Keynote Lecture, Waheed Uddin:
Disaster Resilience Management and Flood Hazard Assessment of Infrastructure Using Computational Modeling and Geospatial Risk Mapping
Advantages of Hiring UIUX Design Service Providers for Your Business
2017 MAIREINFRA Conference, Seoul, South Korea, July 19-21.
1. Floods, Utah & Arizona, 2015
Waheed Uddin, PhD, PE
@drwaheeduddin
2017 MAIREINFRA International Conference on Maintenance and
Rehabilitation of Constructed Infrastructure Facilities
Seoul, South Korea, July 19 – 21, 2017
Disaster Resilience Management and Flood Hazard
Assessment of Infrastructure Using Computational
Modeling and Geospatial Risk Mapping
1
2. 2
• About 60% of all disasters costing one billion dollars or more in the
United States were related to weather. Worldwide floods and
storms accounted for 65% of total 13,757 natural disasters during
1900 to 2015.
• Extreme weather events are occurring as devastating floods in
recent years worldwide due to heavy rainfall, hurricanes/cyclones,
and hydrological events of dam & levee breaks.
• Extreme weather events caused $208 billion of economic cost in the
United States with more than 1,200 casualties between 2011 & 2013.
• 2005 Hurricane Katrina disaster on Louisiana and Mississippi
Gulf Coast resulted in more than $100 billion in infrastructure and
economic costs.
• Critical transportation infrastructure assets are under a continuous
risk of flood hazards and subject to significant damage, such as
washing away of pavements and bridges.
Background and Motıvatıon
2
4. 4
Flood Destruction: Roadways and Bridges
2005
Mississippi Gulf Coast
Hurricane Irene, 2011
4 I-10 Bridge, Arizona, Aug 2015
Scour failure
2005 Hurricane Katrina
New Orleans
5. 5
Review natural disaster occurrences and their
impacts on the built environment and communities
Implement computational modeling and geospatial
visualization technologies for extreme flood
simulations and coastal disaster risk mapping.
Discuss case studies of disaster vulnerability risk
mapping and damage assessment for selected port
cities.
Results used to enhance decision support systems for
safeguard of bridge and highway infrastructure
from extreme weather related natural disasters such
as floods.
Objectives
5
6. 6
Natural Hazards and Declared Natural
Disasters
6
• Geological disasters: volcanoes, earthquakes, tsunamis,
landslides, land subsidence, cavities.
• Meteorological disasters (including extreme weather and
climate impacts): rainfall floods, storms, hail, coastal hurricanes
and cyclones, snow, drought, famine.
• Hydrological disasters: rainfall floods, flash floods, dam and
levee breaks, river overflow, mudslide.
• Environmental disasters: toxic spills, river and groundwater
contamination, wetland pollution, air pollution, air quality
degradation, nuclear radiation leaks, deforestation
• Fire disasters: wildfire, forest fire, accidental
industrial/chemical fire, terrorism
• Epidemic disasters: epidemics and fatal diseases
• Disaster incidents and/or accidental disasters:
water pipeline breaks, gas pipeline explosions, oil spills
8. 8
Time Series of Global Disaster Occurrences
8
A rate of decrease in disasters of 2.2% per year was
calculated in annual number of disasters from the peak
in year 2000 to 2015 period
9. 9
ARIMA Model vs. the Observed Time Series
9
Worldwide floods and storms accounted for 65% of
total 13,757 natural disasters during 1900 to 2015.
10. 10
10
This evidence contradicts the UN IPCC’s Carbon Dioxide (CO2)-Anthropogenic
Global Warming (AGW) hypothesis of increasing number of weather and
climate change related natural disaster predicted in 2015.
11. 11
11
Physical evidence:
Global Warming is not caused by Anthropogenic
Carbon Dioxide (CO2) as hypothesized by UN IPCC
for 2015 Paris Climate deal, which was based on
fabricated global temperature anomaly.
Global Warming and Climate Change Hypothesis?
12. 12
12
Global Warming is not caused by Anthropogenic CO2 as hypothesized by
IPCC for 2015 Paris Climate deal using fabricated global temperature anomaly.
13. 13
Spatial Map of Worldwide Natural Disasters, 2011
13
2011 Costliest Year: Recovery Effort over US$380 billion
242 Federally declared disasters in the United States
including the Hurricane Irene disaster on the East coast
15. 15
15
An Enhanced BMS Framework (after Uddin et al. 2013)
15
• Vertical Underclearance
• Flood Probability
Flood Vulnerability Rating (FVR)
Flood Disaster Resilience Analysis
16. 16
Infrastructure Disaster Resilience Improvement
How to prioritize infrastructure
asset groups for disaster resilience
improvement?
Goal –
Measure
Quantifiable
Reduction
Identify
Risk
Assess
Risk
Communicate
Risk
Mitigate
Risk
Continuous
Renewal &
Improvement
Map Risk
Data
Assess Present
& Future Risks
Plan for
Risk
Reduce
Risk
Enhance
Resilience:
Hardening
Infrastructure
Disaster Resilience Rating
17. 17
Visualization of First Flood Inundation Simulation, and Calculated Flood Depth
at Selected Feature Locations along River CL (10m Cell), Sardis, Mississippi
Maximum Flood Depth
Feature Number
Hwy 315
Hwy 35
Infrastructure Feature
CAIT / NCCHE
Sardis Site
17
18. 18
Objective of 3D-FE Modeling of Bridge Structure
Structural integrity analysis of US-51 Highway Bridge
(Sardis, Mississippi) subjected to lateral floodwater force
using 3D-FE modeling and simulation
• Deck
• Deck and Girders
• Individual Girder
• Bearings
• Pile Caps
• Piles
• Foundation Soil
18
19. 19
3D-FE Modeling & Simulation: US-51 Bridge
View of US-51 Bridge (Credit: MDOT)
Lateral Hydrodynamic Force Acting on the Bridge
19
20. Highway US-51 Bridge: 3D-FE
Simulation Results
Subjected to Lateral
Floodwater Force
Maximum Lateral Displacement in Floodwater direction: 2.4 m
20
23. 23
23
Data Used in Budget Optimization Problem and Value
Engineering Analysis for Reconstruction or Hardening
Case Study of Concrete Girder Bridge
FVR Group
Unit Cost of
Reconstruction ($)
Unit Cost of
Hardening ($)
Unit Cost
Avoidance ($)
Unit Net
Benefit ($)
Net Benefit
($)
1. Catastrophic Risk 10,000,000 - 15,000,000 5,000,000 5,400,000
2. Very High Risk 5,000,000 - 15,000,000 10,000,000 27,000,000
3. High Risk - 5,000,000 15,000,000 10,000,000 16,200,000
4. Moderate Risk - 1,000,000 4,000,000 3,000,000 1,620,000
5. Low Risk - 1,000,000 4,000,000 3,000,000 162,000
6. Very Low Risk - 1,000,000 4,000,000 3,000,000 81,000
n = Analysis period= 100 years, i = Annual Discount Rate= 5%
( )
( ) ( )
+
−
+
−+
+= nn
n
i1
1
S
i1i
1i1
MCP
The present worth (P) of a flood resilience project for (n) years, with an initial
cost C, a yearly maintenance cost M, and a salvage value S.
23
FVR = Flood
Vulnerability Rating
24. 24
Extreme Flood Modeling and Simulation for Los Angeles
24
In recent years, 130 ports were struck by tropical cyclones each year.
25. 25
25
Extreme Flood Modeling and Simulation for Los Angeles
37% Area Inundated by extreme rainfall flood (using HEC-RAS Software)
26. 26
2m Seal Level Rise (SLR) Simulation and Visualization of
Land Submerge, Projected by NOAA for Year 2100
26
1.68% Land Area Submerges
(using CAIT Methodology)
27. 27
27
2m Seal Level Rise (SLR) Simulation and Visualization of
Land Submerge
2m Peak Wave Height Tsunami simulation shows just 0.4 % less submerged
land area than that by 2 m SLR. However, a tsunami can occur any time if
there is a strong earthquake in Pacific ocean along the west coast.
29. 29
29
Better communications,
emergency response
management and natural
disaster preparedness
contributed to a lower
number of annual
disaster deaths
worldwide.
Thanks to Former Graduate
Students: Dr. Alper Durmus
Dr. Quang Nguyen
W. Tucker Stafford, MS
2017 Book
Hinweis der Redaktion
Traditional asset management systems do not consider failure and disruptions of service arising from catastrophic disasters.
Goals and Policies (Reflect Customer Input)
Short- and Long-Range Plans (Project Selection)
Performance Monitoring (Feedback)
All bridge parts modeled using “Elastic” material model.
8 states have more than 90% of their bridges on rivers/channels.
Displays the number of bridges in Mississippi which are in 80-1,600 ft (approximately 25-500 m) proximity to major rivers.
It is assumed that total 270 bridges identified in 160 ft (approximately 50 m) proximity to a river/channel are already prioritized in FVR groups. Total net benefit in the table (for all identified number of bridges in each FVR group) is based on the assumption that budget is not constrained. If a budget constraint of $15 million is considered, linear programming (LP) optimization Solver selects 15 bridges from FVR category 1 for reconstruction/hardening.