Assessment of Critical Infrastructure Resilience to Flooding Using a Response Curve Approach

Characterizing the level of urban Flood vulnerability using the social-ecological-technological systems framework, the case of Adama city, Ethiopia

This study characterizes the flood vulnerability of Adama City, Ethiopia, where the city faces high flood vulnerability due to its unplanned urbanization in low-lying floodplain areas surrounding deforested mountains and ridges. The study applied an interlinked Social-Ecological-Technological-Systems (SETS) vulnerability framework using a GIS-based Multi-Criteria Decision-Making and Analytical Hierarchy Process (MCDM-AHP). The framework analyzed exposure, sensitivity, and adaptive capacity to flooding for each of the three SETS domains. The study analyzed 18 variables at the city level within each SETS domain. The result revealed that clusters of flood-vulnerable areas were identified by each SETS domain showing the concentration of flood vulnerability in the study area and the need to consider prompt adaptive mechanisms to severe and recurring flooding. The finding has significant implications for holistic approaches to sustainable cities. Moreover, the reduction of complex urban flood vulnerabilities according to their priority as individual or combined solutions for decision-makers and professionals in early warning and flood management systems is the other contribution of the study.

Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network

Resilient stormwater infrastructure is one of the fundamental components of resilient and sustainable cities. For this, the resilience assessment of stormwater infrastructure against earthquake hazards is crucial for municipal authorities. The objective of this study is to develop a resilience assessment framework for stormwater pipe infrastructure against seismic hazards. A Bayesian belief network (BBN)-based stormwater infrastructure resilience model is constructed based on the published literature and expert knowledge. The developed framework is implemented in the city of Regina, Canada, to assess the city's stormwater pipe infrastructure resilience. The outcome of the model indicates that proposed BBN-based stormwater infrastructure resilience model can effectively quantify uncertainties and handle the nonlinear relationships between several reliability and recovery factors. The model is also capable of identifying the most sensitive and vulnerable stormwater pipes within the network.

Building Critical Infrastructures: Evaluating the Roles of Governance and Institutions in Infrastructural Developments in Sub-Sahara African Countries

BACKGROUND

The Sub-Saharan African (SSA) region has notably been in the limelight of infrastructural deficit discussions over the decades. Although the region's infrastructural development is gradually improving, the levels and pace of development remain generally poor compared to the rest of the world.

OBJECTIVES

This study thus aims to empirically examine the roles of governance and institutions in infrastructural developments in the Sub-Sahara African (SSA) region toward addressing the pressing needs for critical infrastructures for the region.

RESEARCH DESIGNS

The empirical strategies utilized in the study include the Common Correlated Efficient Mean Group (CCEMG) and Dynamic CCEMG methods among others. These empirical approaches were applied to analyze data on governance and institutional quality proxies for the SSA region to achieve the study's objectives while controlling for the effects of industrial value-added, foreign capital inflow (FDI), and overall economic growth for the understudied period (1990-2019).

RESULTS

The results reflect the essence of governance and institutional quality as these variables significantly boost infrastructural development in SSA. In addition, industrialization and growth also show a favorable impact on the development of infrastructure thus reflecting that the transition from agrarian to industrial economies occurs in parallel with infrastructure development in the SSA. However, FDI inflows were not found to be significantly instrumental to infrastructural development in the region.

CONCLUSIONS

Hence, the SSA must strive to strengthen institutions and harmonize their industrial and economic push with infrastructural developments while encouraging potential foreign investors to diversify investments to infrastructural projects beyond the usual primary sector/resource-based activities.

Resilience of urban public electric vehicle charging infrastructure to flooding

An adequate charging infrastructure is key to enabling high personal electric vehicle (EV) adoption rates. However, urban flooding—whose frequency and intensity are increasing due to climate change—may be an impediment. Here, we study how geographically-correlated outages due to floods impact public EV charging networks in Greater London. While we find no appreciable impact on the ability of battery EVs to serve typical urban driving behaviors, we observe disproportionate stresses on chargers both near, and surprisingly significantly farther from, the flooded regions. For instance, we find over 50% increase in charger utilization and 260% increase in the distance to the nearest available charger in parts of Greater London over 10 km away. Concerningly, the impact is most concentrated on already-stressed sections of the network, underscoring the infrastructure’s vulnerability. Finally, we develop and evaluate four strategies for city planners to enhance the flood resilience of cities’ public EV charging networks.

A study of how the Greater London electric vehicle charging network is affected by flooding reveals disproportionate impacts on already-stressed parts of the network, peaking as far as over 10 km away from the flooded regions.

Resilience Indicator of Urban Transport Infrastructure: A Review on Current Approaches

Urban transport infrastructures (TIs) play a central role in an urban society that faces more and more disasters. TIs, part of critical infrastructures (CIs), are highly correlated with urban disaster management in terms of their resilience when cities are facing a crisis or disaster. According to many studies, indicator assessment has been frequently used for the resilience management of CIs in recent decades. Defining and characterizing indicators can be useful for disaster managers as it could help monitor and improve the capacities and performance of TIs. The purpose of this paper, therefore, is (1) to identify and summarize the existing indicators of TIs resilience from the currently available literature, and (2) to discuss the possible future studies of the resilience indicator of TIs. The first results indicated that there are some barriers to identify indicators following the common search method through keywords. Additionally, the indicators found are mainly related to technical information, the disruption stage, and internal TIs. Finally, due to the complexity of indicator assessment, sub-indicators and indicator spatialization are widely used in the resilience assessment of urban TIs studies.

Earthquake Resilience Framework for a Stormwater Pipe Infrastructure System Integrating the Best Worst Method and Dempster–Shafer Theory

Stormwater pipe infrastructure is a fundamental requirement of any nation, but pipes can be damaged in natural disasters. Consequently, evaluating the resilience of stormwater infrastructure to earthquake damage is an essential duty for any city because it outlines the capability to recover from a disaster after the event. The resilience quantification process needs various data types from various sources, and uncertainty and partial data may be included. This study recommends a resilience assessment framework for stormwater pipe infrastructure facing earthquake hazards using Hierarchical Evidential Reasoning (HER) on the basis of the Dempster–Shafer (D-S) theory. The developed framework was implemented in the City of Regina, SK, Canada to quantify the resilience of the stormwater pipe infrastructure. First, various resilience factors were identified from the literature. Based on experts’ judgment, the weight of these factors was determined using the Best Worst Method (BWM). After that, the resilience was determined using the D–S theory. Finally, sensitivity analysis was conducted to examine the sensitivity of the factors of the recommended hierarchical stormwater infrastructure resilience model. The recommended earthquake resilience assessment model produced satisfying outcomes, which showed the condition state of resilience with the degree of uncertainty.

Critical Infrastructures Overview: Past, Present and Future

Industrialized societies depend on the proper functioning of a whole range of technological infrastructures, such as electricity, road and railway networks and telecommunications which, due to their importance, are generically referred to as critical infrastructures (CIs). Technical failures, natural disasters and malicious events, if not terrorist, could have devastating effects on these infrastructures. The events of the last few years have accelerated efforts to identify and designate CIs at national and European levels and have reinforced concerns about increasing their protection in sensitive sectors for the safety of the individual and the community. The aim of this research is to provide the basic elements to understand the issue along with the reasons for its importance both at national, European and international level. In particular, after analyzing the origin of the problem, a systematic literature review is carried out to study the current research around future perspectives relating to the management of Cis, with particular focus on three research questions: RQ1 “What types of risk assessment methods are used to manage CIs?”, RQ2 “What are the environmental risk mitigation strategies for CIs?” and RQ3 “What is the role of the human factor in the prevention of risks for CIs?”. The results aim to be guidelines for decision makers and researchers interested in this topic.

Flood Impacts on Critical Infrastructure in a Coastal Floodplain in Western Puerto Rico during Hurricane María

Flooding during extreme weather events damages critical infrastructure, property, and threatens lives. Hurricane María devastated Puerto Rico (PR) on 20 September 2017. Sixty-four deaths were directly attributable to the flooding. This paper describes the development of a hydrologic model using the Gridded Surface Subsurface Hydrologic Analysis (GSSHA), capable of simulating flood depth and extent for the Añasco coastal flood plain in Western PR. The purpose of the study was to develop a numerical model to simulate flooding from extreme weather events and to evaluate the impacts on critical infrastructure and communities; Hurricane María is used as a case study. GSSHA was calibrated for Irma, a Category 3 hurricane, which struck the northeastern corner of the island on 7 September 2017, two weeks before Hurricane María. The upper Añasco watershed was calibrated using United States Geological Survey (USGS) stream discharge data. The model was validated using a storm of similar magnitude on 11–13 December 2007. Owing to the damage sustained by PR’s WSR-88D weather radar during Hurricane María, rainfall was estimated in this study using the Weather Research Forecast (WRF) model. Flooding in the coastal floodplain during Hurricane María was simulated using three methods: (1) Use of observed discharge hydrograph from the upper watershed as an inflow boundary condition for the coastal floodplain area, along with the WRF rainfall in the coastal flood plain; (2) Use of WRF rainfall to simulate runoff in the upper watershed and coastal flood plain; and (3) Similar to approach (2), except the use of bias-corrected WRF rainfall. Flooding results were compared with forty-two values of flood depth obtained during face-to-face interviews with residents of the affected communities. Impacts on critical infrastructure (water, electric, and public schools) were evaluated, assuming any structure exposed to 20 cm or more of flooding would sustain damage. Calibration equations were also used to improve flood depth estimates. Our model included the influence of storm surge, which we found to have a minimal effect on flood depths within the study area. Water infrastructure was more severely impacted by flooding than electrical infrastructure. From these findings, we conclude that the model developed in this study can be used with sufficient accuracy to identify infrastructure affected by future flooding events.

Hazards, Infrastructure Networks and Unspecific Resilience

The aim of this paper is to provide a framework to improve urban resilience independently of the nature of the disturbances. Recent disasters had a significant impact on critical infrastructures providing essential urban services such as energy, transportation, telecommunication, water and food supply or health care. Indeed, several natural and human-made hazards may lead to disruptions, and most critical infrastructures are networked and highly interdependent. Henceforth, resilience building remain focused on specific hazards or on improving the resilience, separately, of single infrastructures. In order to enhance urban resilience, this paper is based on learnings from three case studies that are the 2001 WTC terrorist attack, hurricanes Irma and Maria in 2017 and the 2016 Seine river flood in Paris. These events highlight disruptions to urban services, but also some resilience options. In light of both the literature and our case studies, a framework of unspecific resilience is provided for improving some resilience principles, namely omnivory, redundancy, buffering, high flux, homeostasis and flatness within electric energy, water and food supply and transportation networks. Rebuilding resilience within this framework is further discussed with respect to all kinds of disruptive events.

The Resilience of Critical Infrastructure Systems: A Systematic Literature Review

Risk management is a fundamental approach to improving critical infrastructure systems’ safety against disruptive events. This approach focuses on designing robust critical infrastructure systems (CISs) that could resist disruptive events by minimizing the possible events’ probability and consequences using preventive and protective programs. However, recent disasters like COVID-19 have shown that most CISs cannot stand against all potential disruptions. Recently there is a transition from robust design to resilience design of CISs, increasing the focus on preparedness, response, and recovery. Resilient CISs withstand most of the internal and external shocks, and if they fail, they can bounce back to the operational phase as soon as possible using minimum resources. Moreover, in resilient CISs, early warning enables managers to get timely information about the proximity and development of distributions. An understanding of the concept of resilience, its influential factors, and available evaluation and analyzing tools are required to have effective resilience management. Moreover, it is important to highlight the current gaps. Technological resilience is a new concept associated with some ambiguity around its definition, its terms, and its applications. Hence, using the concept of resilience without understanding these variations may lead to ineffective pre- and post-disruption planning. A well-established systematic literature review can provide a deep understanding regarding the concept of resilience, its limitation, and applications. The aim of this paper is to conduct a systematic literature review to study the current research around technological CISs’ resilience. In the review, 192 primary studies published between 2003 and 2020 are reviewed. Based on the results, the concept of resilience has gradually found its place among researchers since 2003, and the number of related studies has grown significantly. It emerges from the review that a CIS can be considered as resilient if it has (i) the ability to imagine what to expect, (ii) the ability to protect and resist a disruption, (iii) the ability to absorb the adverse effects of disruption, (iv) the ability to adapt to new conditions and changes caused by disruption, and (v) the ability to recover the CIS’s normal performance level after a disruption. It was shown that robustness is the most frequent resilience contributing factor among the reviewed primary studies. Resilience analysis approaches can be classified into four main groups: empirical, simulation, index-based, and qualitative approaches. Simulation approaches, as dominant models, mostly study real case studies, while empirical methods, specifically those that are deterministic, are built based on many assumptions that are difficult to justify in many cases.

Reflexive Governance for Infrastructure Resilience and Sustainability

Infrastructure development is one of the areas most in need of climate-resilient and friendly investments. The COVID-19 pandemic will increase government spending in this direction. This paper demonstrates how the principles of reflexive governance are key to unlock the full potential of such investments. By establishing an adaptive and redundant institutional capacity in the provision of public services, reflexive governance can enable a successful path towards climate resilience and sustainability.

Sustainable Digital Transformation of Disaster Risk—Integrating New Types of Digital Social Vulnerability and Interdependencies with Critical Infrastructure

This article explores the relationship between digital transformation and disaster risk. Vulnerability studies aim at differentiating impacts and losses by using fine-grained information from demographic, social, and personal characteristics of humans. With ongoing digital development, these characteristics will transform and result in new traits, which need to be identified and integrated. Digital transformations will produce new social groups, partly human, semi-human, or non-human—some of which already exist, and some which can be foreseen by extrapolating from recent developments in the field of brain wearables, robotics, and software engineering. Though involved in the process of digital transformation, many researchers and practitioners in the field of Disaster Risk Reduction or Climate Change Adaptation are not yet aware of the repercussions for disaster and vulnerability assessments. Emerging vulnerabilities are due to a growing dependency on digital services and tools in the case of a severe emergency or crisis. This article depicts the different implications for future theoretical frameworks when identifying novel semi-human groups and their vulnerabilities to disaster risks. Findings include assumed changes within common indicators of social vulnerability, new indicators, a typology of humans, and human interrelations with digital extensions and two different perspectives on these groups and their dependencies with critical infrastructure.

Resilience Assessment of Interdependent Infrastructure Systems: A Case Study Based on Different Response Strategies

Resilient infrastructure systems are essential for continuous and reliable functioning of social and economic systems. Taking advantage of network theory, this paper models street network, water supply network, power grid and information infrastructure network as layers that are integrated into a multilayer network. The infrastructure interdependencies are described using five basic dependence patterns of fundamental network elements. Definitions of dynamic cascading failures and recovery mechanisms of infrastructure systems are also established. The main contribution of the paper is a new infrastructure network resilience measure capable of addressing complex infrastructure system, as well as network component (layer) interdependences. The new measure is based on infrastructure network performance, proactive absorptive capacity and reactive restorative capacity, with three resilience features of network—robustness, resourcefulness, and rapidity. The quantitative resilience measure using dynamic space-time simulation model is illustrated with a multilayer infrastructure network numerical test, including different response strategies to floods of different scale. The results demonstrate that the resilience measure provides an evaluation method of various protection and restoration strategies that will optimize the performance of interdependent infrastructure system. The sector-specific decisions could not always lead to optimal system solutions, and systems approach offers significant benefits for increasing infrastructure system resilience. This study can assist municipal decision makers in (i) better understanding the effects of different response strategies on the resilience of interdependent infrastructure system, and (ii) deciding which strategy should be adopted under different types of disasters.

A Two-Stage Restoration Resource Allocation Model for Enhancing the Resilience of Interdependent Infrastructure Systems

Infrastructure systems play a critical role in delivering essential services that are important to the economy and welfare of society. To enhance the resilience of infrastructure systems after a large-scale disruptive event, determining where and when to invest restoration resources is a challenge for decision makers. Comprehensively considering the recovery time of infrastructure systems and the overall losses resulting from a disaster, this study proposes a two-stage restoration resource allocation model for enhancing the resilience of interdependent infrastructure systems. First, to evaluate the effect of resource allocation during the recovery process, dynamic resilience is selected as the criterion for the recovery of infrastructure systems. Second, taking into consideration the decision makers’ point of view, a two-stage resource allocation model is proposed. The objective of the first stage is to quickly recover the infrastructure systems’ dynamic resilience to meet the basic needs of the users. The second stage is aimed at minimizing the overall losses in the following recovery process. The effects of infrastructure interdependencies on resource allocation are incorporated in the model using the dynamic inoperability input–output model. Through a case study, the proposed approach is compared with other resource allocation strategies. The results show that: (1) the restoration resource allocation strategy obtained from the proposed approach balances the recovery time and the overall losses to infrastructure systems; and (2) the value of the usage cost of the unit restoration resource has a significant impact on the recovery time and the overall losses under different strategies. The proposed model is both effective and efficient in solving the post-disaster resource allocation problem and can provide decision makers with scientific decision support.

A Framework to Evaluate Urban Flood Resilience of Design Alternatives for Flood Defence Considering Future Adverse Scenarios

In urbanized plains that are subject to flooding, the socioeconomic aspects, climate characteristics, built environment, and riverine processes exhibit bi-univocal relationships with the flood formation itself, creating a pattern of development without a predefined equilibrium state. The complexity of processes involved in flood management and the need for a comparative assessment method to hierarchise different design alternatives or planning scenarios requires practical and quantitative methods for urban diagnoses, including flood risk and resilience aspects. This paper proposes an alternative pathway to evaluate design alternatives for urban flood mitigation, assessing resilience in quantitative terms. In this way, a methodological framework is presented with which to evaluate flood resilience in urban watersheds planning, through the application of the Urban Flood Resilience Index (UFRI) and Future Scenarios Criteria (FSC). A case study illustrates the method using an urban watershed in Rio de Janeiro/Brazil. This study considered two possible design alternatives for flood control, with concentrated and distributed measures. The resilience mapping using the UFRI showed that the adoption of distributed measures could increase the areas classified as showing very high resilience by 41%, while very low resilience areas would be reduced by 87%. The FSC is able to present the integrated results of resilience variation from present and future conditions, considering, for example, climate change effects or unplanned urbanisation scenarios. The framework is able to perform comparisons between alternatives, showing the advantages associated with adopting distributed measures over the watershed, which reflected in a resilience value that was 24% higher when compared to the results obtained for the concentrated solutions scenario.

A Time-Integrated Index for Flood Risk to Resistance Capacity

The lack of open spaces and the intense land use occupation in flood plains makes floods in consolidated urban areas difficult to mitigate. In these areas, setting a standard pre-defined return period for projects can limit and even preclude flood mitigation actions. However, it is possible to propose flood control alternatives that are compatible with available spaces. Thus, determining how much the original risk is reduced and how significant the residual risk can be becomes the main target. In this context, a time-integrated index for risk to resistance capacity is proposed to address these questions. This index correlates the exposure of buildings and urban infrastructure to the hazard of a given flood and is then evaluated over a project horizon through a sequence of events. The proposed index is applied to the Canal do Mangue catchment, a highly urbanized watershed located in Rio de Janeiro. The results demonstrate the difficulty of designing flood mitigation measures in extremely occupied watersheds and the importance of evaluating residual risks associated with proposed projects. As an additional result, a scenario with concentrated measures is compared to another with distributed interventions, evidencing the greater coverage of the latter.

A Conceptual Time-Varying Flood Resilience Index for Urban Areas: Munich City

In response to the increased frequency and severity of urban flooding events, flood management strategies are moving away from flood proofing towards flood resilience. The term ‘flood resilience’ has been applied with different definitions. In this paper, it is referred to as the capacity to withstand adverse effects following flooding events and the ability to quickly recover to the original system performance before the event. This paper introduces a novel time-varying Flood Resilience Index (FRI) to quantify the resilience level of households. The introduced FRI includes: a) Physical indicators from inundation modelling for considering the adverse effects during flooding events, and b) social and economic indicators for estimating the recovery capacity of the district in returning to the original performance level. The district of Maxvorstadt in Munich city is used for demonstrating the FRI. The time-varying FRI provides a novel insight into indicator-based quantification methods of flood resilience for households in urban areas. It enables a timeline visualization of how a system responds during and after a flooding event.

Flood Resilience of Critical Infrastructure: Approach and Method Applied to Fort Lauderdale, Florida

In order to increase the flood resilience of cities (i.e., the ability to cope with flood hazards), it is also crucial to make critical infrastructure functions resilient, since these are essential for urban society. Cities are complex systems with many actors of different disciplines and many interdependent critical infrastructure networks and functions. Common flood risk analysis techniques provide useful information but are not sufficient to obtain a complete overview of the effects of flooding and potential measures to increase flood resilience related to critical infrastructure networks. Therefore, a more comprehensive approach is needed which helps accessing knowledge of actors in a structured way. Fort Lauderdale, Florida, United States has suffered from flood impacts, especially from disruptions in critical infrastructure. This paper shows how shared insight among different sectors and stakeholders into critical infrastructure resilience and potential resilience-enhancing measures was obtained using input from these actors. It also provides a first quantitative indication of resilience, indicated by the potential disruption due to floods and the effect of measures on resilience. The paper contributes to the existing literature on resilience specifically by considering the duration of disruption, the inclusion of critical infrastructure disruption in flood impact analysis, and the step from resilience quantification to measures.

Assessment and Possible Solution to Increase Resilience: Flooding Threats in Terni Distribution Grid

In recent years, because of increasing frequency and magnitude of extreme weather events, the main stakeholders of electric power systems are emphasizing issues about resilience. Whenever networks are designed and development plans are drawn, this new feature must be assessed and implemented. In this paper, a procedure to evaluate the resilience of a distribution network against flooding threats is presented. Starting from a detailed analysis about the resilience of each asset of the grid, the procedure implements the exploration of the network in order to evaluate the impact of interruptions (e.g., in terms of number of disconnected users) produced by the specific threat; then, it calculates the resilience indices of the whole system. The procedure is applied with respect to the flooding threats, on a real distribution network in the center of Italy (i.e., the distribution network of Terni). Referring to this case study, the proposed method suggests countermeasures able to reduce the impact of flooding events and evaluates their benefits. Results indicate that, at the present time, the network is adequately resilient with respect to flooding events, as demonstrated by the index values. However, the remedial actions identified by the procedure are also able to improve the resilience of the network and, in addition, they are in agreement with the development plan already established by the distribution system operator (DSO).