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Enabling Community Resilience
This chapter is based on the first panel of the workshop and broadly examines how technology and enabling improvements to infrastructure systems can enhance community resilience. Specifically, it explores ways in which physical systems within a community can better connect to social and human systems, and also considers ways to adapt infrastructure to produce deft, flexible responses that can better serve communities. A better understanding of how to speed the recovery of infrastructure systems after a hazard event will ultimately support the resilience of the community overall.
Arrietta Chakos, policy advisor at Urban Resilience Strategies, moderated a discussion among Reginald DesRoches, provost of Rice University; Steve Moddemeyer, principal at CollinsWoerman Architects; and Janice Barnes, principal/director of resilience at Waggonner & Ball. During the discussion, speakers made appeals for broadening the ways in which we perceive and consider community resilience and for increased communication with the public through methods such as crowdsourcing.
DEVELOPMENT OF A RAPID POST-EARTHQUAKE SITUATIONAL AWARENESS TOOL FOR CALIFORNIA BRIDGES
Reginald DesRoches introduced a project focused on developing a rapid post-earthquake situational awareness tool. The project uses innovative technologies to better understand the outcomes that are likely to occur in California’s transportation system following a major earthquake. Specifically, his team examined the post-earthquake assessment process for California bridges, which is a crucial component of the overall transportation system. DesRoches noted that the ability to assess the state of infrastructure following a large event is critical to increase rapid response efficiency and, thereby, improve recovery. Knowledge of where the most extensive damages will occur in the system can better inform emergency response efforts and maintenance crews on what to prioritize. For example, following the Loma Prieta and Northridge earthquakes, bridges endured a range of damages, such as to columns, on the seating of supports, as well as liquefaction and damage to abutments.
To execute this work, DesRoches and his team developed a performance based grouping approach to sort bridges into classes with similar design or structural performance—a significant advancement from the usual approach of using the HAZUS classifications (an acronym for Hazards-US), which is a multi-hazard risk assessment and loss estimation software program
developed by the Federal Emergency Management Agency (FEMA).1 Using detailed non-linear analytical models, bridge fragility curves2 were developed for each class and then implemented in ShakeCast’s ShakeMap3 (Figure 3-1) to analyze regional seismic activity and bridge performance vulnerabilities, respectively. A key challenge in California is that there are more than 24,000 bridges with varying characteristics, such as material properties, design standards, and frame types.
There is a significant amount of uncertainty associated with individual bridges. DesRoches acknowledged that the best method to address this challenge would be to develop fragility curves for each individual bridge; however, developing models that characterize the uniqueness of the large number of bridges would not be plausible.
SOURCE: USGS.
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1 See: https://www.fema.gov/hazus.
2 Fragility curves demonstrate the conditional probability of a structure meeting or exceeding a certain level of damage conditioned on some input parameter, in this case a particular level of ground motion, see: “What is the concept of fragility curve. More information available at: https://www.researchgate.net/post/What_is_the_concept_of_fragility_curve.
3 ShakeMap uses strong motion data to measure ground motions. See: https://earthquake.usgs.gov/data/shakemap/.
4 See: https://usgs.github.io/shakemap/manual3_5/shakemap_archives.html.
The goal of this project was to improve the ability to classify these bridges into manageable groups and identify unique attributes of each group to better predict damages. The research was broken into different parts that allowed for a better understanding of how to classify the bridges, how to develop fragility curves for bridges in each group, applying this knowledge to speed reconstruction, and prioritizing retrofitting strategies.
DesRoches and his students grouped the nearly 24,000 bridges into a subset of 129 classes.5 For each of these classes they developed unique fragility curves, taking into account all of the uncertainties associated with the groupings, including ground motion uncertainty, material uncertainty, geometric uncertainty, and structural design uncertainty. The method characterizes both the overall bridge response and the vulnerability of various bridge components.
Ultimately, the ANOVA approach (ANOVA is an acronym for “analysis of variation”) can provide emergency responders and maintenance crews with high fidelity situational awareness about bridge conditions following an event.6 “We want to be able to tell the inspectors the likely places they should look first on the bridge,” DesRoches explained. This capability allows for the creation of detailed summaries that signal to bridge inspectors where vulnerabilities exist and what types of damages are likely to occur. Paired with inspector starting locations, this capability could increase the rate at which damages to bridges are addressed. He also noted that this research could be used with other natural hazards. For example, a colleague at Rice University is applying this methodology to damages associated with storm surge. Ultimately, a better understanding of how to speed recovery of the infrastructure systems after a hazard event will support the resilience of the community overall.
Finally, DesRoches discussed three projects that seek to advance this field of research into the future. First, his team is developing a method that provides unique fragility curves for every bridge in California using Artificial Neural Networks.7 To achieve this, existing models are trained to access the Caltrans database and predict performance of a specific bridge based on information collected directly from the database.8 DesRoches also described a project at the University Transportation Research Center that examines the use of robotics to better understand bridge infrastructure. More specifically, this study examines cracking in the bridge columns (the ground to bridge support structures) to ascertain the remaining bridge life and the vulnerability of the bridge to further damage. Lastly, DesRoches proposed that this technology could be enhanced with crowdsourcing data. Everyday people can use a smartphone application to update the conditions of bridges in real time if they are driving or walking across or near the bridges. “If you have people going to the bridge, it [crowdsource data] allows us to then update the condition of the bridge and update our models in real time,” he explained.
REDUCING THE MISERY BY ACCELERATING RECOVERY
Steve Moddemeyer discussed how different approaches to resilience planning efforts and design thinking can accelerate recovery of a community following a disaster. Currently,
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5 To group the bridges, the statistical method of Analysis of Variation (ANOVA), coupled with Fisher’s Least Significant Difference Method was used.
6 See: https://www.statisticshowto.com/probability-and-statistics/hypothesis-testing/anova.
7 Artificial Neural Networks are computing systems that are inspired by biological neural networks and based on a collection of connected units or nodes called artificial neurons, which loosely model the neurons in a biological brain.
8 See: https://dot.ca.gov/programs/environmental-analysis/cultural-studies/california-historical-bridges-tunnels.
infrastructure is designed to withstand the impacts from a specific magnitude of disaster. But this approach does not factor in the amount of time it takes to recover. Though existing design standards focus on keeping people safe, they lack the foresight to prepare a community for a long recovery period that can last many years.
Much of Moddemeyer’s work is based on his early career in which he focused on understanding the resilience of salmon populations in the face of disturbance. As a landscape architect and urban designer and planner working on infrastructure, Moddemeyer explores ways that natural habitat responses to disturbance can be applied to develop sustainable and resilient cities.
SOURCE: Steve Moddenmeyer.
Moddemeyer referred to the adaptive cycle10 of natural systems (Figure 3-2). The cycle includes an initial phase of growth that becomes more mature over time, then enters a
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9 Holling, C.S. 1986. The resilience of terrestrial ecosystems: local surprise and global change,” in Sustainable Development of the Biosphere. Cambridge: Cambridge University Press. Pp. 292-317.
10 Ibid.
conservation stage that is very stable and resistant to change. Species that survive over time experience this cycle over and over. Similarly, this model can be applied to cities that often last hundreds to thousands of years, which also start small, grow, and go through many cycles. Moddemeyer suggested that Seattle is currently in the stable or “conserve” stage of this cycle. However, he warned, an impending earthquake could throw the region into the breakdown, or “release” stage, much as it did when the Great Seattle Fire of 1889 decimated downtown. For this reason, Moddemeyer argued, engineers must design from “cradle to cradle,” a method that accounts for all stages of the adaptive cycle, including the inevitable recovery period. “We want you to rebuild our bridges and our roads and our buildings… but we want you to pick the alternative that recovers the most quickly after an event, regardless of what caused it to fail,” he stated.
Moddemeyer pointed to the NIST Community Resilience Planning Guide,11 designed for community-level decision makers, as a way to help communities think through planning for disasters. The recovery guide does not point to specific hazards, or the size and intensity of a hazard, but rather focuses on time to recovery. This approach prioritizes community functions and provides time frames for repairs essential to recovery success. It also allows for consideration of the increased variability that comes with climate change. Communities first identify their goals, and then consider the potential cascading impacts through the infrastructure that supports those goals, which helps to illustrate the interdependencies between infrastructure systems. Moddemeyer gave an example in which a school, damaged by an event, remains closed for a month. If there are no schools available to the community’s children, parents could be obligated to remain home instead of returning to work, hindering community recovery. In this scenario, because schools would need to come back faster, they would need to be designed to a better standard, and the infrastructure that supplies water and energy would also need to match that recovery goal. For example, school designs could be changed to require a water treatment system in the school’s basement.
Finally, Moddemeyer recounted his efforts with the Boulder County Collaborative, which addressed the region’s recovery following the major floods in Colorado in 2013.12 Using the NIST approach as a foundation, the Boulder County Collaborative developed a resilient performance standard for infrastructure called the Resilient Design Performance Standard, which included a checklist of 23 questions to consult when designing infrastructure solutions.13 The purpose of this Resilient Design Performance Standard was to create more integrated and sustainable community-based results by guiding the design teams that rebuild infrastructure towards efforts that support faster recovery. Moddemeyer said he believed every community can benefit from this approach to infrastructure design within current infrastructure spending budgets by adding this extra layer of rigor, and by challenging designers and engineers with alternative thinking about recovery.
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11 See: https://www.nist.gov/topics/community-resilience/community-resilience-planning-guide.
12 See: http://www.bccollaborative.org.
13 See: http://www.bccollaborative.org/uploads/6/6/0/6/66068141/resilientdesignperformancestandard_scoresheet.pdf.
HEALTH DISTRICTS: MAKING OUR INFRASTRUCTURE WORK HARDER FOR US
Janice Barnes, principal and director of resilience at Waggonner and Ball, indicated that one key issue in designing better infrastructure is to consider the consequences of potential disruptions instead of focusing so narrowly on immediate challenges. This would mean augmenting the work a designer is commissioned to do: to ask questions regarding risk escalation, cost awareness, the means of implementation and maintenance over the long-term, governance and potential partners, and how to apply measures of success or progress.14 Barnes asserted that though one may not choose the disaster to which he or she must respond, one may choose the way he or she sees, focuses, and is motivated to act.
Designing infrastructure should incorporate social, economic, and environmental issues as well as provide multiple benefits to the community. One way to develop a comprehensive approach, Barnes explained, is by envisioning a community as a health district, “where investments are targeted to improve population health outcomes and to inspire healthy behaviors.”15 With health districts, the dialogue associated with health systems planning is broadened beyond a hospital or health center to include other systems essential to the health of the community. The health center is the community anchor that catalyzes a broader network of actors and contributes to overall community resilience in addition to health.
Initial data could provide a baseline of knowledge about the community, its resources, and health. Much of this data could be collected over an extensive range of community factors through open sources, including data related to geography, transportation access, amenities, culture, and demographics. By viewing all of these datasets holistically, a broader picture will emerge; this could go beyond the way projects are typically scoped to align with the overall resilience needs of a community.
Barnes cited work in the Wyckoff Heights Health Improvement District in Brooklyn, New York to illustrate the benefit of working with the community as a health district. This approach addressed the need to increase preventative care options in the area in an effort to decentralize care delivery from one primary hospital, reduce emergency room congestion, and to help residents avoid unnecessary healthcare costs. A goal was to establish a coalition of health service providers and community organizations to open up more opportunities for residents to access preventative care and increase wellness in the community. Additionally, these partnerships could enable multiple sources of funding, for example, through federal and state funds, foundation grants, community micro-loans, and others.
To conclude, Barnes pointed to key takeaways from this work. She reiterated the need for infrastructure planning, investment, and monitoring to include connections to social, economic, and environmental design equally. She encouraged the development of a network of professionals with different points of view to better understand the issues and identify solutions. For example, in addressing extreme heat days as part of the Climate Ready DC program, the Department of Health came to the table with the Department of Transportation to look at their individual departmental issues. These issues included the need to train health care workers and the impacts of extreme heat on steel rails, and to better understand the interdependencies of how health and transportation systems could impact populations in the community. Barnes indicated
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14 Having a means of monitoring success or progress, Barnes notes, is especially important for the purposes of maintaining funding.
15 See: https://perkinswill.com/area-of-expertise/health-district-planning.
that broadening the conversation and inviting people to this kind of dialogue allows for new opportunities to understand the influence of infrastructure and new ways to fund, enhance, and maintain a project. It also furthers connections with the community and creates new networks so that community members can learn and benefit from each other.
DISCUSSION
Arrietta Chakos asked each panelist about opportunities for future resilience, particularly in light of the need for recovery from recent disasters, such as Hurricanes Harvey and Maria.16 DesRoches responded that the recent response efforts offer opportunities for the increased use of technologies—specifically, technology with the ability to inform recovery efforts. Moddemeyer suggested that modeling efforts in existing recovery and disaster zones from the Community Resilience Planning Guide would enable affected communities to recover in a time frame that matches community needs. He further explained that prior to the respective disasters in both locations, Puerto Rico was more vulnerable to an event than Houston for a number of physical, socio-economic, and political reasons. Factors such as Puerto Rico’s political representation, economic situation, and the poor state of its physical facilities contributed to this comparatively increased vulnerability. For this reason, Moddemeyer emphasized that there was more to be done in Puerto Rico than “just fixing things.” Instead, he recommended that recovery efforts should have a more holistic approach. Barnes reiterated the need to open the recovery and resilience conversation to members of the community to leverage their local knowledge and expertise. She recounted the experience of a farmer in rural Tennessee who altered his planting cycle due to climate change, resulting in corn yields earlier than neighboring farmers. As a result, he is able to sell his corn at higher rates. She emphasized that “we as professionals need to understand that while we have expertise we’re not the only experts.”
An audience member asked what could be done to change the way resources are allocated for the greater good, given that those with the least are impacted the most by disasters. Barnes pointed to three organizations working on these issues. First, the Institute for Sustainable Economic Educational and Environmental Design (I-SEEED)17 works in low income communities to address social problems and give communities a voice in decision making. In one example, they analyzed Geographic Information Systems (GIS) data in communities and found that GIS data in Oakland, California indicated there were 30 available “grocery” stores when only two existed. This discrepancy was because GIS data included convenience stores, which lack the fresh food choices of groceries. I-SEEED discovered this discrepancy by using cell phones, tools that already existed within the community. In Africa, IDEO and Rockefeller’s Amplify Program18 is leveraging a phone technology system for mobile banking to disseminate information on emergency issues. Finally, the Asian Development Bank (ADB)19 has been building “community-led resilience” into its infrastructure investment by stipulating that infrastructure initiatives must be community-led in order to receive funding. Barnes noted that the Community Development Block Grant Disaster Recovery (CDBGDR) in New York has recently adopted this same requirement.
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16 This workshop took place in September 2017 during the aftermath of Hurricanes Harvey and Irma, and a devastating magnitude 8.1 earthquake in Mexico.
17 See: https://iseeed.org/about-us.
Lauren Alexander Augustine, director of the Resilient America Roundtable, asked whether panelists believed there is a greater need for innovation in resilience technology or process. Moddemeyer stressed the importance of both technology and process innovation. He drew on the field of ecological resilience, noting that there are many unmeasured thresholds: “As we get closer to our thresholds, our ability to handle perturbation minimizes. The thing that we want to avoid is tipping over into a sub-optimal steady state,” he explained. Referencing post-hurricane conditions in Puerto Rico, Moddemeyer stated that a main concern is that residents will leave because they have no other options, and Puerto Rico’s population will decline. Thus, the country could move into a sub-optimal state. He proposed that artificial intelligence and other kinds of advanced technologies could be used to better identify thresholds. Then, those thresholds could be accounted for in the process of planning and determining goals for resilience. DesRoches added that innovation is needed in communicating resilience. For example, investments in flood mitigation (e.g., floodgates) that Texas Medical Center made in advance of Hurricane Harvey resulted in savings of several billion dollars. DesRoches stressed the importance of communicating this example and attempting to inspire others to follow it. “Clearly, we know that technology will make communities more resilient, but how do you communicate the cost benefit of that? It’s a challenge that I think we all face in this field.” Chakos said that many technical solutions already exist and will continue to be refined in the future, but that she believed improvements were needed in the areas of partnership formation and political engagement. In the San Francisco Bay area, Chakos explained, much work has been done to create political adaptations and tax revenue to support and reinvest into local school and infrastructure systems, as well as the state’s larger civic infrastructure.
Finally, an audience member asked panelists how to inspire public confidence in resilience efforts. Steve Moddemeyer suggested the need to celebrate the advances made in the field of resilience, such as with public safety, and to involve everyone in resilience solutions. “I think that it’s easy to lose track of [the idea] that, really, it’s all of us, and it’s not just the buildings or the infrastructure that failed.”
