Understanding solute mixing within real vegetation is critical to predicting and evaluating the performance of engineered natural systems such as storm water ponds. For the first time, mixing has been quantified through simultaneous laboratory measurements of transverse and longitudinal dispersion within artificial and real emergent vegetation. Dispersion coefficients derived from a routing solution to the 2‐D Advection Dispersion Equation (ADE) are presented that compare the effects of vegetation type (artificial, Typha latifolia or Carex acutiformis) and growth season (winter or summer). The new experimental dispersion coefficients are plotted with the experimental values from other studies and used to review existing mixing models for emergent vegetation. The existing mixing models fail to predict the observed mixing within natural vegetation, particularly for transverse dispersion, reflecting the complexity of processes associated with the heterogeneous nature of real vegetation. Observed stem diameter distributions are utilized to highlight the sensitivity of existing models to this key length‐scale descriptor, leading to a recommendation that future models intended for application to real vegetation should be based on probabilistic descriptions of both stem diameters and stem spacings.

Flow resistance due to vegetation is of interest for a wide variety of hydraulic engineering applications. This note evaluates several practical engineering functions for estimating bulk drag coefficient (C D) for arrays of rigid cylinders, which are commonly used to represent emergent vegetation. Many of the evaluated functions are based on an Ergun-derived expression that relates C D to two coefficients, describing viscous and inertial effects. A re-parametrization of the Ergun coefficients based on cylinder diameter (d) and solid volume fraction (φ) is presented. Estimates of C D are compared to a range of experimental data from previous studies. All functions reasonably estimate C D at low φ and high cylinder Reynolds numbers (R d). At higher φ they typically underestimate C D. Estimates of C D utilizing the re-parametrization presented here match the experimental data better than estimates of C D made using the other functions evaluated, particularly at low φ and low R d .

Green roofs have been adopted in urban drainage systems to control the total quantity and volumetric ow rate of runo . Modern green roof designs are multi-layered, their main components being vegetation, substrate and, in almost all cases, a separate drainage layer. Most current hydrological models of green roofs combine the modelling of the separate layers into a single process; these models have limited predictive capability for roofs not sharing the same design. An adaptable, generic, two-stage model for a system consisting of a granular substrate over a hard plastic "egg box"-style drainage layer and brous protection mat is presented. The substrate and drainage layer/protection mat are modelled separately by previously veri ed sub-models. Controlled storm events are applied to a green roof system in a rainfall simulator. The time-series modelled runo is compared to the monitored runo for each storm event. The modelled runo pro les are accurate (mean R t 2 = 0.971), but further characterization of the substrate component is required for the model to be generically applicable to other roof con gurations with di erent substrate.

Predicting how pollutants disperse in vegetation is necessary to protect natural watercourses. This can be done using the one-dimensional advection dispersion equation, which requires estimates of longitudinal dispersion coefficients in vegetation. Dye tracing was used to obtain longitudinal dispersion coefficients in emergent artificial vegetation of different densities and stem diameters. Based on these results, a simple non-dimensional model, depending on velocity and stem spacing, was developed to predict the longitudinal dispersion coefficient in uniform emergent vegetation at low densities (solid volume fractions < 0.1). Predictions of the longitudinal dispersion coefficient from this simple model were compared with predictions from a more complex expression for a range of experimental data, including real vegetation. The simple model was found to predict correct order of magnitude dispersion coefficients and to perform as well as the more complex expression. The simple model requires fewer parameters and provides a robust engineering approximation.

2 3Experimental data characterising dispersion within Typha latifolia were previously collected in a laboratory setting. This mixing characterisation was combined with previously proposed computational fluid dynamics modelling approaches to predict residence time distributions for vegetated stormwater treatment pond layouts (including a wetland) derived from Highways England design guidance. The results showed that the presence of vegetation resulted in residence times closer to plug flow, indicating significant improvements in stormwater treatment capability. The new modelling approach reflects changes in residence time due to mixing within the vegetation, but it also suggests that it is more important to include vegetation within the model in the correct location than it is to accurately characterise it.Estimates of hydraulic efficiency suggest that fully vegetated stormwater ponds such as wetlands should function well as a treatment device, but more typical ponds with clear water need to be designed to be between 50% and 100% larger than their nominal residence times would suggest when designed against treatment criteria.