Sewer Overflow Flood Risk Analysis MOdel Dafni Enabled (SOFRAMODE)
Lead Research Organisation:
Newcastle University
Department Name: Sch of Engineering
Abstract
The overall aim of this proposal is to develop and demonstrate a state-of-the-art platform on DAFNI for understanding and simulating urban drainage related to surface water flooding and high-profile storm overflow events, for any UK town or city. Scenarios will encompass a wide range of current and future rainfall event magnitudes, and provide functionality for consultants and industry, as well as researchers, to design and test a range of strategies to mitigate Storm Overflow spills and surface water flooding. The platform will be underpinned by the CityCat model.
Through a series of consultations, and co-creation and co-development workshops, we will make the model more widely available and useful to non-academic and non-expert users through addressing the following objectives:
1. Extend functionality of the existing workflow on DAFNI to allow users to assess the effectiveness of blue-green mitigation features.
2. Optimise BGI (Blue Green Infrastructure) design using a Genetic Algorithm (GA) tool to optimise the location of BGI to allow more users, including communities and local authorities, to rapidly assess flood and Storm Overflow risk and test a range of affordable management portfolios under different scenarios.
3. Develop a tool to better visualise and use the (surface and pipe) drainage network for model set up and analysis of results, to use in community and stakeholder engagement as well as design and risk assessment.
4. Resilience scenarios framework: develop a methodology to flexibly explore a wide range of rainfall events and design constraints.
Through a series of consultations, and co-creation and co-development workshops, we will make the model more widely available and useful to non-academic and non-expert users through addressing the following objectives:
1. Extend functionality of the existing workflow on DAFNI to allow users to assess the effectiveness of blue-green mitigation features.
2. Optimise BGI (Blue Green Infrastructure) design using a Genetic Algorithm (GA) tool to optimise the location of BGI to allow more users, including communities and local authorities, to rapidly assess flood and Storm Overflow risk and test a range of affordable management portfolios under different scenarios.
3. Develop a tool to better visualise and use the (surface and pipe) drainage network for model set up and analysis of results, to use in community and stakeholder engagement as well as design and risk assessment.
4. Resilience scenarios framework: develop a methodology to flexibly explore a wide range of rainfall events and design constraints.
