Rationale
Flooding stands as the most prevalent natural hazard. However, whilst substantial research effort has been reported in the last decade to develop high-performance physics-based models for more accurate prediction of different types of flooding processes, these latest flood modelling technologies have not yet been fully leveraged to support practical flood risk management.
This shortfall is attributed to the demanding computational requirements and the need for high-level expertise in specialized knowledge and programming skills. Simultaneously, effective flood risk management demands a spatially explicit assessment to pinpoint flooding exposure and risk at an object-based scale. However, conducting object-based evaluation requires comprehensive data support. Data is often dispersed across different organizations, stored in various formats, or challenging to obtain, particularly in developing countries.
Therefore, we aim to develop a user-friendly web-based platform that integrates Loughborough's in-house High-Performance Integrated hydrodynamic Modelling System (HiPIMS) [2], with various high-quality open-source datasets covering exposure and vulnerability to buildings, infrastructure, and people.
Consequently, the platform not only functions as a web service for high-performance flood simulations but also serves as a data and analytics portal, providing a comprehensive, one-stop solution for flood risk assessment to support practical flood risk management in both data-rich and scarce environments.
Methodology
This exciting PhD project aims to harness the latest developments in high-performance numerical models and data analytics technologies to address some of the key practical challenges in flood modelling and risk management, and finally achieve a web-based platform for large-scale rapid flood risk assessment to improve current practice. The project will deliver the following key research tasks:
- Develop a user-friendly graphical interface (GUI) based on the JavaScript library ReactJs, in which the HiPIMS can be completely set up, run, and analysed in a standard web browser. HiPIMS computations can be executed on local GPUs or through cloud-based GPU services, empowering users to conduct large-scale fast flood simulations without worrying about computational resources.
- Collect a variety of spatial datasets related to exposure and vulnerability and present them in a standardized format in the platform, enabling users to access and analyse the datasets easily and effectively.
- Streamline the object-based flood risk evaluation by seamlessly integrating HiPIMS hazard results with exposure and vulnerability datasets to assess flood impact and risk on individual buildings and objects.
Demonstrate the platform for practical flood risk assessment in a selected case study site.
This project is part of the NERC funded Flood-CDT studentship competition. For more information, please visit the Flood-CDT website .
Please see this PhD project’s dedicated webpage for more information via the above ‘Apply’ button.
Additional Funding Information
Studentship type – UKRI through Flood-CDT (flood-cdt.ac.uk). The studentship is for 3.5 years and provides a tax-free stipend of £18,622 per annum plus tuition fees at the UK rate. Excellent International candidates are eligible for a full international fee waiver however due to UKRI funding rules, no more than 30% of the studentships funded by this grant can be awarded to International candidates.
For details on what documents you will be required to submit for this, please see the dedicated project page, available via the Apply button.