One of the key challenges for Scottish transport infrastructure is the identification and assessment of assets at greatest risk to damage from landslides, storms and flooding. This is particularly the case with the vulnerability of the rural and coastal road network. The Scottish Climate Change Adaptation Framework (Transport) states that the location and design of new infrastructure, must take account of an increased likelihood of risks from flooding and landslides. Many coastal areas already appear to be experiencing increased intensity of storms and extreme rainfall events and recent high profile events (e.g. inundation of A78, Skelmorlie, extensive damage to vital roads and causeways in the Western Isles, landsliding at Stonehaven and the repeated disruption along the A83 at the Rest and be Thankful, Argyll and Bute attest to the need for an accurate assessment of those areas at greatest risk and for the implementation of potential mitigation measures. Adaptation Scotland provides a wealth of existing science, data and advice on how to adapt in the face of increasing change, but there is a need to develop robust tools for using this to assess the corresponding risk and economic impact for effective whole-life asset management. The aim of the project is therefore to develop a robust risk management tool, easily utilized by asset managers to assess threats to rural road transport assets in Scotland that are likely to be at risk from the effects of extreme rainfall and storms and differing future climate change scenarios. This will be determined by the following objectives: - Adaptation of an existing framework for landslide hazard assessment through the incorporation of recently-developed datasets to allow application also to flooding/coastal geohazards; - Production of diagnostic criteria to assess the nature of the different hazards (these include susceptibility to the various hazards and the spatial relation to the asset or road), - Analysis of the risk posed to key areas of the network infrastructure (local and trunk roads) by means of an assessment of the elements at risk (road and road users) and their vulnerability within a multi-hazard environment; - Assessment of economic impact to inform climate change adaptation plans and decision making for stakeholders at various levels from transport authority to local authority. Two case studies will be examined: (i) A78 Shore Road area and (ii) North and South Uists and Benbecula with island-linked causeways providing vital access to the Western Isles. The stakeholder is Transport Scotland. Keywords. extreme events, adaptation, resilience, management tool.

Landslides or the threat of landslides can cause significant economic disruption and pose a risk to life. Relatively small events can affect wide areas, particularly where the primary road network is sparse and there is limited scope for rerouting and diversion. Rainfall triggers the majority of landslides in the U.K. and national level 24-hr forecasts exist (for emergency response agencies), but there is uncertainty surrounding what combination(s) of duration and intensity trigger slope failures on a site specific level and why similar events do not always lead to the same event/no-event outcome. These knowledge gaps are critical where decisions must actively be made to warn users of (or close) linear infrastructure such as roads and rail in order to saves lives and costs. This lack of specificity, combined with the high costs of traditionally instrumenting known 'at risk' locations, hinders effective decision-making for key authorities and their partners. As a result many essential components of the environment are not monitored in advance, or on a wide-scale / high-resolution (spatial and temporal) basis. LIMIT will make use of and develop the next generation of low-cost and low-power integrated network (and networks of networks) sensors combined with edge processing and multi-threshold trigger based streaming of key data in near real-time to allow decisions underpinned by advanced theories of failure mechanics. The result is low cost, wide coverage provision of data that analyses the state of the environment and forecasts future behaviour at higher spatial and temporal resolutions than previously possible, integrated into a seamless 'data chain' from site to decision-makers. Data and key derivations based on fundamental process science are automatically ingested/shared into a newly constructed digital environment via an intelligent hierarchical platform. The outputs are fit for national data sets and modelling; policy makers deciding on sensor networks for monitoring evolving risk due to long-term environmental changes; operational decision-makers tasked with real-time management of acute threats to life; right though to data provision and two-way engagement with the individuals at risk. Innovative low-cost, in situ near real-time data streaming/processing sensors resiliently linked to an integrated portal with automated reporting offers a viable and transformative solution to end-user challenges. The LIMIT feasibility study will generate new field validated intelligent monitoring informatics, underpinned by advanced theories of failure mechanics, to provide critical data on the increasing likelihood and then the occurrence of slope failures in real-time.

Storm Desmond produced intense and prolonged rainfall which resulted in extensive flooding in the U.K. A number of landslides were also triggered, many of which damaged infrastructure and the transport network in particular. We are in a unique position, holding pre-event, and during event data for slopes that failed during and after Storm Desmond (Figs. 1, 2) at the most 'at risk' trunk road in Scotland1-3, the A83 Rest and Be Thankful (RABT), Argyll and Bute, which is a key arterial route. Since 2007 at least 13 debris flows have occurred, with road closures causing annual estimated losses of £286,300 to the local economy1-3. Existing monitoring (Fig. 1) has been invaluable in defining post-event conditions and sediment dynamics with instruments often installed after events, but there are no complete (pre- and post-) data on a single large event. This is essential in refining and validating physical and numerical modelling approaches, which can be used for enhanced management of the problem, and the design/refinement of appropriate monitoring and mitigation strategies that our project partners are responsible for putting into operation. Our proposal is to collect transient post-event data to allow follow-on funding proposals to answer the outstanding science questions, which are relevant for multiple sites beyond the RABT, and to document the transience of key evidence to inform how 'urgently' we do need respond to future large events to adequately quantify them.

This co-designed project with Highways England will reduce the ice hazard on motorways. As part of a nationwide trial of smart motorways, 'all lane' and 'hard shoulder running' are being used to increase capacity on critical sections of the GB motorway network. However, this approach, along with traditional road widening, has implications for winter road maintenance strategy. Significant surface temperature differences exist between lanes on motorways and it is not uncommon to find a difference of 2C between the inside and outside lane of the motorway. For example, in the case of hard shoulder running, differences between the inside lane and the previously un-trafficked hard shoulder of the motorway will be significant. A consequence of this, is when the hard shoulder is first opened to traffic (e.g. during the morning rush hour), an ice hazard may exist on this lane, whilst the other lanes remain above freezing. There is a need to better understand, and monitor, these differences in temperature so that it can be incorporated into the winter maintenance strategy used by Highways England. This project will translate existing technology developed on previous research projects to quantify the temperature difference between motorway lanes. The data will be available in real time, using an 'internet of things' approach alerting engineers of the need to conduct gritting operations on cooler lanes. Hence, this project will not only impact on the actions of the project partners (potentially saving money on gritting operations), but will also improve the safety of the network for all road users. The project is particularly timely given the ongoing inquiry into 'all lane running' by the commons select transport committee. The overall aim of this project is to produce a prototype decision support system that will provide information regarding the surface temperature of all motorway lanes which can be used to make efficiency savings as well as being consulted prior to opening the hard shoulder to traffic. This aim will be realised by the following objectives: 1. Installation of transects of networked low-cost sensors across motorway gantries, providing surface temperature information across all lanes. 2. Development of a cloud based data hub to process and visualise data 3. Integration of data into existing winter maintenance / smart motorways strategies. This short project has two key deliverables. Firstly, the project will provide tacit knowledge of temperature differences on multi-laned roads. This information can then be used inform winter maintenance strategy more generally across the network without significant further investment. Secondly, the prototype decision support system will provide detailed and reliable real-time measurements on the selected road section leading to efficiency savings for the project partner. This approach could readily be extended across the network, given the compatibility of this approach with the 'smart motorway' approach. The project will last for 7 months to cover a substantial part of the winter season (November 2016 - May 2017) and will cost in the region of £70k (£56k 80% FEC).

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