Garcia Valerie, Cooter Ellen, Crooks James, Hinckley Brian, Murphy Mark, Xing Xiangnan
Environmental Protection Agency, (MD-E243-02), 109 TW Alexander Drive, RTP, NC 27711, United States.
Environmental Protection Agency, (MD-E243-02), 109 TW Alexander Drive, RTP, NC 27711, United States.
Sci Total Environ. 2017 May 15;586:16-24. doi: 10.1016/j.scitotenv.2017.02.009. Epub 2017 Feb 12.
This study demonstrates the value of a coupled chemical transport modeling system for investigating groundwater nitrate contamination responses associated with nitrogen (N) fertilizer application and increased corn production. The coupled Community Multiscale Air Quality Bidirectional and Environmental Policy Integrated Climate modeling system incorporates agricultural management practices and N exchange processes between the soil and atmosphere to estimate levels of N that may volatilize into the atmosphere, re-deposit, and seep or flow into surface and groundwater. Simulated values from this modeling system were used in a land-use regression model to examine associations between groundwater nitrate-N measurements and a suite of factors related to N fertilizer and groundwater nitrate contamination. Multi-variable modeling analysis revealed that the N-fertilizer rate (versus total) applied to irrigated (versus rainfed) grain corn (versus other crops) was the strongest N-related predictor variable of groundwater nitrate-N concentrations. Application of this multi-variable model considered groundwater nitrate-N concentration responses under two corn production scenarios. Findings suggest that increased corn production between 2002 and 2022 could result in 56% to 79% increase in areas vulnerable to groundwater nitrate-N concentrations ≥5mg/L. These above-threshold areas occur on soils with a hydraulic conductivity 13% higher than the rest of the domain. Additionally, the average number of animal feeding operations (AFOs) for these areas was nearly 5 times higher, and the mean N-fertilizer rate was 4 times higher. Finally, we found that areas prone to high groundwater nitrate-N concentrations attributable to the expansion scenario did not occur in new grid cells of irrigated grain-corn croplands, but were clustered around areas of existing corn crops. This application demonstrates the value of the coupled modeling system in developing spatially refined multi-variable models to provide information for geographic locations lacking complete observational data; and in projecting possible groundwater nitrate-N concentration outcomes under alternative future crop production scenarios.
本研究证明了一个耦合化学迁移模型系统在调查与氮肥施用和玉米产量增加相关的地下水硝酸盐污染响应方面的价值。耦合的社区多尺度空气质量双向和环境政策综合气候模型系统纳入了农业管理实践以及土壤与大气之间的氮交换过程，以估算可能挥发到大气中、重新沉积以及渗入或流入地表水和地下水的氮水平。该模型系统的模拟值被用于土地利用回归模型，以检验地下水硝酸盐氮测量值与一系列与氮肥和地下水硝酸盐污染相关的因素之间的关联。多变量建模分析表明，施用于灌溉（而非雨养）谷物玉米（而非其他作物）的氮肥施用量（相对于总量）是与地下水硝酸盐氮浓度相关性最强的氮相关预测变量。应用这个多变量模型考虑了两种玉米生产情景下的地下水硝酸盐氮浓度响应。研究结果表明，2002年至2022年间玉米产量的增加可能导致易受地下水硝酸盐氮浓度≥5mg/L影响的区域增加56%至79%。这些超阈值区域出现在水力传导率比研究区域其他地方高13%的土壤上。此外，这些区域的动物饲养场（AFO）平均数量几乎高出5倍，平均氮肥施用量高出4倍。最后，我们发现，归因于扩张情景的易出现高地下水硝酸盐氮浓度的区域并非出现在灌溉谷物玉米农田的新网格单元中，而是聚集在现有玉米作物区域周围。本应用展示了耦合模型系统在开发空间精细化多变量模型以提供缺乏完整观测数据的地理位置的信息方面的价值；以及在预测未来替代作物生产情景下可能的地下水硝酸盐氮浓度结果方面的价值。
