Nutrient Cycling in Agroecosystems

, Volume 109, Issue 3, pp 211–232 | Cite as

Model comparison of soil processes in eastern Canada using DayCent, DNDC and STICS

  • G. Guest
  • R. KröbelEmail author
  • B. Grant
  • W. Smith
  • J. Sansoulet
  • E. Pattey
  • R. Desjardins
  • G. Jégo
  • N. Tremblay
  • G. Tremblay
Original Article


Process-based models are useful tools for estimating the complex interactions between plant, soil and climate systems, assessments which are necessary for improving nutrient cycling and reducing trace gas emissions. Incorporation of knowledge gained through new research is ongoing, thus there is a need for evaluation of model processes and process interactions. In this study, three sites in eastern Canada (St. Bruno, St. Jean, and Ottawa) planted with spring wheat during the years 1993–2007 were used to evaluate and compare the water and N process simulations of the models DayCent, DNDC, and STICS. The simulated soil moisture by all models was generally well represented with low ARE (< 8%) and an EF > 0.1. The unsaturated flow mechanism included in DayCent further improved soil moisture estimates compared to the other models. When sufficient replicate data was available measurement variability was considered, resulting in soil nitrogen being only slightly underestimated (ARE of −10, −1, and −22%, for DayCent, DNDC, and STICS, respectively). On average across the three sites, considering all statistics, the DNDC model proved to be most accurate for simulating mineral N, followed by DayCent and then STICS. Continued process model development is reliant on measurement datasets that can accurately represent carbon and nitrogen dynamics. Frequently, site specific biases convolute model mechanism evaluation and thus assessments have to be conducted across numerous sites to better benchmark model performance. On this premise a comprehensive multi-site inter-model mechanism evaluation was conducted and future model development needs were identified.


DNDC DayCent STICS N dynamics Soil moisture 



The authors thank the research technicians and professionals (Ottawa: Dave Dow and Christophe Forget, St. Jean: Edith Fallon, St. Bruno: Marc Saulnier) and students that participated in the field experimentation and data processing. This work was funded by the Agriculture and Agri-Food Canada A-base and SAGES initiative on “Understanding and predicting nitrogen dynamics in Canadian cropping systems to improve efficiency of nitrogen utilization and reduce environmental losses”.

Supplementary material

10705_2017_9880_MOESM1_ESM.docx (28 kb)
Supplementary material 1 (DOCX 28 kb)


  1. Abdalla M, Wattenbach M, Smith P, Ambus A, Jones M, Williams M (2009) Application of the DNDC model to predict emissions of N2O from Irish agriculture. Geoderma 151:327–337CrossRefGoogle Scholar
  2. Beheydt D, Boeckx P, Sleutel S, Li CS, Van Cleemput O (2007) Validation of DNDC for 22 long-term N2O field emission measurements. Atmos Environ 41:6196–6211CrossRefGoogle Scholar
  3. Bessou C, Mary B, Leonard J, Roussel M, Grehan E, Gabrielle B (2010) Modelling soil compaction impacts on nitrous oxide emissions in arable fields. Eur J Soil Sci 61(3):348–363CrossRefGoogle Scholar
  4. Bolinder MA, Andrén O, Kätterer T, de Jong R, VandenBygaart AJ, Angers DA, Parent L-E, Gregorich EG (2007) Soil carbon dynamics in Canadian Agricultural Ecoregions: quantifying climatic influence on soil biological activity. Agr Ecosyst Environ 122:461–470CrossRefGoogle Scholar
  5. Brisson N, Mary B, Ripoche D, Jeuffroy MH, Ruget F, Nicoullaud B, Gate P, Devienne-Barret F, Antonioletti R, Durr C, Richard G, Beaudoin N, Recous S, Tayot X, Plenet D, Cellier P, Machet JM, Meynard JM, Delécolle R (1998) STICS: a generic model for the simulation of crops and their water and nitrogen balances. 1. Theory and parameterization applied to wheat and corn. Agronomie 18:311–346CrossRefGoogle Scholar
  6. Brisson N, Ruget F, Gate P, Lorgeau J, Nicollaud B, Tayot X, Plenet D, Jeuffroy MH, Bouthier A, Ripoche D, Mary B, Justes E (2002) STICS: a generic model for simulating crops and their water and nitrogen balances. II. Model validation for wheat and maize. Agronomie 22:69–92CrossRefGoogle Scholar
  7. Celette F, Valdés H, Gary C, García de Cortázar I, Ortega-Farias S, Acevedo C (2008) Evaluation of the STICS model for simulating vineyard water balance under two different water management strategies. Acta Hort (ISHS) 792:155–162.
  8. Chen DL, Gao G, Xu CY, Guo J, Ren GY (2005) Comparison of the Thornthwaite method and pan data with the standard Penman–Monteith estimates of reference evapotranspiration in China. Clim Res 28:123–132CrossRefGoogle Scholar
  9. Choudhury BJ, Ahmed NU, Idso SB, Reginato RJ, Daughtry CST (1994) Relations between evaporation coefficients and vegetation indices studied by model simulations. Remote Sens Environ 50:1–17CrossRefGoogle Scholar
  10. Confalonieri R, Bechini L (2004) A preliminary evaluation of the simulation model CropSyst for alfalfa. Eur J Agron 21:223–237CrossRefGoogle Scholar
  11. Constantin J, Beaudoin N, Launay M, Duval J, Mary B (2011) Long-term nitrogen dynamics in various catch crop scenarios: test and simulations with STICS model in a temperate climate. Agric Ecosyst Environ 147:36–46CrossRefGoogle Scholar
  12. Coucheney E, Buis S, Launay M, Constantin J, Mary B, García de Cortázar-Atauri I, Ripoche D, Beaudoin N, Ruget F, Andrianarisoa KS, Le Bas C, Justes E, Léonard J (2015) Accuracy, robustness and behavior of the STICS soil-crop model for plant, water and nitrogen outputs: evaluation over a wide range of agro-environmental conditions in France. Environ Model Softw 64:177–190. doi: 10.1016/j.envsoft.2014.11.024 CrossRefGoogle Scholar
  13. Del Grosso SJ, Halvorson AD, Parton WJ (2008a) Testing DayCent model simulations of corn yields and nitrous oxide emissions in irrigated tillage systems in Colorado. J Environ Qual 37:1383–1389CrossRefPubMedGoogle Scholar
  14. Del Grosso SJ, Parton WJ, Ojima DS, Keough CA, Riley TH, Mosier AR (2008b) DayCent simulated effects of land use and climate on county level N loss vectors in the USA. In: Hatfield JL, Follett RF (eds) Nitrogen in the environment: sources, problems, and management, chapter 18. USDA Agricultural Research Service, LincolnGoogle Scholar
  15. Del Grosso SJ, Parton WJ, Keough CA, Reyes-Fox M (2011) Special features of the DAYCENT modeling package and additional procedures for parameterization, calibration, validation, and applications. In: Ahuja LR, Ma L (eds) Methods of introducing system models into agricultural research. ASA, CSSA, SSSA Inc., Madison, pp 155–177Google Scholar
  16. Diekkrüger B, Söndgerath D, Kersebaum KC, McVoy CW (1995) Validity of agroecosystem models. A comparison of results of different models applied to the same data set. Ecol Model 81:3–29CrossRefGoogle Scholar
  17. Environment Canada. Weather data available online:
  18. Fanko U, Oelschlägel B, Schenk S (1995) Simulation of temperature-, water- and nitrogen dynamics using the model CANDY. Ecol Model 81:213–222CrossRefGoogle Scholar
  19. FAO (Food and Agriculture Organization of the United Nations) (1998) Crop evapotranspiration—guidelines for computing crop water requirements. FAO Irrigation and drainage, Paper 56,
  20. Fernandes R, Korolevych V, Wang SS (2007) Trends in land evapotranspiration over Canada for the period 1960–2000 based on in situ climate observations and a land surface model. J Hydrometeorol 8:1016–1030CrossRefGoogle Scholar
  21. Frick B, Thomas AG (1992) Weed surveys in different tillage systems in southwestern Ontario field crops. Can J Plant Sci 72:1337–1347CrossRefGoogle Scholar
  22. Frolking SE, Mosier AR, Ojima DS, Li C, Parton WJ, Potter CS, Priesack E, Stenger R, Haberbosch C, Dörsch P, Flessa H, Smith KA (1998) Comparison of N2O emissions from soils at three temperate agricultural sites: simulations of year-round measurements by four models. Nutr Cycl Agroecosyst 52:77–105CrossRefGoogle Scholar
  23. Galloway JN, Cowling EB (2002) Reactive nitrogen and the world: 200 years of change. Ambio 31(2):64–71CrossRefPubMedGoogle Scholar
  24. Gandolfi C, Facchi A, Maggi D (2006) Comparison of 1D models of water flow in unsaturated soils. Environ Model Softw 21:1759–1764CrossRefGoogle Scholar
  25. Gold HJ (1977) Mathematical modelling of biological systems. Wiley, TorontoGoogle Scholar
  26. Harmel RD, Smith PK (2007) Consideration of measurement uncertainty in the evaluation of goodness-of-fit in hydrologic and water quality modelling. J Hydrol 337:326–336CrossRefGoogle Scholar
  27. Harmel RD, Smith PK, Migliaccio KW (2010) Modifying goodness-of-fit indicators to incorporate both measurement and model uncertainty in model calibration and validation. Trans ASABE 53(1):55–63CrossRefGoogle Scholar
  28. Hutson JL, Wagenet RJ (1991) Simulating nitrogen dynamics in soils using a deterministic model. Soil Use Manag 7:74–78CrossRefGoogle Scholar
  29. Jarecki M, Parkin TB, Chan ASK, Hatfield JL, Jones R (2008) Comparison of DayCent-simulated and measured nitrous oxide emissions from a corn field. J Environ Qual 37:1685–1690CrossRefPubMedGoogle Scholar
  30. Jégo G, Pattey E, Bourgeois G, Morrison MJ, Drury CF, Tremblay N, Tremblay G (2010) Calibration and performance evaluation of soybean and spring wheat cultivars using the STICS crop model in Eastern Canada. Field Crop Res 117:183–196CrossRefGoogle Scholar
  31. Jégo G, Sánchez-Pérez JM, Justes E (2012) Predicting soil water and mineral nitrogen contents with the STICS model for estimating nitrate leaching under agricultural fields. Agric Water Manag 107:54–65CrossRefGoogle Scholar
  32. Jégo G, Chantigny M, Pattey E, Belanger G, Rochette P, Vanasses A, Goyer C (2014) Improved snow-cover model for multi-annual simulations with the STICS crop model under cold, humid contintental climates. Agric For Meteorol 195–196:38–51CrossRefGoogle Scholar
  33. Jing Q, Jégo G, Bélanger G, Chantigny MH, Rochette P (2017) Simulation of water and nitrogen balances in a perennial forage system using the STICS model. Field Crops Res 201:10–18. doi: 10.1016/j.fcr.2016.10.017 CrossRefGoogle Scholar
  34. Kröbel R, Sun QP, Ingwersen J, Chen XP, Yhang FS, Müller T, Römheld V (2010) Modelling water dynamics with DNDC and DAISY in a soil of the North China Plain: a comparative study. Environ Modell Softw 25:583–601CrossRefGoogle Scholar
  35. Kröbel R, Smith WN, Grant BB, Desjardins RL, Campbell CA, Tremblay N, Li CS, Zentner RP, McConkey BG (2011) Development and evaluation of a new Canadian spring wheat sub-model for DNDC. Can J Soil Sci 91:503–520CrossRefGoogle Scholar
  36. Kumar KK, Kumar KR, Rakhecha PR (1987) Comparison of Penman and Thornthwaite methods of estimating potential evapotranspiration for Indian conditions. Theor Appl Climatol 38:140–146CrossRefGoogle Scholar
  37. Legge AH, Peake E, Strosher M, Nosal M, McVehil GE, Hansen M (1990) Characteristics of the background air quality. In: Legge AH, Krupa SV (eds) Acidic deposition: sulphur and nitrogen oxides. Lewis Publishers Inc, Chelsea, pp 129–248Google Scholar
  38. Li CS, Frolking S, Frolking TA (1992a) A model of nitrous oxide evolution from soil driven by rainfall events: 1. Model structure and sensitivity. J Geophys Res 97:9759–9776CrossRefGoogle Scholar
  39. Li CS, Frolking S, Frolking TA (1992b) A model of nitrous oxide evolution from soil driven by rainfall events: 2. Model applications. J Geophys Res 97(9777–9783):1992Google Scholar
  40. Li CS, Frolking S, Harris R (1994) Modeling carbon biogeochemistry in agricultural soils. Glob Biogeochem Cycles 8:237–254CrossRefGoogle Scholar
  41. 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: 10.1029/2003GB002045 CrossRefGoogle Scholar
  42. Loague K, Green RE (1991) Statistical and graphical methods for evaluating solute transport models: overview and application. J Contam Hydrol 7:51–73CrossRefGoogle Scholar
  43. Manzoni S, Porporato A (2007) A theoretical analysis of nonlinearities and feedbacks in soil carbon and nitrogen cycles. Soil Biol Biochem 39:1542–1556CrossRefGoogle Scholar
  44. Manzoni S, Porporato A (2009) Soil carbon and nitrogen mineralization: theory and models across scales. Soil Biol Biochem 41:1355–1379CrossRefGoogle Scholar
  45. Mayer DG, Butler DG (1993) Statistical validation. Ecol Model 68:21–32CrossRefGoogle Scholar
  46. McKeague JA (ed) (1978) Manual on soil sampling and methods of analysis, 2nd edn. Soil Research Institute, Agriculture Canada, OttawaGoogle Scholar
  47. Mintz Y, Walker GK (1993) Global fields of soil moisture and land surface evapotranspiration derived from observed precipitation and surface air temperature. J Appl Meteorol 32:1305–1334CrossRefGoogle Scholar
  48. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900CrossRefGoogle Scholar
  49. Nakagawa Y, Yan C, Shiono T, Miyamoto T, Kameyama K, Shinogi Y (2008) Evaluating the validity and sensitivity of the DNDC model for Shimajiri dark red soil. Jpn Agric Res Q 42(3):163–172CrossRefGoogle Scholar
  50. Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models, part 1—a discussion of principles. J Hydrol 10(3):282–290CrossRefGoogle Scholar
  51. Ng HYF, Tan CS, Drury CF, Gaynor JD (2002) Controlled drainage and subirrigation influences tile nitrate loss and corn yields in a sandy loam soil in Southwestern Ontario. Agr Ecosyst Environ 90:81–88CrossRefGoogle Scholar
  52. Parton WJ, Ojima DS, Cole CV, Schimel DS (1994) A general model for soil organic matter dynamics: sensitivity to litter chemistry, texture and management. In: Bryant RB, Arnold RW (eds) Quantitative modeling of soil forming processes. SSSA, Madison, pp 147–167Google Scholar
  53. Parton W, Hartman M, Ojima D, Schimel DS (1998) DayCent and its land surface submodel: description and testing. Glob Planet Change 19:35–48CrossRefGoogle Scholar
  54. Pereira AR, Paes de Camargo A (1989) An analysis of the criticism of Thornthwaite’s equation for estimating potential evapotranspiration. Agric Forest Meteorol 46(149):157Google Scholar
  55. Richards LA (1931) Capillarity condition of liquids through porous mediums. Phys J Gen Appl Phys Am Phys Soc 1:318–333Google Scholar
  56. Sansoulet J, Pattey E, Kroebel R, Grant B, Smith WN, Jego G, Desjardins RL, Tremblay N, Tremblay G (2014) Comparing the performance of the STICS, DNDC and DayCent models for predicting N uptake and biomass of spring wheat in eastern Canada. Field Crops Res 156:135–150CrossRefGoogle Scholar
  57. Saxton KE, Rawls WJ (2006) Soil water characteristics estimates by texture and organic matter for hydrologic solutions. Soil Sci Soc Am J 70:1569–1578CrossRefGoogle Scholar
  58. Schindler DW, Donahue WF (2006) An impending water crisis in Canada’s western prairie provinces. Proc Natl Acad Sci 103(19):7210–7216CrossRefPubMedPubMedCentralGoogle Scholar
  59. Sierra J, Brisson N, Ripoche D, Noël C (2003) Application of the STICS crop model to predict nitrogen availability and nitrate transport in a tropical acid soil cropped with maize. Plant Soil 256:333–345CrossRefGoogle Scholar
  60. Smit B, Brklacich M, Stewart RB, McBride R, Brown M, Bond D (1989) Sensitivity of crop yields and land resource potential to climatic change in Ontario, Canada. Clim Change 14:153–174CrossRefGoogle Scholar
  61. Smith WN, Grant BB, Desjardins RL, Rochette P, Drury CF, Li CS (2008) Evaluation of two process-based models to estimate soil N2O emissions in eastern Canada. Can J Soil Sci 88:251–260CrossRefGoogle Scholar
  62. Stockle CO, Martin SA, Campbell GS (1994) CropSyst, a cropping systems simulation model: water/nitrogen budgets and crop yield. Agric Syst 46:335–359CrossRefGoogle Scholar
  63. Tan CS, Drury CF, Gaynor JD, Welacky TW, Reynolds WD (2002) Effect of tillage and water table control on evapotranspiration, surface runoff, tile drainage and soil water content under maize on a clay loam soil. Agric Water Manag 54:173–188CrossRefGoogle Scholar
  64. Tournebize J, Kao C, Nikolic N, Zimmer D (2004) Adaptation of the STICS model to subsurface drained soils. Agronomie 24:305–313CrossRefGoogle Scholar
  65. Tran TS, Tremblay G (2000) Recovery of 15N-labeled fertilizer by spring bread wheat at different N rates and application times. Can J Soil Sci 80:533–539CrossRefGoogle Scholar
  66. Tremblay G, Vasseur C (1994) Management effects on yield and above-ground biomass of three spring wheat cultivars. Can J Plant Sci 74:279–285CrossRefGoogle Scholar
  67. Tremblay N, Wang ZJ, Ma BL, Bélec C, Vigneault P (2009) A comparison of crop data measured by two commercial sensors for variable-rate nitrogen application. Precis Agric 10:145–161CrossRefGoogle Scholar
  68. Tremblay N, Wang ZJ, Bélec C (2010) Performance of DUALEX in spring wheat for crop nitrogen status assessment, yield prediction and estimation of soil nitrate content. J Plant Nutr 33:57–70CrossRefGoogle Scholar
  69. Xu CY, Singh VP (1998) Dependence of evaporation on meteorological variables at different time-scales and intercomparison of estimation methods. Hydrol Proc 12:429–442CrossRefGoogle Scholar
  70. Xu CY, Singh VP (2001) Evaluation and generalization of temperature-based methods for calculating evaporation. Hydrol Proc 15:305–319CrossRefGoogle Scholar
  71. Zhang Y, Li CS, Zhou XJ, Moore B III (2002) A simulation model linking crop growth and soil biogeochemistry for sustainable agriculture. Ecol Model 151:75–108CrossRefGoogle Scholar
  72. Ziadi N, Bélanger G, Cambouris AN, Tremblay N, Nolin MC, Claessens A (2008) Relationship between phosphorus and nitrogen concentrations in spring wheat. Agron J 100:80–86CrossRefGoogle Scholar
  73. Ziadi N, Bélanger G, Claessens A, Lefebvre L, Cambouris AN, Tremblay N, Nolin MC, Parent LE (2010) Determination of a critical nitrogen dilution curve for spring wheat. Agron J 102:241–250CrossRefGoogle Scholar

Copyright information

© Her Majesty the Queen in right of Canada as represented by: Agriculture Agri-Food Canada 2017

Authors and Affiliations

  • G. Guest
    • 1
  • R. Kröbel
    • 2
    Email author
  • B. Grant
    • 1
  • W. Smith
    • 1
  • J. Sansoulet
    • 1
  • E. Pattey
    • 1
  • R. Desjardins
    • 1
  • G. Jégo
    • 3
  • N. Tremblay
    • 4
  • G. Tremblay
    • 5
  1. 1.ECORC, AAFC-AACOttawaCanada
  2. 2.LRC, AAFC-AACLethbridgeCanada
  3. 3.SCRDC, AAFC-AACQuebecCanada
  4. 4.HRDC, AAFC-AACSaint-Jean-sur-RichelieuCanada
  5. 5.Centre de recherche sur les grains (Inc.)St-Mathieu-BeloeilCanada

Personalised recommendations