Abstract. Precipitation intensities and the frequency of extreme events are projected to increase under climate change. These rainfall changes will lead to increases in the magnitude and frequency of flood events that will, in turn, affect patterns of erosion and deposition within river basins. These geomorphic changes to river systems may affect flood conveyance, infrastructure resilience, channel pattern, and habitat status as well as sediment, nutrient and carbon fluxes. Previous research modelling climatic influences on geomorphic changes has been limited by how climate variability and change are represented by downscaling from global or regional climate models. Furthermore, the non-linearity of the climatic, hydrological and geomorphic systems involved generate large uncertainties at each stage of the modelling process creating an uncertainty "cascade".This study integrates state-of-the-art approaches from the climate change and geomorphic communities to address these issues in a probabilistic modelling study of the Swale catchment, UK. The UKCP09 weather generator is used to simulate hourly rainfall for the baseline and climate change scenarios up to 2099, and used to drive the CAESAR landscape evolution model to simulate geomorphic change. Results show that winter rainfall is projected to increase, with larger increases at the extremes. The impact of the increasing rainfall is amplified through the translation into catchment runoff and in turn sediment yield with a 100 % increase in catchment mean sediment yield predicted between the baseline and the 2070-2099 High emissions scenario. Significant increases are shown between all climate change scenarios and baseline values. Analysis of extreme events also shows the amplification effect from rainfall to sediment delivery with even greater amplification associated with higher return period events. Furthermore, for the 2070-2099 High emissions scenario, sediment discharges from 50-yr return period events are predicted to be 5 times larger than baseline values.

Critical infrastructure networks, including transport, are crucial to the social and economic function of urban areas but are at increasing risk from natural hazards. Minimizing disruption to these networks should form part of a strategy to increase urban resilience. A framework for assessing the disruption from flood events to transport systems is presented that couples a high-resolution urban flood model with transport modelling and network analytics to assess the impacts of extreme rainfall events, and to quantify the resilience value of different adaptation options. A case study in Newcastle upon Tyne in the UK shows that both green roof infrastructure and traditional engineering interventions such as culverts or flood walls can reduce transport disruption from flooding. The magnitude of these benefits depends on the flood event and adaptation strategy, but for the scenarios considered here 3–22% improvements in city-wide travel times are achieved. The network metric of betweenness centrality, weighted by travel time, is shown to provide a rapid approach to identify and prioritize the most critical locations for flood risk management intervention. Protecting just the top ranked critical location from flooding provides an 11% reduction in person delays. A city-wide deployment of green roofs achieves a 26% reduction, and although key routes still flood, the benefits of this strategy are more evenly distributed across the transport network as flood depths are reduced across the model domain. Both options should form part of an urban flood risk management strategy, but this method can be used to optimize investment and target limited resources at critical locations, enabling green infrastructure strategies to be gradually implemented over the longer term to provide city-wide benefits. This framework provides a means of prioritizing limited financial resources to improve resilience. This is particularly important as flood management investments must typically exceed a far higher benefit–cost threshold than transport infrastructure investments. By capturing the value to the transport network from flood management interventions, it is possible to create new business models that provide benefits to, and enhance the resilience of, both transport and flood risk management infrastructures. Further work will develop the framework to consider other hazards and infrastructure networks.

Short-duration, high-intensity rainfall causes significant disruption to transport operations, and climate change is projected to increase the frequency and intensity of these events. Disruption costs of flooding are currently calculated using crude approaches. To support improved business cases for adapting urban infrastructure to climate change, this paper presents an integrated framework that couples simulations of flooding and transport to calculate the impacts of disruption. A function, constructed from a range of observational and experimental data sources, is used to relate flood depth to vehicle speed, which is more realistic than the typical approach of categorizing a road as either blocked or free flowing. The framework is demonstrated on Newcastle upon Tyne in the United Kingdom and shows that by the 2080s disruption across the city from a 1-in-50-year event could increase by 66%. A criticality index is developed and is shown to provide an effective metric to prioritize intervention options in the road network. In this case, just two adaptation interventions can reduce travel delays across the city by 32%.

A Blue-Green City aims to recreate a naturally-oriented water cycle while contributing to the amenity of the city by bringing water management and green infrastructure together. The Blue-Green approach is more than a stormwater management strategy aimed at improving water quality and providing flood risk benefits. It can also provide important ecosystem services and socio-cultural benefits when the urban system is in a non-flood, or green, condition. However, quantitative evaluation of benefits and the appraisal of the relative significance of each benefit in a given location are not well understood. The Blue-Green Cities Research Project aims to develop procedures for the robust evaluation of the multiple functionalities of Blue-Green infrastructure (BGI) components within flood risk management (FRM) strategies. The salient environmental challenge of FRM cuts across disciplinary boundaries, hence an interdisciplinary approach aims to avoid partial framing of the ongoing FRM debate. The Consortium will produce an urban flood model to simulate the movement of water and sediment through Blue-Green features. Individual and institutional agents will be incorporated into the model to illustrate how behavioural changes impact on flooding and vice versa. A methodological approach for evaluating the interaction of urban FRM components with the wider urban system will be developed and highlight where, when and to whom a range of benefits may accrue from BGI and other flood management interventions under non-flood and flood conditions. Recognition of the compound uncertainties involved in achieving multiple benefits at scale will be part of the robust method of uncertainty evaluation that will run throughout the project. The deliverables will be applied to the Demonstration Case Study, Newcastle, UK, in the final year of the project (2015). This paper will introduce the Blue-Green Cities Research Project and the novel, interdisciplinary framework that is adopted to investigate multiple benefits of FRM strategies.

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Achieving urban flood resilience at local, regional and national levels requires a transformative change in planning, design and implementation of urban water systems. Flood risk, wastewater and stormwater management should be re-envisaged and transformed to: ensure satisfactory service delivery under flood, normal and drought conditions, and enhance and extend the useful lives of ageing grey assets by supplementing them with multi-functional Blue-Green infrastructure. The aim of the multidisciplinary Urban Flood Resilience (UFR) research project, which launched in 2016 and comprises academics from nine UK institutions, is to investigate how transformative change may be possible through a whole systems approach. UFR research outputs to date are summarised under three themes. Theme 1 investigates how Blue-Green and Grey (BG + G) systems can be co-optimised to offer maximum flood risk reduction, continuous service delivery and multiple co-benefits. Theme 2 investigates the resource capacity of urban stormwater and evaluates the potential for interoperability. Theme 3 focuses on the interfaces between planners, developers, engineers and beneficiary communities and investigates citizens’ interactions with BG + G infrastructure. Focussing on retrofit and new build case studies, UFR research demonstrates how urban flood resilience may be achieved through changes in planning practice and policy to enable widespread uptake of BG + G infrastructure.

Urban flood risk modelling is a highly topical example of intensive computational processing. Such processing is increasingly required by a range of organisations including local government, engineering consultancies and the insurance industry to fulfil statutory requirements and provide professional services. As the demands for this type of work become more common, then ownership of high-end computational resources is warranted but if use is more sporadic and with tight deadlines then the use of Cloud computing could provide a cost-effective alternative. However, uptake of the Cloud by such organisations is often thwarted by the perceived technical barriers to entry. In this paper we present an architecture that helps to simplify the process of performing parameter sweep work on an Infrastructure as a Service Cloud. A parameter sweep version of the urban flood modelling, analysis and visualisation software "CityCat" was developed and deployed to estimate spatial and temporal flood risk at a whole city scale -far larger than had previously been possible. Performing this work on the Cloud allowed us access to more computing power than we would have been able to purchase locally for such a short time-frame (∼21 months of processing in a single calendar month). We go further to illustrate the considerations, both functional and non-functional, which need to be addressed if such an endeavour is to be successfully achieved.