GEO4180. Strategies for Mitigation of Risk Associated with Geohazards

Transcription

1 GEO4180 Geohazard Mitigation Strategies for Mitigation of Risk Associated with Geohazards Classification of geohazard mitigation strategies (1) land use plans, (2) enforcement of building codes and good construction practice, (3) early warning systems, (4) community preparedness and public awareness campaigns, (5) measures to pool and transfer the risks, (6) construction of physical protection barriers, and (7) network of escape routes and "safe" places. 1

2 DEFINITIONS (Based on Glossary of TC32 of the ISSMGE) Danger (Threat): Natural phenomenon that could lead to damage. Described by geometry, mechanical and other characteristics. Can be an existing one, or a potential one, such as a rockfall. Characterisation of threat involves no forecasting. Hazard: Probability that a particular danger (threat) occurs within a given period of time. Risk: Measure of the probability and severity of an adverse effect to life, health, property, or the environment. Risk = Hazard Potential Worth of Loss Definition of Risk (from an engineer s viewpoint) Risk = Hazard x Consequence R = H. V. U H = Hazard (temporal probability of a threat) V = Vulnerability of element(s) at risk U = Utility of the consequence to the element(s) at risk 2

3 Quantitative Risk Assessment (QRA) for natural threats QRA refers to the assessment of threat, hazard, risk and countermeasures in terms of numbers. It addresses the following questions: (1) What can cause harm? threat identification (2) How often? frequency of failure occurrence (hazard) (3) What can go wrong? consequence of failure (4) How bad? severity of failure consequence (5) So what? acceptability of risk (6) What should be done? risk management QRA is a tool for decision making under uncertainty Collect Information Deterministic (Model) Phase QRA Probabilistic (Model) Phase Updating Information (Model) Phase Decision 3

4 Risk management process is easy Risk management process is easy 4

10 Risk management process is easy R I S K M A N A G E M E N T R I S K A S S E S S M E N T R I S K A N A L Y S I S Political Aspirations Other constraints Budget Social demands Regulation Risk acceptance criteria Elements at risk Vulnerability Temporal Spatial probability H A Z A R D A N A L Y S I S LANDSLIDE (DANGER) Frequency CHARACTERISATION analysis Mechanics, Location Volume,Travel Distance and Velocity Consequences Values Judgement Risk mitigation Control options & Control plan Monitor and Review Landslide risk management framework (JTC1 experts) R I S K M A N A G E M E N T R I S K A S S E S S M E N T R I S K A N A L Y S I S Political Aspirations Other constraints Budget Social demands Regulation Risk acceptance criteria Elements at risk Vulnerability Temporal Spatial probability H A Z A R D A N A L Y S I S LANDSLIDE (DANGER) Frequency CHARACTERISATION analysis Mechanics, Location Volume,Travel Distance and Velocity Consequences Values Judgement Risk mitigation Control options & Control plan Monitor and Review 10

11 Computation of Hazard Heuristic methods Statistical methods Probabilistic methods Reliability analyses Monte Carlo Simulations Example of heuristic/statistical approach New York State Rockfall Hazard Rating Procedure Relative Hazard = GF x SF x HEF GF = Geologic Factor = Sum of Seven Subjectively Assessed Indicators: Fractures, Bedding Planes, Block Size, Rock Friction, Water/Ice, Rock Fall History, Backslope SF = Section Factor Ditch and Slope Geometry (Largely Deterministic) HEF = Human Exposure Factor Probability of Being Hit by Falling Rock or Hitting Rock Lying on Road (Objective or Subjective Probabilistic Assessment) 11

12 Probabilistic methods: Reliability Analysis FAILURE BOUNDARY ρ=-0.99 ρ=-0.75 ρ=0 SAFE REGION β = Reliability Index σ 2 X 2 m 2 σ 2 ρ=0.99 ρ=0.75 ρ=0 Single variable: E[ X ] X β = σ[ X ] * σ 1 σ 1 UNSAFE REGION m 1 Multiple variables: β = min X Ω Σ 1 T ( X E[ X ]) ( X E[ X ]) X X 1 Slope Stability z w z z p F c' γ = + w tanφ' 1 m γ szsinβcosβ γ s tanβ mz mzcos 2 β Failure Surface Variable Mean St. Dev c' 15 5 β D φ' 30 5 z 25 0 γw 1 0 γs m β L P[F<1] = P[T]=

13 Computation of Hazard Hazard = P[Threat] = P[Factor of safety < 1] = % y 0.25 c n e u q re F 0.2 e tiv la a e R Relative Frequency Cummulative Frequency 90.00% 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% % % Factor of Safety Relation Between Marginal Cost and Hazard Reduction Hazard Insufficient Countermeasures Initial Hazard Insufficient Countermeasures Optimal Countermeasures Excessive Countermeasures Mitigation Cost 13

14 How much risk is acceptable? Consequence Extent of damage Probability of occurrence Hazard 1 "Marginally Accepted" ANNUAL PROBABILITY OF FAILURE, Pf Mine Pit Slopes Geyser Slopes Foundations Fixed Drill Rigs Canvey Refineries Other LNG Studies Dams Merchant Shipping Mobile Drill Rigs Estimated U.S. Dams Commercial Aviation 10-6 Lives lost Cost in1984 USD 1 m 10 m 100 m 1 b 10 b CONSEQUENCE OF FAILURE "Accepted" Canvey LNG storage Canvey Recommended 14

15 How much risk are we willing to accept? Depends on whether the situation is voluntary or imposed. Acceptable / Tolerable Risk Criteria of Hong Kong Geotechnical Engineering Office Societal: F - N Charts (Ho et al., 2000) ALARP = As Low As Reasonably Practical Annual frequency of event causing fatalities E-005 1E-006 1E-007 1E-008 ALARP Acceptable Unacceptable Tolerable Detailed study required 1E Number of fatalities (N) 15

16 Consideration of Life Losses Option A 10-2 Option B (Preferred option) Unacceptable 10-4 Unacceptable ALARP Broadly Acceptable Intense Security Region ALARP Intense Security Region Number (N) of Fatalities Number (N) of Fatalities What is an early warning system? In common usage, an EWS is a component of a risk management system for detecting and dealing with an anticipated natural or manmade hazard. Early warning systems are not restricted to natural hazards and disasters. They are applicable to any activity or situation that may create a problem that must be dealt with. 16

17 An Early warning System (EWS) is a system or procedure designed to warn of a potential or an impending problem One boulder wrecks a train (2003) One landslide in Italy kills 27. Property damage and remedial works cost 400 mill. Euros (1986) One bridge collapses in Minneapolis and 13 people die (2007) Elements of an EWS An early warning system will normally have a minimum of 5 components: Knowledge of and means of forecasting the danger faced Information from technical monitoring and visual observations A response plan Dissemination of meaningful warnings to population at risk Public awareness and preparedness to respond to the warning. 17

18 How early is early? EWSs mitigate risk by reducing the consequences. Thus, the systems must issue warnings early enough to give sufficient time to implement actions to protect persons and/or property. Not all EWSs can satisfy this requirement. Remote sensing using orbiting satellites that pass over a point on the surface of the earth every 2 to 4 weeks are sometimes referred to in the literature as EWSs! For most earthquakes an early warning can only be issued after the first tremor has been detected. This is obviously not early enough for evacuation of population at risk. Available Technology for EWSs EWS technology is readily available today, for the most part, as off-the-shelf components. Sensors and sensing technology Communication technology Data collection systems as well as data processing, reporting and analyzing software Forecasting methods and modelling tools 18

19 Principal activities in an EWS EWSs nothing new? Early warning systems are not new. However, since the December 2004 tsunami catastrophe in the Indian Ocean, early warning systems have received a lot of attention. Geotechnical engineers have always relied extensively in their work on the concept early warning but under another name, namely the Observational Method. 19

20 The key to a successful EWS The key to a successful EWS is to be able to identify and measure the relevant precursors to the event. For example, typical precursors for an impending landslide event are: Intense rainfall Earthquakes and ground vibrations High rate of slope movement Rapid increases in pore water pressure Erosion at the toe of the slope Two major problems with EWS The most difficult problem in designing an EWS is to be able to specify proper threshold values for the alarms. Avoiding false alarms. The consequences of false alarms are often so serious that every possible action must be taken to avoid them. 20

21 Steps to avoid false alarms Use well-proven components in the monitoring system Provide redundancy in instrumentation Put emphasis on data quality control measures in data processing Make maximum use of human intelligence and engineering judgment in decision making. Successful early warning? Some experts refer to this case as an example of what can happen when human intelligence and judgment are lacking in decision making, while others refer to this as an example of a successful early warning. Evacuation from Hurricane Rita, September 23,

22 Example: Usoi Dam on Lake Sarez in Tajikistan Usoi Dam is a 600m high landslide dam. It is the largest dam in the world! Usoi Dam Usoi dam and Lake Sarez Scarp of the landslide The volume of the landslide was 2.2 km 3 22

23 Usoi dam U s o i D a m How big is Usoi dam? Bennett dam, 183 m One of the largest dams in North America Eifel tower in Paris Horizontal scale of Usoi Dam is compressed 23

24 Lake Sarez Length, ~ 60 km Maximum depth: 500 m Maximum width: 3.3 km Average width: 1.3 km Volume: ~ 17 km 3 Elevation m The threat and consequences The 600 m high Usoi dam is the largest dam in the world. Lake Sarez behind the dam currently holds 17 cubic-kilometers of water. If the dam were to fail, the resulting flood would be a catastrophe of inconceivable dimensions! Flood waters would flow down the Bartang valley to the Panj River valley and end up in the Aral Sea. 24

25 Valleys downstream Bartang valley Panj valley between Tajikistan and Afghanistan Disaster scenarios at Lake Sarez Active landslide Probable disaster scenarios Dam failure risk Seismic activity Rising water level Landslide into lake 25

26 Right bank active landslide The Right Bank Landslide ~1.8 km Current rate of movement is ~15 mm/year No mitigation measures 26

27 Mitigation with early warning system (EWS) Mitigation with EWS and lowering of reservoir 27

28 Åknes Tsunamigenic Rockslide Threat Loen, 1905 Tafjord, 1934 Western Norway 1900 s: 3 rockslides causing tsunami Caused 175 fatalities Loen,

29 Ålesund Hellesylt Skodje Ørskog Sykkylven Stordal Stranda Åknes Sylte Hegguraksla Tafjord Geiranger Åknes Åknes, Sunnylvsfjorden The potential slide area is shown Tafjord, million m 3 rock mass dropped into the fjord The tsunami reached 62m above sea level More than 40 people were killed 29

30 Åknes Large rockslide Tsunami analyses 8 mill. m 3 35 mill. m 3 30

31 Run-up height (m) 8 mill. m 3 35 mill. m 3 Oaldsbygda (Stokke) > 50 >100 Hellesylt Geiranger Raudbergvika Stranda Gravaneset Eidsdal Sylte/Muri Norddal Fjøra Linge Tafjord Dyrkorn Stordal Sjøholt Artist s depiction of a tsunami disaster 31

32 Hurricane Katrina Hurricane Katrina was a category 5 hurricane on August 28, 2005, One day before it made landfall on the Gulf Coast The Levees are Breached: Water pours into New Orleans 32

33 Aerial photograph of the 17th Street Canal Breach About 1800 people lost their lives because of Hurricane Katrina. Here is a makeshift grave on a street in New Orleans. 33

34 Indian Ocean tsunami of 26 Dec Generated by M = 9.3 earthquake 34

35 Patong City 35