Flooding is the deadliest and most costly natural hazard on the planet, affecting societies across the globe. Nearly one billion people are exposed to the risk of flooding in their lifetimes and around 300 million are impacted by floods in any given year. The impacts on individuals and societies are extreme: each year there are over 6,000 fatalities and economic losses exceed US$60 billion. These problems will become much worse in the future. There is now clear consensus that climate change will, in many parts of the globe, cause substantial increases in the frequency of occurrence of extreme rainfall events, which in turn will generate increases in peak flood flows and therefore flood vast areas of land. Meanwhile, societal exposure to this hazard is compounded still further as a result of population growth and encroachment of people and key infrastructure onto floodplains. Faced with this pressing challenge, reliable tools are required to predict how flood hazard and exposure will change in the future. Existing state-of-the-art Global Flood Models (GFMs) are used to simulate the probability of flooding across the Earth, but unfortunately they are highly constrained by two fundamental limitations. First, current GFMs represent the topography and roughness of river channels and floodplains in highly simplified ways, and their relatively low resolution inadequately represents the natural connectivity between channels and floodplains. This restricts severely their ability to predict flood inundation extent and frequency, how it varies in space, and how it depends on flood magnitude. The second limitation is that current GFMs treat rivers and their floodplains essentially as 'static pipes' that remain unchanged over time. In reality, river channels evolve through processes of erosion and sedimentation, driven by the impacts of diverse environmental changes (e.g., climate and land use change, dam construction), and leading to changes in channel flow conveyance capacity and floodplain connectivity. Until GFMs are able to account for these changes they will remain fundamentally unsuitable for predicting the evolution of future flood hazard, understanding its underlying causes, or quantifying associated uncertainties. To address these issues we will develop an entirely new generation of Global Flood Models by: (i) using Big Data sets and novel methods to enhance substantially their representation of channel and floodplain morphology and roughness, thereby making GFMs more morphologically aware; (ii) including new approaches to representing the evolution of channel morphology and channel-floodplain connectivity; and (iii) combining these developments with tools for projecting changes in catchment flow and sediment supply regimes over the 21st century. These advances will enable us to deliver new understanding on how the feedbacks between climate, hydrology, and channel morphodynamics drive changes in flood conveyance and future flooding. Moreover, we will also connect our next generation GFM with innovative population models that are based on the integration of satellite, survey, cell phone and census data. We will apply the coupled model system under a range of future climate, environmental and societal change scenarios, enabling us to fully interrogate and assess the extent to which people are exposed, and dynamically respond, to evolving flood hazard and risk. Overall, the project will deliver a fundamental change in the quantification, mapping and prediction of the interactions between channel-floodplain morphology and connectivity, and flood hazard across the world's river basins. We will share models and data on open source platforms. Project outcomes will be embedded with scientists, global numerical modelling groups, policy-makers, humanitarian agencies, river basin stakeholders, communities prone to regular or extreme flooding, the general public and school children.

Accurate flow measurement in rivers is vital to build well calibrated, reliable simulation models able to predict accurately the timing and extent of floods, and also to provide the data needed for effective management of water resources in a river catchment. This project will develop a new method of acoustic wave holography to measure remotely the velocity, flow depth and bed characteristics within river channels. The proposed holography method records the pattern of reflected acoustic waves (the hologram) above a dynamic flow surface and uses this pattern to reconstruct the water surface wave field throughout a three-dimensional region of space. The project will use recent advances in computational fluid mechanics and turbulence theory. The underpinning concept is that the free surface of turbulent river flows is never flat and is always dynamically rough. There is overwhelming evidence that the 3-dimensional pattern of the free surface of a river flow is caused by the turbulence structures within the flow. These structures are generated at the river bed and rise to the free surface and express themselves in the form of a pattern of surface waves which propagate at a particular velocity which does not necessarily coincide with the mean surface water velocity. Therefore, the free surface wave pattern carries comprehensive information about the underlying hydrodynamic processes in the flow, including the flow velocity, depth, turbulence scale and intensity and bed roughness characteristics. This process is very complex and it has not been sufficiently studied in the past because of a lack of accurate and robust instruments and accurate fluid dynamics models to relate the free surface wave pattern to the flow structure beneath. Thus, there is now an opportunity to develop a clear understanding how the pattern observed on the free surface of a river flow and the underlying turbulence structures and bed surface roughness in fluvial environments interact. This new knowledge in the hydrodynamics of turbulent river flows combined with new acoustic holographic measurement capabilities will provide a paradigm shift in the accuracy, spatial resolution and speed of deployment of flow monitoring in rivers. In this respect, the proposed work has a very high degree of novelty in comparison to the broader research context of this area internationally. The proposal is timely because it will contribute significantly to the need for us to better understand our natural environment especially under extreme conditions and in the development of Robotics and Autonomous Sensor technologies. These technologies were outlined in a report by David Willetts as one of the "Eight Great Technologies" that should be promoted and developed by the UK. The Willetts' report also states a clear need for real time forecasting of rivers, better water resource management and autonomous surveillance vehicles which require accurate on-board sensing. Our project takes an important step towards providing technology to address these requirements. The new sensor technology will also enable new theoretical foundations to be developed in the areas of wave propagation, inverse problems, holography, signal processing and computational fluid dynamics.

Historic rock-mounted lighthouses play a vital role in the safe navigation around perilous reefs. However their longevity is threatened by the battering of waves which may be set to increase with climate change. Virtual navigational aids such as GPS are fallible, and reliance on them can be disastrous. Mariners will therefore continue to need the physical visual aids of these strategic structures. The loss of any reef lighthouse will be incalculable in terms of safety, trade and heritage. Plymouth University has trialled the use of recording instruments to capture limited information on the loading and response of Eddystone Lighthouse, with the support of the General Lighthouse Authorities (GLAs) having legal responsibility to safeguard aids to marine navigation around the British Isles. The study evaluated the extreme logistical constraints of lighthouse operations and the feasibility of using instrumentation to understand the response of the lighthouse to wave loads, with results strongly encouraging a comprehensive study of the load and response environment. Hence a full-scale project is proposed whereby field, laboratory and mathematical/computer modelling methods, novel both individually and collectively, will be used to assess six of the most vulnerable rock lighthouses in the UK and Ireland. Depending on the findings the investigation will then focus on extended full-scale evaluation of one lighthouse for the following two winters. The field instrumentation run by University of Exeter, and which will include modal testing and long term instrumentation will require novel procedures and technologies to be created to deal with the challenging environmental and logistical constraints e.g. of access, timing power. The modal test data will be used to guide the creation, by UCL, of sophisticated multi-scale numerical simulations of lighthouses that can be used with the data to diagnose observed performance in the long-term monitoring. The numerical structural model will also be linked with advanced physical modelling at Plymouth University's COAST Laboratory, and numerical (computational fluid dynamic) simulations. Finally, based on the structural and wave loading models, the long term monitoring will be used to characterize the wave loading in-situ at full scale. Outcomes of the project will be used to inform the comprehensive structural health monitoring of other lighthouses both in the British Isles and further afield through the International Association of Lighthouse Authorities. This will lead to the identification of structural distress and reduction in the risk of failure through preventative measures. Methods developed will also be of relevance to other masonry structures under wave loads so the project team includes a number of industrial partners: AECOM, Atkins, HR Wallingford and the Environment Agency who have interests in this area. As the UK has a large number of ageing coastal defences whose vulnerability to wave load was demonstrated in the winter 2013/14 storms, the applicability of the STORMLAMP findings to these structures is an important additional benefit of the project.

Fluid dynamics underpins large areas of engineering, environmental and scientific research, and is becoming increasingly important in medical science. At Leeds, we possess research expertise across each of these domains and we have an established record of working across disciplinary boundaries. This proposal builds upon this record through the establishment of a multidisciplinary CDT in Fluid Dynamics. Research techniques that will be applied, and developed, will encompass: mathematical modelling & theory; numerical methods, CFD & high performance computing (HPC); and measurement & experimentation. Engineering application areas to be addressed include: reacting flows; carbon capture, transport & storage; flow of polymer melts; mixing problems; particulate flows; coating & deposition; lubrication; medical devices; pathogen control; heat transport; wind turbines; fluid-structure interaction; and nuclear safety. Environmental application areas will consist of: groundwater flow; river/estuary flows; tidal flows; oceanography; atmospheric pollution; weather forecasting; climate modelling; dynamics of the Earth's interior; and solar & planetary flow problems. Facilities available to undertake this research include: the University's HPC system which, combined with the N8 regional facility that is hosted at Leeds, provides ~10000 computational cores, an extensive suite of licensed software and dedicated support staff; flow measurement techniques (including Particle Imaging Velocimetry (PIV), 2-component Laser Doppler Anemometry (LDA), Phase Doppler Anemometry (PDA) and Ultrasonic Doppler Velocity Profiling (UDVP)); techniques for measuring fluid concentration (Ultrasonic High Concentration Meter (UHCM) and Optical Backscatter Probes (OBS)) and a range of optical metrology systems (e.g. pulsed and continuous wave lasers). The UK has a substantial requirement for doctoral scientists and engineers who have a deep understanding of all aspects of fluid dynamics from theory through to experimental methods and numerical simulation. In manufacturing and process engineering, for example, many processes depend critically on fluid flows (e.g. extrusion of polymer melts, deposition of coatings, spray drying, etc.) and it is essential to understand and control these processes in order to optimize production efficiency and reliability (see letter of support from P&G for example). In large-scale mechanical engineering there is a demand for expertise in reacting turbulent flows in order to optimize fuel efficiency and engine performance, and in wetting and surface flows for the design and manufacture of pumps and filters. There is also a need for a wide variety of skilled experts in environmental fluid flows to support the growing need to understand and predict local pollution and threats to safety (atmospheric, surface water, ocean and sub-surface flows), and to predict weather, climate and space weather for satellite technology. We will train a new generation of researchers who will have a broad range of skills to transfer into industry and environmental agencies, hence our approach will be multi-disciplinary throughout. All students will undertake both modelling and experimental training before embarking on their PhD project - which will be co-supervised by academics from different Schools. The MSc component of the programmee will be specifically tailored to develop expertise in the mathematical background of fluid dynamics, in CFD/HPC, and in experimental techniques. Team-based projects will be used to develop the teamwork and communication skills we believe are essential. Finally, engagement with industry will be a key feature of this CDT: all students will undertake an industrial placement, a large number of projects will be industrially sponsored, and our non-academic partners will contribute actively to our management, implementation and strategic development.

Numerical morphodynamic modelling systems used in coastal engineering practice consist of coupled models for waves, currents, sediment transport and bed level change. The sediment transport model usually comprises an advection-diffusion model for the wave-averaged suspended sediment and a practical sand transport formula for bed-load or near-bed total-load, in which the sand transport is empirically related to the local flow and sediment conditions. Well-founded practical models are based on a combination of measurements of net sand transport rates and understanding of the key fundamental processes, which are captured in the model in a parameterised way. However, most practical models are based on measured transport rates and processes from laboratory experiments involving regular, non-breaking waves almost exclusively. The fact that waves are in reality irregular and are breaking in many (if not most) cases of practical interest in coastal engineering, raises the question: what key processes associated with wave irregularity and wave breaking need to be included in a practical sand transport model for the model to be applicable to irregular and breaking wave conditions?The proposed research has two main aims: (1) To substantially improve understanding of the near-bed hydrodynamics and sand transport processes occurring under large-scale irregular and breaking wave conditions and (2) to develop a new practical model for predicting sand transport under waves, accounting for wave irregularity and wave breaking in a way that is well founded on experimental data and understanding of the fundamental processes. The transnational project team involves the Universities of Aberdeen, Liverpool and Twente in collaboration with UK and Dutch industry-based Project Partners. Large-scale experiments will be conducted in the Aberdeen Oscillatory Flow Tunnel and the Large Scale Wave Flume at the Catalonia University of Technology in Barcelona. Physical understanding and data from these experiments, combined with insights from two process-based numerical models, will be used to develop a new practical sand transport model that accounts for wave irregularity and wave breaking. Working with the industry Project Partners, the new model will be implemented in morphodynamic modelling systems used by coastal engineering practitioners and tested for practical applications.