Interagency Performance Evaluation Task (IPET) Force Engineering and Operational Risk and Reliability Analysis Robert C. Patev Deputy and Technical Lead, IPET Risk and Reliability Team
IPET Risk Assessment Topics IPET Background Risk Assessment Model System Identification Hazard Identification System Performance Consequences Lessons Learned
Interagency Performance Evaluation Task (IPET) Force to provide credible and objective scientific and engineering answers. Chief of Engineers System Storm Performance Consequences Risk Repair/Rebuild Higher Protection Report - Draft JUN06 Report - Final MAR07 Maps JUN/JUL 07 Maps AUG 07 Maps MAR 08 Report Draft NOV 07 Report Final MAY 08 https://ipet.wes.army.mil NOLArisk.usace.army.mil
IPET Risk and Reliability Core Team Mr. Jerry Foster, HQUSACE Mr. Robert Patev, NAD Mr. H. Wayne Jones, ITL-ERDC Dr. Greg Baecher, Univ. of Maryland Dr. Marty McCann, Stanford Univ. Dr. Terri McAllister, NIST Dr. Don Resio, CHL-ERDC Dr. Bilal Ayyub, Univ. of Maryland Dr. Ed Link, Director, IPET
What is the uncertainty in these estimates of annual rates of occurrence? Mission of IPET Risk Team What was the reliability of the pre-katrina hurricane protection system (HPS) for preventing flooding of protected areas given the range of hurricanes expected to impact New Orleans? What is the reliability of the current, post-katrina HPS for preventing flooding of protected areas given the range of hurricanes expected to impact New Orleans? Specifically, what is the annual rate of occurrence of system failure due to the range of expected hurricane events? What are the annual rates of occurrence of economic consequences and loss of life resulting from failures of the HPS given the range of hurricanes expected to impact New Orleans?
What Risk Assessment Is Not Risk assessment is not forecasting Risk assessment does not reflect the impact of any single storm Risk assessment is a long-term look at relative vulnerability from the spectrum of storms that can occur Risk assessment in the current context is intended to support planning decisions and not intended to support engineering design decisions
What is Risk? People use the term risk differently Dictionaries have differing definitions Risk = f(probability, consequence) High impact High exposure Event consequence Low Risk High Risk Improbable Event probability Highly probable Low impact
IPET Risk Assessment Process Chance of Hazard System X Performance = Vulnerability to Flooding X Consequences = Risk Surge and wave levels estimated at 138 locations 152 possible hurricanes 300 to 5000- year storm events Performance of entire 350-mile system - Pre-Katrina - 2007 Reaches, features and transitions Chance of flooding and flood depth By location and HPS scenario With / without pumping - Potential loss of life vs flood depth - Potential property damage vs flood depth Based on Pre- Katrina population and property values Expected annual loss of life Expected annual economic loss Based on Pre- Katrina population and property values
IPET Risk Assessment Steps Step 1: Define The HPS Step 2: Determine The Hazard Step 3: Evaluate The System Performance Step 4: Determine The Consequences Step 5: Determine The Risk Step 6: Determine the Uncertainty
Risk Assessment Flow Chart
Step 1: Determine the HPS
Step 1: System Definition
Step 1: System Definition HPS Definition Performed for eight basins, 37 subbasins 135 defined reaches (Pre-Katrina), 138 reaches (HPS 2007) 197 features (I-wall/levee transitions, pump stations, gate transitions (highway and railroad), ramps, drainage structures) 178 gates Recon Multi-steps GDM Recon CADD/GIS/Aerial Recon Available as-built drawings August 2005/Sept 2005 aerials Microsoft Live birds-eye aerials Field Recon Three USACE teams validated GIS level recon Over 600 hours of field inspection logged
Step 1: System Definition Aerials/Bird s Eye Field Recons
Step 1: System Definition Recon Steps (cont.) CADD/GIS Stationing and layout of GDM system HPS components and reaches defined Design elevations defined Pre-Katrina elevation points defined Boring locations defined Stability analysis sections defined ArcMap GIS Reaches defined Elevations defined
Step 2: The Hazard
Step 2: The Hazard
Step 2: The Hazard
Step 2: The Hazard Joint Probability Method (JPM) - Optimal Sampling (OS) Combinations The JPM used four parameters to characterize storms: Central pressure Radius of maximum wind speed Storm forward speed The angle of the storm track relative to the coast
Frame 001 28 Mar 2008 Pressure differential (1013-c p ) (mb) 120 Historical Storms in Gulf of Mexico JPM combinations 100 80 60 40 20 0 0 20 40 60 Radius to Maximum Winds [R p ](nm)
Step 2: The Hazard Hydrographs
Hurricane Water Level Processing Top of Levee/Wall SB1 - Reach 72 Wave Runup 14.0 12.0 Extend Tails Elevations (ft) 10.0 8.0 6.0 4.0 2.0 0.0 ADCIRC/STWAVE 0 20 40 60 80 100 120 140 160 180 200 Hydrograph Time Steps (15 Min. Increments) Pre-storm level
Step 3: System Performance
Step 3: System Performance Event Tree
Systems Analysis for Probability of Flooding.3 Rainfall Volume Sub-basin Interflow h 1.3 Breach 1.0 Pumps On Volume 1 Branch Rate 1 1.0 Overtopping.7 No Breach 0.0 Pumps Off h 1.1.9 Open Gates 0.0 No Overtopping Volume 2 Branch Rate 2 Closed Gates Volume 3 Branch Rate 3
Step 3: System Performance Fragility Curves Conditional
Step 3: System Performance Fragility Curves Based on factors of safety for Design Top of Wall/Levee ½, 1, 2, 3 and 6 feet overtopping Adjusted for variations in soil conditions, construction methods, and levee/wall designs Different for each reach Included length effects for each reach No partial safety factors Calibrate fragility curves to known performance
Step 3: System Performance Fragility Curve Concept for Levees Variability 1 2.0 ft 3.0 ft Erosion Conditional Probability of Failure 0 1.0 ft 0.5 ft Top of Levee Design Global Stability Elevation (NAVD88 (2004.65))
Step 3: System Performance Example of Levee Fragilities Basin X - Levee Fragilities Reach 2 1.0E+00 Reach 4 Reach 6 8.0E-01 Reach 8 6.0E-01 4.0E-01 2.0E-01 0.0E+00 Low Limit Design Top 0.5-ft OT 1.0-ft OT 2.0-ft Prob. of Failure OT 3.0-ft OT 6.0-ft OT Reach 9 Breach Fragility Curve
Step 3: System Performance Fragility Curve Concept for I-Walls Variability 1 2.0 ft 3.0 ft Erosion Conditional Probability of Failure 1.0 ft 0 Top of Wall 6 ft from Top of Wall Stability Elevation (NAVD88 (2004.65))
Step 3: System Performance Example of I-wall Fragilities Basin X - Wall Fragilities 1.0E+00 8.0E-01 6.0E-01 4.0E-01 2.0E-01 0.0E+00 Low Limit Design Top 0.5-ft OT 1.0-ft OT 2.0-ft OT 3.0-ft OT 6.0-ft OT Prob. of Failure Wall - Reach 1 Wall - Reach 3 Wall - Reach 5 Wall - Reach 7 Breach Fragility Curve
Step 3: System Performance Fragility Curves for Transitions Transition Points Failure modes Erosion due to overtopping Point fragility Transition Components Drainage/Control Structures Pumping Stations Gates (T-Wall/I-Wall/Levee) Gates Open/Closed Point Probability
Step 3: System Performance Qualitative Levee Damage Assessment Overtopping of Levees Three categories for levee materials examined Hydraulic fills Clay (including clay levees with sand core) Protected slopes (concrete paving and grouted riprap) Examined for interval of increasing water height (0.5-1, 2-3, 3+ (in feet)) Based on height of water (and velocity) over levee Based on overtopping field performance of failed levee sections during Katrina Wave run-up and stillwater Damage assessment for HPS levee sections Determine amount of damaged sections in proportion to the height of water over levee during Katrina Estimate qualitatively the probability of failure (for a measured breach width and depth) of the levee sections due to overtopping
Step 3: System Performance Erosion of HF Levees Due to Overtopping ~ 2 feet 2 ft
Step 3: System Performance Levee Assessment HF Sections Overtopping ~ 2 feet
Step 3: System Performance Fragility Curves - Overtopping Walls Levees H w (feet) Hydraulic Fill Clay Protected Slope H w (feet) Hydraulic Fill Clay Protected Slope 3 1 0.5 0.1 2 0.5 0.25 0 1 0 0 0 3 1 0.5 0.1 2 1 0.25 0 1 0 0 0
Step 3: System Performance IPET Breach Model Development Mapped in ARCGIS based on IPET basin/subbasins Assessed entire NO HPS (wall, levees, pump stations, transitions, gates, etc ) Entire HPS highlighted as: Heavily damaged or breached (red) Damaged but not breached (yellow) No or slight damage (green) This includes damage to transitions, gates, pump stations, etc Damaged sections were measured for Length of damage/breach Depth of damage/breach
Step 3: System Performance Measurement of Levee Breaches D D L L
Step 3: System Performance IPET Breach Model Development From damage assessment data, a table was developed for breach widths to be used in risk model Correlated to reach lengths and material types Included table for breaches at transitions, gates, ramps, etc
Step 3: System Performance
Step 4: The Consequences
Step 4: The Consequences Flood Elevation and Frequency Relationships OM Stage-Storage Stage in feet. 40 30 20 10 0-10 -20-30 -40 1.00E+ 03 1.00E+ 04 1.00E+ 05 1.00E+ 06 1.00E+ 07 1.00E+ 08 1.00E+ 09 1.00E+ 10 1.00E+ 11 OM1 OM2 OM3 OM4 OM5 Storage (cu-ft) OM Stage-Frequency 15 Stage in feet 10 5 0-5 -10 OM1 OM2 OM3 OM4 OM5-15 0.000 0.020 0.040 0.060 0.080 0.100 Events/Year
Step 4: Consequences Flood Depth Maps 2007 HPS 2007, 50-Year 2007, 100-Year 2007, 500-Year
Before Katrina, you had a 1% chance every year of flooding this deep from Hurricanes Notes: The water surface elevations are mean values The scale sensitivity of the legend is +/- 2 feet The info does not depict interior drainage modeling results The storm surge is characterized as the result of a probabilistic analysis of 5 to 6 storm parameters of a suite of 152 storms and not a particular event Assumes 0% Pumping Capacity
1% Hurricane Based Flood Depth Maps with Pumping Pre-Katrina, 2007 HPS, 2011 HPS Pre-Katrina, 1% Hurricane Flood Depth, 0% Pumps 2007, 1% Hurricane Flood Depth, 0% Pumps 2011, 1% Hurricane Flood Depth, 0% Pumps Pre-Katrina, 1% Hurricane Flood Depth, 50% Pumps Pre-Katrina, 1% Hurricane Flood Depth, 100% Pumps 2007, 1% Hurricane Flood Depth, 50% Pumps 2007, 1% Hurricane Flood Depth, 100% Pumps 2011, 1% Hurricane Flood Depth, 50% Pumps 2011, 1% Hurricane Flood Depth, 100% Pumps
Pre-Katrina, 500-year, 0% Pump 2007, 500-year, 0% Pump 2011, 500-year, 0% Pump Pre-Katrina, 500-year, 50% Pump Pre-Katrina, 500-year, 100% Pump 2007, 500-year, 50% Pump 2007, 500-year, 100% Pump 2011, 500-year, 50% Pump 2011, 500-year, 100% Pump
Step 5: Determine the Risk
Step 5: Determine the Risk Flood Damage and Fatalities Stage-loss relationships for Pre-Katrina population and property
Loss of Life Risk Maps (Pre-K Population and Property) Pre-Katrina, 100-year, 0% pump 2007, 100-year, 0% pump 2011, 100-year, 0% pump Pre-Katrina, 100-year, 50% pump 2007, 100-year, 50% pump 2011, 100-year, 50% pump
500-year (0.2%) Loss of Life Risk 2007, 500-year, 50% Pump Pre-Katrina, 500-year, 50% Pump 2011, 500-year, 50% Pump Pre-Katrina Population
Economic 1% Risk Maps (Pre-K Population and Property) Pre-Katrina, 100-year, 0% Pump 2007, 100-year, 0% Pump 2011, 100-Year, 0% Pump Pre-Katrina, 100-year, 50% Pump 2007, 100-Year, 50% Pump 2011, 100-Year, 50% Pump PAST PRESENT FUTURE
500-year (0.2%) Economic Risk 2007, 500 Year 50% Pump Pre-K, 500 Year 50% Pump 2011, 500 Year 50% Pump % of Value, Pre-Katrina Property
Lesson Learned Risk framework is specific to the system under investigation Risk team must include a diverse membership that includes not only engineers with expertise in a range of disciplines but economists and operational staff as well Many additional factors could have been included or considered in more detail: Interior drainage and pumping system Impact of past maintenance on performance Human factors (political decisions, design decisions, operation during storms, etc.) Changing demographics of the impacted area
Lessons Learned Large system-wide risk assessments are challenging but can be done Involvement with District personnel and local sponsor staff Extensive data gathering and processing Lack of sufficient or questionable data Assumptions need to be made Specific risk models have to be developed Uncertainties in risk model Epistemic and aleatory Generally large due to the number of unknowns and inputs to a large systems risk model Quantification is a challenging task and needs care
Lesson Learned ROME WAS NOT BUILT IN A DAY Risk model development for large engineered systems takes time and patience Risk model development for large engineered system has many steps forward but also has many steps back Risk model development of large engineered systems can be expensive but is very beneficial in assisting with making risk informed decisions