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A multi-site approach to risk assessment for the insurance industry - - PowerPoint PPT Presentation

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A multi-site approach to risk assessment for the insurance industry Linda Speight Supervisors: Jim Hall, Chris Kilsby, Paul Kershaw linda.speight@ncl.ac.uk HydroPredict, Prague 2010 Outline Introduction Methodology Modelling

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A multi-site approach to risk assessment for the insurance industry

Linda Speight

Supervisors: Jim Hall, Chris Kilsby, Paul Kershaw

linda.speight@ncl.ac.uk HydroPredict, Prague 2010

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Outline

  • Introduction
  • Methodology

– Modelling extreme events – Flood defences

  • Calculating Risk
  • Conclusions
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Catastrophe Models

Premium = AAL + Risk Load + Expense Load

AIR model output

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Aims and Objectives

To develop a method for multi-site concurrent damages due to weather related extremes

FLOODsite 2007 Flood (BBC News)

Spatial dependencies at multiple scales

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Methodology

Statistical modelling of extreme events Statistical modelling of flood defence failure Process based modelling of water level & floodplain inundation Multiple sites nested in national framework Deterministic calculation of damage

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For each site

Damage per site conditional on event

For each event

Repeat until P(breach sequence) → 0

Sample breach widths Simulate crest height and defence reliability Sample breach failure state Sample sequence of defence failure. Hydraulic modelling

  • f water level and

flow through breach Estimate peak flows and hydrographs Simulate extreme event across network Hydraulic modelling for breach sequence Calculate damage Floodplain inundation modelling Estimate probability of breach sequences Hydraulic modelling of water level assuming no breaching

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For each site

Damage per site conditional on event

For each event

Repeat until P(breach sequence) → 0

Sample breach widths Simulate crest height and defence reliability Sample breach failure state Sample sequence of defence failure. Hydraulic modelling

  • f water level and

flow through breach Estimate peak flows and hydrographs Simulate extreme event across network Hydraulic modelling for breach sequence Calculate damage Floodplain inundation modelling Estimate probability of breach sequences Hydraulic modelling of water level assuming no breaching

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Modelling extreme events

  • Aim

– Spatial dependency between events – Large scale model for UK – Good representation of extremes

  • Method

– Conditional dependence model of Heffernan and Tawn (2004) applied by Keef et al (2009) Y|X, x > ux

a = strength of dependences b = changing dependence Z = residuals

Y = a(x) + b(x)Z

Y = set of gauges X = conditional gauge x = daily mean flow ux = threshold

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Example application

· = observed

below threshold

  • = observed
  • = simulated

55026 55023 55008 54022 54019 54002 54001 28046 28018

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For each site

Damage per site conditional on event

For each event

Repeat until P(breach sequence) → 0

Sample breach widths Simulate crest height and defence reliability Sample breach failure state Sample sequence of defence failure. Hydraulic modelling

  • f water level and

flow through breach Estimate peak flows and hydrographs Simulate extreme event across network Hydraulic modelling for breach sequence Calculate damage Floodplain inundation modelling Estimate probability of breach sequences Hydraulic modelling of water level assuming no breaching

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Estimating peak flows at site

Peak flow conversion methods

  • Shape of hydrograph
  • Catchment characteristics

5 10 15 20 25 30 35 40 2 4 6 8 10 12 14 16 18 20 22 24

Flow(m3/s) Time (h) Daily mean flow Hydrograph Flood Peak

Ungauged site transfer methods

  • Analogue sites
  • Weighted by distance and

catchment characteristics

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For each site

Damage per site conditional on event

For each event

Repeat until P(breach sequence) → 0

Sample breach widths Simulate crest height and defence reliability Sample breach failure state Sample sequence of defence failure. Hydraulic modelling

  • f water level and

flow through breach Estimate peak flows and hydrographs Simulate extreme event across network Hydraulic modelling for breach sequence Calculate damage Floodplain inundation modelling Estimate probability of breach sequences Hydraulic modelling of water level assuming no breaching

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Flood defence system

Characterised by

  • Design standard
  • Construction

type

Defence wall SOP = 100 years Embankment SOP = 25 years Embankment SOP = 5 years

d1 d2 d3

High ground Floodplain

Novel aspects

  • No restriction on

length

  • Consideration of

upstream breaches

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Sampling crest heights

Autocorrelation function for crest height = f (defence type, age, condition, data quality)

6 6,1 6,2 6,3 6,4 6,5 6,6 6,7 6,8 6,9 7 10 20 30 40 50 60 70 80 90 100

Crest height (m) Chainage (m)

design crest level defence A - old embankment Defence B - sea wall

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Defence reliability

  • Initiation

– Fragility curves – Type

Photos from FLOODsite

Fragility curve from Hall et al (2003)

– Condition – Sequencing

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Sampling breaches

0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1 6 6,1 6,2 6,3 6,4 6,5 6,6 6,7 6,8 6,9 7 20 40 60 80 100

P(failure) Elevation (m) Chainage (m) P(varying failure) crest height water level breaches

Autocorrelation function for strength = f (defence type, age, condition)

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Breach widths

FLOODsite

  • Growth Rate

– Materials – Floodplain type – Amount of water – Sequencing

  • Max width

Case study Observed values Assumed values Source Elbe 20m to 200m Median 20m Log normal width mean of 64m De Kok and Grossmann 2010 Lower Rhine Width 100 – 400m Apel et al 2004 Lower Rhine Width 50 - 150m Kamrath et al 2006 UK RASP method Function of load and defence length Hall et all 2003 Netherlands Largest 520m wide and 36m deep Muir-Wood and Bateman 2005 River Po Normal Width: 100m - 300m Depth: 0.5m - 4m Govi and Turitto 2000

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For each site

Damage per site conditional on event

For each event

Repeat until P(breach sequence) → 0

Sample breach widths Simulate crest height and defence reliability Sample breach failure state Sample sequence of defence failure. Hydraulic modelling

  • f water level and

flow through breach Estimate peak flows and hydrographs Simulate extreme event across network Hydraulic modelling for breach sequence Calculate damage Floodplain inundation modelling Estimate probability of breach sequences Hydraulic modelling of water level assuming no breaching

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SLIDE 19

For each site

Damage per site conditional on event

For each event

Repeat until P(breach sequence) → 0

Sample breach widths Simulate crest height and defence reliability Sample breach failure state Sample sequence of defence failure. Hydraulic modelling

  • f water level and

flow through breach Estimate peak flows and hydrographs Simulate extreme event across network Hydraulic modelling for breach sequence Calculate damage Floodplain inundation modelling Estimate probability of breach sequences Hydraulic modelling of water level assuming no breaching

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Damage

  • Raster based floodplain inundation model

depths

  • Depth-damage curves

damage

  • 1
  • 0,75
  • 0,5
  • 0,25

0,25 0,5 0,75 1 1,25 1,5 1,75 2 2,25 2,5 2,75 3 50 100 150 200 250 300 350 400 450 500

Depth Metres Damage £/m2

Penning-Roswell et al (2006)

BBC News

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Risk

Risk = Probability x Consequence P(Imax,i,j|Fi,j|OTi,j ,Bi,j , BWi,j|Lj,i,Ci,j,Ri,j |Qi,j | Xi ) Imax,i,j = maximum inundation depth across site j for event i

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Risk

Risk = Probability x Consequence P(OTi,j) = f(Ci,j, Li,j) P(Bi,j) = f(Ci,j, Li,j , Ri,j , OTi,j) P(BWi,j) = f(type, material, Li,j) Fi,j = Flow over or through defence P(Imax,i,j|Fi,j|OTi,j ,Bi,j , BWi,j|Lj,i,Ci,j,Ri,j |Qi,j | Xi )

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Risk

Risk = Probability x Consequence Xi = Large scale spatial event P(Li) = f(upstream breaches, Qi,j) Ci, Ri = f(type, age, condition) Qi,j = Inflow to hydraulic model P(Imax,i,j|Fi,j|OTi,j ,Bi,j , BWi,j|Lj,i,Ci,j,Ri,j |Qi,j | Xi )

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Conclusions

  • Integrated system model
  • Detail nested in national scale
  • Consider risk load

– If modelling of flood defences is poor how much impact does this have? – Which areas could flood at the same time / where are we over exposed?

  • Future...

– Sensitivity testing – Resilience measurers Informed decision!

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Thank you

Linda Speight Civil Engineering & Geosciences Newcastle University, UK Linda.speight@ncl.ac.uk

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  • 1. Extreme data at conditional gauge
  • 2. Extreme dependence between gauges

Fit Generalised Pareto

  • Shape (β)
  • Scale (ε)
  • threshold

Modelling extreme events (2)

Solid lines: parametric Dashed lines: nonparametric (residuals)

Fit dependence model

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SLIDE 27

References

Hall, J. W., R. Dawson, et al. (2003). A methodology for national-scale flood risk assessment. Proceedings

  • f the Institution of Civil Engineers-Water and Maritime Engineering, 156: 235-247

Heffernan and Tawn (2004) A conditional approach to modelling multivariate extreme values. Journal of the Royal Statistical Society Series B, 66(3), 497-547 Keef, C., Lamb, R., et al. (2009a) Spatial coherence of flood risk – Methodology report. Science Report – SC060088/SR., Environment Agency Keef, C., Svensson, C., et al. (2009b) Spatial dependence in extreme river flows and precipitation for Great Britain. J. Hydrology, 378, 240-252. Keef, C., Tawn, J., et al. (2009c) Spatial risk assessment for extreme river flows. Journal of the Royal Statistical Society Series C- Applied Statistics 58(5), 601-618. Penning-Roswell et al (2006) The benefits of flood and coastal risk management: a manual of assessment techniques, Middlesex University FHRC