Climate Impact Forecasting for Slopes

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Climate Impact Forecasting for Slopes

• An EPSRC-funded network based at
• Loughborough University

CLIFFS core group British Geological
Survey British Waterways Cementation Foundations
Skanska Ltd Geotechnical Consulting
Group British Geotechnical Association Halcrow
Group Ltd Highways Agency Imperial College
London Isle of Wight Council Kingston
University Loughborough University Mott
MacDonald Nottingham Trent University Queen's
University Belfast UK Climate Impacts
Programme University of Bristol University of
Birmingham University of Newcastle
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Aim of network

• To stimulate an integrated research response to
  address the intricately linked problem of
  forecasting, monitoring, design, management and
  remediation of climate change induced variations
  in slope instability

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Network operation

• Meetings and workshops involving academics and
  industrialists to
• Synthesise knowledge
• Agree a prioritised set of research needs
• Seek funding
• Disseminate outcomes

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Workshops

• main activity of the network
• sharing of expertise and ideas
• focus and prioritise research
• construct appropriate research teams
• develop proposals
• keep stakeholders informed
• stakeholders guidance on priorities
• issues raised by end user community

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Workshops

• Workshop 1 (20 February 2006)
• Focus on uncertainty and risk assessment and
  validation of groundwater models
• Workshop 2 (5 July 2006)
• Focus on natural slopes
• Workshop 3 (Jan 2007)
• Focus on embankment and cuttings
• Workshop 4 (2007)
• Focus on dissemination, communication, planning,
  design implications and data management

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Outcomes thus far..

• positive towards probabilistic approaches (but
  largely doesnt know how to do it yet)
• we need sites and long-term data sets to test out
  our models
• pore pressures in complex geological environments
  what happens when slides move?
• data management i.e. how to convert data on
  slopes into useable information.
• solid, old-fashioned models have worked well.
  How can we convince managers that they need to
  change?
• we will need to find ways so that our old
  models dont become obsolete.
• cost implications for design/maintenance changes
  - we need the best science available

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Outcomes thus far..

• usefulness of PBMs remains limited by
  uncertainties (both parameters and processes, eg
  trigger modes).
• data scarcity is also a problem (hydrological
  trigger conditions, pore pressure changes).
• further research is needed into model error and
  error propagation.
• difficult to translate limited understanding into
  clear suggestions for valuable joint
  probabilities
• we need to continue to look for causative
  linkages
• prescriptive approaches into input parameter
  requests may do more harm than good.
• model performance assessment is better served by
  daily time series rather than daily statistics

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