This research will directly benefit society in the UK and abroad by increasing the effectiveness of water companies. The aim of the fellowship is to establish new research avenues for innovation in the field of urban water engineering and to bring novel practical solutions to the water-related challenges, in particular climate change, existing in the UK and worldwide. The proposal addresses the EPSRC/LWEC fundamental question "How can our cities, their hinterlands, linking infrastructure, rural surround and the regions they are in, be transformed to be resilient, sustainable, more economically viable and generally better places to live?". To answer this challenging question the research will investigate the impact of environmental change on drinking water distribution systems (DWDS) with the aim of generating new knowledge and tools that will improve the way drinking water is supplied in our cities, in a sustainable and economically viable way. As a consequence of climate change water sources used for water supply will be more contaminated and limited, the temperature of the water will increase and long-term changes in water demand will affect pipe hydraulics. All these changes will significantly affect biological and physico-chemical processes taking place in DWDS and will force water companies to modify the way they deliver water via DWDS. The fellowship will support the essential first steps in a new research line where my aim is to integrate microbiology, genetics and water engineering to explore in detail hidden aspects of DWDS in order to develop a whole system understanding. At present, the monitoring strategies for drinking water involve detecting microorganisms in water from taps using "old-fashioned" culture methods. However, the microbial composition of water is not representative of the biofilms (microbial assemblages) attached to pipes and culture-dependent methods underestimate the real microbial diversity in DWDS. Biofilms have great importance since they contain most of the microbial biomass in DWDS and they influence water quality and safety by, for example, hosting pathogens, promoting pipe corrosion and changes in water taste and colour. Consequently, there is an urgent need for research on how microorganisms will respond to environmental change within DWDS and how this will impact on DWDS performance and on drinking water safety and quality. Since DWDS are not sterile (i.e. completely free from microorganisms), research is also needed to identify which parameters support the presence of "friendly microorganisms" capable of maintaining the good performance of DWDS but also discouraging harmful microorganisms from surviving in the pipes. To answer these questions the research will assess different climate change situations in DWDS tested under controlled laboratory conditions including: increase in water temperature, increase in water nitrogen and phosphorus and extreme hydraulic fluctuations. Analysis of DNA/RNA from experimental samples will be used to uncover the link between microbial diversity (who is there?) and function (what are they doing?), and will help to identify genes involved in a range of processes including resistance to disinfection and pathogenic potential. Biological and environmental data will be integrated using hydro/bioinformatic methods with the ultimate aim of developing novel monitoring and management tools: 1) a new risk assessment framework; and 2) Biological Early Warning Systems (BEWS). The efficiency of these tools will be tested using real data from UK water companies and European partners. Dissemination of findings to industry, academics and the general public will be supported by the Pennine Water Group and through the Sheffield Water Centre. The fellowship will facilitate the development of my career as a world leader in urban water research by creating a new platform for innovation in molecular microbiology and hydraulic engineering.

Land-use and agriculture are responsible for around one quarter of all human greenhouse gas (GHG) emissions. While some of the activities that contribute to these emissions, such as deforestation, are readily observable, others are not. It is now recognised that freshwater ecosystems are active components of the global carbon cycle; rivers and lakes process the organic matter and nutrients they receive from their catchments, emit carbon dioxide (CO2) and methane to the atmosphere, sequester CO2 through aquatic primary production, and bury carbon in their sediments. Human activities such as nutrient and organic matter pollution from agriculture and urban wastewater, modification of drainage networks, and the widespread creation of new water bodies, from farm ponds to hydro-electric and water supply reservoirs, have greatly modified natural aquatic biogeochemical processes. In some inland waters, this has led to large GHG emissions to the atmosphere. However these emissions are highly variable in time and space, occur via a range of pathways, and are consequently exceptionally hard to measure on the temporal and spatial scales required. Advances in technology, including high-frequency monitoring systems, autonomous boat-mounted sensors and novel, low-cost automated systems that can be operated remotely across multiple locations, now offer the potential to capture these important but poorly understood emissions. In the GHG-Aqua project we will establish an integrated, UK-wide system for measuring aquatic GHG emissions, combining a core of highly instrumented 'Sentinel' sites with a distributed, community-run network of low-cost sensor systems deployed across UK inland waters to measure emissions from rivers, lakes, ponds, canals and reservoirs across gradients of human disturbance. A mobile instrument suite will enable detailed campaign-based assessment of vertical and spatial variations in fluxes and underlying processes. This globally unique and highly integrated measurement system will transform our capability to quantify aquatic GHG emissions from inland waters. With the support of a large community of researchers it will help to make the UK a world-leader in the field, and will facilitate future national and international scientific research to understand the role of natural and constructed waterbodies as active zones of carbon cycling, and sources and sinks for GHGs. We will work with government to include these fluxes in the UK's national emissions inventory; with the water industry to support their operational climate change mitigation targets; and with charities, agencies and others engaged in protecting and restoring freshwater environments to ensure that the climate change mitigation benefits of their activities can be captured, reported and sustained through effectively targeted investment.

It is widely acknowledged that the water and wastewater infrastructure assets, which communities rely upon for health, economy and environmental sustainability, are severely underfunded on a global scale. For example, a funding gap of nearly $55 billion has been identified by the US EPA (ASCE, 2011). In England and Wales, the total estimated capital value of water utility assets is £254.8 billion (Ofwat, 2015), but between 2010 and 2015 only £12.9 billion was allocated for maintaining and replacing assets. Combined with the drive to reduce customers' bills, there will be even more pressure on water companies to find ways to bridge the gap between the available and required finances. As a result of this it is not surprising that optimisation methods have been extensively researched and applied in this area (Maier et al., 2014). The inability of those methods to include into optimisation 'unquantifiable' or difficult to quantify, yet important considerations, such as user subjective domain knowledge, has contributed to the limited adoption of optimisation in the water industry. Many cognitive and computational challenges accompany the design, planning and management involving complex engineered systems. Water industry infrastructure assets (i.e., water distribution and wastewater networks) are examples of systems that pose severe difficulties to completely automated optimisation methods due to their size, conceptual and computational complexity, non-linear behaviour and often discrete/combinatorial nature. These difficulties have first been articulated by Goulter (1992), who primarily attributed the lack of application of optimisation in water distribution network (WDN) design to the absence of suitable professional software. Although such software is now widely available (e.g., InfoWorks, WaterGems, EPANET, etc.), the lack of user under-standing of capabilities, assumptions and limitations still restricts the use of optimisation by practicing engineers (Walski, 2001). Automatic methods that require a purely quantitative mathematical representation do not leverage human expertise and can only find solutions that are optimal with regard to an invariably over-simplified problem formulation. The focus of the past research in this area has almost exclusively been on algorithmic issues. However, this approach neglects many important human-computer interaction issues that must be addressed to provide practitioners with engineering-intuitive, practical solutions to optimisation problems. This project will develop new understanding of how engineering design, planning and management of complex water systems can be improved by creating a visual analytics optimisation approach that will integrate human expertise (through 'human in the loop' interactive optimisation), IT infrastructure (cloud/parallel computing) and state-of-the-art optimisation techniques to develop highly optimal, engineering intuitive solutions for the water industry. The new approach will be extensively tested on problems provided by the UK water industry and will involve practicing engineers and experts in this important problem domain.

Despite improved recycling infrastructure and public awareness, the UK still sends a staggering 17 million tonnes of municipal solid waste into landfill every year. This leads to the build up of leachate, the liquid which drains from a landfill site. Leachate contains trace chemicals, which can have strong contaminating effects on the environment, and therefore effective treatment methods are required. More to the point, however, ambitions for waste management should go beyond protection of human health and the environment, with conservation of energy and recovery of natural resources high on the agenda. This translational project aims to demonstrate an integrated process for leachate treat went and resource recovery. It involves three innovations: a novel physical pre-treatment, enhanced treatment with adaptively evolved microbial consortia and resource recovery through efficient biomass harvesting, and hence, contributing to the UK circular economy. The outcomes cut across several NERC research priority themes e.g. 'sustainable use of natural resources' and 'environment, pollution and human health.' Leachate can vary considerably in composition, depending on the age and type of waste within the landfill, containing both dissolved and suspended organic and inorganic material. Viridor Waste Management Ltd is the third largest waste management organisation in the UK, owning over 40 sites. Approximately half the sites use foul sewers to carry contaminated wastewater to a sewage works for treatment, the rest is either transported using tankers or released to surface waters. The total annual leachate production is 1,056,716 m3 and the operational costs vary between £4-£10 per m3 (e.g. disposal costs, energy or chemicals used). The previous work includes isolation of natural microbial consortia from leachate, novel harvesting method development and estimation of potential resources recovered. The main translational activities in this project are to design and build a pilot scale photobioreactor that is fitted with all the innovations from previous NERC and non-NERC funded research. This will be installed by Varicon Solutions, TUOS Research Technician and staff at Viridor at a local landfill site (Erin). Pre-processed leachate will be fed into the photobioreactor and growth and operating parameters carefully monitored. The data will be used in a techno economic assessment for Viridor but also other end-users. An easy-to-use Resource Recovery calculator will also be created. The process will be filmed in time-lapse and used to make a video for marketing, knowledge exchange and educational purposes. Both the video and photobioreactor system will be demonstrated at a relevant Trade Show in late 2017/early 2018. The ultimate aim is to demonstrate the progress of the NERC funded research up technology readiness levels with industrial, societal and environmental impact, together with economic benefits for the project partner and wider waste management community.

Water companies across the UK (and world) regularly inspect their sewers to prioritise maintenance and ensure the effective operation of their network. Failure to do so can result in incidents, including the discharge of untreated sewage to the environment, pipe collapse or even the formation of sewer blocking fatbergs. The importance of minimising these events is reinforced by the UKWIR objective to achieve zero uncontrolled sewer discharges by 2050. In most cases these occurrences are prevented using CCTV surveying and resolved with an early intervention. However, surveys are time consuming and expensive. Moreover, these reports are often inconsistent and inaccurate, largely due to human error and the subjective nature of fault codes. This project aims to augment the existing annotation and reporting process, with the overall ambition of fully automating the full CCTV surveying process. This proposed combination of AI and robotics will revolutionise sewer surveying and maintenance, improving the speed accuracy and efficiency of the entire practice. In turn this should result in the completion of more surveys and a much higher chance of pre-empting sewer failure. Currently SWW and the UoE are completing a KTP project, to internally implement the prototype fault detection method, investigated during the preceding PhD. The two-year partnership (due to complete in November 2020), has developed and trained the detection system on SWW's archive of CCTV footage and implementing this as a decision support tool. This is capable of highlighting faults and estimating their general type from recorded CCTV footage; extremely useful for the quick analysis of previously unused video that lacks annotation. Alongside technical developments, the project has built a network of collaborators (including iTouch and the WRc), whilst being widely publicised at both academic and industry events. Although the KTP has achieved its goal of bringing a functional tool to SWW, it is clear that the technology has potential for so much more, driving up efficiency and accuracy over current practices. The three key goals of the project are: (1) Develop the annotation capabilities of the technology to achieve the full standards outlined in the MSCC. (2) Implement the developed software so as to assist and perform live reporting. (3) Record and annotate previously unreported pipe features. The proposed project offers the opportunity to not only develop this research into a fully flourished technology for both UK and international use, but provides the resources and foundations for future image processing and machine learning research within SWW and the water industry as a whole. This research would continue to contribute solutions to national and global initiatives, aligning with the UN sustainable development goal ('protecting important sites for terrestrial and freshwater biodiversity'), UKWIR's Big Questions ('How do we achieve zero uncontrolled discharges from sewers by 2050?') and the UK industrial Strategy ('Increase sector productivity utilising AI'). Whether this takes the form of future visual inspection techniques or automation and support of other operational functions, the work would continue to drive efficiencies and improve performance using cutting edge computer science techniques.