Modelling the role of SuDS management trains to minimise the flood risk of new-build housing developments in the UK

  • Craig Lashford

Student thesis: Doctoral ThesisDoctor of Philosophy


In a changing climate with an increasing risk of flooding, developing a sustainable approach to flood management is paramount. Sustainable Drainage Systems (SuDS) present a change in thinking with regards to drainage; storing water in the urban environment as opposed to rapidly removing it to outflows. The Non-Statutory Standards for SuDS (DEFRA 2015a) presented a requirement for all developments to integrate SuDS in their design to reduce runoff. This research models the impact on water quantity of combining different SuDS devices to demonstrate their success as a flood management system, as compared to conventional pipe based drainage. The research uses MicroDrainage®, the UK industry standard flood modelling tool which has an integrated SuDS function, to simulate the role of SuDS in a management train. As space is often cited as the primary reason for rejecting SuDS, determining the most effective technique at reducing runoff is critical. Detention basins were concluded as being highly effective at reducing peak flow (150 l/s when combined with swales), however Porous Pavement Systems (PPS) was nearly twice as effective per m3, reducing peak flow by up to 0.075 l/s/m3 compared to 0.025 l/s/m3. This therefore suggests that both detention basins and PPS should be high priority devices when developing new sites, but that no matter what combination of modelled SuDS are installed a reduction in runoff in comparison to conventional drainage can be achieved. A SuDS decision support tool was developed to assist design in MicroDrainage® by reducing the time spent determining the number of SuDS required for a site. The tool uses outputs from MicroDrainage® to rapidly predict the minimum and maximum peak flow for a site, in comparison to greenfield runoff, based on the site parameters of area, rainfall rate, infiltration, combined with the planned SuDS. The tool was underpinned by a model analysis for each site parameter and each SuDS device, which produced r2 values >0.8, with 70% above 0.9. This ensured a high level of confidence in the outputs, enabling a regression analysis between runoff and each site parameter and SuDS device at the 99% confidence level, with the outputs combined to create the tool. The final aspect of the research validated MicroDrainage® to analyse the accuracy of the software at predicting runoff. Using field data from Hamilton, Leicester, and laboratory data for PPS and filter drains, a comparison could be made with the output from MicroDrainage®. The field data created a Nash-Sutcliffe Efficiency (NSE) of 0.88, with filter drains and PPS providing an NSE of 0.98 and 0.94 respectively. This demonstrates the success with which MicroDrainage® predicts runoff and provides credibility to the outputs of the research. Furthermore, it offers SuDS specialists the confidence to use MicroDrainage® to predict runoff when using SuDS.
Date of Award2016
Original languageEnglish
Awarding Institution
  • Coventry University
SponsorsCoventry University
SupervisorSM Charlesworth (Supervisor), Frank Warwick (Supervisor) & Matthew Blackett (Supervisor)


  • SuDS
  • flood management
  • MicroDrainage®
  • management train
  • decision-support tool

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