INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Multi-hazard risk assessment and risk evaluation Cees van Westen

Programme for this week  Tuesday: Multi-hazard risk assessment  Presentations of risk exercises  Lecture on multi-hazard risk assessment & risk evaluation  Guest lecture:(12.30) Climate change scenarios  GIS exercise: Multi-hazard risk assessment  Wednesday: Cost-benefit analysis  Lecture & practical  Thursday: Using risk information in Disaster Risk Management (disaster preparedness)  GIS simulation: Emergency response  Friday: Using risk information in spatial planning  Friday afternoon: Final project (Konversatorium)

Last part of the course  Practicals:  mark for the practical is based on 3 assignments (hazard, risk, and simulation exercise)  Theory exam: 26 May  Closed book exam. Partly multiple choice, partly open questions. Bring calculator. Takes apr. 2 hours.  Konversatorium:  On Friday I prsent a list of topics  You may also suggest your own topic (related to GIS for hazard and risk assessment)  Report of pages  Submit by 27 May  Maybe : presentation by SKYPE on 27 May.

Multi hazard risk assessment

From single to multi-hazard risk  This is a difficult step:  Hazard processes are very different  Models used are very different  Data availability is very different  Temporal probability is biggest problem  Vulnerability is second biggest problem  Huge amount of data is needed  Are the hazards independent?  Are they caused by the same trigger?  Are they in chain

6 Preparatory factors Cause Effect Avalanches Shallow landslides Rockfall Torrential processes Floods Avalanches Shallow landslides Rockfall Torrential processes Floods MH Relationships: Spatial After de Pippo et al. (2008) and Tarvainen et al. (2006)

Multi-hazard risk assessment Risk curves of the hazards due to windstorms, floods and earthquakes for the city of Cologne. These curves comes directly from multiple one-by-one probabilistic hazard curves (from Grunthal et al., 2006)

Probabilistic risk assessment  Probabilistic techniques employ statistical analysis of historical datasets to simulate hazard intensities and frequencies across a country’s territory.  Includes the effect of all possible events, each one with different:  Probability of occurrence  Intensity and (uncertainty)  Includes physical vulnerability (and its uncertainty)  Results in loss probability curve

ISL 2004 HAZUS (advanced)

Probabilistic Risk Modeling Risk (i.e. probable losses) Hazard (i.e. earthquake) Exposure (i.e. houses) Damage Functions (of house to quake) Disaster Impact Analysis INFRASTRUCTUREENVIRONMENTALECONOMICSOCIAL - Scenario or Stochastic - Vulnerability

Hazard exceedance curves

RiskScape Open Source Multi-hazard risk assessment software:

Other projects on multi-hazards  FEMA’s Software Program for Estimating Potential Losses from Disasters (HAZUS- MH)  GeoSciences Australia  Natural Hazard Research Center / Sydney – PerilAUS Software  Pacific Disaster Center: e.g. Asia Pacific Natural Hazards and Vulnerabilities Atlas  Reducing Risk from Natural Hazards Program (RRNH), Canada  United Nations University - Multi-Hazards Urban Risk Assessment with Dynamic Spatial Information; In cooperation with University of Tokyo  Center for Disaster Management and Risk Reduction Technology (CEDIM), University of Karlsruhe

Baysian event tree Bayesian Event tree for tsunami propagation, given that rock slide in Aknes has occurred (V= rockslide volume, R=run-up height). From Lacasse et al., 2008

Event trees

Fault tree analysis

Population at risk Individual Risk Individual risk is the risk of fatality or injury to any identifiable (named) individual who lives within the zone impacted by a hazard, or follows a particular pattern of life, that might subject him or her to the consequences of a hazard. Societal Risk Societal risk is the risk of multiple fatalities or injuries in the society as a whole, and where society would have to carry the burden of a hazard causing a number of deaths, injury, financial, environmental, and other losses.

Individual risk CauseProbability / yearCauseProbability / year All causes (illness)1.19E-02Rock climbing8.00E-03 Cancer2.80E-03Canoeing2.00E-03 Road accidents1.00E-04Hang-gliding1.50E-03 Accidents at home9.30E-05Motor cycling2.40E-04 Fire1.50E-05Mining9.00E-04 Drowning6.00E-06Fire fighting8.00E-04 Excessive cold8.00E-06Police2.00E-04 Lightning1.00E-07Accidents at offices4.50E-06  Individual risk can be calculated as the total risk divided by the population at risk.  For example, if a region with a population of one million people experiences on average 5 deaths from flooding per year, the individual risk of being killed by a flood in that region is 5/1,000,000, usually expressed in orders of magnitude as 5×10−6.

ISL 2004 How to express risk?  Suppose: What is the risk of flying by airplane? Is it higher than driving a car?

f-N curves Left: f-N curves showing the number of Fatalities against annual frequency. For natural and man- made hazards Usually used to express societal risk. Important to define acceptable / tolerable risk

How to generate F-N curves  the frequency of events which causes at least N fatalities is plotted against the number N on log log scales  The difference between the frequency of events with N or more fatalities, F(N), and that with N+1 or more, F(N+1), is the frequency of events with exactly N fatalities, usually represented by f(N), with lower-case f.  Because f(N) must be non-negative, it follows that F(N) ≥ F(N+1) for all N, so that FN-curves never rise from left to right, but are always falling or flat  The lower an FN-curve is located on the FN-graph, the safer is the system it represents, because lower FN- curves represent lower frequencies of fatal events than higher curves.

Societal risk  The value F(1) is the frequency of accidents with 1 or more fatalities, or in other words the overall frequency of fatal accidents. This is the left-hand point on FN-curves, where the curve meets the vertical axis (usually located at N = 1 with logarithmic scales).  F-N curves can be constructed based on historical data in the form of number of events (floods, landslides, etc) and related fatalities  They can also be based on different future risk scenarios, in which for a number of events with different magnitudes the number of casualties is estimated

How to calculate F-N curves  In this exercise you will calculate F-N curves for accidents that have occurred in Europe in the period 1967 to  Three different types of accident data area available: for roads, railroad and aviation.  The analysis is based on empirical data, collected from historical accidents records.

How to calculate F-N curves  First calculate the total number of fatalities for road, railroad and aviation accidents by multiplying the number of events with the fatality class. Also calculate the average number of fatalities per year..  Then calculate the cumulative number of events, starting with the lowest one in the table (related to 146 fatalities) and summing them up upwards.  Then calculate the cumulative frequency of events per year, by dividing the cumulative number by the number of years.

How to calculate F-N curves  Plot these values in the graph indicated at the bottom of the spreadsheet in a log-log manner, with Fatalities (N) or the X-axis, and the cumulative frequency per year on the Y-Axis.  Compare the results. What can you conclude on the:  Severity of the accident type  Frequency of the accident type

Analyzing changing multi-risk

Exercise today  Create risk curves  Risk = H * V * A  R = PT * P L * V * A

Exercise today

ISL 2004 Seismic risk Step 1: Defining earthquake scenario. Step 2: Calculate the attenuation Step 3: Calculate soil amplification Step 4: Convert PGA to MMI Step 5: Apply Vulnerability Functions for Building types Step 6: Apply Vulnerability Functions for Infrastructure types Step 7: Apply Vulnerability Functions for casualties If additional information is available: Step 8: Apply cost information to the buildings and combine with vulnerability to calculate losses for different return periods. Step 9: Combine loss information for different return periods and calculate the risk by adding up the losses from these periods. Step 10: Combine information and make summary

ISL 2004 Seismic risk Return period Probability Loss Risk Risk = Hazard * Vulnerability * Amount

ISL 2004 Flood hazard modeling  Sobek: a two dimensional hydraulic model.  Input:  Digital Surface Model (Lidar)  Discharge data  Roughness data (landuse) Output: Flood depth Flow velocity (Per time step) Discharge Time

ISL 2004 Flood risk 5 years 10 years 25 years 50 years 100 years Mapping units 5 years 10 years 25 years 50 years 100 years Hazard polygonsBuildings Affected

ISL 2004 Flood risk  Risk = Hazard * Vulnerability * Amount

ISL 2004 Flood risk Return period Probability Loss Risk Risk = Hazard * Vulnerability * Amount

ISL 2004 Calculating buildings in hazard zones Calculates the number of houses in High, Moderate and Low susceptibility zones using a Building footprint map Building mapSusceptibility 4426 buildings 9645 buildings buildings Cross

ISL 2004 Quantitative risk assessment 4426 buildings 9645 buildings buildings Risk = Hazard * Vulnerability * Amount How much percentage of the high, moderate and low hazard classes may be affected by landsides? In which period will these landslides occur? What is the vulnerability to landslides? Results using mapping units HighModerateLow Known nowStill to doOnly susceptibility Hazard = Spatial probability * Temporal probability The temporal probability that landslides may occur due to a triggering event. Here we will link the return period of the triggering event with the landslides that are caused by it. We have differentiated return periods of: 50, 100, 200, 300 and 400 years. The spatial probability that a particular area would be affected by landslides of the given temporal probability. This is calculated as the landslide density within the landslide susceptibility class.

ISL 2004 From susceptibility to hazard Million dollar information!!! Landslide related to different return periods Landslide_ID map If the indication of the high, moderate and low areas susceptibility is correct, different landslide events with different return periods will give different distributions of landslides in these classes. The probability can be estimated by multiplying the temporal probability (1/return/period for annual probability) with the spatial probability (= what is the chance that 1 pixel is affected) Susceptibility Cross Density in high Densi ty in moderate Densi ty in low

ISL 2004 Calculating hazard Assumption is that events with a larger return period will also trigger those landslides that would be triggered by events from smaller return periods Susceptibility classes Return periods

ISL 2004 Calculating Vulnerability Simple assumption: The more buildings there are with 3 floors or higher, the lower will be the landslide vulnerability, as it becomes less likely that large buildings will be destroyed by landslides. Vuln:=iff(PerVacant=1,0,1-(Perc3floor+Percover3floor)) Estimating landslide vulnerability is very complex. It requites knowledge on the building types and on the expected landslide volumes and velocities. These are difficult to estimate. In many study landslide vulnerability of buildings is simply taken as 1, assuming complete destruction of the elements at risk. This would, however, in our case give too exaggerated values of risk.

ISL 2004 Calculate losses Loss_50_high:=0.0181*vuln*nr_b_high Loss_50_moderate:= E-06*vuln*nr_b_moderate Loss_50_low:= E-07*vuln*nr_b_low etc Losses = Spatial Probability * Consequences Losses = Spatial P * V * A

ISL 2004 Calculate losses What can you conclude when you compare the spatial probabilities and consequences for the high, moderate and low susceptibility classes ? Losses for a return period = sum of losses in high, moderate and low susceptibility areas

ISL 2004 Calculate risk Period

ISL 2004 Calculate total risk Total Risk = Area under curve Two methods: 1: Add trendline and integrate trendline 2: Use graphical method with triangles and rectangles

ISL 2004 Technological risk Hazard classsc1sc2 Buildings Return period50500 Probability Vulnerability0.1 Loss Risk22 Risk = Hazard * Vulnerability * Amount

ISL 2004 Combine hazard types

Risk curves  Plotting the return period on the X-axis and the Losses on the Y- axis  Plotting the return period on the X-axis and the annualized risk on the Yaxis  Plotting the losses on the X-axis and the annual probability on the Y-axis.  Such a risk curve is also called the Loss Exceedance Curve (LEC).

Results ScenarioReturn PeriodAnnualBuilding LossesSpecific RPProbabilityV*AAnnualized Risk PTPT P T *V*A FloodFlood_10y Flood_50y Flood_100y LandslideLandslide_50y Landslide_100y Landslide_200y Landslide_300y Landslide_400y EarthquakeSeismic_VI Seismic_VII Seismic_VIII Seismic_IX TechnologicalTech_sc Tech_sc  Make 3 risk curves:  Plot the Return Period on the X-axis and the Building Losses on the Y-axis  Plot the Return Period on the X-axis and the Specific Annualized risk on the Y axis  Plot the Building losses on the X-Axis and the Annual Probability on the Y-Axis.

Calculate area under the curve  Determine in Excel a trendline for the curve and calculate the area under the curve.  Divide the area under the curve in triangles and squares

ISL 2004 Calculate total risk Total Risk = Area under curve Two methods: 1: Add trendline and integrate trendline 2: Use graphical method with triangles and rectangles