Biogeochemistry

, Volume 93, Issue 1–2, pp 7–30 | Cite as

Modeling denitrification in a tile-drained, corn and soybean agroecosystem of Illinois, USA

  • Mark B. David
  • Stephen J. Del Grosso
  • Xuetao Hu
  • Elizabeth P. Marshall
  • Gregory F. McIsaac
  • William J. Parton
  • Christina Tonitto
  • Mohamed A. Youssef
Article

Abstract

Denitrification is known as an important pathway for nitrate loss in agroecosystems. It is important to estimate denitrification fluxes to close field and watershed N mass balances, determine greenhouse gas emissions (N2O), and help constrain estimates of other major N fluxes (e.g., nitrate leaching, mineralization, nitrification). We compared predicted denitrification estimates for a typical corn and soybean agroecosystem on a tile drained Mollisol from five models (DAYCENT, SWAT, EPIC, DRAINMOD-N II and two versions of DNDC, 82a and 82h), after first calibrating each model to crop yields, water flux, and nitrate leaching. Known annual crop yields and daily flux values (water, nitrate-N) for 1993–2006 were provided, along with daily environmental variables (air temperature, precipitation) and soil characteristics. Measured denitrification fluxes were not available. Model output for 1997–2006 was then compared for a range of annual, monthly and daily fluxes. Each model was able to estimate corn and soybean yields accurately, and most did well in estimating riverine water and nitrate-N fluxes (1997–2006 mean measured nitrate-N loss 28 kg N ha−1 year−1, model range 21–28 kg N ha−1 year−1). Monthly patterns in observed riverine nitrate-N flux were generally reflected in model output (r2 values ranged from 0.51 to 0.76). Nitrogen fluxes that did not have corresponding measurements were quite variable across the models, including 10-year average denitrification estimates, ranging from 3.8 to 21 kg N ha−1 year−1 and substantial variability in simulated soybean N2 fixation, N harvest, and the change in soil organic N pools. DNDC82a and DAYCENT gave comparatively low estimates of total denitrification flux (3.8 and 5.6 kg N ha−1 year−1, respectively) with similar patterns controlled primarily by moisture. DNDC82h predicted similar fluxes until 2003, when estimates were abruptly much greater. SWAT and DRAINMOD predicted larger denitrification fluxes (about 17–18 kg N ha−1 year−1) with monthly values that were similar. EPIC denitrification was intermediate between all models (11 kg N ha−1 year−1). Predicted daily fluxes during a high precipitation year (2002) varied considerably among models regardless of whether the models had comparable annual fluxes for the years. Some models predicted large denitrification fluxes for a few days, whereas others predicted large fluxes persisting for several weeks to months. Modeled denitrification fluxes were controlled mainly by soil moisture status and nitrate available to be denitrified, and the way denitrification in each model responded to moisture status greatly determined the flux. Because denitrification is dependent on the amount of nitrate available at any given time, modeled differences in other components of the N cycle (e.g., N2 fixation, N harvest, change in soil N storage) no doubt led to differences in predicted denitrification. Model comparisons suggest our ability to accurately predict denitrification fluxes (without known values) from the dominant agroecosystem in the midwestern Illinois is quite uncertain at this time.

Keywords

Crop yields Mollisol N2Nitrate Soil moisture 

References

  1. Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment part I: model development. J Am Water Resour Assoc 34:73–89CrossRefGoogle Scholar
  2. Bechtold I, Kohne S, Youssef MA, Lennartz B, Skaggs RW (2007) Simulating nitrogen leaching and turnover in a subsurface-drained grassland receiving animal manure in northern Germany using DRAINMOD-N II. Agric Water Manag 93:30–44CrossRefGoogle Scholar
  3. Boyer EW, Alexander RB, Parton WJ, Li C, Butterbach-Bahl K, Donner SD, Skaggs RW, Del Grosso SJ (2006) Modeling denitrification in terrestrial and aquatic ecosystems at regional scales. Ecol Appl 16:2123–2142CrossRefGoogle Scholar
  4. Brevé MA, Skaggs RW, Parsons JE, Gilliam JW (1997) DRAINMOD-N, a nitrogen model for artificially drained soils. Trans ASAE 40:1067–1075Google Scholar
  5. Chung SW, Gassman PW, Huggins DR, Randall GW (2001) EPIC tile flow and nitrate loss predictions for three Minnesota cropping systems. J Environ Qual 30:822–830Google Scholar
  6. Cui JB, Li CS, Trettin C (2005a) Analyzing the ecosystem carbon and hydrologic characteristics of a forested wetland using a biogeochemical procees model. Glob Chang Biol 11:278–289CrossRefGoogle Scholar
  7. Cui JB, Li CS, Trettin C (2005b) Modeling biogeochemistry and forest management practices for assessing GHGs mitigation strategies in forested wetlands. Environ Model Assess 10:43–53CrossRefGoogle Scholar
  8. David MB, Gentry LE (2000) Anthropogenic inputs of nitrogen and phosphorus and riverine export for Illinois, USA. J Environ Qual 29:494–508Google Scholar
  9. David MB, Gentry LE, Kovacic DA, Smith KM (1997) Nitrogen balance in and export from an agricultural watershed. J Environ Qual 26:1038–1048Google Scholar
  10. David MB, Gentry LE, Starks KM, Cooke RA (2003) Stream transport of herbicides and metabolites in a tile drained, agricultural watershed. J Environ Qual 32:1790–1801Google Scholar
  11. David MB, Wall LG, Royer TV, Tank JL (2006) Denitrification and the nitrogen budget of a reservoir in an agricultural landscape. Ecol Appl 16:2177–2190CrossRefGoogle Scholar
  12. Davidson EA, Seitzinger S (2006) The enigma of progress in denitrification research. Ecol Appl 16:2057–2063CrossRefGoogle Scholar
  13. Del Grosso SJ, Parton WJ, Mosier AR, Ojima DS, Kulmala AE, Phongpan S (2000) General model for N2O and N2 gas emissions from soils due to denitrification. Glob Biogeochem Cycles 14:1045–1060CrossRefGoogle Scholar
  14. Del Grosso SJ, Parton WJ, Mosier AR, Hartman MD, Brenner J, Ojima DS, Schimel DS (2001a) Simulated interaction of carbon dynamics and nitrogen trace gas fluxes using the DAYCENT model. In: Schaffer M et al (eds) Modeling carbon and nitrogen dynamics for soil management. CRC Press LLC, Boca Raton, pp 303–332Google Scholar
  15. Del Grosso SJ, Parton WJ, Mosier AR, Hartman MD, Keough CA, Peterson GA, Ojima DS, Schimel DS (2001b) Simulated effects of land use, soil texture, and precipitation on N gas emissions using DAYCENT. In: Follett RF, Hatfield JL (eds) Nitrogen in the environment: sources, problems, and management. Elsevier, The Netherlands, pp 413–431CrossRefGoogle Scholar
  16. Del Grosso SJ, Ojima DS, Parton WJ, Mosier AR, Peterson GA, Schimel DS (2002) Simulated effects of dryland cropping intensification on soil organic matter and greenhouse gas exchanges using the DAYCENT ecosystem model. Environ Pollut 116:S75–S83CrossRefGoogle Scholar
  17. Del Grosso SJ, Mosier AR, Parton WJ, Ojima DS (2005) DAYCENT model analysis of past and contemporary soil N2O and net greenhouse gas flux for major crops in the USA. Soil Tillage Res 83:9–24CrossRefGoogle Scholar
  18. Del Grosso SJ, Parton WJ, Mosier AR, Walsh MK, Ojima DS, Thornton PE (2006) DAYCENT national scale simulations of N2O emissions from cropped soils in the USA. J Environ Qual 35:1451–1460CrossRefGoogle Scholar
  19. Elmi AA, Madramootoo CA, Egeh M, Liu A, Hamel C (2002) Environmental and agronomic implications of water table and nitrogen fertilization management. J Environ Qual 31:1858–1867Google Scholar
  20. Elmi AA, Astatkie T, Madramootoo CA, Gordon R, Burton D (2005a) Assessment of denitrification gaseous end-products in the soil profile under two water table management practices using repeated measures analysis. J Environ Qual 34:446–454Google Scholar
  21. Elmi AA, Gordon R, Burton D, Madramootoo C (2005b) Impacts of water table management on N2O and N2 from a sandy loam soil in southwestern Quebec, Canada. Nutr Cycl Agroecosyst 72:229–240CrossRefGoogle Scholar
  22. Fouss JL, Bengston RL, Carter CE (1987) Simulating subsurface drainage in the lower Mississippi Valley with DRAINMOD. Trans ASAE 30:1679–1688Google Scholar
  23. Gassman PW, Williams JR, Benson VW, Izaurralde RC, Hauck L, Jones CA, Atwood JD, Kiniry J, Flowers JD (2005) Historical development and applications of the EPIC and APEX models. Working paper 05-WP 397 Center for Agricultural and Rural Development, Iowa State University, Ames (available on-line http://wwwcardiastateedu/publications/DBS/PDFFiles/05wp397pdf)
  24. Gassman PW, Reyes MR, Green CH, Arnold JG (2007) The soil and water assessment tool: historical development, applications, and future research directions. Working paper 07-WP 443, Center for Agricultural and Rural Development, Iowa State University, Ames http://wwwcardiastateedu/publications/DBS/PDFFiles/07wp443pdf
  25. Gentry LE, David MB, Smith KM, Kovacic DA (1998) Nitrogen cycling and tile drainage nitrate loss in a corn/soybean watershed. Agric Ecosyst Environ 68:85–97CrossRefGoogle Scholar
  26. Gentry LE, David MB, Royer TV, Mitchell CA, Starks KM (2007) Phosphorus transport pathways to streams in tile-drained agricultural watersheds. J Environ Qual 36:408–415CrossRefGoogle Scholar
  27. Grizzett B, Bouraoui F, Granlund K, Rekolainen S, Bidoglio G (2003) Modeling diffuse emission and retention of nutrients in the Bantaanjoki watershed (Finland) using the SWAT model. Ecol Model 169:25–38CrossRefGoogle Scholar
  28. Groffman PM, Altabet MA, Böhlke JK, Butterbach-Bahl K, David MB, Firestone MK, Giblin AE, Kana TM, Nielsen LP, Voytek MA (2006) Methods for measuring denitrification: diverse approaches to a difficult problem. Ecol Appl 16:2091–2122CrossRefGoogle Scholar
  29. He X, Izaurralde RC, Vanotti MB, Williams JR, Thomson AM (2006) Simulating long-term and residual effects of nitrogen fertilization on corn yields, soil carbon sequestration, and soil nitrogen dynamics. J Environ Qual 35:1608–1619CrossRefGoogle Scholar
  30. Heinen M (2006) Simplified denitrification models: overview and properties. Geoderma 133:444–463CrossRefGoogle Scholar
  31. Hofstra N, Bouwman AF (2005) Denitrification in agricultural soils: summarizing published data and estimating global annual rates. Nutr Cycl Agroecosyst 72:267–278CrossRefGoogle Scholar
  32. Hu X, McIsaac GF, David MB, Louwers CAL (2007) Modeling riverine nitrate export from an east-central Illinois watershed using SWAT. J Environ Qual 36:996–1005CrossRefGoogle Scholar
  33. Izaurralde RC, Williams JR, McGill WB, Rosenberg NJ, Jakas MCQ (2006) Simulating soil C dynamics with EPIC: model description and testing against long-term data. Ecol Model 192:362–384CrossRefGoogle Scholar
  34. Kaluli JW, Madramootoo CA, Zhou X, MacKenzie AF, Smith DL (1999) Subirrigation systems to minimize nitrate leaching. J Irrig Drain Eng 125:52–58CrossRefGoogle Scholar
  35. Kelly RH, Parton WJ, Hartman MD, Stretch LK, Ojima DS, Schimel DS (2000) Intra and interannual variability of ecosystem processes in shortgrass steppe. J Geophys Res 105:20093–20100CrossRefGoogle Scholar
  36. Li CS, Frolking S, Frolking TA (1992) A model of nitrous oxide evolution from soil driven by rainfall events: 1 model structure and sensitivity. J Geophys Res 97:9759–9776Google Scholar
  37. Li CS, Mosier A, Wassmann R, Cai ZC, Zheng XH, Huang Y, Tsuruta H, Boonjawat J, Lantin R (2004) Modeling greenhouse gas emissions from rice-based production systems: sensitivity and upscaling. Glob Biogeochem Cycles 18:GB1043. doi:101019/2003GB002045 CrossRefGoogle Scholar
  38. Li CS, Frolking S, Xiao XM, Moore BIII, Boles S, Qiu JJ, Huang Y, Salas W, Sass R (2005a) Modeling impacts of farming management alternatives on CO2, CH4, and N2O emissions: a case study for water management of rice agriculture of China. Glob Biogeochem Cycles 19:GB3010. doi:10.1029/2004GB002341 CrossRefGoogle Scholar
  39. Li Y, Chen DL, Zhang YM, Edis R, Ding H (2005b) Comparison of three modeling approaches for simulating denitrification and nitrous oxide emissions from loam-textured arable soils. Glob Biogeochem Cycles 19:GB3002. doi:101029/2004GB002392 CrossRefGoogle Scholar
  40. Louwers CA (2003) Application of the SWAT model to examine a N management program on East-Central Illinois watersheds. MS thesis, University of Illinois, UrbanaGoogle Scholar
  41. McIsaac GF, David MB, Gertner GZ, Goolsby DA (2002) Relating net nitrogen input in the Mississippi River basin to nitrate flux in the lower Mississippi River: a comparison of approaches. J Environ Qual 31:1610–1622Google Scholar
  42. Mitchell JK, McIsaac GF, Walker SE, Hirschi MC (2000) Nitrate in river and subsurface drainage flows from an east-central Illinois watershed. Trans ASAE 43:337–342Google Scholar
  43. Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2005) Soil and water assessment tool theoretical documentation, version 2005. Grassland, Soil and Water Research Laboratory, Agricultural Research Service, Texas, USAGoogle Scholar
  44. NRCS (1996) Soil Survey of Vermilion County, Illinois. United States Department of Agriculture, Natural Resources Conservation ServiceGoogle Scholar
  45. Parton WJ, Scurlock JMO, Ojima DS, Gilmanov TG, Scholes RJ, Schimel DS, Kirchner T, Menaut JC, Seastedt T, Garcia Moya E, Kamnalrut A, Kinyamario JL (1993) Observations and modeling of biomass and soil organic matter dynamics for the grassland biome worldwide. Glob Biogeochem Cycles 7:785–809CrossRefGoogle Scholar
  46. Parton WJ, Mosier AR, Ojima DS, Valentine DW, Schimel DS, Weier K, Kulmala AE (1996) Generalized model for N2 and N2O production from nitrification and denitrification. Glob Biogeochem Cycles 10:401–412CrossRefGoogle Scholar
  47. Parton WJ, Hartman M, Ojima D, Schimel D (1998) DAYCENT and its land submodel: description and testing. Glob Planet Chang 19:35–48CrossRefGoogle Scholar
  48. Parton WJ, Holland EA, Del Grosso SJ, Hartman MD, Martin RE, Mosier AR, Ojima DS, Schimel DS (2001) Generalized model for NOx and N2O emissions from soils. J Geophys Res 106:17403–17419CrossRefGoogle Scholar
  49. Paul EA, Clark FE (1996) Soil microbiology and biochemistry, 2nd edn. Academic Press, LondonGoogle Scholar
  50. Potter CS, Matson PA, Vitousek PM, Davidson EA (1996) Process modeling of controls on nitrogen trace gas emissions from soils worldwide. J Geophys Res 101:1361–1377CrossRefGoogle Scholar
  51. Prince SD, Haskett J, Steininger M, Strand H, Wright R (2001) Net primary production of U.S. Midwest croplands from agricultural harvest yield data. Ecol Appl 11:1194–1205CrossRefGoogle Scholar
  52. Qian JH, Doran JW, Weir KL, Mosier AR, Peterson TA, Power JF (1997) Soil denitrification and nitrous oxide losses under corn irrigated with high-nitrate groundwater. J Environ Qual 26:348–360CrossRefGoogle Scholar
  53. Royer TV, Tank JL, David MB (2004) Transport and fate of nitrate in headwater agricultural streams in Illinois. J Environ Qual 33:1296–1304Google Scholar
  54. Royer TV, David MB, Gentry LE (2006) Timing of riverine export of nitrate and phosphorus from agricultural watersheds in Illinois: implications for reducing nutrient loading to the Mississippi River. Environ Sci Technol 40:4126–4131CrossRefGoogle Scholar
  55. Seitzinger S, Harrison JA, Böhlke JK, Bouwman AF, Lowrance R, Peterson B, Tobias C, Van Drecht G (2006) Denitrification across landscapes and waterscapes: a synthesis. Ecol Appl 16:2064–2090CrossRefGoogle Scholar
  56. Skaggs RW (1978) A water management model for shallow water table soils. Tech. Rep. 134. University of North Carolina Water Resour. Res. Inst., RaleighGoogle Scholar
  57. Skaggs RW (1982) Field evaluation of a water management simulation model. Trans ASAE 25:666–674Google Scholar
  58. Skaggs RW (1999) Drainage simulation models. In: Skaggs RW, van Schilfgaarde J (eds) Agricultural drainage. Agron. Monogr. 38. ASA, CSSA, SSSA, Madison, pp 469–500Google Scholar
  59. Skaggs RW, Fausey NR, Nolte BH (1981) Water management evaluation for north central Ohio. Trans ASAE 24:922–928Google Scholar
  60. Sogbedji JM, McIsaac GF (2006) Evaluation of the ADAPT model for simulating nitrogen dynamics in a tile drained agricultural watershed in central Illinois. J Environ Qual 35:1914–1923CrossRefGoogle Scholar
  61. Stumm W, Morgan JJ (1981) Aquatic chemistry: an introduction emphasizing chemical equilibria in natural waters. Wiley, NY 780 pGoogle Scholar
  62. Tonitto C, David MB, Drinkwater LE, Li C (2007a) Application of DNDC model to tile-drained Illinois agroecosystems: model calibration, validation, and uncertainty analysis. Nutr Cycl Agroecosyst 78:51–63CrossRefGoogle Scholar
  63. Tonitto C, David MB, Drinkwater LE, Li C (2007b) Application of the DNDC Model to tile-drained Illinois agroecosystems: model comparison of conventional and diversified rotations. Nutr Cycl Agroecosyst 78:65–81CrossRefGoogle Scholar
  64. USEPA (2007a) Inventory of U.S. greenhouse gas emissions and sinks: 1990–2005. Washington, DCGoogle Scholar
  65. USEPA (2007b) Hypoxia in the northern Gulf of Mexico, an Update by the EPA Science Advisory Board EPA-SAB-08-004, December 2007 Washington, DCGoogle Scholar
  66. Williams JR, Dyke PT, Jones CA (1983) EPIC: a model for assessing the effects of erosion on soil productivity In: Laurenroth WK et al (eds) Analysis of ecological systems: State-of-the-Art in ecological modeling, Amsterdam, The Netherlands, pp 553–572Google Scholar
  67. Youssef MA (2003) Modeling nitrogen transport and transformations in high water table soils. Ph.D. dissertation, North Carolina State University, RaleighGoogle Scholar
  68. Youssef MA, Skaggs RW, Chescheir GM, Gilliam JW (2005) The nitrogen simulation model, DRAINMOD-N II. Trans ASAE 48:611–626Google Scholar
  69. Youssef MA, Skaggs RW, Chescheir GM, Gilliam JW (2006) Field evaluation of a model for predicting nitrogen losses from drained lands. J Environ Qual 35:2026–2042CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Mark B. David
    • 1
  • Stephen J. Del Grosso
    • 2
  • Xuetao Hu
    • 3
  • Elizabeth P. Marshall
    • 4
  • Gregory F. McIsaac
    • 1
  • William J. Parton
    • 5
  • Christina Tonitto
    • 6
  • Mohamed A. Youssef
    • 7
  1. 1.Department of Natural Resources and Environmental SciencesUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.USDA-ARS, Natural Resources Research CenterFort CollinsUSA
  3. 3.Department of Civil and Environmental EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA
  4. 4.World Resources InstituteWashingtonUSA
  5. 5.Natural Resource Ecology LaboratoryColorado State UniversityFort CollinsUSA
  6. 6.Department of HorticultureCornell UniversityIthacaUSA
  7. 7.Department of Biological and Agricultural EngineeringNorth Carolina State UniversityRaleighUSA

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