Category: Articles

3 Nov

500 years of earthquake history: how academia and government are collaborating to reduce earthquake risk in the Dominican Republic?

500 years of earthquake history: how academia and government are collaborating to reduce earthquake risk in the Dominican Republic?

By Ashley Morales-Cartagena, MSc

The Dominican Republic (DR) is considered a hotspot for disasters resulting from natural hazards. According to the World Bank from 1980 to 2008 disasters affected 2.65 million people in the DR. We have learned from more frequent hydro-meteorological disasters, however, earthquakes have been less frequent, and there is no ‘culture of preparedness’ for earthquakes.

While the scientific community has long anticipated the “Big One”, the seismic risk has not been adequately communicated to the public. It is up to the emerging generation of leaders in risk reduction and mitigation to ensure the country’s resilience to future earthquakes. Academia, industry, and civic organizations are working to identify ways to help build an earthquake-resilient country. In this blog post, I will discuss seismicity and the risk profile in the DR, prior and ongoing work to understand and reduce earthquake risk, and academic-government organizations tackling the challenges of communicating and reducing earthquake risk.

1. Seismic Hazard of the Dominican Republic

The DR is a country located on the island of La Hispaniola, which it shares with the Republic of Haiti, in the Greater Antilles of the Caribbean. It occupies the eastern two-thirds of the island. It has witnessed destruction from natural hazards, due to its exposure to recurrent phenomena of hydro-meteorological and, less frequently, earthquakes.

La Hispaniola is located within a seismically active region, characterized mainly by the interaction of the North America Plate with the Caribbean Plate. The interaction of these two plates is characterized by a sinistral transcurrent component in the northwestern part of the boundary, which extends from the Yucatan block to the Lesser Antilles, and a component of subduction in its eastern part, causing a complex zone of deformation, with relative movements of 21-25 mm/year (Figure 1).

Figure 1. Tectonic setting of the Caribbean (Courtesy: National Science Foundation/ Eric Calais, Purdue University)

The country has several active fault systems with the potential to generate large-scale earthquakes, notably the Septentrional fault, the Camú fault, the Enriquillo fault, the San Juan-Ocoa, and the Hispaniola fault. The Septentrional is a left-lateral strike-slip fault that is known to be the main North America – Caribbean plate boundary, representing a big threat to DR’s north region. It is located in a densely populated area, the Cibao Valley, which includes the second most economically important city, Santiago. Los Muertos Trench is the source of the highest hazard for Santo Domingo, DR’s capital. The Enriquillo-Plantain Garden Fault Zone contributes greatly to the hazard in the southwest region of the country.

 

Figure 2. Major tectonic faults of the Dominican Republic (modified from MOPC, 2011)

On the Island, significant seismic events have been recorded in the years 1562, 1615, 1673, 1691, 1775, 1842, 1843, 1887, 1946, 1953, 2003, 2010, with the most significant occurring in 1946. The M8.1 Bahia Escocesa earthquake on August 4th, 1946 caused widespread damage across the country and generated a tsunami that inundated the community of Matancitas in the province María Trinidad Sánchez.

 

2. Local Context: Dominican Seismic Risk Reality

The limited government efforts in seismic risk reduction and mitigation result, among many reasons, from the lack of awareness of the local population to their seismic exposure and vulnerability, which in many cases were tied to “luck” or “misinformation.” For example, the destructive Bahia Escocesa earthquake occurred during a dictatorship, and historians believe that reports about earthquake damage were suppressed, as communications were supposedly controlled by the autocrat. The population was not informed of the destruction caused by the earthquake and there is scant institutional memory.

More recently, the 2003 M6.5 Puerto Plata earthquake caused the collapse of one public school and severely damaged many other school buildings. This earthquake occurred at 12:45 AM local time, so there were no fatalities related in the schools. Despite this recent earthquake, Dominicans are not aware of the high likelihood that a destructive earthquake will occur in the country.

Vulnerability is a driving component of risk in the DR. The Dominican Republic has great challenges in terms of building design, construction, and supervision as well as land planning and use. A large proportion of infrastructure has been built without a seismic code or a code at all. This problem is accentuated by informal construction in vulnerable and densely populated areas as shown in Figure 3.

Figure 3. Infrastructure scenarios of Santo Domingo, Dominican Republic. Photos a,b,c source: Diario Libre.

 

While earthquake risk mitigation has not been a priority for the Dominican government for many decades, certain measures have been taken recently. There are institutions and disaster risk reduction practices that exist to protect Dominican communities from natural hazards. Following the 2010, after the M7.0 Haitian earthquake in the neighboring country, Haiti, local Dominican regulations were enhanced, made more stringent, and earthquake safety initiatives have increased.

 

3. Government Regulations

In 1979, the first regulation on seismic analysis and design was enacted, however, it was a non-mandatory policy, meant to only be provisional guidance. This criterion governed structural design until recently. In 2011, the first mandatory code for seismic analysis and design of structures was approved by the Ministry of Public Works (MOPC). As a result, only structures designed after 2011 required seismic design. The country was divided into seismic zones, similar to how seismic hazard has been handled in much of Latin America: Zone I with high seismicity and Zone II with moderate seismicity (Figure 4). The seismic vulnerability of structures in the DR are thus classified as follows: built before 1979, from 1979 to 2011 and after 2011.

Figure 4. Current seismic hazard zonation in the DR seismic code R-001 (MOPC, 2011)

In response to the seismic vulnerability of the Dominican Republic, stemming from the lack of seismic codes and lack of building code enforcement, a new institution was created by decree 715-01 in 2001. The Oficina Nacional de Evaluación Sísmica y Vulnerabilidad de Infraestructuras y Edificaciones (ONESVIE) – National Bureau of Seismic Evaluation and Vulnerability of Infrastructure and Buildings -was created to identify high seismic zones and to evaluate the seismic vulnerability of private and public infrastructure of the Dominican Republic, as well as to propose the retrofit of vulnerable structures. This entity is charged with advising the President on measures to reduce the seismic risk in the country and to create awareness of seismic risk. From its conception, it has evaluated over 6000 buildings (mostly public schools and hospitals), designed the retrofit of over 100 structures, and identified areas for public investment in risk reduction. Funding for the execution of the retrofits, however, is a goal for the government in the coming decades.

In 2001, the Emergency Operations Center (COE, Centro de Operaciones de Emergencias) was created with the decree 360-01. The COE’s purpose is to manage emergency situations and disasters and be responsible for planning and coordinating the operations between different agencies, jurisdictions, and functions of institutions during an emergency. This is the official organization that responds after disasters and serves to support regional operations if there is a disaster in other Caribbean and Central America countries. In case of an earthquake, COE and ONESVIE deploy teams to evaluate the damage.

In 2002, Disaster Risk Management Law (Law 147-02) was enacted. This law gave the government the power to regulate the preparedness of government agencies and ministries for disasters. It also created Prevention, Mitigation and Response Committees in each municipality to support preparedness actions taken in the country. The Law was mostly focused on hydrometeorological hazards but also applied to earthquakes.

 

4. Engaging students and academia to promote awareness of seismic risk

Opportunities in academia to help build resilience and directly contribute to earthquake risk reduction depend largely on the availability of resources to fund research. In many developing countries, such resources are limited or non-existent. Additionally, the lack of specialists, doctoral programs, and tenure-track professorships, introduces complexity to this challenge. However, international partnerships and collaborations could help advance efforts to explore opportunities to advance earthquake risk reduction practices in academia.

The Dominican Republic has identified ways to mitigate these challenges through capacity building efforts and international partnerships. In fact, undergraduate students can be easily trained in tools such as FEMA P-154 Rapid Visual Screening of Buildings for Potential Seismic Hazards, EERI’s Virtual Earthquake Reconnaissance Team, and the Post Disaster Needs Assessment (PDNA) from United Nations Development Programme UNDP. Thanks to these knowledge and skill-building activities, trained students were the first onsite to volunteer as evaluators for reconnaissance activities following recent earthquakes in the Dominican Republic and internationally.

With initiatives such as establishing EERI chapters, students can be motivated and engaged in earthquake risk reduction programs for longer periods. For example, students from the Pontificia Universidad Católica Madre y Maestra (PUCMM) EERI Student Chapter have led small reconnaissance pilots after moderate earthquakes that have occurred in the past years in the Dominican Republic (Figure 5), and have also visited local schools to train children on how to prepare, respond and recover after earthquakes. Although creating this chapter was quite a challenge for me, as a young academic, because there were no previous similar experiences at the university, it became a great asset in the community and four years later, we keep growing.

Figure 5. Students from the EERI PUCMM chapter on a reconnaissance mission after M5.8 (2018) Villa Elisa, Earthquake.

Similarly, students have pioneered independent studies that have become research projects in collaboration with government agencies, civic society organizations, and consulting professionals. Through this experience, leading researchers have learned about the importance of engaging with a diverse group of stakeholders, but more importantly about the role of research towards the advancement of risk reduction efforts.

After learning from other countries’ successful experiences with research centers such as CIGIDEN in Chile and QuakeCORE in New Zealand, I decided to create a similar program in the Dominican Republic to contribute to the national goals of disaster risk reduction and resilience. A space where government agencies, civil society organizations, and academic institutions can converge and together work under a neutral umbrella ensures the continuity of projects, regardless of institutional changes, and leverages the scarcity of resources allocated for these topics.

The Resilience and Multi-Hazard Risk Research Center (Centro de Investigación de Resiliencia y Riesgos Multi-Amenaza – CIRRMA) within the Pontificia Universidad Católica Madre y Maestra (PUCMM) was created to allow more research opportunities and engage students, professionals, and research specialists to help build resilience in the country. This Center was launched in February of 2020 in Santo Domingo, Dominican Republic.

CIRRMA’s main objective is to generate scientific knowledge and promote and transfer its application for disaster risk reduction from the national to the local level. The Center aims to serve from a multi-disciplinary approach in the phases of preparedness, response, recovery, and mitigation for natural events. CIRRMA is founded in three main pillars: research, education, and extension for the community. The main collaborators of the Center are the Dominican Geological Survey (SGN), the National Bureau of Seismic Evaluation (ONESVIE), the Dominican Society of Earthquake Engineering and Seismology (SODOSISMICA) and representatives from the civil society. Other local and international collaborators are in the process of incorporating formally to CIRRMA. Although COVID-19 has delayed some plans for the Center, many efforts are being made to have a larger presence in civil society and to enhance the development of public-private partnerships for disaster risk reduction in the country.

This center is one of the ways government and academia can merge to reduce earthquake risk in the Dominican Republic. There is a long path to walk to achieve our “big goal,” but these steps can help us create the foundation for a safer future in countries like mine.

 

5. Conclusions

Earthquake hazard of the Dominican Republic is well-known by the scientific community, yet, in my opinion, the country needs to take big steps to reduce the vulnerability, thus, the risk. As a young professional having a life goal, to reduce earthquake risk in my country and prevent lives’ losses when the big one occurs, I found that with academia I could start building capacities that will provide the tools that make the Dominican Republic more resilient to these events. Thanks to EERI, I have been exposed to opportunities and tools that are helping me to put my grain of sand in the DR. Experiences as the LFE Travel Study Program, having developed the first EERI Student Chapter and forming a community of students and professionals advocating for earthquake safety, research projects thanks to networking done at the Annual Meetings, are having this story like the result.

16 Jun

A Critical Look at the Numerical Modeling of Reinforced Concrete Structures for Extreme Events

A Critical Look at the Numerical Modeling of Reinforced Concrete Structures for Extreme Events

By Maha Kenawy, PhD, University of Nevada, Reno

The early 2000s witnessed the rise of performance-based earthquake engineering, and with it came the emphasis on understanding ‘extreme’ structural performance; i.e., how structures behave at very large deformation demands, and how rapidly they lose their ability to carry loads when subjected to extreme events. This fundamental change to the structural design philosophy was followed by continuing refinements and guidelines on how to assess expected structural performance under extreme loads (For example, FEMA P-58 (Applied Technology Council, 2018)). Today, estimating the expected collapse capacity of structural systems and components is a common practice for engineers and researchers. At the base of determining the collapse capacity of a structure is the fundamental assumption that numerical structural models are capable of simulating the deterioration of structural components and materials. Many challenges stand in the way of having such models.

Structural engineers often seek to utilize computationally inexpensive models. Naturally, computational efficiency is the result of creating a set of idealizations to simplify the way that the model works, without significantly compromising its performance. When the issue at hand is predicting the behavior of structural components subjected to extreme loading conditions (such as those of earthquakes), the ability to simulate anticipated structural damage is a critical component of our modeling tools. In this context, the structural engineering modeling philosophy lends itself to two major types of modeling tools; each comes with their own compromises. The first type is concentrated or lumped plasticity models, which idealize structural components as elastic elements with nonlinear hinges at their ends. This type of model typically possesses superior numerical performance; however, it requires extensive calibrations based on experimental tests of structural components (which makes it difficult to generalize its applicability), and suffers from other performance limitations that come from the very nature of its idealizations. Despite its limitations, this type of model remains the most common numerical tool today for assessing the collapse capacity of reinforced concrete (RC) structures.

The other common modeling approach offers more granularity – and therefore accuracy – to predicting the performance of structural components. The so-called fiber-discretized (FD) component model is a type of distributed-plasticity frame finite element (FE) approach that relies upon convenient and limited calibrations based on the fundamental behavior of materials (in this case, concrete and steel), which make the model easy to generalize to various applications. Because this type of model is more sophisticated than the former in terms of its predictive capability and versatility, it quickly gained much popularity as a superior tool for assessing structural performance.

Figure 1 – Schematic description of mesh bias in fiber-discretized frame finite elements. On the left, damage to a RC column in the 2016 Kaikoura, New Zealand earthquake is pictured (photo from EERI photo gallery by Dmytro Dizhur and Marta Giaretton). Simulation of damage as constitutive softening illustrates the dependence of the member deterioration on the size of the numerical model elements. The mesh bias appears at the global level (load-displacement behavior) of a column loaded with axial and lateral loads, as well as the local level (strain or curvature distribution along the member)

In the past few decades, however, the rising demand for predicting the deterioration of structural components has exposed the extent of the shortcomings associated with the FD element modeling approach. To break down the fundamental issue with FD models, one has to go back to the underlying modeling of progressive damage (or cracking) in quasi-brittle materials as constitutive “softening” or negative stiffness, which became popular in the 1970s (a large number of publications by Zdeněk Bažant discusses the subject in due depth – in addition to his unique anecdotal account in Bažant, 2002). The advent of computerized FE analysis exposed the major limitation of constitutive softening: mesh bias. In other words, the numerical solution to a physical problem describing material damage depends on the characteristic size of the FE model, leading to non-objective, and therefore unphysical, model predictions. This issue is schematically described in figure 1.

The 1980s were ripe with several approaches proposed by researchers to overcome mesh bias in constitutive softening problems. Such approaches were not widely adopted in structural frame models until the 2000s. Some structural engineering researchers proposed simple approaches to amend the current FD modeling tools (which suffer from the same mesh bias issues); others created fundamentally new FE formulations that suspend the traditional idea that individual finite elements are independent, and introduce some continuity between neighboring elements in a numerical model. This family of approaches is known as the nonlocal models (I review many of these approaches in Kenawy 2018). My former research group at the University of California, Davis, led by Amit Kanvinde and Sashi Kunnath, proposed new structural component and constitutive formulations that advance the latter approach for both reinforced concrete and steel structures.

Figure 2 – Results of the verification study of the proposed nonlocal model by Kenawy et al. (2018). In a pushover analysis of a RC column, the conventional fiber-discretized frame model (left) fails to converge to a unique solution. The novel nonlocal model (right) overcomes mesh bias and rapidly converges to a unique solution.

The frame FE formulation and concrete constitutive model I developed as a doctoral student overcome the mesh bias of FD models (as shown in figure 2), without imposing too many restrictions that would limit the applicability of the model (Kenawy et al. 2018; Kenawy et al. 2020). The major drawback of the proposed framework is an inevitable added computational expense to our numerical structural models. The model also requires additional assumptions regarding the extent of damage in a structural member (referred to as a characteristic length in a continuum, and more commonly approximated as a plastic hinge length by structural engineers). My doctoral work also proposes a rather simple approach to characterize this characteristic length for a wide range of structural problems. Figure 3 shows representative blind predictions of the behavior of RC columns along with their observed behavior in laboratory experiments. These plots are part of a large validation study which suggests that the proposed framework and underlying assumptions are capable of simulating the observed degradation of RC components due to crushing of the concrete material. Much work remains to extend this modeling approach to simulate different types of structural components (structural walls, for example) and failure modes, and to assess its ability to simulate the performance of entire structures (for which experimental test data are rather scarce). Nonetheless, the findings of my doctoral work, along with those of a few recent studies by structural engineering researchers, bring the promise of more sophisticated and reliable modeling approaches for assessing the performance of RC structures subjected to extreme loads, and utilizing these novel methods to improve structural design provisions.

Figure 3 – Representative results of the validation study of the nonlocal model. The simulated cyclic lateral load vs. drift response of several RC columns by the nonlocal model is compared against the observed component behavior in laboratory experiments. The experimental datasets were obtained from the PEER column database

Selected References

Applied technology Council (2018). FEMA P-58: Seismic Performance Assessment of Buildings. Federal Emergency Management Agency.

Bažant, Z. P. (2002). Reminiscences on four decades of struggle and progress in softening damage and size effect. Concr. J.(Japan Concr. Inst.), 40, 16-28.

Kenawy, M. (2018). Nonlocal Computational Framework for Simulating Extreme Limit States in Reinforced Concrete Structures. Ph.D. Dissertation, University of California, Davis.

Kenawy, M., Kunnath, S., Kolwankar, S., & Kanvinde, A. (2018). Fiber-based nonlocal formulation for simulating softening in reinforced concrete beam-columns. Journal of Structural Engineering, 144(12), 04018217.

Kenawy, M., Kunnath, S., Kolwankar, S., & Kanvinde, A. (2020). Concrete Uniaxial Nonlocal Damage-Plasticity Model for Simulating Post-Peak Response of Reinforced Concrete Beam-Columns under Cyclic Loading. Journal of Structural Engineering, 146(5), 04020052.

 

BENCHMARKING OF FEMA P-58 EXPECTED SEISMIC LOSSES TO OBSERVED LOSS DATA FROM THE 1994 NORTHRIDGE EARTHQUAKE

Benchmarking of FEMA P-58 Expected Seismic Losses to Observed Loss Data from the 1994 Northridge Earthquake

By Dustin Cook, P.E.

Recent developments in seismic risk analysis and performance-based design have opened doors to statistically rigorous and systematic frameworks for the quantification of seismic risk to buildings. One such method was recently formalized by the Applied Technology Council and is known as FEMA P-58: Seismic Performance Assessment of Buildings (FEMA, 2018c). FEMA P-58 provides a probabilistic approach to assess the seismic risk of individual buildings. Through FEMA P-58, seismic risk is quantified in terms of performance metrics that are valuable to engineers, building owners, and the public, such as economic losses, potential casualties, and disaster recovery time, facilitating decisions among design or mitigation alternatives. One of the pressing challenges of new and evolving seismic risk assessment methods is the need to validate, confirm, and/or verify the outcome of these assessments to support their broader use.

Records and estimations of damage and loss from the 1994 Northridge earthquake in southern California provide a unique opportunity to benchmark new performance-based risk assessment methodologies, such as FEMA P-58, to empirical data, especially for buildings of wood frame construction. To evaluate the results obtained through a FEMA P-58 assessment, this study compares the hindcast losses using the FEMA P-58 methodology, in terms of repair costs of buildings, with observed losses during the 1994 Northridge Earthquake. This article summarizes the methods and findings of recent a study performed jointly by the University of Colorado Boulder and the Haselton Baker Risk Group.

Figure 1 – Highway damage during the 1994 Northridge Earthquake. Photo from David Butow/Corbis/Getty Images.

Unprecedented levels of damage were observed during the Northridge Earthquake, with total estimated losses ranging between $40 and $44 billion (1994 USD), making it the costliest earthquake in U.S. history (Eguchi, 1998). Other sources estimate an additional $8 billion in indirect losses from business interruption, lost tax revenue, vacated housing, and defaults on Small Business Administration loans (Petak & Elahi, 2001). Widespread damage was observed in many different types of buildings across a large region. Wood frame structures make up a majority of the building stock in the US, and represent around 96% of the buildings in Los Angeles County, accounting for around 85% of the value of the building stock at the time of the Northridge Earthquake. Damage to wood frame structures was extensive due to the large number of buildings that were affected. In total, over 340,000 insurance claims were submitted for damage to residential structures, mostly from damage to nonstructural components (Eguchi, 1998). Considering both insured and uninsured damage, losses from wood frame residential structures are estimated to represent about half of the total building losses from the earthquake (Petak & Elahi, 2001).

FEMA P-58 only quantifies direct losses to the building (i.e. structural and nonstructural components), and does not represent losses to contents, detached structures, and loss of use. Therefore, adjustments are made to the estimated total direct losses to derive a best estimate of direct loss from building damage, to compare against FEMA P-58 losses.  In the Northridge Earthquake, direct building loss represented about 67% of the total loss from insurance claims (Eguchi, 1998, Petak & Elahi, 2001). We propose the reduction factor to go from reported loss to losses comparable to FEMA P-58 is likely to be somewhere between 60% and 75%, resulting in a range of estimated loss from $25 billion to $32 billion by multiplying the average reported estimated direct loss of $40 to $44 billion (Petak & Elahi, 2001) with this ratio range.

To quantify FEMA P-58 expected loss from the Northridge earthquake, this study uses the Haselton Baker Risk Group’s FEMA P-58 Risk Model (SP3-RiskModel) and the USGS Northridge ShakeMap to perform a scenario assessment on a set of 2.6 million buildings affected by the event. The SP3-RiskModel uses embedded algorithms to generate structural properties, building configurations, and building components from a simplified set of building inputs based on typical building configurations and inventories, engineering analysis, and expert judgment. This tool helps expedite the FEMA P-58 analyses for large building inventories with limited building information, such as the building data available in tax assessor databases, and can be used to run millions of performance models in a batch setting. This study uses a proprietary inventory database based on tax assessors and insurance data that contains building inventories of the greater Los Angeles region. Losses from the assessment are aggregated for all buildings within the ShakeMap region and compared with observed data.

Table 1 – Breakdown of FEMA P-58 predicted loss for each type of building where quantitative loss data is available. Dollar values represent 1994 USD.

Type of Building Number of Buildings Total Value FEMA P-58 Predicted Loss          Estimated Observed Loss
All Buildings 2,586,638 $722 billion $31 billion $25 to $32 billion
Residential 2,405,382 $508 billion $16 billion $12 to $16 billion
Tilt-Ups 39,677 $52 billion $5 billion > $1 billion

 

Figure 2 – 1994 Northridge Earthquake mean losses from FEMA P-58 for part of Los Angeles County.

The total hindcast losses from the FEMA P-58 assessment of the Northridge scenario came out to $31 billion due to building damage, which is on the higher end, but well within the range of observed loss. Mean loss results presented here represent the average cost, in 1994 USD, to repair structural and nonstructural components in the building. The total hindcast loss from residential buildings also compare well with observed losses. This comparison indicates that probabilistic methods such as FEMA P-58 can provide accurate predictions of post-earthquake economic losses.  However, results from probabilistic methods are heavily dependent upon modeling decisions. If factors that affect the response of structures at low levels of shaking are not properly accounted for, such as effective damping and stiffness, predictions of loss can change significantly. Outcomes of alternative modeling decisions are discussed in the full report. For more information on the complete findings of the study, please contact the Haselton Baker Risk Group at (530) 531-0295 or support@hbrisk.com

Dustin Cook is a Ph.D. Candidate in the Department of Civil, Architectural, and Environment Engineering at the University of Colorado Boulder and is a member of the Haselton Baker Risk Group. Dustin holds a M.S. from University of California, Los Angeles and is a licensed Professional Engineer in the state of California. You can reach him by email at dustin.cook@colorado.edu.

 

What might have been: counterfactual thinking in risk analysis

What might have been: counterfactual thinking in risk analysis

By Yolanda C. Lin, Ph.D.

After an earthquake, earthquake engineers and scientists work tirelessly to understand exactly the mechanisms of what happened, what was damaged, who was affected, how we can best move forward. In the process, we typically strive to identify what valuable lessons-learned can be harnessed from the event, so that a future, similar event may be safer and less impactful for the next community.

Are we restricted to only learning from our past disasters? This has been the central question driving my work this past year as a Research Fellow at Nanyang Technological University’s Disaster Analytics for Society Lab (DASL), led by Dr. David Lallemant. Driving our work is the fact that every event that has transpired is driven at least in some part by randomness, and how those hazard events transpire through damage, impact, and recovery are subject to these random realizations. For every event that has happened, there exists a whole family of possible and similar-probability events that didn’t happen, only by chance. And yet, there are lessons to be learned in these as well. Even events that already seem like a disaster could actually be considered a near-miss, when compared to the full range of outcomes that could have transpired. This is counterfactual thinking: reimagining the past somehow different than it actually was. We specifically are interested in downward counterfactual thinking, where the outcomes are worse than in the actual past event. According to counterfactual scholars in psychology research, we are already experts at counterfactual thinking, but we’re not wired to think in a downward way — we usually want to reimagine things for the better, and need some extra scaffolding to think in the negative direction.

 

Figure 1: Conceptual diagram of applying counterfactual changes Δ1 and Δ2 to a past event (represented by the grey swan) in a 2-parameter model space to reach a downward counterfactual event with worse consequences (represented by the black swan). Contour lines represent levels of consequences.

Take, for example, the 1971 San Fernando earthquake. At M6.7, it was a surprisingly large event at that point in history, and the consequences of this event included the death of over 60 people, and damages valued at near half a billion dollars. Though already a costly disaster in many ways, this event could have been even more devastating. Exactly a year before in 1970, the Van Norman dam was nearly full at 6.5 billion gallons of water, but in 1971 it was just half full at 3.6 billion gallons of water. According to a study from the University of California, Los Angeles, the 1971 earthquake damaged the top 30 feet of the dam, and if this earthquake had occurred a year earlier, the dam may have failed and consequently claimed between 71,600 and 123,400 lives (Ayyaswamy 1974, Reich 1996). Instead, California has had a relatively safe record for direct deaths due to earthquakes in the last 60 years of about 200 lives lost (Woo 2017).

This August, we hosted the Counterfactual Black Swan Workshop at NTU in Singapore, with twenty-eight participants from six countries across three continents, to build momentum around this concept and establish a new community of practice centered on counterfactual thinking in risk analysis, bridging multiple disciplines and industries, such as earthquake engineering, insurance, human geography, and risk communication, spanning multiple geographic contexts (read more about the workshop here).

In one session of the workshop, we tested an activity of “Counterfactual Round Tables,” which is designed to guide participants through the process of building a counterfactual event, based on a real past event. The challenge is to find ways to make something from the past even worse — possibly even a so-called Black Swan, a low-probability, high-impact, and surprising event. Starting with one participant, the “event expert” describes a past event, using supporting materials (maps, figures, etc) as needed. Other participants are invited to ask clarifying questions, and finally all participants engage in counterfactual thinking to devise ways in which this event could have been worse.

We provided prompt cards (Figure 2) around the table to help guide downward counterfactual thinking. Participants then discussed their various counterfactual ideas and grouped their thoughts, written on post-it notes, onto a poster board in order to build a narrative around one or more counterfactual versions of their event. This process was then repeated for all participants at the table, with one past event per participant. The activity had a facilitator at each table, and there were three participants per table. The resulting counterfactual black swans were then shared during an informal coffee break poster session following the activity, and afterwards we also invited general impressions and feedback to share with the rest of the group. 

Figure 2. Example categories for counterfactual changes. These were printed and used as prompts to stimulate downward counterfactual changes to past events.

Many participants at our workshop voiced surprise at the difficulty in pushing back against the automatic “upward” counterfactual thinking, wanting instead to engage in finding ways that the situation could have been better. They needed to consciously remind themselves (and be reminded by the moderator and fellow participants) to think downwards instead, which points to the need for a facilitated group exercise around this process.

Ultimately, this exercise can jumpstart our imagination to understand any lucky near-misses that can be addressed in the future, provide the basis for a guided search through a high-dimensional model space, explore multi-hazard scenarios that are currently difficult to model computationally, and provide a structured framework for gathering  expert-opinions for a scenario in planning and preparedness purposes.

Next time you are gathered with two or three of your favorite earthquake engineering colleagues and experts, I invite you to grab some post-it notes and try this activity with a past event of your choice. Full directions for the activity are available here, and printable prompt cards are available upon request. Let me know what you come up with!

This work was supported by the National Research Foundation Singapore and the Earth Observatory of Singapore.


Yolanda C. Lin is a Research Fellow in the Disaster Analytics for Society Lab at Nanyang Technological University in Singapore. Yolanda holds a Ph.D. in Civil Engineering from Cornell University, a M.S. from University of Colorado Boulder, and an A.B./B.E. from Dartmouth College. You can reach her by email at ylin@ntu.edu.sg or on twitter @DisasterYolanda.

4 Dec

Learning from Earthquakes: Returning to New Zealand

Learning from Earthquakes: Returning to New Zealand to observe long-term recovery efforts after the 2010-2011 Canterbury earthquake sequence and 2016 Mw 7.8 Kaikoura earthquake

By Christine Z. Beyzaei, Ph.D., P.E.

Post-earthquake reconnaissance typically, and by necessity, focuses on documenting observations immediately following an earthquake. Subsequent efforts may involve follow-up visits to the affected area, but these are often performed as part of individual research projects investigating specific observations from the event and may be focused primarily within a specific discipline (e.g., geotechnical, structural, social sciences). Documenting the long-term recovery process represents a unique opportunity to learn not only from the impacts of the event itself, but also from the response and recovery of an entire affected community. That is after all the ultimate goal in pursuing reconnaissance and research – to enable communities that can better withstand an earthquake event and recover quickly when one does occur.

The EERI Learning from Earthquakes (LFE) Travel Study Program provides the opportunity for young professionals to visit areas previously impacted by earthquakes and observe the long-term recovery efforts and resiliency measures implemented in the years following the earthquake event. The 2019 LFE Travel Study program brought a group of 25 young professionals to New Zealand, to observe recovery following the 2010-2011 Canterbury earthquake sequence and the 2016 Mw 7.8 Kaikoura earthquake. The program was co-hosted by EERI and QuakeCoRe (a NZ Crown Research Institute), with participants from around the world comprising a diverse, multidisciplinary group. At the outset, participants were sorted into sub-groups representing components of community: Built Environment, Natural Environment, and Social/Economic Environment. Our goal was to consider our observations in the context of these community components, thinking beyond our technical disciplines to broader, interdisciplinary, and community-oriented applications.

Figure 1. 2019 LFE Travel Study Program participants and organizers (Image source: Laura Whitehurst, Holmes Consulting).

 

Figure 2. Modified from “Integrated & Holistic Recovery”, Focus on Recovery: A Holistic Framework for Recovery in New Zealand (Ministry of Civil Defence & Emergency Management 2005).

The program began in the South Island, in Christchurch and Kaikoura, and continued throughout the Canterbury and Marlborough regions. We visited damage sites yet to be repaired and rebuild sites demonstrating innovation and a community dedication to building back better. We met with engineers, government officials, emergency responders, business owners, health care professionals, and others, all of whom shared their time and experiences to transfer knowledge on what they’d learned in the 8-9 years following the Canterbury earthquake sequence, and the three years following the Kaikoura earthquake. We ended the program in Wellington, focusing on recovery following the Kaikoura event and preparedness for future events. A common theme throughout the program was that for community recovery to truly take effect, multiple sectors must work together and there must be clear and open communication with the community throughout the process.

Figure 3. Overview map showing locations of Christchurch, Kaikoura, and Wellington. Inset shows country of New Zealand (Image source: Google Earth).

At the completion of the program, each group prepared a report summarizing our observations (URL). Highlights from the program are presented in the figures below.

Figure 4. Red Zone to Green Space: Severe liquefaction and lateral spreading along the Avon River in Christchurch caused pervasive damage throughout the adjacent neighborhoods, resulting in the area being designated as the “Red Zone.” Homes throughout the Red Zone have since been demolished, leaving open green space. The future use of this area is still under debate, with potential plans including permanent designation as a recreational green space. Base map source: Land Information New Zealand – Canterbury Maps (https://www.linz.govt.nz/crown-property/types-crown-property/christchurch-residential-red-zone/residential-red-zone-areas). Inset photo source: Christine Beyzaei, from 2014, taken in the eastern Red Zone neighborhood of Bexley.

Embracing the concept of “building back better,” repair and construction efforts at Ohau Point have worked to incorporate considerations of both the natural environment and tourism needs. This includes construction of a sea wall with a seal passageway, a new pullover and lookout area with parking, and improved rockfall protection along the coast. Photos taken by author.

Figure 5. Structural systems: seismic repair and retrofit at the University of Canterbury campus in Christchurch. Viscous dampers installed above office space. Tour led by Didier Pettinga (Holmes Consulting). Photos taken by author.
Figure 6. Landslide dam formed in 2016 Kaikoura earthquake (known as the “Leader Dam”). Photos and lidar scanning from 2019 field exercise led by Michael Olson (Oregon State University). Equipment provided by the NHERI RAPID Facility. Observation and documentation have been ongoing since the 2016 post-earthquake reconnaissance. Photos taken by author, lidar imaging provided by Michael Olson
Figure 7. Fault scarp along the Leader Fault generated by rupture during the 2016 Kaikoura earthquake. Photo taken in May 2019 during Kaikoura Earthquake Ruptures fault walk led by Tabitha Bushell (University of Canterbury). Vertical offset of 3 meters measured during 2016 post-earthquake reconnaissance. The Kaikoura earthquake resulted from complex ruptures across multiple faults. There are ongoing research efforts to map and characterize the faults involved in the event. Photo taken by author.
Figure 8. Kaikoura Recovery: The 2016 Kaikoura earthquake underscored that the natural environment and the tourism industry are vital to the city of Kaikoura and the well-being of the community. Damage along the coast isolated communities and exposed vulnerabilities in existing infrastructure systems. Embracing the concept of “building back better,” repair and construction efforts at Ohau Point have worked to incorporate considerations of both the natural environment and tourism needs. This includes construction of a sea wall with a seal passageway, a new pullover and lookout area with parking, and improved rockfall protection along the coast. Photos taken by author.

It was an exceptional experience to work with such a diverse group and learn from others’ perspectives and experiences. On a personal note, the 2019 program also marked 5 years since my initial visit to New Zealand in 2014 for my doctoral research. In 2014 and 2016 I worked in Christchurch at the University of Canterbury, investigating observations from the Canterbury earthquake sequence and during that time saw the recovery as it unfolded. Returning with the LFE program gave me a greater appreciation for the aspects beyond geotechnical engineering, and the opportunity to see how it all fits together. A sincere thanks to EERI, QuakeCoRE, and the people who generously shared their time and their communities.


Christine Z. Beyzaei is a Senior Engineer in the Civil Engineering Practice at Exponent in Oakland, where she specializes in geotechnical engineering. Christine holds a Ph.D. and M.Sc. from the University of California, Berkeley and a B.S. from George Washington University.
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