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USAID/OFDA PREPARE Program for Costa Rica and Colombia

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The PREPARE (Preparing Rescue and Emergency Personnel to Ameliorate the Response to Earthquakes) program, for a disaster risk reduction (DRR) and disaster risk management (DRM) program in San José, Costa Rica started in 2015 and its first phase was completed in early 2017. The program was implemented with financial support from USAID/OFDA. The targeted beneficiaries include an estimated 470,000 residents of San José. The goal of PREPARE is to provide national and municipal DRR institutions with a clearer picture of the probable impact of an earthquake, and to assist them to meet their goals to reduce fatalities and lessen the social and economic impact of future earthquakes. In the Phase I component, seismic risk assessment for the built environment was conducted. This program used the OpenQuake platform from the Global Earthquake Model (GEM) to estimate the expected values of number of fatalities, injuries, structural damage, post-earthquake building tag distribution, and debris volume for a (500-year) earthquake scenario. As part of this phase, rigorous data collection was undertaken to classify the building types and distribution of buildings in the target area. The data collection, performed electronically, employed the FEMA 154 type methodology (i.e., rapid visual survey to identify various building characteristics such as structural type, material, configuration, soil, etc.), and accounted for the local construction. Monte Carlo simulations with 10,000 realizations were conducted and the data was aggregated to compute the seismic risk for the city and to identify the zones most vulnerable to the earthquakes due to large pool of weak buildings, high seismicity, large population, or a combination of factors. Analysis showed that high fatality rates (order of 1%), large percentage of damaged buildings (6% tagged yellow or red) and high ratio of physical damage (over 40%) would be expected. The results from this phase is being utilized to develop a post-earthquake damage assessment program, allocate resources for risk reduction and developing a risk management plan with the goal of developing more resilient cities.
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Eleventh U.S. National Conference on Earthquake Engineering
Integrating Science, Engineering & Policy
June 25-29, 2018
Los Angeles, California
USAID/OFDA PREPARE PROGRAM FOR
COSTA RICA
H. Kit Miyamoto
1,
Amir SJ Gilani
2
, and Tsutomu Nifuku
3
ABSTRACT
The PREPARE (Preparing Rescue and Emergency Personnel to Ameliorate the Response to
Earthquakes) program, for a disaster risk reduction (DRR) and disaster risk management (DRM)
program in San José, Costa Rica started in 2015 and its first phase was completed in early 2017.
The program was implemented with financial support from USAID/OFDA. The targeted
beneficiaries include an estimated 470,000 residents of San José. The goal of PREPARE is to
provide national and municipal DRR institutions with a clearer picture of the probable impact of
an earthquake, and to assist them to meet their goals to reduce fatalities and lessen the social and
economic impact of future earthquakes. In the Phase I component, seismic risk assessment for the
built environment was conducted. This program used the OpenQuake platform from the Global
Earthquake Model (GEM) to estimate the expected values of number of fatalities, injuries,
structural damage, post-earthquake building tag distribution, and debris volume for a (500-year)
earthquake scenario. As part of this phase, rigorous data collection was undertaken to classify the
building types and distribution of buildings in the target area. The data collection, performed
electronically, employed the FEMA 154 type methodology (i.e., rapid visual survey to identify
various building characteristics such as structural type, material, configuration, soil, etc.), and
accounted for the local construction. Monte Carlo simulations with 10,000 realizations were
conducted and the data was aggregated to compute the seismic risk for the city and to identify the
zones most vulnerable to the earthquakes due to large pool of weak buildings, high seismicity,
large population, or a combination of factors. Analysis showed that high fatality rates (order of
1%), large percentage of damaged buildings (6% tagged yellow or red) and high ratio of physical
damage (over 40%) would be expected. The results from this phase is being utilized to develop a
post-earthquake damage assessment program, allocate resources for risk reduction and developing
a risk management plan with the goal of developing more resilient cities.
1
President, Miyamoto International, , Los Angeles, CA. kmiyamoto@miyamotointernational.com
2
Manager Earthquake Engineering, Miyamoto International, Sacramento, CA,agilani@miyamotointernational.com
3
Project Engineer, Miyamoto International, Sacramento, CA,
tnifuku@miyamotointernational.com
Eleventh U.S. National Conference on Earthquake Engineering
Integrating Science, Engineering & Policy
June 25-29, 2018
Los Angeles, California
USAID/OFDA PREPARE Program for Costa Rica and Colombia
H. Kit Miyamoto
1,
Amir SJ Gilani
2
, and Tsutomu Nifuku
3
ABSTRACT
The PREPARE (Preparing Rescue and Emergency Personnel to Ameliorate the Response to
Earthquakes) program, for a disaster risk reduction (DRR) and disaster risk management (DRM)
program in San José, Costa Rica started in 2015 and its first phase was completed in early 2017.
The program was implemented with financial support from USAID/OFDA. The targeted
beneficiaries include an estimated 470,000 residents of San José. The goal of PREPARE is to
provide national and municipal DRR institutions with a clearer picture of the probable impact of an
earthquake, and to assist them to meet their goals to reduce fatalities and lessen the social and
economic impact of future earthquakes. In the Phase I component, seismic risk assessment for the
built environment was conducted. This program used the OpenQuake platform from the Global
Earthquake Model (GEM) to estimate the expected values of number of fatalities, injuries, structural
damage, post-earthquake building tag distribution, and debris volume for a (500-year) earthquake
scenario. As part of this phase, rigorous data collection was undertaken to classify the building types
and distribution of buildings in the target area. The data collection, performed electronically,
employed the FEMA 154 type methodology (i.e., rapid visual survey to identify various building
characteristics such as structural type, material, configuration, soil, etc.), and accounted for the local
construction. Monte Carlo simulations with 10,000 realizations were conducted and the data was
aggregated to compute the seismic risk for the city and to identify the zones most vulnerable to the
earthquakes due to large pool of weak buildings, high seismicity, large population, or a combination
of factors. Analysis showed that high fatality rates (order of 1%), large percentage of damaged
buildings (60% tagged yellow or red) and high ratio of physical damage (over 40%) would be
expected. The results from this phase is being utilized to develop a post-earthquake damage
assessment program, allocate resources for risk reduction and developing a risk management plan
with the goal of developing more resilient cities.
Introduction
The PREPARE program intends to develop a new disaster risk reduction (DRR) and disaster risk
management (DRM) program in the canton of San José, Costa Rica. The multiyear program, with
financial support from the United States Agency for International Development/Office of U.S.
Foreign Disaster Assistance (USAID/OFDA), includes cooperation and support of local Costa
Rican partner organizations. The targeted beneficiaries are the citizens of the canton of San José
1
President, Miyamoto International, , Los Angeles, CA. kmiyamoto@miyamotointernational.com
2
Manager Earthquake Engineering, Miyamoto International, Sacramento, CA,agilani@miyamotointernational.com
3
Project Engineer, Miyamoto International, Sacramento, CA,tnifuku@miyamotointernational.com
who live in zones that are at high risk for future earthquakes. The PREPARE program aims to
provide national and municipal DRR institutions with a clearer picture of the probable impact of
an earthquake. The program also wants to help these institutions meet their goals of reducing
casualties and lessening the socioeconomic impact of future earthquakes. The overarching
PREPARE objectives are: i) to strengthen earthquake-response planning and preparedness of
national and municipal DRR institutions in San José (Costa Rica); and ii) to strengthen the risk
management policy and practice of national and municipal DRR institutions for a reduction in
fatalities, injuries, financial costs, and economic disruptions. This objective fits within the OFDA
Policy and Planning subsector and the Capacity Building and Training subsector.
Three main PREPARE components are to be implemented during three phases: i) Assess seismic
hazards and seismic risk to determine the probabilistic damage to building structures and probable
fatalities among the residents in each municipality; ii) Analyze earthquake scenarios based on the
findings from risk assessments; review plans, policies, and practices for the response, including
rapid damage assessments and debris management, and iii) Implement DRR training activities
based upon a review of the results of the earlier phases. The aim is that after completing the
PREPARE program, the partner organizations will have gained knowledge for conducting seismic
risk assessments and analyzing earthquake scenarios, and will continue to improve their DRR and
DRM capacity in the future. The findings have been reviewed and discussed with key stakeholders
including local planning agencies and academia. This paper focuses on Phase I of the project.
Phase I description
The canton of San José, Costa Rica, is in a high seismic zone and is at high risk for damaging
earthquakes. The 1991 Mw 7.8 Limón Earthquake resulted in 50 fatalities and caused collapse of
many buildings. Many of the newer buildings in the San José have been constructed using modern
seismic codes, are well constructed, and meet high seismic. The canton also houses numerous older
structures that are not well built, especially in poorer neighborhoods.
The risk assessment algorithm used the following parameters as input: (1) design-level seismic
hazard; (2) citywide exposure data, including structural properties and number of occupants; (3)
building fragility for the common building types; and (4) consequence functions, relating the
number of fatalities, structural damage, and debris volume to the building damage state. The
seismic hazard parameters were based on the recent studies that characterized the seismicity of
key Central American cities [5].
Exposure model
The exposure model (incorporating the number and type of buildings, building footprint, and
occupants) was developed through a statistical methodology by using available census data and
the field survey of buildings [1] and [2]. In the statistical process, building typologies and
homogeneous development patterns (described in the following sections) are associated with each
other and the building exposure distributions according to its typology in each zone were
developed with occupant information. The generated exposure model was then used as input for
OpenQuake. The key data for the target area is presented in Table 1. Figure 1 presents key factors
for the exposure model.
Table 1. Key statistics for the canton of San José
Political divisions Buildings Occupants
Barrios Districts No. Area, m
2
Day Night
196 11 85,800 26,900,000 472,000 352,000
Districts and neighborhoods Number of buildings
Daytime population Nighttime population
Figure 1. Components of the exposure model
Zones for surveyed buildings
The canton of San José was divided into zones based on the 7 development patterns; see Table 2.
The target area was divided into 654 polygons according to the development types; see Figure 2.
Table 2. Development patterns
Pattern Description
1 Open space
2 Informal
3 Industrial
4 Single family
5 Urban
6 High urban
7 Commercial Figure 2. Zoning according to development type
Building typologycurves
Buildings in the canton of San José were categorized into eight construction types based on the
lateral-force-resisting system (LFRS) and the construction material. Seven of the construction
types were further subdivided into two groups based on the number of stories. The resulting 15
building types are listed in Table 3. Fragility curve for these building types was then developed
and used in seismic risk analysis.
Table 3. Building typology that was used in analysis
Type LFRS and material
01 & 02 Nonengineered light structure
03 & 04 Unreinforced masonry
05 & 06 Confined/reinforced masonry
07 & 08 Reinforced concrete moment frame
09 & 10 Reinforced concrete shear wall
11 & 12 Steel moment frame
13 & 14 Steel braced frame
15 Unreinforced masonry informal area
Building exposure inventory
2,575 building assets were developed through the statistical process described above and included
in the exposure pool. Each asset contains multiple buildings (i.e., total number is then 85,800) and
corresponding occupants but one building type. All assets representatively reflect the building
environment of San Jose and are distributed over the target area through the exposure development
process. The exposure inventory was obtained by using satellite imagery, available census data
and development patterns and supplemented by field surveys of 576 buildings. The spatial
distribution of those surveyed buildings is shown in Figure 3.
Figure 3. Geographic distribution of surveyed buildings
Fragility and Damage Functions
The fragility curves for the 15 building types were based on data from FEMA Hazus ([3] and [4]),
which is a natural hazard analysis tool established by FEMA. The fragility curve consists of
earthquake intensity and occurrence probability of damage state in order to express building
seismic capacity by damage probability. FEMA Hazus provides PGA fragility curves according to
building types and height, however those fragility curves have to be modified to use for other
environment and country because the curves were originally developed for the U.S. FEMA Hazus
prepares the modification procedure and this project followed the procedure and adjusted the
fragility curves to match with San Jose environment. The adjustments accounted for the spectral
shape, average magnitude [5], site class [6] , soil amplification factor, and epicentral distance.
Figure 4 presents the sets of plots for the various DS fragility curves for the low rise buildings.
The figures were generated by using the San José-modified parameters of fragility curves.
Non-engineered Unreinforced masonry
Confined masonry Reinforced concrete moment frame
Reinforced concrete shearwall Informal construction
Figure 4. Fragility curves for low-rise buildings
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6
ProbabilityofExceedingaDS
PGA(g)
DS1
DS2
DS3
DS4
Risk assessment procedure
The probabilistic risk assessment used Monte Carlo simulations (MCSs). To obtain convergence
in results, 10,000 MCSs were performed. The risk analysis procedure was as follows (Figure 5).
The procedure for each building and for each of the MCS runs involved selecting a scenario
earthquake and using the fragility and exposure data to run OpenQuake engine, determine the DS
distributions, and then by using the consequence functions (fatalities, structural damage, and debris
volume) and the obtained DSs, compute structural damage, fatality, and debris volume. The
expected values for each structure were then computed and aggregated for the city.
Figure 5. Process flow using the OpenQuake risk engine
Figure 6 presents MCS outcomes for a sample building. For this particular building, out of 10,000
simulations, approximately 1,400, 800, 2,350, 3,600, and 1,850 outcomes fall into the No Damage,
Slight, Moderate, Extensive, and Complete damage states, respectively.
Figure 6. Distribution of MCS outcomes for a sample building
Earthquake seismic risk analysis results
Geographical distribution of seismic risk
The graphical distribution of findings from probabilistic risk analyses are presented in Figure 7,
which presents the spatial distribution of structural damage, fatalities, and red-tagged buildings
and debris volume, respectively. In the figures, the color distribution indicates the expected
intensity of each consequence. The data from these maps can be used to identify the barrios that
are most susceptible to earthquake losses, which can then be prioritized for allocation of resources
for seismic retrofit and earthquake preparedness. In particular:
The distribution of fatalities in barrios differs significantly for daytime and nighttime earthquake
scenarios. This difference is attributed to citizens’ commuting to work from their households during
the day. As such, it is imperative that both cases be considered for risk planning.
Depending on the consequence parameter (fatality, damage, debris) chosen, various barrios show
increased vulnerability. However, certain barrios appear to be vulnerable for multiple risks. For
example, see the barrio circled in the figures. Such barrios may need extra attention when planning
risk mitigation and preparedness programs.
Ratio of highly damaged buildings Building area
Daytime fatalities Nighttime fatalities
Red-tagged buildings Debris volume, m
3
Figure 7. Spatial distribution of seismic risk consequences
Aggregated results
Table 1 presents the exposure data for the studied area. The canton of San José is home to
approximately 352,000 (nighttime) to 472,000 (daytime) occupants and has nearly 85,800
buildings. It is important to keep these numbers in mind when reviewing the aggregated data.
The anticipated physical damage to the built area that is subject to the design-level earthquake is
listed in Table 4. Note that approximately 60% of the buildings would be yellow- or red-tagged.
The damage area is nearly 42% of the total building area, and the earthquake could result in over
4,940,000 m3 of debris or approximately 350,000 truckloads (based on. 14 m3 per truckload). The
anticipated fatalities from a design-level earthquake are listed in listed in Table 4. The area could
experience close to 3,000 fatalities, which is nearly 0.7% of the population of the canton.
Table 4. Expected values of structural loss and fatalities
Damage Daytime
fatalities
Nighttime
fatalities Yellow-tagged Red-tagged Volume,
m3
% Area, m2 % No. % No. % No. % No.
42% 11,350,000 0.64% 3,000 0.76% 2,700 33% 28,000 26% 22,500 4,940,000
Conclusions
Experience from past and recent earthquakes in Central and South America has shown that
extensive damage affects the entire built environment, resulting in loss of life and causing physical
damage that can be a significant portion of the country’s GDP. Within Central America, San
José—the capital and the major economic center of Costa Rica, with a population of approximately
450,000—is the subject of this report. The analysis results show that:
The number of buildings that are expected to be yellow-tagged (moderately damaged) or red-tagged
(severely damaged or collapsed) is estimated at about 51,000 structures, or approximately 60% of
the building stock.
Depending on the time of event, approximately 3,000 fatalities (for an estimated rate of 0.7%) is
anticipated.
The generated debris volume of 4,940,000 m3 or 350,000 truckloads is significant and must be
accounted for.
The high physical damage and fatality rates from an earthquake that are computed point to the
need for development of a risk mitigation program. Results of the findings were presented to
stakeholders and the project report (Spanish) was distributed to various agencies to provide
information about the potential earthquake consequences, the need to take action, and to assist in
development of such program. As part of such a program, it is recommended that the following
strategies should be implemented:
To mitigate risk, provide a seismic strengthening program for key structures that are identified as
having the most risk because of their inherent structural vulnerability and density of occupants.
To prepare for risk, establish a damage assessment program for earthquake hazard. It is critical to
train and certify engineers and to establish logistics. Such a program will improve response and
recovery efforts after major earthquakes.
To inform about the risk, establish communication and public outreach programs. It is critical to
communicate results and the abovementioned recommendations. Communities should be informed
about earthquake risk and risk reduction methods.
Acknowledgements
The Financial support of USAID in sponsoring this project is kindly acknowledged. The technical
support from the Global Earthquake Model engineers is also acknowledged. The authors would
like to thank many local engineers and volunteers who assisted in data collection, performing
surveys, and facilitating the project; in particular, the significant contributions of. F. Lanning,
Diana Ubico, Jaime Eraso, and Sabine Cast are acknowledged.
References
[1] Global Earthquake Model Foundation (GEM) (2016). The OpenQuake-engine User Manual, Global Earthquake
Model (GEM) Technical Report 2016-03.
[2] Global Earthquake Model Foundation (GEM) (2014). User guide: Tool for spatial inventory data development,
Global Earthquake Model (GEM) Technical Report 2014-05.
[3] Federal Emergency Management Agency (FEMA) (2001a). Hazus-MH 2.1, Multi-hazard Loss Estimation
Methodology, Earthquake Model. Federal Emergency Management Agency, Washington, DC, USA.
[4] Federal Emergency Management Agency (FEMA) (2001b). Hazus-MH MR5, Advanced Engineering Building
Module (AEBM), Technical and User’s Manual. Federal Emergency Management Agency, Washington, DC,
USA.
[5] Climent, Á., Rojas, W., Alvarado, G.E., and Benito, B. (2008). Proyecto Resis II Evaluación de la amenaza
sísmica en Costa Rica.
[6] CR (2010) Codigo Sismico de Costa Rica, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica.
... From the results, it can be interpreted that the set of buildings studied is predominantly composed of one-or twostorey residences, built with a wall lateral load resisting system (LLRS) of confined-reinforced masonry (MCR), a local Costa Rican material/construction practice. This is in general agreement with recent exposure models developed for Costa Rica, at a national level by Calderón and Silva (2019) and at the local San José canton level by Miyamoto et al. (2018), using an indirect top-bottom and direct bottomup approach respectively, as defined by (Simpson et al. (2014). ...
Article
Full-text available
The present work shows the implementation of a data collection strategy for characterizing large amounts of buildings efficiently by the conduction of remote surveys on 360° panoramic images and aerial photographs. A set of 7,296 buildings from the Latin American city of San José, Costa Rica were studied and characterized from a structural engineering point of view, obtaining information like occupancy type, height, type of lateral load resisting system, and structural irregularities, among others. Also, an estimation of the error of the remote surveys was performed, by contrasting its results with the ones of field ( in situ ) surveys applied on a subset of 556 structures denominated “control buildings.” The results show that for San José buildings, the predominant occupancy type, height, type, and material of the lateral load resisting system are, respectively, residential, one or two storey, wall type of confined-reinforced masonry. The overall precision level estimated for the remote surveys was 75 %, which the authors consider acceptable and an improvement when compared to more popular surveys, for example, the field surveys carried out during a population and housing census that typically have an estimated precision level of 50 %. The results proved the adopted strategy to be a promising one, albeit subject to improvements to increase its precision and reduce the implementation time.
... Field surveys are often undertaken when the size of the building inventory is relatively small, thus allowing a detailed characterization of the assets. For example, Miyamoto et al. (2018) performed in situ inspections of more than 500 buildings in the municipality of San Jose´, the capital of Costa Rica. The study used detailed information about the exposed assets to calculate the volume of debris caused by earthquakes and proposed post-disaster management solutions. ...
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This study proposes a framework to forecast the spatial distribution of population and residential buildings for the assessment of future disaster risk. The approach accounts for the number, location, and characteristics of future assets considering sources of aleatory and epistemic uncertainty in several time-dependent variables. The value of the methodology is demonstrated at the urban scale using an earthquake scenario for the Great Metropolitan Area of Costa Rica. Hundreds of trajectories representing future urban growth were generated using geographically weighted regression and multiple-agent systems. These were converted into exposure models featuring the spatial correlation of urban expansion and the densification of the built environment. The forecasted earthquake losses indicate a mean increase in the absolute human and economic losses by 2030. However, the trajectory of relative risk is reducing, suggesting that the long-term enforcement of seismic regulations and urban planning are effectively lowering seismic risk in the case of Costa Rica.
Hazus-MH 2.1, Multi-hazard Loss Estimation Methodology, Earthquake Model
Federal Emergency Management Agency (FEMA) (2001a). Hazus-MH 2.1, Multi-hazard Loss Estimation Methodology, Earthquake Model. Federal Emergency Management Agency, Washington, DC, USA.
Technical and User's Manual
Federal Emergency Management Agency (FEMA) (2001b). Hazus-MH MR5, Advanced Engineering Building Module (AEBM), Technical and User's Manual. Federal Emergency Management Agency, Washington, DC, USA.
Proyecto Resis II Evaluación de la amenaza sísmica en Costa Rica
  • Á Climent
  • W Rojas
  • G E Alvarado
Climent, Á., Rojas, W., Alvarado, G.E., and Benito, B. (2008). Proyecto Resis II Evaluación de la amenaza sísmica en Costa Rica.
Codigo Sismico de Costa Rica
CR (2010) Codigo Sismico de Costa Rica, Instituto Tecnológico de Costa Rica, Cartago, Costa Rica.