Tian, Zhan & van Velthuizen, Harrij & Liang, Zhuoran, 2017. "Mission Impossible? Maintaining regional grain production level and recovering local groundwater table by cropping system adaptation across the North China Plain," Agricultural Water Management, Elsevier, vol. 193(C), pages 1-12.
    6. Dokoohaki, Hamze & Gheysari, Mahdi & Mousavi, Sayed-Farhad & Zand-Parsa, Shahrokh & Miguez, Fernando E. & Archontoulis, Sotirios V. & Hoogenboom, Gerrit, 2016. "Coupling and testing a new soil water module in DSSAT CERES-Maize model for maize production under semi-arid condition," Agricultural Water Management, Elsevier, vol. 163(C), pages 90-99.
    7. Siad, Si Mokrane & Iacobellis, Vito & Zdruli, Pandi & Gioia, Andrea & Stavi, Ilan & Hoogenboom, Gerrit, 2019. "A review of coupled hydrologic and crop growth models," Agricultural Water Management, Elsevier, vol. 224(C), pages 1-1.
    8. Youssef, Mohamed A. & Liu, Yu & Chescheir, George M. & Skaggs, R. Wayne & Negm, Lamyaa M., 2021. "DRAINMOD modeling framework for simulating controlled drainage effect on lateral seepage from artificially drained fields," Agricultural Water Management, Elsevier, vol. 254(C).
    9. Singh, Shailendra & Bhattarai, Rabin & Negm, Lamyaa M. & Youssef, Mohamed A. & Pittelkow, Cameron M., 2020. "Evaluation of nitrogen loss reduction strategies using DRAINMOD-DSSAT in east-central Illinois," Agricultural Water Management, Elsevier, vol. 240(C).
    10. Liang, Hao & Qi, Zhiming & Hu, Kelin & Li, Baoguo & Prasher, Shiv O., 2018. "Modelling subsurface drainage and nitrogen losses from artificially drained cropland using coupled DRAINMOD and WHCNS models," Agricultural Water Management, Elsevier, vol. 195(C), pages 201-210.
    11. Negm, Lamyaa M. & Youssef, Mohamed A. & Jaynes, Dan B., 2017. "Evaluation of DRAINMOD-DSSAT simulated effects of controlled drainage on crop yield, water balance, and water quality for a corn-soybean cropping system in central Iowa," Agricultural Water Management, Elsevier, vol. 187(C), pages 57-68.
    12. Revuelta-Acosta, J.D. & Flanagan, D.C. & Engel, B.A. & King, K.W., 2021. "Improvement of the Water Erosion Prediction Project (WEPP) model for quantifying field scale subsurface drainage discharge," Agricultural Water Management, Elsevier, vol. 244(C).

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