Improving DNDC model to estimate ammonia loss from urea fertilizer application in temperate agroecosystems
Process-based biogeochemical models such as the DeNitrification–DeComposition (DNDC) model can provide reliable estimations of agricultural nitrogen loss, information necessary for developing better management practices. The Canadian version of the model (DNDC v.CAN) was recently developed to predict NH3 volatilization after the field application of liquid animal manure; however it did not include a mechanism for simulating soil pH buffering or fertilizer application at depth. Using published data collected from four studies in Québec, Canada, this research included the effects of urea hydrolysis and buffer capacity on soil pH in DNDC v.CAN. The improved model was tested for estimating NH3 loss after surface and incorporated urea applications. Owing to the developments, the NH3 loss estimations of the improved DNDC v.CAN model better correlated to observations in all four field studies (r = 0.95 for P ≤ 0.05) compared to the previous model versions (0.63 and 0.47 respectively). Soil pH predictions were also better correlated (r = 0.56) while the other versions had poor correlations of −0.27 and −0.33, respectively. An assessment of environmental and management factors on NH3 losses using scenario and sensitivity analyses was also carried out. The scenario assessment suggested that incorporated urea application had the highest reduction in cumulative NH3 loss and the sensitivity analysis indicated that soil pH and temperature had the greatest influence on estimates of NH3 loss under the incorporated and split scenarios. The improvements to the mechanisms regulating N losses in DNDC v.CAN will have positive implications to accurately simulate N cycling in agro-ecosystems.
KeywordsUrea Ammonia volatilization DNDC Modeling pH buffer Scenario assessment
The authors would like to thank the students and research professionals who assisted with the field and laboratory measurements and data handling at the research sites in Québec. This work was funded by Agriculture and Agri-Food Canada’s Growing Forward 2 (GF2) policy framework program.
- Environment Canada (2015) Historical climate data, Québec City. http://climate.weather.gc.ca/
- Fontoura SMV, Bayer C (2010) NH3 volatilization in no-till system in the south-central region of the State of Paraná, Brazil. Rev Bras de Ciência do Solo 34(5):1677–1684Google Scholar
- Giltrap DL, Rodriguez J, Berben P, Palmada T, Saggar S (2015) Modelling NH3 volatilisation from a urine patch and urea application using NZ-DNDC. In: 28th annual FLRC workshop, 10–12 February 2015, Massey University, NZGoogle Scholar
- Hansen S, Jensen HE, Nielsen NE, Svendsen H (1990) DAISY—soil plant atmosphere system model. Report A10 issued by The Royal Veterinary and Agricultural University, CopenhagenGoogle Scholar
- Jones CA, Koenig RT, Ellsworth JW, Brown BD, Jackson GD (2007) Management of urea fertilizer to minimize volatilization, Ext Bull 173, Mont. State Univ., BozemanGoogle Scholar
- Saggar S, Singh J, Giltrap DL, Zaman M, Luo J, Rollo M, Kim DG, Rys G, van der Weerden TJ (2012) Quantification of reductions in ammonia emissions from fertiliser urea and animal urine in grazed pastures with urease inhibitors for agriculture inventory: New Zealand as a case study. Sci Total Environ 465:136–146CrossRefPubMedGoogle Scholar
- Schaub WR (1991) A method for estimating missing hourly temperatures using daily maximum and minimum temperatures. USAF Environmental Technical Applications Center USAFETAC/DNOGoogle Scholar
- Smith WN, Grant BB, Desjardins RL, Rochette P, Drury CF, Li C (2008) Evaluation of two process-based models to estimate soil N2O emissions in Eastern Canada. Can J Soil Sci 88(251):260Google Scholar
- Soh KG (2001) Global supply and demand for urea. International Fertilizer Industry Association, Paris, FranceGoogle Scholar
- Svenson JD, Santner TJ, Dean AM, Moon H (2014) Estimating sensitivity indices from computer simulator output. J Stat Plan Infer 144(1):60–172Google Scholar