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Assessing the impacts of tillage and fertilization management on nitrous oxide emissions in a cornfield using the DNDC model
Author(s) -
Deng Qi,
Hui Dafeng,
Wang Junming,
Yu ChihLi,
Li Changsheng,
Reddy K. Chandra,
Dennis Sam
Publication year - 2016
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2015jg003239
Subject(s) - tillage , environmental science , greenhouse gas , manure , nitrification , fertilizer , nitrous oxide , agronomy , agriculture , soil carbon , denitrification , nitrogen , soil water , soil science , chemistry , ecology , biology , organic chemistry
Quantification and prediction of N 2 O emissions from croplands under different agricultural management practices are vital for sustainable agriculture and climate change mitigation. We simulated N 2 O 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 N 2 O emissions as well as soil properties under different agricultural management practices. The modeled emissions of N 2 O 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 N 2 O emission in a short term, but over a long term (100 years) the treatments significantly altered N 2 O emission (+35%, −10%, respectively). Sensitivity analysis showed that N 2 O 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.