Assessing the impacts of tillage and fertilization management on nitrous oxide emissions in a cornfield using the DNDC model

Abstract

Quantification and prediction of N2O emissions from croplands under different agricultural management practices are vital for sustainable agriculture and climate change mitigation. We simulated N2O emissions under tillage and no‐tillage,and different nitrogen (N) fertilizer types and application methods (i.e., nitrification inhibitor, chicken manure, and split applications) in a cornfield using the DeNitrification‐DeComposition (DNDC) model. The model was parameterized with field experimental data collected in Nashville, Tennessee, under various agricultural management treatments and run for a short term (3 years) and a long term (100 years). Results showed that the DNDC model could adequately simulate N2O emissions as well as soil properties under different agricultural management practices. The modeled emissions of N2O significantly increased by 35% with tillage, and decreased by 24% with the use of nitrification inhibitor, compared with no‐tillage and normal N fertilization. Chicken manure amendment and split applications of N fertilizer had minor impact on N2O emission in a short term, but over a long term (100 years) the treatments significantly altered N2O emission (+35%, −10%, respectively). Sensitivity analysis showed that N2O emission was sensitive to mean annual precipitation, mean annual temperature, soil organic carbon, and the amount of total N fertilizer application. Our model results provide valuable information for determining agricultural best management practice to maintain highly productive corn yield while reducing greenhouse gas emissions.

Mapping Conservation Management Practices and Outcomes in the Corn Belt Using the Operational Tillage Information System (OpTIS) and the Denitrification–Decomposition (DNDC) Model

“…Since both SOC and N2O emissions were well-validated in North America [40][41][42][43][44][45][46][47][48], and the "out of the box" approach has demonstrated its consistency with field studies [52], we believe that our approach and use of the model is reasonable in this case. In this study, we used the DNDC model to estimate the impacts of conservation management practices on SOC dynamics and N2O emissions across 645 counties in the Corn Belt from 2005 to 2018, based on OpTIS mapping results.…”

“…Jarecki et al [43] also reported that the modeled and observed SOC were in good agreement at both sites in Canada, with differences ranging from 0.39 to 4.1 Mg C ha −1 . DNDC has also been validated against N 2 O flux and N leaching measurement data in North America (i.e., USA and Canada), Europe (i.e., Belgium, UK), and East Asia (i.e., China, Japan, and Thailand) [44][45][46][47][48][49][50][51]. In addition, our previous study has compared the not-validated DNDC simulations of N 2 O emissions and N leaching in the Corn Belt with 56 peer-reviewed field studies of similar interventions, and the results showed that those simulations were consistent with the meta-analysis of Midwest corn N 2 O mitigation potential [52].…”

The importance of management information and soil moisture representation for simulating tillage effects on N<sub>2</sub>O emissions in LPJmL5.0-tillage

“…In the LPJmL.G.Orig scenario, all management information as well as soil C and N pools were used as within the default global simulation of LPJmL (Table 3). The amount of mineral and organic fertilizers was provided by the global gridded crop model intercomparison (Elliott et al, 2015) of the Agricultural Model Intercomparison and Improvement Project (AgMIP; Rosenzweig et al, 2013). It is based on global, gridded data sets for each crop (Mueller et al, 2012;Potter et al, 2010).…”

Enhancing the soil and water assessment tool model for simulating N 2 O emissions of three agricultural systems

“…Investigating the confounding impacts of multiple environmental factors on N 2 O emissions is critical for enriching understanding of N 2 O production, emission, and mitigation (Deng et al. , Liu et al. ).…”