USDA-ARS National Laboratory for Agriculture and the Environment, Ames, IA, United States.
USDA-ARS National Laboratory for Agriculture and the Environment, Ames, IA, United States.
Sci Total Environ. 2018 Mar 15;618:982-997. doi: 10.1016/j.scitotenv.2017.09.054. Epub 2017 Oct 24.
Anthropogenic perturbation of the global nitrogen cycle and its effects on the environment such as hypoxia in coastal regions and increased NO emissions is of increasing, multi-disciplinary, worldwide concern, and agricultural production is a major contributor. Only limited studies, however, have simultaneously investigated NO losses to subsurface drain flow and NO emissions under corn-soybean production. We used the Root Zone Water Quality Model (RZWQM) to evaluate NO losses to drain flow and NO emissions in a corn-soybean system with a winter rye cover crop (CC) in central Iowa over a nine year period. The observed and simulated average drain flow N concentration reductions from CC were 60% and 54% compared to the no cover crop system (NCC). Average annual April through October cumulative observed and simulated NO emissions (2004-2010) were 6.7 and 6.0kgNO-Nhayr for NCC, and 6.2 and 7.2kgNha for CC. In contrast to previous research, monthly NO emissions were generally greatest when N loss to leaching were greatest, mostly because relatively high rainfall occurred during the months fertilizer was applied. NO emission factors of 0.032 and 0.041 were estimated for NCC and CC using the tested model, which are similar to field results in the region. A local sensitivity analysis suggests that lower soil field capacity affects RZWQM simulations, which includes increased drain flow nitrate concentrations, increased N mineralization, and reduced soil water content. The results suggest that 1) RZWQM is a promising tool to estimate NO emissions from subsurface drained corn-soybean rotations and to estimate the relative effects of a winter rye cover crop over a nine year period on nitrate loss to drain flow and 2) soil field capacity is an important parameter to model N mineralization and N loss to drain flow.
人为干扰全球氮循环及其对环境的影响，如沿海地区缺氧和氮氧化物排放增加，引起了越来越多的多学科关注，而农业生产是主要贡献者。然而，只有有限的研究同时调查了玉米-大豆生产下地下排水流失和氮氧化物排放的氮损失。我们使用根区水质模型（RZWQM）来评估在爱荷华州中部的一个玉米-大豆系统中，冬季黑麦覆盖作物（CC）下氮向地下排水流失和氮氧化物排放的损失，该系统经过了九年的研究。与无覆盖作物系统（NCC）相比，观察到的和模拟的 CC 平均排水氮浓度降低了 60%和 54%。与 NCC 相比，2004-2010 年 4 月至 10 月的平均年累积观测和模拟氮氧化物排放量分别为 6.7 和 6.0kgNO-Nha-1yr-1，CC 为 6.2 和 7.2kgNha-1yr-1。与之前的研究不同，当淋溶损失氮最大时，每月氮氧化物排放量通常最大，这主要是因为在施肥期间发生了相对较高的降雨量。使用测试模型估计 NCC 和 CC 的氮氧化物排放因子分别为 0.032 和 0.041，与该地区的田间结果相似。局部敏感性分析表明，较低的土壤田间持水量会影响 RZWQM 模拟，包括增加地下排水硝酸盐浓度、增加氮矿化和减少土壤含水量。结果表明：1）RZWQM 是估计地下排水玉米-大豆轮作氮氧化物排放的一种很有前景的工具，并且可以估计在九年期间冬季黑麦覆盖作物对硝酸盐向地下排水流失的相对影响；2）土壤田间持水量是模拟氮矿化和氮向地下排水流失的重要参数。
