Department of Agronomy, University of Wisconsin-Madison, Madison, Wisconsin, USA.
Nelson Institute Center for Sustainability and the Global Environment, University of Wisconsin-Madison, Madison, Wisconsin, USA.
J Environ Qual. 2023 Nov-Dec;52(6):1102-1114. doi: 10.1002/jeq2.20521. Epub 2023 Nov 9.
The Wisconsin Central Sands is home to large scale vegetable production on sandy soils and managed with frequent irrigation, fertigation, and widespread nitrogen fertilizer application, all of which make the region highly susceptible to nitrate loss to groundwater. While the groundwater is used as the primary source of drinking water for many communities and rural residences across the region, it is also used for irrigation. Considering the high levels of nitrate found in the groundwater, it has been proposed that growers more accurately account for the nitrate in their irrigation water as part of nitrogen management plans. Our objectives were to 1) determine the magnitude of nitrate in irrigation water, 2) quantify the spatiotemporal variability of nitrate, and 3) determine key predictors of nitrate concentration in the region. We sampled irrigation water from 38 fields across six farms from 2018 to 2020. Across the 3 years of our study, nitrate concentration varied more across space than time. On average, our samples were tested at 19.0 mg L nitrate-nitrogen, or nearly two times the U.S. Environmental Protection Agency (EPA) threshold for safe drinking water, equivalent to 48.1 kg ha of applied nitrate-nitrogen with 25.4 cm (or 10 in.) of irrigation. To better understand the spatiotemporal variability in nitrate levels, week of sampling, year, well depth, well casing, and nitrogen application rate were analyzed for their role as predictor variables. Based on our linear mixed effects model, nitrogen application rate was the greatest predictor of the nitrate concentration of irrigation water (p < 0.05).
威斯康星中央沙丘地区以沙质土壤上的大规模蔬菜生产为特色，采用频繁灌溉、施肥和广泛施用氮肥的方式进行管理，所有这些都使该地区极易受到硝酸盐向地下水流失的影响。虽然该地区的地下水是许多社区和农村居民的主要饮用水源，但它也被用于灌溉。考虑到地下水中发现的硝酸盐含量很高，有人建议种植者更准确地计算灌溉水中的硝酸盐，作为氮素管理计划的一部分。我们的目标是：1）确定灌溉水中硝酸盐的含量；2）量化硝酸盐的时空变异性；3）确定该地区硝酸盐浓度的关键预测因子。我们从 2018 年至 2020 年期间在六个农场的 38 个田地中抽取了灌溉水样本。在我们研究的三年中，硝酸盐浓度的空间差异大于时间差异。平均而言，我们的样本检测到硝酸盐氮浓度为 19.0 mg L，几乎是美国环境保护署（EPA）安全饮用水阈值的两倍，相当于 25.4 cm（或 10 英寸）灌溉量下应用的硝酸盐氮为 48.1 kg ha。为了更好地了解硝酸盐水平的时空变异性，我们分析了采样周、年份、井深、井套管和氮施用量作为预测变量的作用。根据我们的线性混合效应模型，氮施用量是灌溉水硝酸盐浓度的最大预测因子（p < 0.05）。
