Landslide Mitigation Informatics (LIMIT): Effective decision-making for complex landslide geohazards.

Lead Research Organisation: Newcastle University
Department Name: Sch of Geog, Politics and Sociology

Abstract

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.

Planned Impact

WP3 output white paper will be used by the Scottish Government and Transport Scotland (TS), and their operating companies / contractors to review the acute response and long-term monitoring strategy for hazardous slopes effecting trunk-road infrastructure in Scotland. The Geotechnical Manager for TS is the primary user, who is responsible for advising TS / Scottish Government and directing the operating company's landslide response. Improved planning and decision making will be evidence-based via a business case and the outputs of WP1-WP3 on the required investment in monitoring partnered to infrastructure works to deliver processed data in real and near real-time.

WP1-WP3 will be used throughout the 12 month project by TS and their operating companies to respond to detected landslides, and the increased threat of landslides using our new and integrated sensors and processing. This will be used in the deployment of additional monitoring / staff resources.

Short-term impact will be measured and evidenced by appropriate responses of both TS and the operating company to detected events or quiescence in assumed unstable areas using the newly constructed digital environment. We anticipate a dramatic reduction in false alarms (warnings activated but no landslides occurring) and far more proactive investigations of areas of concern as we implement our monitoring approach, responsively document events, and refine the protocols for follow up monitoring after an 'event'.

Medium-term to long-term impact and Partner benefits can be measured with the acceptance of monitoring recommendations as part of TS policy, and, follow-on monitoring contracts and implementations to third parties, the operating companies, or Universities. In addition journey delays and their economic impacts can be evaluated against former best practice decision-making chains.

Although we do not directly engage with the final end-users, the general public, at this feasibility and validation stage they will be directly impacted through decreased risk. In the short-term increased knowledge of areas of concern may actually trigger more road closure days and use of the diversion route, but, this potentially negative impact has to be viewed against the overall lowering of individual risk and long-term improvements in the reliability and effectiveness of mitigation measures.

Publications

10 25 50
 
Description The award researched and developed a new way to process time-lapse camera imagery to track the deformation that occures before landslides are triggered. This has now been implemented permanently at the A83 in Scotland, by Transport Scotland.
Exploitation Route They can, and will, be used as the way to approach other at risk roads in Scotland by the major stakeholders.
Sectors Environment,Other

 
Description The findings from the project led to the Transport Scotland (Project Partner) implementation of the time-lapse vector tracking software as an operational means to detect active landslides at the A83
First Year Of Impact 2022
Sector Environment,Transport
Impact Types Policy & public services

 
Description Consulted to add to Goverment Post Note on Civillain Drones
Geographic Reach National 
Policy Influence Type Implementation circular/rapid advice/letter to e.g. Ministry of Health
Impact Goverment Post Note: misuse of Civvilan Drones, used to provide guidance to MPs. I am a named source on the Post Note
URL https://post.parliament.uk/research-briefings/post-pn-0610/
 
Description New slope monitoring
Geographic Reach Local/Municipal/Regional 
Policy Influence Type Contribution to new or improved professional practice
 
Title Rest and be Thankful - Newcastle University rainfall data 
Description September-December 2018 15-minute rainfall data 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://data.ncl.ac.uk/articles/dataset/Rest_and_be_Thankful_-_Newcastle_University_rainfall_data/14...
 
Title Rest and be Thankful - Newcastle University rainfall data 
Description September-December 2018 15-minute rainfall data 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://data.ncl.ac.uk/articles/dataset/Rest_and_be_Thankful_-_Newcastle_University_rainfall_data/14...
 
Title Rest and be Thankful - Seismics data 
Description Raspberry Shake miniseed data files for October 9th 2018 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://data.ncl.ac.uk/articles/dataset/Rest_and_be_Thankful_-_Seismics_data/14046920/1
 
Title Rest and be Thankful - Seismics data 
Description Raspberry Shake miniseed data files for October 9th 2018 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://data.ncl.ac.uk/articles/dataset/Rest_and_be_Thankful_-_Seismics_data/14046920
 
Title Rest and be Thankful - Time lapse imagery 
Description Images from the time-lapse camera 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://data.ncl.ac.uk/articles/dataset/Rest_and_be_Thankful_-_Time_lapse_imagery/14047163
 
Title Rest and be Thankful - Time lapse imagery 
Description Images from the time-lapse camera 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
URL https://data.ncl.ac.uk/articles/dataset/Rest_and_be_Thankful_-_Time_lapse_imagery/14047163/1