Value of AwardValue of Award
UK citizens are eligible for 100% of UK tuition fees paid and annual living expenses of £14,553 (full award).
EU citizens from outside the UK are eligible for fees only (partial award).
Start Date and DurationStart Date and Duration
Project Start Date: September 2017
The funding covers a three-year PhD
Application Closing DateApplication Closing Date
27 April 2017
Flooding, from its multiple sources, is an important societal challenge for the UK given the range of direct (e.g. loss of life, damage to critical infrastructure) and indirect (e.g. loss of business, disruption of services, health issues) impacts. The Cabinet Office’s National Risk Register  identifies flooding as one of the four key risks to the UK and the Climate Change Risk Assessment  highlighted flooding as the top climate risk to the UK. Together with projected climate change and demographic and related development challenges, flood risk will remain.
Detailed, high resolution, cross-sections to characterise river profiles, along with details of in-channel sediment and riparian vegetation, is critical for improving 2D hydrodynamic models to accurately model flood events and adaptations required to ensure management and resilience against extreme events. In addition, such data enables typology of river physical habitat, including habitat quality, identifying pool-riffle sequences, backwaters, gravel bars, etc., which provides the foundation for habitat classification, and underpins river restoration initiatives.
Traditionally, this information is derived via conventional aerial photography, direct measurement of river cross-sections, and walk-over surveys. However, geospatial information is of increasing relevance, and offers an effective, non-contact means of deriving variables at high spatial resolution. In the context of hydromorphological characterisation, photogrammetric computer vision approaches and new lidar (light detecting and ranging) technologies offer potential for significantly enhancing efficiency and provision of relevant information relating to physical processes.
Typically fluvial and pluvial flood risk studies are carried out separately for two reasons: a) There is insufficient detail in currently available lidar data to independently characterise river profiles and therefore used only to setup hydrodynamic models for pluvial flooding; b) limitations of the hydrodynamic models themselves. However, meaningful urban flood risk assessments require models which can handle both fluvial and pluvial risks and this can be achieved through the proposed approach of this PhD.
Unmanned aerial vehicle (UAV) platforms, coupled with algorithmic developments, are of particular relevance, offering the potential to provide a flexible and low-cost approach for reach-scale characterisation. UAV surveys have been implemented for a range of applications, most commonly utilising compact digital cameras to generate digital elevation models (DEMs) and ortho-imagery for mapping purposes. The potential of UAV imagery for measurement of channel bathymetry (depth) has also been demonstrated , making this technique especially attractive for fluvial applications. However, intelligent processing of such imagery is relatively immature, and challenges exist in terms of defining optimised data collection strategies and implementing efficient big data analytics approaches to processing.
Furthermore, recent advances in bathymetric lidar for mapping riverbed topography has been demonstrated in river reaches in Austria . The latest bathymetric lidar systems have been optimised for measurement under very shallow-water conditions, and provide high pulse repetition rate and relatively smaller footprint size which in combination allow for greater spatial resolution and capture of finer features.
These emerging instruments offer the potential to deliver a genuine step-change in the comprehensive mapping of fluvial topography in both aquatic and riparian zones, thereby providing detailed characterisation of river reaches required for 2D hydrodynamic models. The approach will be tested on a bathymetric lidar dataset acquired through funding from SEPA/Scottish Government – a unique dataset to the UK.
Aim and Objectives
This project aims to fully exploit the potential of combining data from UAVs for characterisation at the reach scale and bathymetric lidar for river cross-sections. This will be achieved through the following objectives:
- assemble multi-source datasets of channel and floodplain topography for characteristic environments;
- develop novel big data approaches to optimise information extraction from acquired datasets;
- combine, automatically, the multi-source datasets into a format suitable for the hydrodynamic model, CityCat ;
- validate the approach by instrumenting the river reaches where data is available to provide evidence of the improved models.
Proposed programme of work
WP1: literature critique related to: flood modelling and limits of current approaches, as well as future challenges and wider applications of the approach; review of computer vision approaches for feature extraction, image classification, with emphasis on 2D and 3D integration from UAV images; extraction and interpretation of bathymetric lidar data. WP1 will also involve hardware and software familiarisation, including training in UAVs and an opportunity to attend relevant MSc modules at Newcastle University and training opportunities at JHI.
WP2: data for the selected river reaches will be collected via a range of techniques: UAV, surveys, aerial photography to complement the bathymetric lidar data. Subsequently, there will be a focus on development of novel, semi-automated algorithms for classification of important channel features from UAV and bathymetric lidar data. This will support extraction of channel morphology, bathymetric depth, classification of gravel bars, riparian vegetation, woody debris, etc. Computer vision approaches, integrating spatial, spectral and temporal information will be developed, and object-based classification methods explored. River flow and depth gauges will be installed at the reaches.
WP3: will focus on combining the various datasets collected in WP2, in an automated way, so that they are in a suitable format to provide input data to the hydrodynamic model, CityCat.
WP4: run various simulations of CityCat with the improved data to demonstrate how modelling can be improved and simultaneously consider both fluvial and pluvial sources. The model will then be validated with the observational data collected from instruments installed in WP2. At this stage, outcomes will be derived relating to the wider relevancy of the approach, implications for stakeholders and suitability in support of flood management applications.
Training & Skills
The proposed PhD contains a number of highly practical elements, which will allow the student to develop skills in UAV operation and data collection, field survey, and hydrodynamic modelling. There will be opportunity for the student to attend and present their work at national and international conferences, as well as undertake a secondment at the James Hutton Institute.
 Cabinet Office (2012). National Risk Register for Civil Emergencies - January 2012 edition, Cabinet Office, London.
 Tamminga, A. et al., 2015. Hyperspatial remote sensing of channel reach morphology and hydraulic fish habitat using an unmanned aerial vehicle (UAV): a first assessment in the context of river research and management. River Res. Appl., 31(2015): 379-391;
 Mandlburger, G., Hauer, C., Wieser, M. and Pfeifer, N., 2015. Topo-bathymetric LiDAR for monitoring river morphodynamics and instream habitats—a case study at the Pielach River. Remote Sensing, 7(5): 6160–6195.
 Glenis, V., McGough, A.S., Kutija, V., Kilsby, C.G. & Woodman, S. ‘Flood Modelling for Cities using Cloud Computing’, Journal of Cloud Computing, Volume 2, Issue 7
Eligibility CriteriaEligibility Criteria
You must have, or expect to achieve, at least a 2:1 honours degree or international equivalent, in Civil Engineering, Geomatics, Mathematics.
The award is available to UK/EU applicants only. Depending on how you meet the EPSRC’s eligibility criteria, you may be entitled to a full or a partial award.
How to ApplyHow to Apply
You must apply through the University’s online postgraduate application system. To do this please ‘Create a new account’.
All relevant fields should be completed, but fields marked with a red asterisk must be completed. The following information will help us to process your application. You will need to:
- insert the programme code 8040F in the programme of study section
- select ‘PhD Civil Engineering and Geosciences (Water)’ as the programme of study
- insert the studentship code CI-799 in the studentship/partnership reference field
- attach a covering letter and CV. The covering letter must state the title of the studentship, quote reference code C799 and state how your interests and experience relate to the project
- attach degree transcripts and certificates and, if English is not your first language, a copy of your English language qualifications
You should also send your covering letter and CV to Dr Claire Walsh by email to firstname.lastname@example.org.