In nature-based treatment systems, such as constructed wetlands, plant uptake of nutrients can be a significant removal pathway. Current methods for quantifying plant uptake of nitrogen in constructed wetlands, which often involve harvesting biomass and assuming that all nitrogen stored in plants was derived from wastewater, are inappropriate in pilot- and full-scale systems where other sources of nitrogen are available. To improve our understanding of nitrogen cycling in constructed wetlands, we developed a new method to quantify plant uptake of nitrogen by using stable isotopes and a mixing model to distinguish between nitrogen sources. We applied this new method to a pilot-scale horizontal levee system (i.e., a subsurface constructed wetland) over a two-year monitoring period, during which 14% of nitrogen in plants was wastewater-derived on average and the remaining plant nitrogen was obtained from the soil. Analysis of nitrogen isotopes indicated substantial spatial variability in the wetland: 82% of nitrogen in plants within the first 2 m of the slope came from wastewater while less than 12% of plant nitrogen in the remainder of the wetland originated from wastewater. By combining these source contributions with remote-sensing derived total biomass measurements, we calculated that 150 kg N (95% CI = 50 kg N, 330 kg N) was taken up and retained by plants during the two-year monitoring period, which corresponded to approximately 8% of nitrogen removed in the wetland. Nitrogen uptake followed seasonal trends, increased as plants matured, and varied based on design parameters (e.g., plant types), suggesting that design decisions can impact this removal pathway. This new method can help inform efforts to understand nitrogen cycling and optimize the design of nature-based nutrient control systems.

The interleaving of impermeable and permeable surfaces along a runoff flow path controls the hillslope hydrograph, the spatial pattern of infiltration, and the distribution of flow velocities in landscapes dominated by overland flow. Predictions of the relationship between the pattern of (im)permeable surfaces and hydrological outcomes tend to fall into two categories: (i) generalized metrics of landscape pattern, often referred to as connectivity metrics, and (ii) direct simulation of specific hillslopes. Unfortunately, the success of using connectivity metrics for prediction is mixed, while direct simulation approaches are computationally expensive and hard to generalize. Here we present a new approach for prediction based on emulation of a coupled Saint Venant equation‐Richards equation model with random forest regression. The emulation model predicts infiltration and peak flow velocities for every location on a hillslope with an arbitrary spatial pattern of impermeable and permeable surfaces but fixed soil, slope, and storm properties. It provides excellent fidelity to the physically based model predictions and is generalizable to novel spatial patterns. The spatial pattern features that explain most of the hydrological variability are not stable across different soils, slopes, and storms, potentially explaining some of the difficulties associated with direct use of spatial metrics for predicting landscape function. Although the current emulator relies on strong assumptions, including smooth topography, binary permeability fields, and only a small collection of soils, slope, and storm scenarios, it offers a promising way forward for applications in dryland and urban settings and in supporting the development of potential connectivity indices.

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