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Long-term DSSAT simulation of nitrogen loss to artificial subsurface drainage flow for a corn-soybean rotation with winter rye in Iowa

Author

Listed:
  • Chatterjee, Amitava
  • Thorp, Kelly R.
  • O’Brien, Peter L.
  • Kovar, John
  • Rogovska, Natalia
  • Malone, Robert W.

Abstract

Cereal rye (Secale cereale L.) as winter cover crop can reduce nitrate (NO3) loss through subsurface tile drainage under corn (Zea mays L.) -soybean (Glycine max L.) production system. The Decision Support System for Agrotechnology Transfer (DSSAT) model can simulate processes of subsurface drainage flow and NO3 loss to artificial subsurface drainage, but few model evaluations with field-measured data are available. The objective of this study was to evaluate the DSSAT model for simulating crop yield and flow and NO3 losses to tile drainage in a corn -soybean rotation with (CC) and without (NCC) winter rye cover crop in Central Iowa during the 2002–2010 growing seasons. Simulations successfully reproduced the cumulative (9 years) subsurface drainage flow, observed and predicted values were 331 cm and 309 cm for NCC and, 323 cm and 284 cm for CC. Similarly, for cumulative NO3 loss in tile flow, observed and predicted values were 444 kg N ha−1 and 459 kg N ha−1 for NCC and 187 kg N ha−1 and 196 kg N ha−1 for CC; simulated and observed indicated CC treatment could reduce NO3 in drainage by 57 %. Early (-10 d) and late (+ 10 d) termination did not influence main crop yield and tile NO3 loss. Simulation of the long-term (23-years) influence of CC suggest that tile flow and NO3 load could be reduced by 15 % and 73 %, respectively for a corn-soybean production system in central Iowa.

Suggested Citation

  • Chatterjee, Amitava & Thorp, Kelly R. & O’Brien, Peter L. & Kovar, John & Rogovska, Natalia & Malone, Robert W., 2025. "Long-term DSSAT simulation of nitrogen loss to artificial subsurface drainage flow for a corn-soybean rotation with winter rye in Iowa," Agricultural Water Management, Elsevier, vol. 312(C).
    • Handle: RePEc:eee:agiwat:v:312:y:2025:i:c:s0378377425001787
    DOI: 10.1016/j.agwat.2025.109464
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