Groundwater discharge of legacy nitrogen at the scale of river networks: Where are stream interface sediments conduits or filters?

应用于地表的活性氮(N)随降水渗透，并在地下水含水层中积累，形成遗留N的来源，后来从地下水排放到地表水。地下水的运移时间可能比地表水的运移时间长几个月、几十年甚至几个世纪，这会导致氮素从施入陆地表面到实际进入地表水之间存在很大的滞后。这些集中的地下水排放可能会阻碍以减少目前氮素应用为基础的水质管理战略。然而，并不是所有进入地下水系统的氮都被输送到地表水中。部分氮在沿区域地下水流动路径的运输过程中被微生物过程去除。在漫长的地下水流动路径的末端，河岸和河床沉积物可以相对较高的速率去除N，进一步减少N向地表水的输送。该项目将跨河流网络的大量现场测量与地下水模型相结合，以1)表征地下水排放的空间模式和向河流输送遗留氮，以及2)量化和预测河流界面沉积物在清除遗留氮方面的作用。该项目为不同的参与者提供培训，包括高中生、社区大学生、本科生和研究生以及公民科学家。该项目的目标是1)描述河网尺度上集中地下水排放的空间模式，2)量化遗留N通过河流界面(河床和河岸)沉积物的传输和清除的模式和驱动因素，3)尺度遗留N循环到河网。该项目的重点分水岭是法明顿河分水岭，该分水岭流入康涅狄格河和长岛海湾。长岛海湾经历了由过量氮污染造成的季节性死区。该项目包括使用手持相机和无人驾驶航空系统(无人机)对大约95公里的河流和河流长度进行大规模热红外(TIR)调查，以测量向河网排放地下水的空间分布。TIR技术允许优先排泄区的地理位置与区域地下水模拟中使用的较粗模型网格大小更接近。因此，该项目还根据TIR调查数据集得出的指标(如渗漏频率、渗漏空间范围)评估和改进地下水数值模型(MODFLOW)的空间预测。该项目利用对地下水排放和流域尺度运移时间滞后的空间模式的现场和模型估计，来描述并最终预测河流界面沉积物在N循环中的作用。在TIR调查期间确定的排放地点，将测量反硝化速率、N浓度和通量、地下水年龄以及一系列沉积物的物理和化学性质。这些数据集将被用来开发对河流界面沉积物中遗留氮的装载和处理的空间预测。地下水流量和氮通量的空间预测将被用作为法明顿河网实施的河网模型的额外输入，以量化从渗漏位置通过河网输送的遗留氮循环。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Reactive nitrogen (N) applied to land surfaces infiltrates with precipitation and accumulates in groundwater aquifers, creating a source of legacy N that is later discharged from groundwater to surface waters. Groundwater transport times can be months, decades, or even centuries longer than surface water transport times, which causes substantial lags between when N is applied to land surfaces and when it actually enters surface waters. These focused groundwater discharges can obstruct water quality management strategies that are based on reducing present-day N applications. Yet, not all N that enters the groundwater system is delivered to surface waters. Some fraction of N is removed by microbial processes during transport along regional groundwater flow paths. At the end of long groundwater flow paths, streambank and streambed sediments can remove N at relatively high rates, further reducing N delivery to surface waters. This project integrates extensive field measurements across a river network with groundwater models to 1) characterize the spatial patterns of groundwater discharge and legacy N delivery to streams and 2) quantify and predict the role of stream interface sediments in removing legacy N. Results will be shared with practitioners to help with issues surrounding N pollution management in the Long Island Sound. The project provides training for a diverse set of participants, including high school students, community college students, undergraduate and graduate students, and citizen scientists. The objectives of this project are to 1) characterize the spatial patterns of focused groundwater discharge at the river network scale, 2) quantify patterns and drivers of legacy N transport through and removal within stream interface (streambed and streambank) sediments, 3) scale legacy N cycling to the river channel network. The focal watershed for this project is the Farmington River watershed which drains to the Connecticut River and the Long Island Sound. The Long Island Sound experiences seasonal dead zones caused by excess N pollution. This project includes expansive thermal infrared (TIR) surveys with handheld cameras and unmanned aerial systems (drones) across approximately 95 kilometers of stream and river length to measure the spatial distribution of groundwater discharge to the river network. TIR technology allows the geolocation of preferential discharge zones more comparable to coarser model grid sizes used in regional groundwater modeling. Thus, this project also evaluates and refines spatial predictions from numerical groundwater (MODFLOW) models against metrics (e.g., frequency of seeps, spatial extent of seeps) derived from TIR survey datasets. The project utilizes both field and modeled estimates of the spatial patterns of groundwater discharge and basin-scale transport time lags to characterize and ultimately predict the role of stream interface sediments in N cycling. At discharge locations identified during TIR surveys, denitrification rates, N concentrations and fluxes, groundwater age, and a suite of sediment physical and chemical properties will be measured. These datasets will be used develop spatial predictions of legacy N loading to and processing within stream interface sediments. Spatial predictions of groundwater discharge and N fluxes will be used as additional inputs to a river network model implemented for the Farmington River network to quantify legacy N cycling as it is transported from seepage locations through the river channel network.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.