Precipitation and irrigation induce pulses of NO emissions in agricultural soils, but the magnitude, duration, and timing of these pulses remain uncertain. This uncertainty makes it difficult to accurately extrapolate emissions from unmeasured time periods between chamber sampling events. Therefore, we developed a modeling protocol to predict NO emissions from data collected daily for 7 d after wetting events. Within a cover crop-based corn ( L.) production system in Beltsville, MD, we conducted the 7-d time series during four time periods representing a range of corn growth stages in 2013 and 2014. Treatments included mixtures and monocultures of grass and legume cover crops that were fertilized with pelletized poultry litter or urea-ammonium nitrate solution (9-276 kg N ha). Most fluxes did not exhibit the expected exponential decay over time (82%); therefore, cumulative emissions were calculated using trapezoidal integration over 7 d after the wetting event. Cumulative 7-d emissions were well correlated with single point gas fluxes on the second day after a wetting event using a generalized linear mixed model (ln[emissions] = 0.809∙ln[flux] + 2.47). Soil chemical covariates before or after a wetting event were weakly associated with cumulative emissions. The ratio of dissolved organic C to total inorganic N was negatively correlated with cumulative emissions ( = 0.23-0.29), whereas nitrate was positively correlated with cumulative emissions ( = 0.23-0.33). Our model is an innovative approach that is calibrated using site-specific time series data, which may then be used to estimate short-term NO emissions after wetting events using only a single flux measurement.

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http://dx.doi.org/10.2134/jeq2016.02.0048DOI Listing

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