Severe weather, with heavy rainfall and strong winds, has been the cause of recent dramatic land and coastal flooding, and of strong beach and cliff erosion along the British coast. Both the winters of 2012-2013 and 2013-2014 have seen severe environmental disasters in the UK. The prediction of severe rainfall and storms and its use to forecast river flooding and storm surges, as well as coastal erosion, poses a significant challenge. Uncertainties in the prediction of where and how much precipitation will fall, how high storm surges will be and from which direction waves and wind will attack coast lines, lie at the heart of this challenge. This and other environmental challenges are exacerbated by changing climate and need to be addressed urgently. As the latest IPCC reports confirms, sea level rise and storm intensity combined are very likely to cause more coastal erosion of beaches and cliffs, and of estuaries. However, it is also clear that there remains considerable uncertainty. To address the challenges posed by the prediction and mitigation of severe environmental events, many scientific and technical issues need to be tackled. These share common elements: phenomena involving a wide range of spatial and temporal scales; interaction between continuous and discrete entities; need to move from deterministic to probabilistic prediction, and from prediction to control; characterisation and sampling of extreme events; merging of models with observations through filtering; model reduction and parameter estimation. They also share a dual need for improved mathematical models and for improved numerical methods adapted to high-performance computer architectures. Since all these aspects are underpinned by mathematics, it is clear that new mathematical methods can make a major contribution to addressing the challenges posed by severe events. To achieve this, it is crucial that mathematicians with the relevant expertise interact closely with environmental scientists and with end-users of environmental research. At present, the UK suffers from limited interactions of this type. We therefore propose to establish a new Network - Maths Foresees - that will forge strong ties between researchers in the applied mathematics community with researchers in selected strategic areas of the environmental science community and governmental agencies. The activities proposed to reach our objectives include: (i) three general assemblies, (ii) three mathematics-with-industry style workshops, in which the stakeholders put forward challenges, (iii) focussed workshops on mathematical issues, (iv) outreach projects in which the science developed is demonstrated in an accessible and conceptual way to the general public, (v) feasibility projects, and (vi) workshops for user groups to disseminate the network progress to government agencies.

Sea and society interact most strongly at the coast where communities both benefit from and are threatened by the marine environment. Coastal flooding was the second highest risk after pandemic flu on the UK government's risk register in 2017. Over 1.8 million homes are at risk of coastal flooding and erosion in England alone. Extreme events already have very significant impacts at the coast, with the damage due to coastal flooding during the winter 2013/14 in excess of £500 million, and direct economic impacts exceeding £260 million per year on average. Coastal hazards will be increasing over the next century primarily driven by unavoidable sea level rise. At the same time, the UK is committed to reach net zero carbon emissions by 2050. It is therefore essential to ensure that UK coasts are managed so that coastal protection is resilient to future climate and the net zero ambition is achieved. Protecting the coast by maintaining hard 'grey' defences in all locations currently planned is unlikely to be cost-effective. Sustainable coastal management and adaptation will therefore require a broader range of actions, and greater use of softer 'green' solutions that work with nature, are multifunctional, and can deliver additional benefits. Examples already exist and include managed realignment, restoration of coastal habitats, and sand mega-nourishments. However, the uptake of green solutions remains patchy. According to the Committee on Climate Change, the uptake of managed realignment is five times too slow to meet the stated 2030 target. Reasons are complex and span the whole human-environment system. Nature-based solutions often lack support from public opinion and meet social resistance. Despite removing long-term commitment to hard defences, the economic justification for green approaches remains uncertain due to high upfront costs, difficulty in valuing the multiple co-benefits offered, and uncertainties inherent to future environmental and socio-economic projections. The frameworks used to support present day coastal management and policy making (e.g. Shoreline Management Plans) do not provide comprehensive and consistent approaches to resolve these issues. Consequences are that the effectiveness of these policy approaches is reduced. Delivering sustainable management of UK coasts will therefore require new frameworks that embrace the whole complex human-environment system and provide thorough scientific underpinning to determine how different value systems interact with decision making, how climate change will impact coastal ecosystem services, and how decision support tools can combine multiple uncertainties. Co-Opt will deliver a new integrated and interdisciplinary system-based framework that will effectively support the required transition from hard 'grey' defences to softer 'green' solutions in coastal and shoreline management. This framework will combine for the first time a conceptual representation of the complex coastal socio-ecological system, quantitative valuation of coastal ecosystem services under a changing climate, and the characterisation of how social perceptions and values influence both previous elements. Our new framework will be demonstrated for four case studies in the UK in collaboration with national, regional, and local stakeholders. This will provide a scalable and adaptive solution to support coastal management and policy development. Co-Opt has been co-designed with project partners essential to the implementation and delivery of coastal and shoreline management (e.g. Environment Agency, Natural Resources Wales, NatureScot, coastal groups) and will address their specific needs including development of thorough cost-benefit analyses and recommendations for action plans when preferred policy changes. Co-Opt will further benefit the broad coastal science base by supporting more integrated and interdisciplinary characterisation of the complex coastal human-environment system.

Measurements of ambient air-quality have been made routinely in the UK for many decades. The number of measurements has expanded substantially in the past decade following the implementation of the National Air Quality Strategy. This has increased the number of sites and pollutants measured and the number of local meteorological records taken to help interpret air-quality data. The collected air-quality data are generally used to check if the local pollution climate complies with air-quality standards. For this purpose they are summarised as annual statistics e.g. as annual-average concentrations, or as the total hours per year above a designated concentration value. Although such statistics serve to check compliance, they only use part of the information embedded in the air-quality and meteorological data for the purpose of assessing the performance of sources and policies. There have been several attempts to make better use of routine air-quality monitoring data for purposes for tracking the performance of individual sources and for managing air-quality more effectively. Although such studies have shown the advantages of better methods for presenting and interpreting data (e.g. polar plots of concentrations and wind speed) these advantages have not been generally recognised or the methods transferred into regular use by practitioners. This is in spite of the fact that such information would lead to more robust, rapid and cost-effective decisions for air quality management. Furthermore, few attempts have been made to apply novel forms of aerometric analysis to modelled data. When comparing predictions against observations it is important to check that a model 'gives the right answer for the right reasons'. Opportunities now exist to subject the latest generation of 'one atmosphere' models to rigorous forms of aerometric evaluation. This knowledge transfer proposal therefore aims to demonstrate the advantages of 'smarter' forms of aerometric analysis to a wide range of air-quality practitioners. We will show these advantages in a range of practical air-quality situations both for traditional community pollutants (e.g. SO2, NO2, PM10) and 'new priority pollutants' (e.g. methane) so that such methods become established in regular use. We will show how existing and novel techniques can be used to exploit air-quality data more fully and rigorously, and crucially how the extra information can benefit operational and policy decisions e.g. by giving earlier and clearer advice on the performance of individual sources, or on the progress of specific policies. The methods will not only enable measured concentrations to be better exploited, but will also be applied to modelled concentrations - so helping to improve prediction and management of air quality in future. We will disseminate our methods to practitioners via a range of mechanisms including (i) a website for announcements, progress reports and archived resources, (ii) case summaries & evaluation meetings, (iii) handouts & presentations to user bodies, (iv) conference posters/papers, (v) peer-reviewed publications, (vi) a final report and (vi) a closing workshop. In order to transfer the methods into regular use, we will show users that they can inform practical decisions on air quality (e.g. in management areas), resource use (e.g. fuels, abatement costs), societal behaviours (e.g. on transport, waste), health, (e.g. particulates) and quality of life. Our team has well-established links to professional air-quality bodies including: the Institute of Air-Quality Management, the UK's Atmospheric Dispersion Modelling Liaison Committee, and Environmental Protection UK / with its specialist Dispersion Modellers' User Group. We will use these links to consult on the selection of cases studies, to give information on project progress, and to show air-quality practitioners how their decisions can benefit from improved air-quality analysis techniques.

Glaciers and ice sheets are one of the least explored parts of the Earth's surface, and are now known to harbor significant populations of micro-organisms despite the challenging environmental conditions (e.g. extreme cold, desiccation, freezing and high pressure under ice sheets). Many of these microbes accelerate chemical weathering and supply nutrients to downstream ecosystems. A better knowledge of these processes is widely recognized as important for understanding: 1) global impacts of glaciers/ice sheets on the cycling of carbon and nutrients 2) biodiversity and life in extreme environments (e.g. Antarctic Subglacial Lakes) and 3) water flow beneath ice sheets as inferred from meltwater chemistry. Currently, the toolkits available to glaciologists to advance knowledge in these areas are very limited, and a technological leap is required to engage fully in future science campaigns. Building on previous work, this proposal aims to develop the first generation of compact chemical sensors for use in glaciers and ice sheets. While much of this technology has been evaluated for use in the oceans, it has not been assessed or modified for application in icy environments. We will take this technology and evaluate its performance under icy conditions (e.g. at low temperature, under freeze/thaw, at high pressure and with glacial meltwater sample types). This will be followed by design changes and further testing, culminating in a final demonstration of prototype instruments in Svalbard, Norwegian Arctic. These developments will provide key and rate limiting technology for future glacial science, and will have application in subglacial lake exploration (e.g. Subglacial Lake Ellsworth, Antarctica), in marine under-ice operations (e.g. Autosub under ice), and across a wide range of icy ecosystems where in situ measurements are desirable. This work is a forerunner to high impact international science campaigns requiring the development of purpose-built measuring systems that employ a comprehensive array of chemical sensor (e.g. the Lake Ellsworth Exploration Programme, the 'Basal Conditions on Rutford Ice Stream: Bed Access, Monitoring and Ice Sheet History' (BEAMISH) and the US-funded WISSARD programme, with which we have strong links). It also has strong relevance to water quality monitoring in freshwater environments, which will be explored via collaboration with the Environment Agency, UK.

Microseismic monitoring during hydraulic stimulation allows operators to monitor the development of fractures as they propagate. They can then optimise their operations, while ensuring that they are conducted in an environmentally safe manner. Presently, microseismicity is monitored either using geophones placed in dedicated monitoring boreholes, or dense sensor arrays at the surface. These methods are costly, and can pose logistical challenges. In certain settings, monitoring is also limited by the performance of geophones at high temperatures and pressures. As a result, microseismic monitoring arrays are typically deployed for less than 25% of fracturing operations in North America. Improvements in microseismic monitoring systems are needed, allowing operators to deploy effective microseismic arrays at most (or all) hydraulic fracturing sites in an economically and logistically viable manner. This will enable them to optimise hydrocarbon extraction at these sites, while ensuring that they operate in an environmentally-responsible manner. In-well deployment of fibre-optic cabling as a Distributed Acoustic Sensor (DAS) addresses the cost and logistical problems outlined above and has shown significant potential as a microseismic monitoring tool. The use of fibre-optic DAS in this context requires the development of novel data processing algorithms capable of handling this new type of data. This project will develop bespoke DAS instrumentation workflows, to be used by oil and gas companies and microseismic service companies. Chevron, one of the world's largest multinational oil and gas companies, regularly conduct hydraulic stimulation activities and they are exploring the use of fibre-optic DAS as a microseismic monitoring tool. Use of the novel processing workflows developed during this project will enable Chevron to increase the uptake of fibre-optic as a microseismic monitoring tool amongst their operational divisions. Shale gas operators must submit a Hydraulic Fracturing Plan (HFP) to the Environment Agency (EA) and Oil and Gas Authority (OGA) for approval before hydraulic fracturing can take place. The EA strongly recommends the use of microseismic monitoring to map the growth of fractures during stimulation. To ensure regulatory compliance, the EA must therefore develop the capacity to efficiently evaluate microseismic monitoring plans submitted to the agency. Since an HFP will include a proposal to monitor for seismic events, regulators require up-to-date knowledge in this rapidly developing field to assess material submitted to them by the operators. Through close collaboration, this project will allow the EA to determine whether proposed microseismic deployments, including fibre-optic monitoring, satisfy regulatory requirements. The main project of objectives are to: 1. Develop processing workflows for fibre-optic DAS data through partnerships with the full supply chain from equipment supplier (Silixa), to data processing, to end-user (Chevron). 2. Develop tools and guidelines for regulators for the assessment of microseismic monitoring plans including DAS technology for hydraulic fracturing in the UK. These objectives will be achieved by through three work packages. 1. Microseismic processing workflows currently used to treat geophone data will be adapted for application to DAS fibre-optic data. 2. The processing workflows will be optimised for use with large data volumes because any fit-for-purpose processing method must be capable of handling large data volumes. 3. Embed new knowledge in the regulators of the shale gas industry in the UK through a workshop, development of tools for inclusion in their processes and a short-term placement at the EA. With the first UK shale gas sites due to begin hydraulic fracturing this year, this project is particularly timely and important for the future success of the UK shale gas industry, with significant potential worth to the UK's economy.