Nitrogen (N) loss through ammonia \(({\mathrm{NH}}_{3})\) volatilization in agricultural soils is a significant source of atmospheric \({\mathrm{NH}}_{3}\), contributing to low N use efficiency in crops, risk to human health, environmental pollution, and is an indirect source of nitrous oxide \(({\mathrm{N}}_{2}\mathrm{O})\) emissions. Our objective was to develop an ammonia volatilization method within the DayCent ecosystem model that incorporates key 4R N management practices (right type, right rate, right placement, and right timing) that influence \({\mathrm{NH}}_{3}\) volatilization associated with application of urea-based nitrogen fertilizers to agricultural soils. The \({\mathrm{NH}}_{3}\) volatilization method was developed with Bayesian calibration using sampling importance resampling methods and Bayes factors to select the level of complexity in the model that best represents \({\mathrm{NH}}_{3}\) volatilization given the observed data. The final model included urea hydrolysis and the influence of urease inhibitors; short-term soil pH changes following fertilization; fertilizer incorporation into the soil (mechanically and through irrigation/precipitation); and specification of the fertilizer placement method (i.e. broadcast vs. banding and surface vs incorporated). DayCent predicts \({\mathrm{NH}}_{3}\) volatilization with a root-mean-squared error of 158 (95% interval ranging from 133 to 192), bias of 7 (95% interval ranging from − 106 to 102) g NH₃-N ha⁻¹ day⁻¹, and with a Bayesian R² value of 0.39 (95% interval ranging from 0.17 to 0.62). Furthermore, the model incorporates key management options influencing \({\mathrm{NH}}_{3}\) volatilization related to placement method and fertilizer type with and without urease inhibitors that can be used to evaluate management and policy options for reducing losses of NH₃ from urea fertilization.

农业土壤中氨气（（{{mathrm {NH}} _ {3}）\）挥发引起的氮（N）损失是大气\（{{mathrm {NH}} _ {3} \）的重要来源，导致作物中氮的利用率低，对人类健康的风险，环境污染，并且是一氧化二氮\（（{{mathrm {N}} _ {2} \ mathrm {O}）\）排放的间接来源。我们的目标是在DayCent生态系统模型中开发一种氨挥发方法，该方法结合了影响\（{\ mathrm {NH}} _ {3}的关键4R N管理实践（正确的类型，正确的速率，正确的放置和正确的时间）。\）与基于尿素的氮肥在农业土壤上的施用相关的挥发。的\（{\ mathrm {NH}} _ {3} \）使用采样重要性重采样方法和贝叶斯因子，通过贝叶斯校准开发了挥发方法，以在给定观测数据的情况下选择最能代表\（{\ mathrm {NH}} _ {3} \）挥发的模型复杂程度。最终模型包括尿素水解和尿素酶抑制剂的影响。施肥后土壤pH短期变化；将肥料（机械地和通过灌溉/降水）掺入土壤；肥料放置方法的规格和规格（即播散vs.条带和表面vs.结合）。DayCent预测\（{\ mathrm {NH}} _ {3} \）挥发时，均方根误差为158（95％范围从133到192），偏差为7（95％范围从− 106的范围）至102）g NH ₃-N ha ^-1 天^-1，贝叶斯R ²值为0.39（95％区间从0.17到0.62）。此外，该模型还结合了影响\（{{mathrm {NH}} _ {3} \）挥发的关键管理方案，这些方案涉及有无脲酶抑制剂的放置方法和肥料类型，可用于评估管理和政策方案以减少损失来自尿素施肥的NH ₃。