Supporting proactive planning for climate change adaptation and conservation using an attributed road-river structure dataset.

Freshwater species and their habitats, and transportation networks are at heightened risk from changing climate and are priorities for adaptation, with the sheer abundance and individuality of road-river structures complicating mitigation efforts. We present a new spatial dataset of road-river structures attributed as culverts, bridges, or fords, and use this along with data on gradient and stream order to estimate structure sensitivity and exposure in and out of special areas of conservation (SAC) and built-up areas to determine vulnerability to damage across river catchments in Wales, UK. We then assess hazard of flooding likelihood at the most vulnerable structures to determine those posing high risk of impact on roads and river-obligate species (fishes and mussels) whose persistence depends on aquatic habitat connectivity. Over 5% (624/11,680) of structures are high vulnerability and located where flooding hazard is highest, posing high risk of impact to roads and river-obligate species. We assess reliability of our approach through an on-ground survey in a river catchment supporting an SAC and more than 40% (n = 255) of high-risk structures, and show that of the subset surveyed >50% had obvious physical degradation, streambank erosion, and scouring. Our findings help us to better understand which structures pose high-risk of impact to river-obligate species and humans with increased flooding likelihood.

Assessing urban strategies for reducing the impacts of extreme weather on infrastructure networks.

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.