PhD: Exploring effective strategies of communicating flood forecasting using a CHANS modelling framework via FindAPhD

Loughborough University

Loughborough, UK 🇬🇧

About the Project

Rationale

Surface water flooding – also referred to as pluvial flooding – is caused by intense, highly localised convective rainfall creating excessive runoff that cannot drain away quickly enough.

According to a recent Defra report [1], it is the UK’s most widespread form of flooding, with 3.2m properties at risk in England alone. Recent events, e.g., the July 2021 floods in London, demonstrate inadequate preparedness for such events [2]. Several recent UK government reports highlight an urgent need for surface water flood risk mitigation and management so owners of at-risk homes and businesses can better protect their property (e.g., [1]).

Under the National Surface Water Management Action Plan [1], the Environment Agency (EA), Met Office and Flood Forecasting Centreare committed to exploring improved surface water flood forecasting. The challenge of effective communication of forecasts and warnings was further emphasised at the symposium, and users specifically pointed out flood forecasting and warning is ‘30% technology and 70% communication’. This project will deliver inter-disciplinary research to address this important challenge.

Methodology

The aim is to apply a newly developed Coupled Human And Natural Systems (CHANS) model [3] to simulate and understand the interactive human behaviours and social dynamics before and during a surface water flood event induced by intense rainfall. This will be related to different scenarios of flood forecasting and warning provision.

Subsequently, we will design and carry out systematic numerical experiments to explore effective strategies of communicating flood forecasting and warning. The adopted CHANS modelling framework consists of a distributed agent-based model (ABM) to represent the human systems and a hydrodynamic model (the High-Performance Integrated hydrodynamic Modelling System (HiPIMS)) to predict the flooding dynamics in a natural system. The CHANS model is implemented on high-performance multiple graphics processing units to support large-scale high-resolution simulations. In the ABM, agents can be flexibly defined and used to represent individuals, households and related organisations to depict the interactive social dynamics interrupted by flooding or other driving factors. Data from different sources, e.g. UK national census, social media, literature, will be processed to understand and describe human and organisational behaviours.

Participatory Action Research methodologies will be deployed to unlock a deeper understanding of different groups and types of agents and their interactions in order to construct the coupled human and natural system in the case study site (jointly decided with the partners). Scenarios will be co-developed and simulated to understand the human response to flood forecasting and warnings and explore effective communication strategies that maximize their impact on flood forecasting and warning effectiveness.

This project is part of the NERC funded Flood-CDT studentship competition. For more information, please visit the Flood-CDT website.

Background Reading

  • Defra (2021) Surface water management: a government update.
  • GLA (2022) Surface Water Flooding in London. Roundtable progress report.
  • Qin H, Liang Q, Chen H, De Silva V (2024) A high-performance Coupled Human And Natural Systems (CHANS) model for flood risk assessment and reduction. Water Resources Research, revision under review

94% of Loughborough’s research impact is rated world-leading or internationally excellent. REF 2021

Supervisors

  • Primary supervisor: Qiuhua Liang
  • Secondary supervisors: Huili Chen

Entry requirements

FLOOD-CDT is multidisciplinary, and we welcome applicants from diverse disciplines, including but not limited to: physical scientists, engineers, mathematicians, life and social scientists. Students should have an interest in multidisciplinary research, as well as other skills relevant to one or more of the core Research and Training themes within the CDT.

Applicants must already have, or expect to shortly graduate with, a very good undergraduate degree or Master’s degree (at least a UK 2:1 honours degree) – or an equivalent international qualification from a high ranking university – in a relevant subject.

Academic attainment is only one of our criteria for selection; we equally value the ability to work in teams, excitement for research, enthusiasm for the research focus of the CDT and the ability to communicate ideas. 

English language requirements

Applicants must meet the minimum English language requirements. Further details are available on the International website.

How to apply

All applications should be made online. Under the programme name, select Architecture, Building and Civil Engineering. Please quote reference FCDT-24-LU5a application. Failure to include this reference will result in the application not being considered for this studentship competition.

To avoid delays in processing your application, please ensure that you submit the minimum supporting documents:

  • an academic transcript of your undergraduate degree showing the modules studied and marks achieved
  • a copy of your degree certificate, if you have already graduated
  • a copy of your CV
  • a personal statement – this should explain your motivation for studying the programme, any relevant skills and experience you have (through studying or work) for this particular project, and your future career aspirations and how this programme will support you in achieving this. Remember to let your passion for the subject shine through!
  • names of two academic referees

For more information about what documents to submit, please visit our how to start a research application webpage.

Applications close on 7 July (midnight), with interview dates to be confirmed. We will use these selection criteria to make a decision on your application.

Funding Notes

Studentship type – UKRI through Flood-CDT.

The studentship is for 3.5 years and provides a tax-free stipend of £19,237 per annum plus tuition fees at the UK rate. 


POSITION TYPE

ORGANIZATION TYPE

EXPERIENCE-LEVEL

DEGREE REQUIRED

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