Supervisors: Huili Chen (LU), Qiuhua Liang (LU), Russell Green (Arcadis)
Contact email: h.chen2@lboro.ac.uk
Location: Loughborough
Project Rational: 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.
Background Reading:
[1] Chen, H., Zhao, J., Liang, Q., Maharjan, S. B., & Joshi, S. P. (2022). Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data. Science of The Total Environment, 806, 151289.
[2] Xia, X., Liang, Q., & Ming, X. (2019). A full-scale fluvial flood modelling framework based on a high-performance integrated hydrodynamic modelling system (HiPIMS). Advances in Water Resources, 132, 103392.
FLOOD-CDT
This PhD is being advertised as part of the Centre for Doctoral Training for Resilient Flood Futures (FLOOD-CDT). Further details about FLOOD-CDT can be seen here https://flood-cdt.ac.uk. Please note, that your application will be assessed upon: (1) Motivation and Career Aspirations; (2) Potential & Intellectual Excellence; (3) Suitability for specific project and (4) Fit to FLOOD-CDT. So please familiarise yourselves with FLOOD-CDT before applying. During the application process candidates will need to upload:
• a 1 page statement of your research interests in flooding and FLOOD-CDT and your rationale for your choice of project;
• a curriculum vitae giving details of your academic record and stating your research interests;
• name two current academic referees together with an institutional email addresses; on submission of your online application your referees will be automatically emailed requesting they send a reference to us directly by email;
• academic transcripts and degree certificates (translated if not in English) - if you have completed both a BSc & an MSc, we require both; and
• a IELTS/TOEFL certificate, if applicable.
Please upload all documents in PDF format. You are encouraged to contact potential supervisors by email to discuss project-specific aspects of the proposed prior to submitting your application. If you have any general questions please contact floodcdt@soton.ac.uk.
Apply
To apply for this project, please apply through the Loughborough University application portal (available on this link https://www.lboro.ac.uk/study/postgraduate/research-degrees/phd-opportun...) and quote reference number FCDT-25-LU8
