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The 2007 floods prompted the UK Government's "Pitt review", which came up with the idea that we need to start to deal with the causes of flooding upstream of the affected communities, rather than rely solely on the downstream engineering solutions. This stimulated a range of organisations to introduce "natural" features into the landscape that may have benefits in terms of reducing flooding (so called "Natural Flood Management, NFM"). Having introduced features these organisations, and local stakeholders working with them, are increasingly asking "Are these features working?" This has highlighted to funders, those implementing the features and scientists alike that there are gaps in the evidence of how individual features (e.g. a single farm pond or a small area of tree planting) work and what are potential downstream benefits for communities at risk of flooding. Stakeholders want both questions answered at the same time, making this one of the most important academic challenges for hydrological scientists in recent years. The only way to quantify the effects of many individual features at larger scales is to use computer models. To be credible, these models also need to produce believable results at individual feature scales. Meeting this challenge is the focus of this research project. Consequently, our primary objective is to quantify the likely effectiveness of these NFM features for mitigating flood risk at large catchment scales in the most credible way. In this context, credibility means being transparent and rigorous in the way that we deal with what we do know and what we don't know when addressing this problem using models. In doing this we need to address particular scientific challenges in the following ways: * We need to show that our models are capable of reproducing downstream floods while at the same time matching observed local hydrological phenomena, such as patterns of soil saturation. Integral to our methodology are observations of these local phenomena to further strengthen the credibility of the modelling. * We use the same models to predict NFM effects by changing key model components. These changes to the components are made in a rigorous way, initially based upon the current evidence. * As evidence of change is so critical, our project necessarily includes targeted experimental work to address some of the serious evidence gaps, to significantly improve the confidence in the model results. * This rigorous strategy provides us with a platform for quantifying the magnitude of benefit that can be offered by different spatial extents of NFM implementation across large areas. By addressing these scientific goals we believe that we can deliver a step change in the confidence of our quantification of the likely effectiveness of NFM measure for mitigating flood risk at large catchment scales.

Around the world the prediction of microbial water pollution is important for informing policy decisions in order to safeguard human health. However, modelling the fate and transfer of microbial pollutants, such as E. coli (& other pathogens) at different spatial scales poses a considerable challenge to the research and policy community. In the UK much research has focused on trying to understand the movement & survival of pathogens in environmental systems with a view that better knowledge and data on the behavioural characteristics of these micro-organisms will improve our ability to model and predict their interactions with, and responses to, the world around us. The NERC-funded project ReMOFIO (NE/J004456/1) provides an example of research undertaken in the UK to improve our understanding of the magnitude and spatial distribution of microbial risks in the landscape. In turn, this new knowledge has enabled the refinement of a simple modelling framework to allow for improved prediction of microbial risk on agricultural land, based on livestock numbers, farming practices and E. coli survival patterns under environmental conditions (e.g. rainfall and temperature fluctuations). While this model is useful, its current form makes it inaccessible to a wider audience and, most importantly, hinders its wider uptake by the regulatory community and those with a responsibility for catchment management and environmental decision-making. Indeed, models developed by the scientific community are rarely, if ever, designed in such a way to maximise their appeal to different end-users from the outset. Often what is required to effectively 'open-up' the access of sometimes rather complex science into a more user-friendly format is the development of an interface, or 'front-end', that promotes end-user interaction but keeps the underpinning science hidden from view. A common approach to enable this is the design of a Graphic User Interface (GUI) that allows end-users without specific modelling skills or knowledge of a modelling system to take advantage of existing science and modelling capability. A GUI essentially provides an effective means of translating scientific research into a practical tool for end-users. In response, this Innovation Project will promote engagement, deliberation and joint decision-making across a range of science providers (researchers) and science users (regulators, catchment managers and farm networks) in an effort to develop a GUI for the ReMOFIO model, and to explore the translation of this GUI into an App-based format too. This represents a critical step for ensuring that this NERC funded model and data delivers real-world impact through innovative conversion of the underpinning evidence-base into a format that is widely accessible by relevant end-users. The aim of the ViPER (Visualising Pathogen & Environmental Risk) project is to facilitate wider access and uptake of this NERC science, by stakeholders, in order to deliver that impact and to ensure that up-to-date insight and knowledge is transferred to the right people both in the right way and at the right time.

The corrosion of embedded steel rebar in reinforced concrete (RC) structures, which are the backbone of every nation's infrastructure, is a major issue. Interventions relating to the corrosion of RC structures are estimated to amount to about 35% of the total volume of all work in the global building sector. Reinforcement corrosion is induced via mobile chloride ions or other structurally harmful contaminates within the reinforced concrete, which happens due to a variety of reasons such as marine environment, de-icing salt in winter seasons, chloride content in concrete mixing and the use of sea sand, etc. With reinforcement corrosion, the load-bearing resistances of RC structures are reduced, with severe potential safety issues and also immense economic loss. A new intervention method, ICCP-SS (impressed current cathodic protection and structural strengthening), has recently been proposed. ICCP-SS combines the merits of impressed current cathodic protection (ICCP) and structural strengthening (SS) technologies, but uses one dual-functional material - carbon fibre reinforced cementitious matrix (C-FRCM). In this dual functional material, the carbon fibre (CF) mesh serves as the anode for ICCP and also the strengthening material for SS, while the cementitious matrix is the conductor for ICCP and the bonding material for SS. Previous studies have demonstrated effectiveness of the ICCP-SS technology for RC members. However, it has been found that prolonged ICCP would cause calcium leaching in the cementitious matrix at the anode interface, leading to drastic loss of mechanical properties and significant increase of electrical resistance of the bond between the cementitious matrix and CF mesh. Reducing calcium leaching to a level that does not adversely affect structural resistance is possible by increasing the compactness and the electrical conductivity of the cementitious matrix to achieve a more uniform electrical resistive field in the anode interface; introducing a tiny amount of graphene into the cementitious matrix has the potential to do so. The key to solving the problem is to prevent (or significantly slow down) the breakdown of C-S-H gel (i.e. loss of calcium) at anode interface under the same ICCP current density and duration. The remarkable properties of graphene make it a potentially ideal solution to this problem by producing a more uniform electrical field and more compact microstructures of the cementitious matrix. This project aims to solve two issues: to quantify the bond mechanical behaviour (for SS) and the electrical resistance at the CF/cementitious matrix interface (for ICCP) due to leaching, and to investigate means of reducing leaching. In summary, the ICCP-SS intervention method has vast potential in prolonging life of RC structures and introducing a small amount of graphene flakes in the dual-functional cementitious matrix has a number of beneficial synergistic effects to help realise the full potential of ICCP-SS.

Flooding is a major problem in the UK as recent high profile events in the summers of 2006 and 2007 have shown. In these events the damage to property and belongings ran into billions of pounds and a number of people were injured or lost their lives in these events. Therefore, predicting the location and severity of flooding is extremely important in preventing these losses. Current computer models for predicting flooding are highly accurate, but take a very long time to run even on the fastest computers. This project intends to use a technique known as cellular automata, a model based on the localised interactions of small cells, to simulate flooding in such a way that it will be possible to run complicated scenarios on a standard PC. The new approach will gain efficiency by making use of the fact that each cell can only 'see' the cells closest to it and the project will investigate the best ways of allowing each cell to communicate with its neighbours. The approach will be tested over a number of different flooding scenarios and compared with existing methodologies to demonstrate its accuracy and increased efficiency over standard methods.