Intensive agriculture in the Midwestern United States contributes to excess nitrogen in surface water and groundwater, negatively affecting human health and aquatic ecosystems. Complete denitrification removes reactive nitrogen from aquatic environments and releases inert dinitrogen gas. We examined denitrification rates and the abundances of denitrifying genes and total bacteria at three sites in an agricultural watershed and in an experimental stream in Minnesota. Sampling was conducted along transects with a gradient from always inundated (in‐channel), to periodically inundated, to noninundated conditions to determine how denitrification rates and gene abundances varied from channels to riparian areas with different inundation histories. Results indicate a coupling between environmental parameters, gene abundances, and denitrification rates at the in‐channel locations, and limited to no coupling at the periodically inundated and noninundated locations, respectively. Nutrient‐amended potential denitrification rates for the in‐channel locations were significantly correlated (α = 0.05) with five of six measured denitrifying gene abundances, whereas the periodically inundated and noninundated locations were each only significantly correlated with the abundance of one denitrifying gene. These results suggest that DNA‐based analysis of denitrifying gene abundances alone cannot predict functional responses (denitrification potential), especially in studies with varying hydrologic regimes. A scaling analysis was performed to develop a predictive functional relationship relating environmental parameters to denitrification rates for in‐channel locations. This method could be applied to other geographic and climatic regions to predict the occurrence of denitrification hot spots.

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The evolution and migration of large dunes in a realistic intermediate-size experimental stream, the Saint Anthony Falls Laboratory (SAFL) Outdoor StreamLab (OSL), and two large-scale meandering rivers with in-stream rock structures are studied numerically using the SAFL Virtual StreamLab hydro-morphodynamic (VSL3D) model. Due to the challenges arising from mesh quality and large disparity in timescales , coupled morphoand hydro-dynamics simulations of bed forms has, for the most part, been restricted to sand wave amplitudes of few centimeters. In this work, we overcome such difficulties by employing the immersed boundary approach and a dual time-stepping technique of the VSL3D model [63]. The VSL3D employs the curvilinear immersed boundary (CURVIB) method along with a suspended sediment load module and is capable of simulating turbulent stratified flows coupled with bed morphodynamic evolution in realistic riverine environments with arbitrarily complex hydraulic structures. Turbulence is handled either via large-eddy simulation (LES) with the dynamic Smagorinski subgrid scale model or unsteady Reynolds-averaged Navier Stokes (URANS) equations closed with the k − ω turbulence model. Simulations in the intermediate-scale OSL channel, in which we also collected experimental morphodynamic data, show that LES can capture the evolution and migration of bed forms with characteristics that are in good agreement with experimental measurements. The URANS model, however, fails to excite the bed instability in the OSL channel but captures realistic dune evolution in the two large-scale meandering rivers. This finding is especially important as it demonstrates the potential of the VSL3D model as a powerful tool for simulating morphodynamic evolution under prototype conditions. To our knowledge, our work is the first attempt to simulate large-scale bed forms in waterways with an order of magnitude disparity in spatial scales, from the ∼ 2.7m wide OSL channel to the 27m wide rivers. Accordingly, the height of the simulated dunes ranges from ∼ 0.2m to 2.0m and the wavelength ranges from ∼ 0.1m to 50m for the OSL and large-scale rivers, respectively. For all cases the statistical properties of the simulated bed forms are shown to agree well with those of bed forms observed in nature.