Evaluation of the performance of agricultural Beneficial Management Practices (BMPs) intended to protect groundwater resources that may be impacted by the leaching of excess agricultural nutrients is both essential and problematic. Many field-monitoring techniques are hampered by the substantial lag time that often exists between when the BMP is implemented and when a related impact on the groundwater quality might be observed. As a result, agricultural nitrogen models that are adapted to site-specific field conditions are often utilized in concert with field observations to provide estimates of BMP performance. In the current work, the Root Zone Water Quality Model was used to evaluate the long-term reduction of nitrate loading as a result of regional nutrient reduction BMP implementation across agricultural fields located within a municipal well field capture zone. Soil nitrate concentration and soil moisture content profiles were collected from a series of monitoring locations. These data, in conjunction with a heuristic optimization algorithm, were used to calibrate and validate the model. Validation results showed that the simulated moisture content profiles matched very well with the observed profiles, and that the simulated soil nitrate concentration was in general agreement with field observations except for the highly reactive and transient rooting zone. The calibrated model was used to investigate a series of potential nutrient reduction BMP scenarios. Results indicated that the annual nitrate loading varied both spatially and temporally relative to the subsurface conditions and the agricultural land management. The overall results indicate that BMP effectiveness needs to be investigated over relatively long time periods and that short-term, point-scale field measurements may not provide sufficient information to evaluate BMP performance. The results obtained through the integration of field data and an agriculture nitrogen model indicates that this approach can be highly beneficial to assess or evaluate the potential long-term performance of agricultural BMPs.

旨在保护可能受到过量农业养分浸出影响的地下水资源的农业效益管理规范（BMP）绩效的评估既重要又存在问题。在实施BMP与观察到对地下水质量的相关影响之间通常存在很大的滞后时间，这阻碍了许多现场监测技术的发展。结果，经常与田间观察相结合使用适合于特定地点田间条件的农业氮模型，以提供对BMP性能的估计。在目前的工作中，根区水质模型用于评估由于市政井田捕获区内的所有农田实施区域养分减少BMP而导致的硝酸盐负荷的长期减少。从一系列监测地点收集了土壤硝酸盐浓度和土壤水分含量概况。这些数据与启发式优化算法一起用于校准和验证模型。验证结果表明，模拟的水分含量曲线与观测到的曲线非常吻合，并且模拟的土壤硝酸盐浓度除高反应性和短暂生根区外，与实地观测结果基本一致。校准后的模型用于研究一系列潜在的养分减少BMP情景。结果表明，相对于地下条件和农田管理，年度硝酸盐负荷在空间和时间上都发生变化。总体结果表明，BMP有效性需要在相对较长的时间段内进行调查，而短期的点规模现场测量可能无法提供足够的信息来评估BMP的性能。通过现场数据和农业氮模型的集成获得的结果表明，该方法对于评估或评估农业BMP的潜在长期性能非常有益。总体结果表明，BMP有效性需要在相对较长的时间段内进行调查，而短期的点规模现场测量可能无法提供足够的信息来评估BMP的性能。通过现场数据和农业氮模型的集成获得的结果表明，这种方法对于评估或评估农业BMP的潜在长期性能非常有益。总体结果表明，BMP有效性需要在相对较长的时间段内进行调查，而短期的点规模现场测量可能无法提供足够的信息来评估BMP的性能。通过现场数据和农业氮模型的集成获得的结果表明，这种方法对于评估或评估农业BMP的潜在长期性能非常有益。