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.

In the UK the 600,000 km long underground sewer system (including private sewers) is ageing and poorly monitored. In continental Europe, the total value of the sewer assets amounts to 2 trillion Euros. The US EPA estimates that sewer collection systems in the USA have a total replacement value between $1 and $2 trillion. In China alone 40,000 km of new sewer pipes are laid every year. The system is subject to increasing capacity demands because of increased urbanisation and climate change. OFWAT (UK) and similar regulatory bodies in the developed countries impose a legal duty on water utilities to maintain the conditions of their sewer systems and to reduce the risk of flooding incidents. Consequently, monitoring pipes for obstructions and defects remediation forms an important part of an effective management programme to reduce sewer flooding and optimise the operational and maintenance costs. Existing sewer survey methods are limited to the interpretation of CCTV and LightLine images which are relatively slow and require a mobile trolley with camera to traverse through individual sewer pipes. Other existing inspection solutions rely on a limited number of flow metering devices (spot meters) which are installed sparsely across the sewer network. As a result, there are clear indications that less than 2% of the UK network is surveyed every 5 years and that a considerable number of flooding incidents are either unreported or observed with a considerable delay. This prevents the water utilities from developing a proactive maintenance programme which would enable them to achieve zero-failures in terms of sewer flooding. The project proposed here is formulated to develop new science which underpins the emerging fibre-optic sensing technology platform which can be laid with a robot in the invert of a sewer pipe to sense the flow conditions and continuously monitor pipe deterioration pervasively and to respond to events proactively. Theoretical, numerical modelling and extensive laboratory work will be carried out to understand the fluid-structure interactions between the turbulent flow and turbulence-induced vibration in the fibre cable containment system. The optical signals will be studied, numerically predicted and theoretically explained. New signal processing and pattern recognition algorithms will be developed to link these optical signals to key flow characteristics and to the change in any change structural integrity of the pipe. In addition, field measurements and validation will be carried out with support the lead commercial partner, nuron Ltd, using the new fibre-optic cable system. A key outcome of this work will be: (i) new theoretical understanding how this technology works and be developed towards a much higher technology readiness level; (ii) new, user-friendly software which will incorporate the major theoretical findings and post-processing algorithms that convert the optical signal to the flow characteristics measured distributively along the fibre-optic cable length and understood by the end-user. The proposal is timely because it will contribute significantly to the need for us to better understand the hydraulic behaviour and conditions of our buried infrastructure in real time and at an unprecedented spatial resolution. The new sensor technology will also enable new theoretical foundations to be developed in the areas of hydraulics, wave propagation, structural health/condition monifoting and computational fluid dynamics.

Title: Process analysis, observations and modelling - Integrated solutions for cleaner air for Delhi (PROMOTE) Air pollution has been widely recognized as a major global health risk. Given that 1 in every 10 total deaths can be attributed to air pollution (World Bank 2016), there are major implications for the cities of the world. As part of the Indo-Gangetic Plain (IGP), Delhi is subject to air pollution from a complex mixture of sources. As a consequence of the complex emissions and meteorology of the region, particulate matter (PM as PM10 and PM2.5), nitrogen oxides (NOx, NO2), sulphur dioxide (SO2), carbon monoxide (CO) and black carbon (BC) all peak during post-monsoon periods and remain elevated during winter making the National Capital Region (NCR) one of the most polluted areas. Open questions remain regarding the inability of models to accurately predict air pollution during winter time fog events and quantifying incoming air pollution from large distances into Delhi. Over 4 years, PROMOTE aims to reduce uncertainties in air quality prediction and forecasting for Delhi by undertaking process orientated observational and modelling analyses and to derive the most effective mitigation solutions for reducing air pollution over the urban and surrounding region. PROMOTE brings together a cross-disciplinary team of leading researchers from India and the UK to deliver the project aims. Its investigations will address three key questions: Q1 What contribution is made by aerosols to the air pollution burden in Delhi? Q2 How does the lower atmospheric boundary layer affect the long range transport of air pollution incoming into Delhi? Q3 What are the most effective emission controls for mitigation interventions that will lead to significant reductions in air pollution and exposure levels over Delhi and the wider National Capital Region? To address the three key questions we will: 1 Examine the contribution of secondary aerosols to the air pollution burden in Delhi during distinct meteorological seasons by developing a new representative model scheme for subtropical urban environments; 2 Investigate how boundary layer interactions lead to high air pollution events during pre-monsoon and stable winter fog periods affecting Delhi; 3 Quantify local, urban and regional contributions to Delhi's air quality through an improved understanding of aerosols, long-range transport and boundary layer processes; 4 Test the Delhi's air quality forecasting system incorporating improved understanding of aerosol pollution and atmospheric boundary layer processs; 5 Develop the first multiscale modelling system for predicting high resolution concentrations of PM2.5, PM10, NO2 and other pollutants and then provide the analysis for developing effective mitigation strategies for Delhi; 6 Synthesise and translate the outcomes of PROMOTE with other APHH projects to provide datasets for exposure and health studies and contribute to a roadmap for implementing effective local and regional mitigation strategies to meet current and future compliance and health requirements in Delhi and NCR. Through our analysis, we will deliver new knowledge on how local, urban and regional (LRT) sources of air pollution affect Delhi's air quality. With an improved understanding of aerosols and lower atmosphere dynamics, sensitivities between air pollutant concentrations and changes in local (e.g. traffic, industrial) and regional contributions will be quantified with a new multiscale modelling system for recommending interventions and mitigation options for Delhi.