Community Resilience Planning Research Articles

Coastal Community Resilience Planning Toward Disaster: A Case Study on Coastal Area in Malang Regency, East Java, Indonesia

Indonesia is a tropical islands-country which frequently impacted to natural disasters. The coastal area of Southern Java Island is one of an area prone to meteorological disasters, including Desa Gajahrejo. Desa Gajahrejo is susceptible to tidal wave disaster owing to its physical condition. Tidal waves disaster impacted both the socio-economic and environment of the area. The aim of this paper to identify the awareness and preparedness of the community and tourism actors in Desa Gajahrejo as the basis of further tourism planning. This research used field observation, in-depth interview and focus group discussion (FGD) as part of a community service agenda for the data-collection methods. The community service agenda was held in Ungapan Beach, which was attended by the representatives of each board in Desa Gajahrejo. The results showed that the tidal waves disaster has one-month, one-year and 5—7 years return periods. It impacted tourism activity both directly and indirectly. The community has good awareness, knowledge, and response to the multi-disaster hazards. It is shown from the well-understanding of the role and function of each board. Despite that, structured and documented planning is still unavailable. Therefore, further contingency planning is needed for tourism activity and disaster management implementation.

Quantitative modeling of residential building disaster recovery and effects of pre- and post-event policies

Understanding the process of community recovery impacted by various post-disaster decisions such as dynamic policies can effectively guide the recovery process and expedite recovery, thereby establishing a more resilient community. This paper proposes a methodology based on a multi-layer Monte Carlo simulation to model a two-stage recovery process for residential buildings: functional downtime due to delay and functional downtime due to repair. The delay portion of the model was modified based on the REDi framework and models the impeding factors that delay repairs such as post-disaster inspection, insurance claims, and building permits. Household income was examined to estimate the financing delay depending on different funding resources such as insurance and loans available to households at different income levels. The repair portion of the model followed the FEMA P-58 approach (which was originally for post-earthquake analysis) and was controlled by fragility functions. This study also investigates a series of policies to examine an illustrative example, namely the 2011 Joplin tornado. The residential recovery is modeled as a time-stepping process without any empirical data such that policies can be implemented pre-disaster (mitigation) and/or post-disaster. The ability to model hypothetical policy scenarios for residential recovery of a community will enable decision-makers to better understand collective community-wide impacts of their actions and policies, thereby improving community resilience planning.

Exploring neighborhood‐level resilience to flooding: Why the context and scale matter

AbstractThis article explores the role of contextual neighborhood‐level considerations in community resilience planning in coastal urban locations. A comparative case study analysis was conducted in three different locations in the City of Hampton, Virginia, that all share a common challenge of coastal flooding but have distinctly different neighborhood‐level circumstances that shape their flood impacts and resilience building options. The research approach utilizes a co‐production of knowledge and descriptive statistics to identify the overall flood risk and socioeconomic attributes of each locality that may influence broader citywide resilience investments within the realm of three overarching options: protection, accommodation, and relocation. It then applies a geospatial network analysis to determine which study neighborhoods will have significantly reduced access to critical facilities such as emergency services, medical facilities, and schools due to accelerated sea level rise as one of the key coastal hazards in this low‐lying region. The results show that each case study location has its own unique contextual circumstances that define its preferences for different resilience strategies regardless of the actual flood risk. The results also highlight the importance of holistic assessment of granular conditions that play a critical role in prioritization of resource allocation and interventions in coastal municipalities.

Path towards community resilience: Examining stakeholders’ coordination at the intersection of the built, natural, and social systems

It is well established that low-income and communities of color often receive delayed disaster recovery while disproportionately impacted from disasters. Governments have more recently employed equity principles into their policies and frameworks to improve resiliency of such communities to disasters. However, although many city agencies have an overlying goal to advance racial equity, the reality of coordination efforts may reveal shortcomings that perpetuate inequitable outcomes in the decision-making process of city stakeholders. This study assessed internal stakeholder interviews from city agencies, social services, and a nonprofit in summer of 2018 to identify obstacles and opportunities for building community resilience in Southeast Austin. An inductive qualitative analysis was then performed to extract emergent themes from the interviews. Key recommendations for improving equitable community resilience planning were developed such as, increased internal coordination and collaboration, and improved external communication and engagement. This study contributes to understanding the relationship of equity in community resiliency planning and represents an important contribution to understanding the influential factors that shape a decision-makers role in planning efforts. Improving such understandings can support more collaborative and participatory decision-making processes between affected community members and city agencies.

Exploring the food–energy–water nexus approach to enhance coastal community resilience research and planning

Non-technical summary Coastal communities face environmental challenges that put food, energy, and water systems at risk. Although highly interdependent, it is unknown the extent to which coastal resilience research has considered interactions among food–energy–water systems. Twenty peer-reviewed articles were identified that focused on these systems and coastal resilience. Although a nexus approach was not employed universally, these studies most commonly addressed interactions among these systems related to acute hazards. They consistently acknowledged the influence of energy and transportation systems upon the others. As such, planners should incorporate linkages across all three systems during coastal resilience planning especially in relation to acute hazards. Technical summary Coastal communities strive for resilience in the face of an ever-growing suite of threats by planning and preparing for numerous uncertain futures. Food, energy, and water systems are highly interconnected and essential to the well-being of coastal communities. However, it is unknown the extent to which coastal resilience research has included food–energy–water nexus considerations. This study used a systematic literature review of peer-reviewed research articles and identified 20 studies that focused on food, energy, and water systems as related to coastal resilience. Results revealed four main findings: (1) the food–energy–water nexus approach was most commonly applied to coastal resilience in the study of US locations and in the context of acute hazards, (2) a direct food–energy–water or other nexus approach was directly employed by only half of the studies, however, all highlighted the relevance of systems interconnections in the context of coastal resilience, (3) the energy system was shown to impact every system to which it was connected, and (4) the transportation system was also shown to impact every system to which it was connected, which suggests that the food–energy–water nexus should be expanded to include transportation systems. Social media summary Coastal resilience and food–energy–water nexus literature synthesis finds interconnected systems considerations relevant to resilience.

Projecting the effects of a warming climate on the hurricane hazard and insured losses: Methodology and case study

This paper summarizes research (conducted previously by the author) to incorporate (1) sea-surface temperature projections, (2) event-based hurricane simulation models, and (3) loss models to assess the impacts of the changing climate on the hurricane hazard and estimated insured losses. The focus of the work is on the US east coast and hence the formation and movement of hurricanes over the Atlantic Basin. As an illustrative case, the area around Charleston, South Carolina is considered. Specifically, this paper presents a methodology to probabilistically estimate regional hurricane loss considering both hurricane intensity and size as well as projected sea surface temperature change as a function of climate change.It is most common to characterize the hurricane wind hazard using a measure of intensity only. Recent studies have demonstrated the importance of accounting for storm size when characterizing the hurricane hazard in order to properly estimate/predict the spatial extent of damage. For purposes of regional loss estimation, therefore, considering maximum wind speed only may not be adequate. A storm with larger size but lower intensity might result in more damage and hence greater total loss than a smaller, more intense storm. Here, the maximum wind speed (intensity) and the radius of maximum winds (spatial extent) are selected as the two dominant indicators (parameters) characterizing the hurricane (event) hazard. The resulting bivariate hazard model is then used as input to a regional loss estimation model to illustrate its potential application. Only hurricane wind damage (and associated losses from both wind damage and water intrusion) is considered in this study. Collateral damage due to flood or storm surge is not addressed here.Simulated events impacting this region are extracted from a synthetic hurricane database (developed by the author and his colleagues) and the joint distribution of intensity and size is established to characterize the hurricane hazard. Regional loss for each simulated hurricane event is then estimated using the loss estimation module in HAZUS_MH. Finally, distributions of regional loss at different (event) hazard levels are generated.A future climate scenario (increasing sea surface temperature) is next considered and the joint distribution of hurricane intensity and size and the resulting loss distribution curve is recomputed. The results are then able to be compared to those under the current climate scenario. Such comparisons can help to inform codes and standards committees, for example, as they consider whether and how to take potential climate change impacts (in the design lifetime) into account. They also can inform ongoing public discourse around mitigation and adaptation, whether hardening of buildings and other infrastructure systems, community resilience planning, construction practices, or related policies.

Resilience hubs: a Maui case study to inform strategies for upscaling to resilience hub networks across coastal, remote, and island communities

Resilience hubs are buildings that enhance community cohesion during normal operations, while also enhancing resilience during emergencies. Maui Island is part of the Hawaiian archipelago, approximately 2500 miles from the nearest major continent. Due to its remote location, Maui is ideal to pilot projects that enhance resilience in isolated communities. At the neighborhood-scale, there is a need for establishing sites that empower communities to strengthen their cohesion, resilience and self-sufficiency. This can be achieved by investing in facilities that offer critical community services during emergencies (e.g. backup power, telecommunications, medical supplies, shelter from weather, and food and water rations). Ideally, local communities have a sense of ownership of resilience hubs and frequently use them during both normal and emergency periods. This ensures that hubs are accepted and trusted. Use cases presented in this research offer a methodology for assessing the suitability of proposed resilience hub pilot sites. Resilience hubs must also be assessed for vulnerabilities to climate change impacts and natural disasters, such as flooding, tsunamis, hurricanes, wildfires, and sea level rise. Resilient power systems can be developed for resilience hubs to ensure services are powered whether the power grid is operational or down, as well as to provide additional benefits during normal periods. These methodologies can be used by communities pursuing the establishment of resilience hubs. The highlighted methodologies are particularly applicable to island communities, coastal areas and remote locations, which are disproportionately affected by climate change impacts and natural disasters. This research paper describes three sites on Maui assessed for their suitability as resilience hubs by using the aforementioned methodologies. This research provides a methodology for establishing local resilience hubs on Maui, and how to upscale for application in other communities facing similar conditions. Once established, resilience hubs become a critical part of community resilience planning, while providing year-round benefits and services to local residents and enhancing community cohesion and emergency response and recovery capabilities.

Assessment of evacuation training needs: Targeting instruction to meet the requirements of local communities and agencies.

As the need to prepare for, respond to, and recover from major disruptive events continues to become more critical, the use of evacuation as a protective action strategy when confronted with life-threatening disasters is a key component of community resilience planning. While the basic concepts of evacuations are straightforward and consistent across locations and hazard types, the details of planning and managing an evacuation are more varied and complex. To improve evacuation preparedness, the training of emergency managers, police, and transportation agencies becomes key. This study assesses the need for evacuation training among key governmental agencies. A national survey of evacuation planning training needs among emergency managers and those involved in transportation management and operations was undertaken in 2016. This paper summarizes key findings of this survey, which included 727 respondents across 136 cities and 48 states and 2 territories, to reveal the results of this training-needs self-assessment. Based on this analysis, training needs and other recommendations for the development and delivery of curriculum on evacuation planning are presented.

Stochastic optimal control methodologies in risk-informed community resilience planning

The absorptive and restorative abilities of a community are two key elements of community resilience following disasters. The recovery of communities relies on an efficient restoration planning of damaged critical infrastructure systems, household units, and impaired supporting social and economic functions. These interdependent systems form a dynamic system of systems that changes continuously during restoration. Therefore, an effective and practical recovery planning process for a community can be modeled as a sequential dynamic optimization problem under uncertainty. This paper seeks to enhance our understanding of dynamic optimization concepts and their role in formulating post-disaster, community-level recovery strategies. Various methods of classic dynamic programming and reinforcement learning are examined and applied. Simulation-based approximate dynamic programming techniques are introduced to overcome the curse of dimensionality, which is characteristic of large-scale and multi-state systems of systems. The paper aims not only to study the unexplored topic of dynamic optimization in community resilience, but also to be a practical reference for policymakers, practitioners, engineers, and operations analysts to harness the power of dynamic optimization toward assessing and achieving community resilience.

Implementation of Blockchain Technology in Insurance Contracts Against Natural Hazards: A Methodological Multi-Disciplinary Approach

Abstract Risk insurance for disasters plays a relevant part in the implementation of risk reduction strategies during the pre-disaster phase. This is essential to support risk management towards decreasing the marginal risk allowing policy holders to transfer risk to avoid considerable financial loads from the costs incurred during the recovery phase in a post-disaster phase. There is evidence that the introduction of an integrated risk insurance strategy for community resilience planning is still lacking. Thus, this undermines the possibility to have proper optimized holistic risk management; on the one hand this strengthens pre-disaster risk mitigation measures, mostly relying on mitigative infrastructural solutions, and on the other hand it better defines risk prevention strategies mostly connected to land planning and urban development. This paper will show how insurance markets can play a key role towards mitigating the economic consequences of natural and climate change disasters, and how essential it is to better quantify the beneficial effects and costs of engineer-based mitigative solutions. In this context, the legal framework into which the actuarial quantitative model can be implemented will support the creation of an integrated multidisciplinary approach with potential implementation on a novel platform capable of collecting and processing information from different sources and dimensions such as blockchain technology. The scientific community is, in fact, increasingly interested in implementing blockchain technology to overcome problems linked to the contractual dimension of natural disaster risk insurance which can be interpreted as a sort of smart contracting. Through a study that involved four distinct areas, namely: law, environmental engineering, insurance and IT, this paper proposes a specific multidisciplinary methodology to achieve the drafting and implementation of a digital insurance contract on a blockchain platform against natural hazards. This paper proposes the basis to advance a quantitative concept to optimize the impact of catastrophe risk insurance onto the community resilience; in fact providing a key synergy for definition of pre-disaster conditions.

Community Resilience and Urban Planning during the Ninth-Century Maya Collapse: A Case Study from Actuncan, Belize

To remain in place in the immediate aftermath of the ninth-century Maya collapse, Maya groups employed various resilient strategies. In the absence of divine rulers, groups needed to renegotiate their forms of political authority and to reconsider the legitimizing role of religious institutions. This kind of negotiation happened first at the local level, where individual communities developed varied political and ideological solutions. At the community of Actuncan, located in the lower Mopan River valley of Belize, reorganization took place within the remains of a monumental urban centre built 1000 years before by the site's early rulers. I report on the changing configuration and use of Actuncan's urban landscape during the process of reorganization. These modifications included the construction of a new centre for political gatherings, the dismantling of old administrative buildings constructed by holy lords and the reuse of the site's oldest ritual space. These developments split the city into distinct civic and ritual zones, paralleling the adoption of a new shared rule divorced from cosmological underpinnings. This case study provides an example of how broader societal resilience relies on adaptation at the local level.

Community resilience and urban planning in tsunami-prone settlements in Chile.

Urban planning can serve to minimise the effects of a tsunami and enhance community resilience. This study explores to what extent urban planning has addressed tsunami resilience in four villages on Chile's South Pacific coast, each of which was struck by tsunamis in 1960, 2010, and 2015. Through a detailed policy review and semi-structured interviews with residents, this paper analyses whether tsunami mitigation policies were incorporated into regional and local planning tools. It finds that although the government proposed relocation to tsunami-safe areas after the tsunami of 1960, urban development continued mainly in tsunami inundation zones-in the context of weak local planning frameworks and in the absence of community participation. In only one of the four case studies did participatory planning bring about the relocation of an entire village to a safe location. This paper concludes that incorporating participatory risk zone planning into urban planning enhances tsunami resilience.

Urbanisation and disaster risk: the resilience of the Nigerian community in Auckland to natural hazards

ABSTRACTCommunity resources and the ability to organise them in times of challenges are essential in resilience. This study investigated the resilience of the Nigerian community in Auckland to the risk of natural hazards. Auckland has a multi-hazard landscape and an increasing rate of urbanisation which encompasses diverse communities and nationalities. The study examined five resources, the social, economic, communication, disaster competency and physical resources to determine the resilience of the Nigerian community to natural hazards in Auckland. The study collected data from both secondary and primary sources. The primary source included information from surveys and interviews; and secondary data from existing literature and documents in the public domain. The research used both parametric and non-parametric methods and themes identification for analysis. A community resilience index was created to calculate the current resilience status of the Nigerian community. Research findings suggested policy interventions to enhance indicators of low resilience. Enhancing resilience in the community depends on how the government addresses these indicators in future community resilience planning.

Probabilistic decision-support framework for community resilience: Incorporating multi-hazards, infrastructure interdependencies, and resilience goals in a Bayesian network

A probabilistic decision support framework is developed in this study for community resilience planning under multiple hazards using performance goals based guidelines such as the Oregon Resilience Plan and the National Institute of Standards and Technology Community Resilience Planning Guide. Herein, resilience of community infrastructure systems is defined as the joint probability of achieving robustness and rapidity based performance goals, which is quantified using Bayesian networks. The framework assesses the effects of decision support options such as selection of hazards, resilience goals, and mitigation (ex-ante) and response (ex-post) strategies to identify measures that can improve infrastructure performance to meet community defined resilience goals. This framework is applied for resilience assessment of building, transportation, water, and electric power infrastructure systems in Seaside, Oregon, under combined earthquake ground shaking and tsunami inundation hazards corresponding to different return periods. Uncertainties in damage, restoration, and economic losses are explicitly considered and propagated in the framework using Monte Carlo simulation (MCS). The MCS results are then used to inform the Bayesian network, which evaluates the joint resilience of infrastructure systems in Seaside. Results highlight the impact of considering different performance goals, introduction of ex-ante and ex-post measures, and interdependencies between various infrastructure systems on infrastructure resilience.

Participatory Disaster Recovery Simulation Modeling for Community Resilience Planning

A major challenge in enhancing the resilience of communities stems from current approaches used to identify needs and strategies that build the capacity of jurisdictions to mitigate loss and improve recovery. A new generation of resilience-based planning processes has emerged in the last several years that integrate goals of community well-being and identity into recovery-based performance measurement frameworks. Specific tools and refined guidance are needed to facilitate evidence-based development of recovery estimates. This article presents the participatory modeling process, a planning system designed to develop recovery-based resilience measurement frameworks for community resilience planning initiatives. Stakeholder engagement is infused throughout the participatory modeling process by integrating disaster recovery simulation modeling into community resilience planning. Within the process, participants get a unique opportunity to work together to deliberate on community concerns through facilitated participatory modeling. The participatory modeling platform combines the DESaster recovery simulation model and visual analytics interfaces. DESaster is an open source Python Library for creating discrete event simulations of disaster recovery. The simulation model was developed using a human-centered design approach whose goal is to be open, modular, and extensible. The process presented in this article is the first participatory modeling approach for analyzing recovery to aid creation of community resilience measurement frameworks.

Community Businesses as Social Units in Post-Disaster Recovery

With global climate change and rapid development in environmentally vulnerable areas, communities are increasingly looking for ways to manage, adapt to, and mitigate adverse impacts from disaster events. To help communities achieve this goal, planners must first understand how various stakeholders behave in post-disaster situations. In this paper, we use household and business surveys conducted in New York City after the 2012 Hurricane Sandy to examine recovery decisions of businesses compared to households as well as their respective use of social, financial, and institutional network resources to recover. Our findings suggest that community businesses, particularly locally owned small businesses, are not simply economic units but also play critical social roles in community functioning. Business recovery decisions are often made based on social, not purely profit-maximizing reasons. Recognizing this dual characteristic of businesses is an important step to better engaging this stakeholder group in community resilience and recovery planning processes.

Hindcasting community-level building damage for the 2011 Joplin EF5 tornado

Resiliency of communities prone to natural hazards can be enhanced through the use of risk-informed decision-making tools. These tools can provide community decision makers key information, thereby providing them the ability to consider an array of mitigation and/or recovery strategies. The Center for Risk-Based Community Resilience Planning, headquartered at Colorado State University in Fort Collins, Colorado, developed an Interdependent Networked Community Resilience (IN-CORE) computational environment. The purpose of developing this computational environment is to build a decision-support system, for professional risk planners and emergency responders, but even more focused on allowing researchers to explore community resilience science. The eventual goal was being to integrate a broad range of scientific, engineering and observational data to produce a detailed assessment of the potential impact of natural and man-made hazards for risk mitigation, planning and recovery purposes. The developing computational environment will be capable of simulating the effects from different natural hazards on the physical and socioeconomic sectors of a community, accounting for interdependencies between the sectors. However, in order to validate this computational tool, hindcasting of a real event was deemed necessary. Therefore, in this study, the community of Joplin, Missouri in the USA, which was hit by an EF-5 tornado on May 22, 2011, is modeled in the IN-CORE v1.0 computational environment. An explanation of the algorithm used within IN-CORE is also provided. This tornado was the costliest and deadliest single tornado in the USA in the last half century. Using IN-CORE, by uploading a detailed topological dataset of the community and the estimated tornado path combined with recently developed physics-based tornado fragilities, the damage caused by the tornado to all buildings in the city of Joplin was estimated. The results were compared with the damage reported from field studies following the event. This damage assessment was done using three hypothetical idealized tornado scenarios, and results show very good correlation with observed damage which will provide useful information to decision makers for community resilience planning.

Stochastic post-disaster functionality recovery of community building portfolios I: Modeling

Understanding the process of post-disaster recovery is a critical step toward assessing and achieving community resilience. However, the recovery process of a community building portfolio as a spatially distributed system is intrinsically complex and highly uncertain, and is conditional on the resourcefulness and social-economic characteristics of the community as well as the various decisions made by numerous community stakeholders and building owners at different phases of the recovery. We propose a simulation-based building portfolio recovery model (BPRM) to predict the functionality recovery time and recovery trajectory of a community building portfolio following natural scenario hazard events, in two steps: (1) modeling individual building-level restoration as a discrete state, continuous time Markov Chain (CTMC); and (2) modeling building portfolio-level recovery through aggregating the CTMC restoration processes of individual buildings across the domain of the community and over the entire recovery time horizon. We propagate uncertainties associated with the recovery process in a consistent manner in order to quantify portfolio recovery metrics probabilistically. The proposed building portfolio recovery model is intended to support risk-informed community resilience planning and hazard mitigation.

Stochastic post-disaster functionality recovery of community building portfolios II: Application

Part I of this two-part paper introduced a building portfolio recovery model (BPRM) to forecast the stochastic recovery process of building portfolios within a community following an extreme hazard event. The BPRM models restoration of individual building-level functionalities as a discrete state, continuous time Markov Chain, while it models portfolio-level recovery by aggregating the building-level restoration processes in both temporal and spatial dimensions. In this paper, we illustrate the implementation of the BPRM to project the building portfolio recovery of a mid-size community following a predefined scenario earthquake. The recovery analysis integrates the engineering process of building reconstructions with available community resources and social-economic characteristics of different population groups. The spatial variations in recovery speed in different residential zones within the community reflect the disparities in resourcefulness and recoverability of homeowners with different social and economic status. In addition, sensitivity studies are performed to investigate the capability of the BPRM to quantify the impact of candidate pre-disaster mitigation strategies on the building portfolio recovery time and trajectory, illustrating the potential use of the BPRM in supporting risk-informed community resilience planning.

Building portfolio fragility functions to support scalable community resilience assessment

Community resilience planning, risk mitigation, and recovery optimization must assume a system perspective at the level of the overall community built environment. While engineers can quantify the performance of individual buildings and facilities, such information must be aggregated to reflect the vulnerability of the building portfolio as a whole to support resilience-based decisions at the community level. This study presents a methodology for building portfolio analysis that relates the performance of individual buildings exposed to natural hazards to the overall performance of a building portfolio. We introduce the concept of building portfolio fragility function (BPFF), defined as the probability that a building portfolio, as an aggregated system, fails to achieve prescribed performance objectives conditioned on scenario hazards, to characterize the vulnerability of a building portfolio and to directly inform resilience-driven decisions at the community level. The paper concludes with an illustration of the development of BPFFs to the Centerville community.