THE UNITED STATES OF CRITICAL
INFRASTRUCTURE AND SEISMIC HAZARDS
Elyse A. Maurer
Abstract
With areas of known risk, such as the San Andreas Fault, paired with highly populated urban areas,
the technological and economic vulnerability, should a seismic event occur, is at an all-time high.
Due to the potential of technological and economic losses, the importance of seismic hazard
mitigation in areas of critical infrastructure has never been so important. This analysis used ArcGIS
processes such as the identity tool to combine and intersect peak ground acceleration data with
infrastructure data. Results determined how much of our nation’s critical infrastructure is at high,
moderate, and low risk to seismic hazards. Hospitals, dams, ports, interstates, and urban areas
were assessed to determine their potential risk in relation to the peak ground acceleration data.
It has been determined that roughly 10% of the critical infrastructure is at high risk, 19% is at
moderate risk, and 71% is at low risk. That being said, the 10% of infrastructure at high risk is within
highly populated areas. Highly populated areas at high risk pose a greater economic threat should
a seismic event occur.
May 26, 2015
Introduction
Today, our nation has developed an economy that has exceeded any of that before. The value and
economic strength of a nation or its states provides overall success. Much of what allows an economy
to run smoothly and effectively is infrastructure and urbanized environments. There is little that can
interfere with infrastructure on such a large scale that would be detrimental to our economy.
However, natural disasters do have the potential to wreak havoc, or even destroy infrastructure and
the economies dependent upon them.
Of the most dangerous to infrastructure is the earthquake. The ground shaking and jolting easily
breaks foundations, jostles power sources, and can create secondary hazards such as fire, tsunamis,
and flooding. When researched, you will see that there are fault lines nearly everywhere, and that
earthquakes occur all day, every day. Often, these quakes are too small to sense or feel without highly
sensitive equipment. But rarely, and dangerously, and earthquake will be large enough to put cities,
states, and nations at risk of economic loss.
Literature Review
The importance of hazard mitigation in areas of critical infrastructure has never been so important.
With areas of known risk, such as the Andreas fault or the Cascadia Subduction Zone, paired with
highly populated urban areas within seismic risk areas, the technological and economic vulnerability,
should a seismic event occur, is at an all-time high (Calvi, et al., 2006). As a result of a seismic event,
“Failure of critical infrastructure such as bridges, harbor docks, hospitals and communication systems
delayed search and rescue operations and relief efforts, which increased the suffering of the survivors”
(Ghobarah, Saatcioglu, & Nistor, 2006). As of April 2015, researchers have determined that roughly 140
million people live within an earthquake risk area (Oskin, 2015) (Jaiswal, 2015). That number is nearly
1
half of the entire United States population. This research was conducted for the lower 48 states which
is the focus of my analysis.
Other notable applications to the importance of peak ground acceleration data is the use of real-time
predictions of losses due to a seismic events (Erdik, Sesetyan, Demircioglu, Hancilar, & Zulfikar, 2011)
(Hancilar, Tuzun, Yenidogan, & Erdik, 2010). These losses can be economic, intrinsic, or personal (death
of citizens, etc.). Research has developed a real-time analysis for both the global and the local scale,
depending on the scale of the event itself (Erdik, Sesetyan, Demircioglu, Hancilar, & Zulfikar, 2011).
This can become a powerful tool for seismic hazards in order to rapidly mitigate the amount of loss
seen from an event. Due to the quick speed of onset in an earthquake, there is little time to react to
reduce the total losses (Tobin & Montz, 1997). Real-time predictions would greatly benefit our abilities
to curb critical infrastructure loss.
To be clear on the potential impacts of an event occurring, take a look at the current state of the
Seattle fault. The Seattle fault is located in such a densely populated, commercialized, and unprepared
area of Washington State that an earthquake here could be catastrophic. Current reports suggest that
the Seattle fault could produce a magnitude 7.7 earthquake due to its long-term slip rate of 0.25
mm/year (Pratt, Johnson, Potter, Stepherson, & Finn, 1997). Certain infrastructure, such as the
aqueduct or ports, may not be able to withstand such an earthquake.
Even the Seattle fault pales in comparison to the potentially life-altering Cascadia subduction zone
earthquake that has the ability to cripple the northwestern coastline. This earthquake will occur when
the Juan de Fuca plate slips below the North American plate. Shocking studies have measured the
potential impacts of this event to generate a magnitude 9 or higher earthquake (Clague, 1997). Each
magnitude of increase is an energy release 31 times more than that of the previous magnitude. The
2
power of shaking is 10 times greater than that of the previous shaking of an earthquake (Tobin &
Montz, 1997). That translates to a 100 times difference in shaking from a magnitude 7 earthquake to a
magnitude 9 earthquake.
While the west coast of the United States is seemingly littered with potential earthquake zones, an
often overlooked fault is the New Madrid fault in the central portion of the United States. This area is
overlooked due to its relatively low seismic activity compared to that of other regions in the US
(Elnashai, Jefferson, Fiedrich, Cleveland, & Gress, 2009). This geographical area is important due to the
fact that it is home to some of the largest historical earthquakes of our nation (Elnashai, Jefferson,
Fiedrich, Cleveland, & Gress, 2009). Though historical infrastructure damages were not great (this area
was not highly populated in the early 1800s), today, infrastructure damages could be quite high.
Studies have shown that today’s urban development of the area could pose high risk to critical
infrastructure of the area (Elnashai, Jefferson, Fiedrich, Cleveland, & Gress, 2009).
The goal of this analysis is two-fold. One goal is to determine areas of vulnerability using the peak
ground acceleration (PGA) data. The other goal is to determine what amount of critical infrastructure is
at risk. Through analysis, I will be able to synthesize two areas of research to produce a comprehensive
representation of how PGA affects our nation’s infrastructure.
Current research has stressed the importance of peak ground acceleration data in providing efficient
emergency response (Wu, Shin, & Chang, 2001). An effective emergency response system is crucial for
providing access to critical infrastructure. A PGA map allows for data of high to low values of ground
shaking within as early as two minutes after the quake itself (Cite). This data allows emergency
responders to pinpoint the earthquakes’ epicenter while providing data for where emergency
assistance should be dispatched.
3
By providing data that shows the epicenter and resulting intensities of ground shaking, critical
infrastructure can be monitored, protected, and aided. The effects, should an earthquake occur, are
detrimental to the survival and success of infrastructure. Studies of earthquake repercussions suggests
that critical infrastructure failure (such as hospitals, ports, and interstates) create a delayed search and
rescue effort as well as a halted relief method (Hancilar, Tuzun, Yenidogan, & Erdik, 2010). By
extending the time it takes to reach relief or to execute search and rescue missions we are increasing
the damages to our population, infrastructure, and economy. Delaying rescue efforts may not be highly
problematic in areas of low population or infrastructure, but areas of concentrated buildings, people,
and roads pose a much greater concern.
Critical infrastructure in and of itself is stated to be so “critical to [a nation] that their incapacity would
harm the nation’s physical security, economic security, or public health” (Library of Congress, 2005).
Paired with the concentration of infrastructure and people, the potential for incapacity of our
infrastructure is high. For instance, ports are a huge economic support for many major waterways.
Many local, state, and national agencies benefit economically from the smooth productivity of these
ports and rely heavily of them for their economic value. Being that ports are located on waterways,
they are at an exceptionally high risk for hazard damage. A strong enough earthquake could surely
rattle the foundation and severely damage the structure, costing thousands of dollars to fix. That being
said, another danger with ports lies with the secondary hazard that results from an earthquake. The
tsunami can be extremely catastrophic in subduction zone earthquakes such as the Cascadia
Subduction Zone in the Puget Sound.
Ports are not only expensive to maintain, but have high economic values. Damaged ports have the
potential to cripple entire economies. For instance, the west coast has several major ports that provide
commodities for the interior of the United States. These ports are the only western access points to
4
the US without having to navigate through the Panama Canal. If these ports were to be damaged, not
only would the city and state’s economy be affected, but our entire nation would face major increases
in cost for products due to the need for alternate routing. It is important to note that not only are ports
vulnerable, but they are often built near coastlines. This poses an even greater threat due to the
quality of soils found in these areas. Coastal regions are typically softer soils or mud flats that have a
higher potential for liquefaction when shaking occurs (Chleborad & Schuster, Accessed 2015).
Additionally, areas such as the Columbia River Valley are loaded with sand bars and problematic soils
that would close the mouth of the Columbia River to boats should an event occur (Chleborad &
Schuster, Accessed 2015).
In addition to ports, dams are a highly vulnerable man-made structure that provides a valuable
resource to our nation. Energy, water volume regulation, and habitats for species are all a result of
proper dam function. Research has shown that after the shaking of an earthquake, dams can fail as
soon as 24 hours after the event (Seed, De Alba, & Makdisi, 1978). That being said, dams are typically
built to withstand shaking to a certain threshold. Once that threshold is crossed, or the dam is
compromised in any way, the result can become dam failure. Many researchers have used analysis
tools to model the possibilities of infrastructure damage during natural hazard events, including that of
dams and ports.
While I used a simple overlay method of peak ground acceleration and infrastructure data to
determine where infrastructure intersected with set ranges of PGA data, there are other ways to
model this vulnerability. One study has used digitized orthophotos paired with historical information to
create a GIS program that modeled seismic hazard risks associated with landslides and floods (Van
Westen, Montoya, Boerboom, & Coto, 2002). Primary research focused on goals similar to that of my
research: the concern of increased vulnerability in urban areas and the analysis of “potential losses”
5
(Van Westen, Montoya, Boerboom, & Coto, 2002). One key aspect that this research brought to its
analysis was the use of remotely sensed data. This is an important contribution to the hazard analysis
due to the fact that our earth is constantly changing. A satellite image is able to provide up-to-date
images of our earth, pre and/or post hazard events (Van Westen, Montoya, Boerboom, & Coto, 2002).
By using satellite imagery, we are able to determine various land use/land cover types, areas of high
density/low density, and in turn, areas of risk. A bird’s eye view of a landscape reveals more than can
be measured from the ground. Subtle changes such as soil saturation or drought can be indicative to
potential hazard conditions. This can help to mitigate more effectively against potentially harmful
hazard events.
In all, there are multiple methods for developing a seismic hazard analysis. No matter which method
you choose, the bottom line is the same – the importance of analysis on critical infrastructure
vulnerability is at its peak. The advancement of real-time peak ground acceleration and rapid
earthquake loss maps are a crucial advancement to limiting the amount of losses due to a seismic
event. These events are not isolated and have proven to impact a great majority of our nation. Paired
with the economies, urban development, and infrastructure we have achieved in recent decades, we
would be wise to take note of this potential issue.
Methods
Data
Data for this analysis was derived from the United States Geological Service (USGS) Earthquake
Hazards Program, USGS National Map, and Western Washington University data sets. Data was
downloaded by myself for the use of this project. I derived this data to achieve its current format.
6
Region of Interest
For my analysis, I chose to focus on the seismic and critical infrastructure vulnerability in the lower 48
states of the United States of America. An efficient way of measuring seismic vulnerability is by way of
a Peak Ground Acceleration Map. A Peak Ground Acceleration map (PGA) allowed me to visually
represent areas of high to low seismic concern (Figure 1). In order to better work with my data and
allow for unified representation of all datasets involved, data was re-projected into a projected
coordinate system. In my analysis, I chose North America Lambert Conformal Conic for its least amount
of distortion in my area of interest. The PGA map was symbolized by the acceleration value for each of
the lines provided. The acceleration values is a measure of meters per second. This allows for the
analysis of ground shaking as a result of seismic activity. The amount and speed of shaking is essential
to understanding how seismic activity affects our critical infrastructure.
7
Figure 1. This map indicates the acceleration values for the lower 48 states in the United States. The acceleration value
represents the rate in meters per second that occurs during the shaking of a seismic event. Acceleration values are
critical to determining the severity of seismic events.
I chose to symbolize this data into fifteen categories. This allowed me to break the lines into three
equal groups; the groups were divided by acceleration values of 0-14, 15-40, and 41-200. These groups
are seemingly unequal. However, not all data values in-between each of these groups are represented.
In all, each of these categories contains five data points, with the lowest and highest values
represented. Initial PGA data extended into the waters of the Pacific and Atlantic Oceans as well as the
Gulf of Mexico. This data was clipped to represent only the impacts observed on land to further my
analysis of critical infrastructure.
8
The lines of acceleration would not provide me a way to calculate where critical infrastructure fell
within each of the values. To mitigate this problem, I used the Feature to Polygon tool. To allow for the
completion of polygons I first needed to digitize the acceleration lines that were not already closed. In
order to digitize each of the lines, I needed to assign an acceleration value to each of the new lines.
Once completed, I was able to perform the change to polygons. The resulting polygons were able to be
symbolized by the acceleration value field and thus became the basis for my low, moderate, and high
risk values for the critical infrastructure.
Critical Infrastructure
The critical infrastructure was chosen due to their importance to economy, citizen safety, access for
emergency responders, and the possibility of secondary damages caused as a result of seismic activity.
The critical infrastructure represented is interstates, urban areas, dams, ports, and hospitals. These five
components, in relation to the PGA data, will be presented as high, moderate, and low risk.
In order to symbolize infrastructure in a way that represented my PGA acceleration data, I used the
identity tool. This allowed me to spatially join the PGA data as well as the individual infrastructure
data. From here, I was able to symbolize each of the infrastructure datasets by acceleration value
which then matched my PGA data. All infrastructure was then symbolized by the same fifteen values as
the PGA data (3 categories of 5) with risk values of low, moderate, and high.
Infrastructure left in its initial form was expansive and difficult to differentiate. The clipping tool has
allowed me to limit some infrastructure to only defined urban areas. This was beneficial for
components such as dams, which are often in remote locations. However, this was not helpful for
hospitals or ports, which often fall within urban areas, where their use is in the highest demand. To
resolve this issue, I symbolized hospitals and ports with a simple marker and varying degrees of
9
transparency. This allowed me to visualize areas of high infrastructure concentration without
compromising the other data shown.
To determine the severity of infrastructure at risk I selected for infrastructure within each of my risk
values (low, moderate, and high) and counted the number of times each of the infrastructure fell
within each risk value. This allowed me to determine a sense of economic vulnerability. To count the
number of points that fell within each risk value, I used the Select by Attributes tool to query a
selection in each of my three categories. This provided me a raw number without having to handcount. To determine overall risk for each of the values, I divided the total hits per category by the total
number hits in all three categories.
Finally, I showcased hot spots throughout the United States that high both high acceleration values and
representation of critical infrastructure. These areas are to be shown alongside the overall map of the
lower 48 states in the United States.
Results
Calculations and Findings
The conclusion of my infrastructure and seismic hazard map showed that infrastructure along the West
Coast, much of the western half of the United States, and a centralized portion of the south east are at
moderate to high risk. Areas of low risk include the mid-west, much of the southern border, and the
northern and eastern portions of the United States (Figure 2). Infrastructure losses in areas of high
economic value (such as urbanized areas) can see monetary losses totaling “4.5 billion dollars per year
in the long term” (USGS, California Geological Survey, and FEMA). These agencies have declared a 7
percent risk of a magnitude 8 or higher earthquake in California within the next three decades (USGS,
California Geological Survey, and FEMA). (USGS, California Geological Survey, and FEMA). The entirety
10
of the west coast is projected to be at a high risk for seismic hazard, with exception of the Puget Sound
and small portion of southern California.
Figure 2. This map represents the peak ground acceleration with an overlay of critical infrastructure. The green squares
indicate hospitals, the blue triangles are ports, the yellow/green circles are dams within urban areas, and the black lines
are interstates. Due to intersections with various PGA values, the interstates are broken into “portions” and thus the risk
values associated with this infrastructure are very high in relation to the number of interstates shown.
Along the west coast, there are ten ports at high risk and eleven ports at low risk (Figure 3). In the
eastern United States, high risk infrastructure follows an inland path from the coast (Figure 4). In all, it
seems as though majority of the infrastructure fell into the low risk category with exception of dams
which had pretty equal distribution between moderate and high risk (Table 1).
11
Figure 3. This map represents the western portion of the United States and its hot spots of peak ground acceleration.
Here, you can see a clearer depiction of the individual infrastructure that lies within high and moderate risk.
12
Figure 4. This map represents the eastern portion of the United States and its hot spots of peak ground acceleration.
Here, you can see a clearer depiction of the individual infrastructure that lies within high and moderate risk.
Table 1. This table represents each critical infrastructure with the corresponding risk values. All values were computed
using the acceleration value field provided in the PGA data. The Identity tool allowed me to represent infrastructure by
the acceleration value.
Risk
Value
Ports
Hospitals
Urban
Areas
Dams
Interstates
Low
Moderate
High
80
26
14
5,087
1,294
765
4,708
1,276
447
109
31
66
994
312
224
The total number of critical infrastructure (based on the infrastructure shown in this analysis) in the
lower 48 states of the United States totals 15,433 individual counts. Of the 15,433 counts, 1,516 are at
high risk, approximately 2,932 are at moderate risk, and 10,957 are at low risk. This calculates to
13
roughly 10% of all infrastructure at high risk, 19% of all infrastructure at moderate risk, and 71% of all
infrastructure at low risk for seismic hazards.
Discussion
While the percentage of critical infrastructure at high risk is relatively low, it is important to note that I
have not included all infrastructure that could generate potential damages. If all infrastructure was to
be analyzed, the percent at high risk may be altered. Additionally, I experienced some data that could
be enhanced for later analysis. Hospitals, for instance, included little information about the type of
care provided or capacity. This lack of information left me with a very high number of hospitals with no
feasible way to narrow the field to such categories as “major hospitals.”
Similar to the hospital data, the dam’s data did not seem to line up properly with existing rivers data.
While the dam’s data was from USGS, it is important to realize that this may not be the best data
source and could be incorrect or simply inaccurate. That being said, it is possible that the rivers data is
incorrect or that the scale at which the dam’s data was created did not account for such a need in
accuracy.
Another issue I experienced was the fracturing of interstates. Due to the use of acceleration values for
determining overall infrastructure risk, my interstates results became fragmented. Being that an
interstate is a long, continuous piece of data, it makes sense that there would be areas of different risk
values. As a result, my final risk assessments for interstates are described as portions of interstate
rather than the entirety of the interstate itself.
In all, I found the results to be different from what I had expected. I would have assumed that more of
our infrastructure would be at high risk. At only 10% high risk, it seems as though we would not need
to place much worry on these areas and that our risk for economic damages are slim. That being said, I
14
believe that the 10% of high risk infrastructure is in areas of high and dense population. This makes for
a more serious situation even though it seems to be of lesser danger than low risk infrastructure.
Conclusion
While the overall high risk for infrastructure seems low, it is important to note that highly populated
areas, such as where the highest risk areas are located, poses a greater threat to our economies than
that of any more remote locations. These high populated areas provide economic imports, exports,
and stability for the nation as a whole. While the nation’s economy will likely be okay, the state’s
economy could be crippled. In addition, the costs of commodities, access to jobs, and cleanup efforts
would be greatly altered.
Further research should analyze the 10 percent of infrastructure that is at high risk. Due to the fact that
much of the high risk portions are located along the coastlines, this is crucial for additional research
due to the fact that further threats arise from the coastlines. Tsunamis, oil spill contaminations, habitat
destruction, and exports are only a small portion of a greater issue should a large seismic event occur.
In the Puget Sound region of Washington State, three earthquakes, all greater than magnitude 6 are
projected to occur at some point in future, the Cascadia Subduction Zone fault being of the greatest
danger. But this is not the only fault to be concerned with. The San Adreas fault in California, the New
Madrid fault in central United States, and the Seattle Fault in western Washington State all pose great
threats to densely populated areas of the United States. The risk is great, but the knowledge is there
and the ability to mitigate for such an event is possible. Our nation much place more emphasis on the
importance of protecting our critical infrastructure and economic assets, as well as our citizens who
may be a risk in these areas.
15
Works Cited
Calvi, G., Pinho, R., Magenes, G., Bommer, J., Restrepo-Velez, L., & Crowley, H. (2006). Development
of Seismic Vulnerability Assessment Methodologies Over the Past 30 Years. Journal of
Earthquake Technology, 75-104.
Chleborad, A., & Schuster, R. (Accessed 2015). Ground Failure Associated with the Puget Sound
Region. US Geological Survey, 373.
Clague, J. J. (1997). Evidence for Large Earthquakes at the Cascadia Subduction Zone. Reviews of
Geophysics, 439-460.
Elnashai, A. S., Jefferson, T., Fiedrich, F., Cleveland, L. J., & Gress, T. (2009). Impact of New Madrid
Seismic Zone Earthquakes on the Central USA. Urbana, Illinois: Mid-America Earthquake
Center.
Erdik, M., Sesetyan, K., Demircioglu, M., Hancilar, U., & Zulfikar, C. (2011). Rapid Earthquake Loss
Assessment After Damaging Earthquakes. Soil Dynamics and Earthquake Engineering, 247266.
Ghobarah, A., Saatcioglu, M., & Nistor, I. (2006). The Impact of the 26 December 2004 Earthquake and
Tsunami on Structures and Infrastructure. Engineering Structures, 312-326.
Hancilar, U., Tuzun, C., Yenidogan, C., & Erdik, M. (2010). ELER Software - A New Tool for Urban
Earthquake Loss Assessment. Natural Hazards and Earth System Sciences, 2677-2696.
Jaiswal, K. (2015). USGS. Retrieved from U.S. Geological Survey.
Library of Congress. (2005). Vulnerability of Concentrated Critical Infrastructure: Background and
Policy Options. Washington DC: Washington DC Congressional Research Service.
Oskin, B. (2015, April 24). Half the US Faces Earthquake Risk. Retrieved from Live Science:
http://www.livescience.com/50609-half-the-us-faces-earthquake-risk.html
Pratt, T. L., Johnson, S., Potter, C., Stepherson, W., & Finn, C. (1997). Seismic Reflection Images
Beneath Puget Sound, Western Washington State: The Puget Lowland Thrust Sheet
Hypothesis. Journal of Geophysical Research: Solid Earth, 27469-27489.
Seed, H. B., De Alba, P. A., & Makdisi, F. I. (1978). Performance of Earth Dams During Earthquakes.
Journal of the Geotechnical Engineering Division, 967-994.
Tobin, G. A., & Montz, B. B. (1997). Physical Dimensions of Natural Hazards. In Natural Hazards.
Tobin, G., & Montz, B. (1997). Physical Dimensions of Natural Hazards. Natural Hazards.
Van Westen, C. J., Montoya, L., Boerboom, L., & Coto, E. B. (2002). Multi-Hazard Risk Assessment
Using GIS In Urban Areas: A Case Study for the City of Turrialba, Costa Rica. 1-72.
Wu, Y.-M., Shin, T.-C., & Chang, C.-H. (2001). Near Real-Time Mapping of Peak Ground Acceleration
and Peak Ground Velocity Following a Strong Earthquake. Seismological Society of America.
16