Project
Overview
Stormwater run-off typically contains and transports a wide range of pollutants, resulting in negative environmental effects with potential threats to ecosystems and health.
Hundreds of run-off treatment ponds intended to moderate these impacts are likely to be delivering sub-optimal (and perhaps below legally required) levels of improvement in water quality. This is due to poor understanding of flow patterns and the effects of vegetation.
This project aimed to generate a unique dataset to describe the influence of different types and configurations of vegetation on the pond's fundamental flow (and treatment) characteristics.
The project also aimed to deliver a validated set of vegetative resistance and mixing parameters, which are essential if 3D computational modelling tools are to be used with confidence.
Based on the laboratory and field work undertaken, a 3D modelling approach was developed that can be used to help ensure that stormwater ponds meet all their water quality and ecosystem services objectives for current and future legislation.
Background
Stormwater ponds take run-off from urban areas, highways and agricultural land, providing detention and attenuation of peak storm discharges and improving water quality.
Stormwater ponds are able to provide protection to downstream drainage components and receiving waters. They achieve this by holding or treating run-off at or near the source. They also provide nature conservation and amenity benefits.
Within the Highways Agency Drainage Data Management System, there are currently over 800 stormwater ponds. Pond performance (pollutant treatment efficiency) is directly related to hydraulic residence time, a function of the internal flow field. In turn, this is controlled by the pond geometry, and the distribution and type of vegetation present.
The prediction of water quality improvements within drainage features is gaining importance with stormwater professionals. However, performance prediction is complex since water quality processes are functions of the pond hydraulic residence time.
Current evaluations employ the nominal residence time, which assumes plug flow through the pond as the design consideration. It is accepted that the nominal residence time (pond volume/discharge) provides a poor estimate of the actual mean (or median) residence time. Overestimates of treatment times of 100% or more are being uncommon. However, it is still in use, even 'the norm'.
In wastewater treatment wetlands, treatment is good since a high degree of engineering is adopted in creating an efficient, often linear, shape with uniform, dense, vegetation. In contrast, stormwater ponds must fit into existing water courses or urban environments. Together with the additional requirements for biodiversity and ecological function, this leads to pond layouts that may be less than ideal from a hydraulic perspective.
Vegetation can have either a positive or negative role in water quality treatment within stormwater ponds. It provides the appropriate environment for the support of biofilms and the colonisation by algae, enhancing treatment. Yet, variable spatial distribution influences the spread of the hydraulic residence time.
This project sought to better understand and quantify the physical, vegetation-driven, flow mechanisms occurring within a stormwater pond. It aimed to develop a robust physically based modelling tool.
The research proposed aimed to deliver improved understanding of the effects of vegetation (type: emergent, floating and submerged; physical characteristics: porosity and spatial distribution) on flow patterns and residence time distributions (RTDs) within stormwater ponds.
The validated computational modelling approach would permit the assessment of short circuiting, a measure of poor performance, and provide estimates for vegetation contact times, sediment deposition regions and rates. This would provide a tool for predicting the treatment efficiency of vegetated stormwater ponds.
Objectives
The aim of the project was to derive an understanding of how the hydraulic residence time distribution (RTD) within a stormwater pond is affected by the type and spatial distribution of vegetation. Another aim was to identify appropriate modelling tools for the representation of the water quality performance.
Specific objectives:
To collect comprehensive new laboratory data on the bulk porosity and flow resistance of different pond vegetation types (emergent, floating, and submerged) as a function of seasonal growth cycles over a range of typical pond flow velocities.
To conduct laboratory solute tracer studies to quantify the mixing (transverse, longitudinal, and RTD) within, and the exchange coefficient between, clear and vegetated flow zones.
To utilise the laboratory data to validate computational fluid dynamics (CFD) modelling procedures and quantify parameters appropriate for describing the influence of vegetation on velocities and mixing.
To perform field measurement of RTDs in mature vegetated ponds over seasonal growth cycles to validate the 3D CFD methodology.
To conduct scenario modelling to explore the sensitivity of RTDs to vegetation mosaics, discharge and pond shape.
To facilitate the dissemination of the validated modelling methodology, together with appropriate parameter values for the flow resistance and mixing processes.
Grant
Professor Ian Guymer and Dr Virginia Stovin were successfully awarded EPSRC grants EP/K025589/1 and EP/K024442/1 to complete this research. These grants started on 1 September 2013 and were completed on 31 August 2016.
Partial follow on funding was provided by the EPSRC via the Warwick Impact Acceleration Account (IAA EP/K503848/1) and the Highways Agency until 31 July 2018. Upon successful completion, this project has now fully closed down.