Infrastructure KE Fellowship (Enhancing the resilience of infrastructure to climate change & extreme weather using automated monitoring technologies)

Key components of the UK transport and utilities infrastructure networks were built more than 100 years ago. This is particularly true of geotechnical assets (i.e. cuttings and embankments) within the rail and canal networks, and earth dams within the water utilities network. These structures were often very poorly constructed compared to modern engineered infrastructure earthworks. Materials were typically selected on the basis of availability, rather than suitability - consequently many of these structures are deteriorating, and require considerable resources for maintenance and remediation. This was clearly demonstrated this year with extreme rainfall causing numerous earthwork failures and major disruption to critical UK infrastructure.

Current monitoring approaches are very often inadequate for predicting slope failure events. They are overly reliant on meteorological data and surface observations, such as manual walkover, aerial photography, or site investigation (i.e. boreholes and trial pits), which do not adequately quantify (spatially or temporally) subsurface processes that occur as "precursors" to slope failure. Instead, failure is typically identified after it has been initiated, which, in many cases, is too late to implement low cost preventative interventions. There is a growing recognition by geotechnical asset owners that emerging low cost ground sensing technologies (e.g. geophysical ground imaging; new ground motion, pore pressure and moisture sensors; intelligent networks; wireless communications) could provide automated monitoring of the internal condition of assets at unprecedented levels of spatial and temporal resolution - thereby providing early warning of potential slope failure and enhancing the resilience of their networks to environmental risks. This is exemplified by Network Rail's new policy of increasing the number of small scale 'refurbishment and maintenance' interventions, and fewer high cost 'renewal' interventions, which will be underpinned by the significantly increased use of remote monitoring technology.

However, there are a number of major barriers to the uptake of these novel technologies by industry. These include limited industry awareness, caution in adopting novel technology, and lack of case studies validating and demonstrating new technologies for slope monitoring applications. Some of the emerging technologies also require specialist input that is currently available within the research community, but which existing geotechnical monitoring consultancies and contractors cannot yet provide. This is particularly true of some of the geophysical ground imaging technologies, which require complex workflows to derive information relevant to asset owners. An additional challenge is the need to interface new workflows and data streams with current industry standard information delivery systems so that the resulting data is accessible and intelligible to end-users and beneficiaries of the technology.

This project will therefore seek to engage both researchers and industry stakeholders to overcome these barriers to the uptake of automated condition monitoring technologies. I will seek to (1) understand current industry monitoring practices, (2) identify key emerging monitoring technologies that could be applicable for slope monitoring, (3) consider approaches for near-real-time analysis and delivery of remotely streamed monitoring data, (4) raise awareness amongst asset owners and service providers of new technological monitoring solutions, (5) produce a series of guidance documents detailing emerging technologies. To achieve this I will build on my links to industry and academia already established through a series of collaborative infrastructure research and innovation projects funded by the research councils (NERC and EPSRC) and a government development agency, and my participation in EU COST Action TU2012 ('Impact of climate change on engineered slopes for infrastructure').