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ARS Home » Midwest Area » Urbana, Illinois » Global Change and Photosynthesis Research » Research » Publications at this Location » Publication #338320

Title: Evaluation of DeNitrification DeComposition model for estimating ammonia fluxes from chemical fertilizer application

item BALASUBRAMANIAN, SRINIDHI - University Of Illinois
item NELSON, ANDREW - University Of Illinois
item KOLOUTSOU-VAKAKIS, SOTIRIA - University Of Illinois
item LIN, JIE - University Of Illinois
item ROOD, MARK - University Of Illinois
item MYLES, LATOYA - National Oceanic & Atmospheric Administration (NOAA)
item Bernacchi, Carl

Submitted to: Agricultural and Forest Meteorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/4/2017
Publication Date: 5/1/2017
Citation: Balasubramanian, S., Nelson, A.J., Koloutsou-Vakakis, S., Lin, J., Rood, M.J., Myles, L., Bernacchi, C.J. 2017. Evaluation of DeNitrification DeComposition model for estimating ammonia fluxes from chemical fertilizer application. Agricultural and Forest Meteorology. 237:123-34.

Interpretive Summary: A model that predicts how much fertilizer is released from the soil into the atmosphere was compared against a system engineered to measure actual loss of ammonia. The objective of this research is to assess how well the model simulations compare with real measurements. The experiment was conducted over corn grown in Illinois given the extensive planting of corn found in this region of the country. The model did an excellent job at predicting when ammonia would be lost from the soil into the atmosphere, but it did not perform as well in predicting how much left the soil. Because this research tests the model against real data, it provides insights into how the model can be improved to make better assessments of ammonia losses from agricultural ecosystems.

Technical Abstract: DeNitrification DeComposition (DNDC) model predictions of NH3 fluxes following chemical fertilizer application were evaluated by comparison to relaxed eddy accumulation (REA) measurements, in Central Illinois, United States, over the 2014 growing season of corn. Practical issues for evaluating closure were addressed by accounting for fluxes outside the measurement site and differences in temporal resolution. DNDC captured the timing of measured NH3 flux peaks but there were differences in the magnitudes between measured and predicted fluxes. DNDC replicated NH3 flux magnitudes with greater accuracy during the initial 33 days after fertilizer application (ra2>0.74), when measured fluxes were to the atmosphere, compared to time periods when depositional fluxes were measured (ra2>0.52). NH3 fluxes were most sensitive to air temperature, precipitation, soil organic carbon, field capacity, pH, and fertilizer application rate, timing, and depth. By constraining these inputs for conditions in Central Illinois, uncertainty in daily NH3 fluxes was estimated to vary from 0% to 70% on a daily basis, during the corn growing season, with the highest uncertainty values estimated for the period of highest positive NH3 fluxes. These results can guide future improvements in DNDC, which is a valuable tool to assist (1) in the development of NH3 emission inventories with high spatial (constrained by the spatial resolution of input parameters) and temporal resolution (daily) and (2) in upscaling emissions from the site (farm) scale to the regional scale.