Critical Infrastructure Resilience Research Articles

A Markov Decision Process Approach for Cost-Benefit Analysis of Infrastructure Resilience Upgrades.

As climate change threatens to cause increasingly frequent and severe natural disasters, decisionmakers must consider costly investments to enhance the resilience of critical infrastructures. Evaluating these potential resilience improvements using traditional cost-benefit analysis (CBA) approaches is often problematic because disasters are stochastic and can destroy even hardened infrastructure, meaning that the lifetimes of investments are themselves uncertain. In this article, we develop a novel Markov decision process (MDP) model for CBA of infrastructure resilience upgrades that offer prevention (reduce the probability of a disaster) and/or protection (mitigate the cost of a disaster) benefits. Stochastic features of the model include disaster occurrences and whether or not a disaster terminates the effective life of an earlier resilience upgrade. From our MDP model, we derive analytical expressions for the decisionmaker's willingness to pay (WTP) to enhance infrastructure resilience, and conduct a comparative static analysis to investigate how the WTP varies with the fundamental parameters of the problem. Following this theoretical portion of the article, we demonstrate the applicability of our MDP framework to real-world decision making by applying it to two case studies of electric utility infrastructure hardening. The first case study considers elevating a flood-prone substation and the second assesses upgrading transmission structures to withstand high winds. Results from these two case studies show that assumptions about the value of lost load during power outages and the distribution of customer types significantly influence the WTP for the resilience upgrades and are material to the decisions of whether or not to implementthem.

Cybersecurity capabilities for critical infrastructure resilience

PurposeFor many innovative organisations, Industry 4.0 paves the way for significant operational efficiencies, quality of goods and services and cost reductions. One of the ways to realise these benefits is to embark on digital transformation initiatives that may be summed up as the intelligent interconnectivity of people, processes, data and cyber-connected things. Sadly, this interconnectivity between the enterprise information technology (IT) and industrial control systems (ICS) environment introduces new attack surfaces for critical infrastructure (CI) operators. As a result of the ICS cybersecurity risk introduced by the interconnectivity between the enterprise IT and ICS networks, the purpose of this study is to identify the cybersecurity capabilities that CI operators must have to attain good cybersecurity resilience.Design/methodology/approachA scoping literature review of best practice international CI protection frameworks, standards and guidelines were conducted. Similar cybersecurity practices from these frameworks, standards and guidelines were grouped together under a corresponding National Institute of Standards and Technology (NIST) cybersecurity framework (CF) practice. Practices that could not be categorised under any of the existing NIST CF practices were considered new insights, and therefore, additions.FindingsA CI cybersecurity capability framework comprising 29 capability domains (cybersecurity focus areas) was developed as an adaptation of the NIST CF with an added dimension. This added dimension emphasises cloud computing and internet of things (IoT) security. Each of the 29 cybersecurity capability domains is executed through various capabilities (cybersecurity processes and procedures). The study found that each cybersecurity capability can further be operationalised by a set of cybersecurity controls derived from various frameworks, standards and guidelines, such as COBIT®, CIS®, ISA/IEC 62443, ISO/IEC 27002 and NIST Special Publication 800-53.Practical implicationsCI sectors are immediately able to adopt the CI cybersecurity capability framework to evaluate their levels of resilience against cyber-attacks, given new attack surfaces introduced by the interconnectivity of cyber-connected things between the enterprise and ICS levels.Originality/valueThe authors present an added dimension to the NIST framework for CI cyber protection. In addition to emphasising cryptography, IoT and cloud computing security aspects, this added dimension highlights the need for an integrated approach to CI cybersecurity resilience instead of a piecemeal approach.

Assessing critical infrastructure resilience in terms of its service-providing capacity in coastal Bangladesh: A synthesis of geospatial techniques and social responses

Lack of adequate infrastructure, especially in the coastal regions of developing countries, limits the capacity of households to prevent, cope with, and recover from the adverse effects of natural hazards. The services provided by critical infrastructure (CI) contribute to the overall resilience of marginalized coastal households to natural hazards. CI, in turn, may itself be resilient (or not). Resilient CI is capable of providing services to meet the community's demand for that service. This research developed and tested an innovative framework for assessing CI resilience in terms of services it was capable to provide to coastal residents in three separate phases (before, during, and after) of Cyclone Sidr, using empirical evidence from a coastal sub-district of Bangladesh. The disaster-phase-wise level of demand for these services was identified using GIS-based network analysis combined with community rankings of service importance across the disaster phases. Households were surveyed to determine whether they were able to procure CI services in each phase. A comparison of service demand levels with success in procuring CI services was used to assess CI resilience. The results revealed spatio-temporal variation in the service provision of existing CI units to households in the study area. A mixed trend was indicated: less exposed communities contained a somewhat higher percentage of service-receiving households than more exposed communities during the pre- and post-disaster phases, whereas the percentage was higher in the more exposed communities during the syn-disaster phase. This approach has the potential to determine whether the existing CI in a community is resilient enough to support the population in the different phases of a cyclone. The results could guide planners to bolster CI resilience for communities, thereby also improving community resilience to natural hazards.

Cascading disasters triggered by tsunami hazards: A perspective for critical infrastructure resilience and disaster risk reduction

Although many studies have investigated relationships between tsunami characteristics and the impact on physical property and infrastructure, such information cannot explain how the damage to each object or type of infrastructure can trigger failures of other facilities. To understand these connections and the cascading impacts, this article reviewed several recent damaging tsunami events in Japan and Indonesia, including the 2004 Indian Ocean tsunami and the 2011 Great East Japan Earthquake and tsunami. A proposed cascading magnitude scale was applied to each tsunami event to determine and categorize causes, effects, and escalation points. Large tsunamis tend to be associated with earthquakes, liquefaction, and landslides that multiply the scale of impact. The main escalation points for tsunami related disasters were found to be failures of tsunami warnings, power plants, medical facilities, educational facilities, and infrastructure. From the perspectives of critical infrastructure resilience and disaster risk reduction, analysis of cascading impacts of multiple recent tsunami events could contribute to greater understanding of economic, political, and social impacts that stem from technical decisions regarding infrastructure management. Detailed examples of tsunami cases demonstrate the potential scale and extent of damage from cascading events, and by identifying the roles and examples of escalation points, disaster managers and decision-makers can better mitigate cascading impacts by targeting and preventing escalation points. However, more detailed investigation on tsunami characteristics and their impact on failures of each type of facility is still needed to develop tools to support decision-making for better emergency management to address short- and long-term social impacts.

Incentivizing Good Governance Beyond Regulatory Minimums: The Civil Nuclear Sector

The consequences from a blended cyber‐physical terrorist attack on a nuclear power plant are potentially catastrophic. Sabotage of the plant or theft and subsequent use of radiological materials can potentially lead to blackouts, deaths, and injuries and even a release of radiological materials. This threat continues to evolve in sophistication and complexity and is outpacing the ability and resources of governments to anticipate risks and to protect their critical infrastructure and the public from harm. Policymakers are working to keep up with the rapid onset of these threats to reinforce the resilience of critical infrastructure. Cyber vulnerabilities including insider threats are also evolving, with cyberattacks on nuclear facilities the tip of the iceberg as more sophisticated advanced persistent threats develop. This paper suggests governments look beyond regulations and policy directives to harness the power and energy of the market to incentivize operators to voluntarily adopt security measures beyond regulatory requirements.Good organizational governance is important and necessary to secure critical infrastructure including nuclear facilities and increasingly can be rewarded by the market. The definition of what is good organizational governance matters to investors, lenders, insurers, regulators, and the public. Is the organization going to be able to function effectively as an enterprise and provide a return to investors, pay back its loans, protect its workers and community, including the environment? In the nuclear field, the stakes can be high—with stakeholders depending on a stable baseload electric supply without safety or security incidents, especially of a radiological nature.This article documents findings from a multi‐year project to identify incentives for nuclear security beyond regulatory minimums, with a focus on nuclear power plants. We assessed the importance of standards and developed a “Good Governance Template” to support owners/managers in obtaining benefits and reducing potential liabilities. We found that market incentives are developing in areas such as insurance, credit, and other rating systems to support the development of good governance, including incentives for companies to demonstrate due care in the management of risks, especially cyber risks. Building a business case for nuclear security based on these incentives is an important step forward in securing our nuclear future, especially in terms of cyber risks.

Measuring Societal Vulnerability to Critical Infrastructure Failure due to Extreme Weather Events

Climate change and the associated more frequent and unpredictable occurrence of extreme weather events are according to the Global Risk Report (2020), published by the World Economic Forum, among the top five risks today. Although the effects of extreme weather vary around the world and in regions, their effects on social – economic and natural systems are becoming increasingly important and require an active solution. In this context, it is important to address the individual areas of human society vulnerability, as their assessment is the basic information necessary for improving risk reduction and preparedness to extreme weather events. The paper underlines the importance of critical infrastructure as an asset or system whose disruption or destruction could have a range of serious implications for the performance of economic and social functions of the state and thus on the inhabitants in terms of their life, health, security, property and environment protection. It provides selection of past cases of extreme weather events having impacts on critical infrastructure in sector energy and transportation throughout Europe and their impacts on society. Subsequently own approach to measuring societal vulnerability due to impact of extreme weather event on critical infrastructure is presented. In conclusion recommendations supporting the proactive approach to building resilient critical infrastructure which contributes to resilient society are presented.

Towards Resilient Critical Infrastructures – Motivating Users to Contribute to Smart Grid Resilience

AbstractSmart cities aim at improving efficiency while providing safety and security by merging conventional infrastructures with information and communication technology. One strategy for mitigating hazardous situations and improving the overall resilience of the system is to involve citizens. For instance, smart grids involveprosumers—capable of producing and consuming electricity—who can adjust their electricity profile dynamically (i. e., decrease or increase electricity consumption), or use their local production to supply electricity to the grid. This mitigates the impact of peak consumption periods on the grid and makes it easier for operators to control the grid. This involvement of prosumers is accompanied by numerous socio-technical challenges, including motivating citizens to contribute by adjusting their electricity consumption to the requirements of the energy grid. Towards this end, this work investigates motivational strategies and tools, including nudging, persuasive technologies, and incentives, that can be leveraged to increase the motivation of citizens. We discuss long-term and side effects and ethical and privacy considerations, before portraying bug bounty programs, gamification and apps as technologies and strategies to communicate the motivational strategies to citizens.

Towards Resilient Critical Infrastructures: Understanding the Impact of Coastal Flooding on the Fuel Transportation Network in the San Francisco Bay

Sea level rise (SLR) and storm surge inundation are major concerns along the coast of the San Francisco Bay (the Bay Area), impacting both coastal communities and critical infrastructure networks. The oil industry comprises a complex and critical infrastructure network located in the Bay Area. There is an urgent need to assess consequences and identify risk-based solutions to increase the resilience of this industrial network in the Bay Area to SLR and storm surge. In this study, a comprehensive multi-modal network model representing the fuel supply system was built. A total of 120 coastal flooding scenarios, including four General Circulation Models, two Representative Concentration Pathways, three percentiles of future SLR estimates, and five planning horizons (20 year intervals from 2000 to 2100) were considered. The impact of coastal flooding on fuel transportation networks was studied at two different scales: regional and local. At the regional scale, basic network properties and network efficiency were analyzed across multiple flooding scenarios. At the local scale, cascading effects of individual node disruptions were simulated. Based on this research, smarter and more holistic risk-based adaptation strategies can be established which could lead to a more resilient fuel transportation network system.

MODELING AND SIMULATION IN CRITICAL INFRASTRUCTURES PROTECTION

Abstract: Critical infrastructure protection is a complex field that involves using specific research methods, capturing the dynamic and complex reality in which infrastructure systems evolve. Modeling and simulation provides particular tools and approaches adapted to the field of critical infrastructure protection. A good knowledge of the methodology and using the appropriate tools can lead to improvements in the security of critical infrastructures. Creating models for infrastructures or systems facilitates research, followed by the simulation of potential events with a negative impact. The studies carried out at the intersection of the two fields open new research opportunities to improve the modeling and simulation tools and increase the resilience of critical infrastructures. The specific modeling and simulation methods find their applicability at the operator's or owners' activity for the elaboration of the security plans and their validation.

FedResilience: A Federated Learning Application to Improve Resilience of Resource-Constrained Critical Infrastructures

Critical infrastructures (e.g., energy and transportation systems) are essential lifelines for most modern sectors and have utmost significance in our daily lives. However, these important domains can fail to operate due to system failures or natural disasters. Though the major disturbances in such critical infrastructures are rare, the severity of such events calls for the development of effective resilience assessment strategies to mitigate relative losses. Traditional critical infrastructure resilience approaches consider that the available critical infrastructure agents are resource-sufficient and agree to exchange local data with the server and other agents. Such assumptions create two issues: (1) uncertainty in reaching convergence while applying learning strategies on resource-constrained critical infrastructure agents, and (2) a huge risk of privacy leakage. By understanding the pressing need to construct an effective resilience model for resource-constrained critical infrastructure, this paper aims at leveraging a distributed machine learning technique called Federated Learning (FL) to tackle an agent’s resource limitations effectively and at the same time keep the agent’s information private. Particularly, this paper is focused on predicting the probable outage and resource status of critical infrastructure agents without sharing any local data and carrying out the learning process even when most of the agents are incapable of accomplishing a given computational task. To that end, an FL algorithm is designed specifically for a resource-constrained critical infrastructure environment that could facilitate the training of each agent in a distributed fashion, restrict them from sharing their raw data with any other external entities (e.g., server, neighbor agents), choose proficient clients by analyzing their resources, and allow a partial amount of computation tasks to be performed by the resource-constrained agents. We considered a different number of agents with various stragglers and checked the performance of FedAvg and our proposed FedResilience algorithm with prediction tasks for a probable outage, as well as checking the agents’ resource-sharing scope. Our simulation results show that if the majority of the FL agents are stragglers and we drop them from the training process, then the agents learn very slowly and the overall model performance is negatively affected. We also demonstrate that the selection of proficient agents and allowing them to complete only parts of their tasks can significantly improve the knowledge of each agent by eliminating the straggler effects, and the global model convergence is accelerated.

CRITICAL INFRASTRUCTURES AND THEIR IMPORTANCE IN MODERN SOCIETIES – PROTECTION, SAFETY, SECURITY

Abstract: Nowadays, the modern security environment has it foundation based on some vital pilons, that are also important for the normal functionality of the modern society. This paper will offer a new perspective on critical infrastructure protection, defining the relationships that take place freely in a modern society. The international security could be analyzed from functional (systemic) and structural points of view. From the systemic point of view, the global security is characterized by five major systems: political, economic, social (socio-demographic), cultural and ecological. From the structural point of view, besides the above systems there are other ones: military, intelligence, communications and infrastructure (the critical infrastructure, health, financial, culture, education and research). There are certain infrastructures such as: telecommunications, transports, systems of power or water supply, IT systems, diverse systems and emergency services, that are actually fundamental to a prosperous economy and therefore critical to the development of human society. Telecommunications, power systems and transport infrastructures are essential infrastructures that ensure not only the mobility, but also the adequate performance of the armed forces, which is one more reason for which these infrastructures are critical. The degree of development and resilience of national and European critical infrastructures is essential for the economic growth and for ensuring the security and welfare of society on the whole. Therefore, the modern national security, seen as a system or a structure, has been passing through a reform and modernization process in order to adapt to the challenges of the 21st Century and the requirements triggered by North Atlantic Treaty Organization and European Union memberships, and not only. In this context there is a need for some security politics and strategy which could increase the national security condition.

Causes and Consequences of Local Government Efforts to Reduce Risk and Adapt to Extreme Weather Events: Municipal Organizational Robustness

This research article investigates the causes and consequences of municipal institutional arrangements for the provision of resilient critical infrastructure in municipalities. The study explains how the municipal organizational robustness and external institutional dynamics moderate the relation between capacities, leadership, and local government investment decisions. We examine hypotheses on moderating effects with regression methods, using data from 345 Chilean municipalities over a nine-year period, and analyzing the evidence with support of qualitative data. Our results reveal that municipal organizational robustness—operational rules, planning, managerial flexibility and integration, and accountability—is the most quantitatively outstanding moderating factor. The evidence leads us to deduce that efforts to support local governments in the emerging policy domain of resilient critical infrastructure require special attention to the robustness of municipal institutional arrangements. The results are valid for countries where the local governments have responsibilities to fulfill and their decisions have consequences for the adaptation. Since one of the objectives of the Special Issue “Bringing Governance Back Home—Lessons for Local Government Regarding Rapid Climate Action” is to explore how action is enabled or constrained by institutional relations in which the actors are embedded, this study contributes to achieving the goal.

Power system resilience assessment considering critical infrastructure resilience approaches and government policymaker criteria

The electric power system is one of the most important critical infrastructures of a country. Recently, the number of natural and man-made disasters is increased, which can impose extensive damages and costs to the power system. A resilient power system can withstand against, adapt to and recover from these disasters. Power system resilience is quantified by mathematical tools which are called “resilience metrics”. Currently, a lot of resilience metrics are proposed in the power system literature. In this paper, based on the extensive research in the critical infrastructure resilience literature which specifically concentrates on the “area-based” resilience metrics, a new area-based resilience metric is proposed which can measure the power system resilience considering the government policymaker criteria, which are rarely noticed before. The proposed and conventional area-based resilience metrics are evaluated based on the real data from the 2012 Superstorm Sandy in the USA, which led to significant damage to the power distribution system. The simulation results show that the proposed area-based resilience metric is very simple, can successfully address actual power system performance curves and is more meaningful and tangible than the conventional area-based metrics for the government policymaker. The proposed area-based resilience metric has also a general form and can be used for other critical infrastructures.

Resilience estimation of critical infrastructure systems: Application of expert judgment

Resilience is an emerging concept whose application has increased significantly in managing engineering systems. In order to have an effective resilience management, first, an estimation of the system resilience should be undertaken. However, a lack of historical data and limited information are major challenges for system resilience estimation. The main reason is that most data collection systems are not designed for resilience assessment. Moreover, the available study dealing with resilience assessment have been used different indices to quantify the resilience of critical infrastructures including, robustness, recoverability, etc. These indices can be affected in a complex way by different factors such as operational conditions, protective practices, the recovery process, logistic process, etc. However, the available resilience studies are not so detailed regarding identifying and quantifying these influencing factors. Therefore, this paper aims to develop and apply a practical methodology to estimate resilience based on the combination of expert judgment and fuzzy set theory. By adopting this methodology, factors influencing resilience can be modeled effectively. Finally, the application of the proposed methodology is illustrated for the main fan system of an underground coal mine.

Artificial Intelligence (AI) and Augmented Reality (AR): Disambiguated in the Telemedicine / Telehealth Sphere

Abstract The world is navigating through unfamiliar and incomprehensible times – COVID-19, international economic crisis, and crumbling healthcare systems. The United States (US) healthcare industry is grappling with an increased workload and advancing digitization technological concerns. The failure of organizations to offer suitable cybersecurity controls within the critical infrastructure leads to advanced persistent threat (APT) that could have incapacitating effects on organizations. A keen understanding of cybersecurity is vital for leaders and the need is referenced in US policy that advances a national unity of effort to strengthen and maintain secure, functioning, and resilient critical infrastructure. Akin to the Presidential Policy Directive (PPD) 21 Critical Infrastructure Security and Resilience, leaders’ goals should be to reduce vulnerabilities, identify and disrupt threats, minimize consequences and hasten response and recovery efforts related to critical infrastructure. To address the concern, it is necessary to review how AI and AR serve as co-technologies to support security of patient care and monitoring, examine impacts on individuals’ and overall healthcare organizations, address how enhanced comprehension of AI and AR could guide medical professional leaders’ decisions and boost the overall patient experience. Therefore, this literature review examines AI and AR connections to cybersecurity for the healthcare environment.

The Integration of Protection, Restoration, and Adaptive Flow Redistribution in Building Resilient Networked Critical Infrastructures Against Intentional Attacks

It is paramount to ensure the resilience of networked critical infrastructures, which are vital for the economic development and our daily requirements but threatened by intentional attacks. For this purpose, their protection before and restoration after intentional attacks are of great significance. Moreover, in order to keep the prescribed demand continuously satisfied, postdisruption flow redistribution is also necessary. However, due to the severity of intentional attacks, certain components may need to be overloaded as a result of the redistribution and, thus, the network reliability is influenced. To minimize such influence, we first present a new metric of resilience to reflect the incurred reliability changes. Then, a trilevel optimization model integrating protection, restoration, and adaptive flow redistribution to maximize the network resilience is proposed. To deal with the complexity of the proposed problem, an evolutionary algorithm is employed with necessary adaption.

Multi-Level Planning for Enhancing Critical Infrastructure Resilience against Power Shortages—An Analysis of the Swedish System of Styrel

The protection of infrastructure that is critical to society’s functionality, survival and progression has gained significance because of its large-scale and interdependent nature. This complex system-of-system (SoS) imposes extensive requirements on governance efforts to foster critical infrastructure protection (CIP). This paper uses the kaleidoscope for integrative system analysis (KISA) to investigate a Swedish approach for CIP against power shortages, called Styrel. Based on multiple sources of evidence, such as documents with regard to the case, interviews and a survey with involved experts, the analysis focuses on the system of emergency planning and the usage of the resulting plan. The results deliver insights into the governance of the multi-level planning, including issues regarding policies, the management and operation of Styrel, and accelerating problems in the adaption, emergence and entropy of the SoS, during and between process iterations. Since this large-scale approach largely fails to involve the private sector to enhance the resilience of the society, this proceeding results in uncalculated consequences. In addition, the current design of the approach hampers transparency and evaluation, which poses obstacles to the cultivation of mutual trust, collective learning and a shared understanding as well as proper risk communication with the wider public.

Determining a Return on Investment for Cybersecurity Technologies in Networked Critical Infrastructures

Much of modern life is dependent on networked critical infrastructure systems—many known to be susceptible to cyberattacks—such as the electrical grid, water purification, and transportation systems. The consequences of a successful cyberattack on these systems could be catastrophic. Appropriate levels and strategies for cybersecurity investment for networked critical infrastructures present a serious challenge that administering organizations, whether public or private, must overcome in order to provide resilient services. This challenge includes understanding the actual vulnerabilities of an organization's networked systems, as well as the cost of a successful cyberattack on those systems. On top of this, an organization's cybersecurity acquisition workforce must be able to discern reality from the marketing hype that is produced by cybersecurity sales forces. Many product offerings from industry promise to secure critical infrastructures, but there is no good method for determining which product (or combination of products) is most effective for a specific environment or scenario. This paper presents a return on cybersecurity investment (ROCI) model utilized, together with a previously-developed framework for evaluating cybersecurity technologies, by the resilient critical infrastructures through secure and efficient microgrids (ReCIst) capability. ReCIst uses this model to guide decision makers on how to best implement cybersecurity towards energy resiliency, from financial, security posture, and energy efficiency perspectives. Challenges and the current state of cyber investment modeling in this domain are presented along with technical details on ReCIst's ROCI model and future work.

Resilient Critical Infrastructure Planning Under Disruptions Considering Recovery Scheduling

Reliable and safe critical infrastructures are crucial for the sustainability of modern societies. To cope with increasing disruptive events such as man-made and natural disasters attacking infrastructures, resilience should be considered as an integrated perspective into the system planning process. This paper presents a p-robust optimization model for infrastructure network planning against spatially localized disruptions. The optimization aims at minimizing the investment costs for system hardening and expansion and the total system costs under nominal operating conditions, while incorporating resilience requirements by the p-robustness constraints. Importantly, instead of only mitigating system vulnerability, the proposed model integrates the arranging of the repair sequence of damaged components under limited repair resources into the preevent system planning. The complexity of the proposed model is analyzed, and a hybrid algorithm that combines scenario-based decomposition and variable neighborhood search is developed for its efficient solution. The effectiveness of the approach is illustrated through an application to a real power transmission system. Quantitative analysis can assist managers in decision making regarding investing in different system protection actions and making a tradeoff between desired resilience and budget constraints.

Quantifying Road-Network Robustness toward Flood-Resilient Transportation Systems

Amidst sudden and unprecedented increases in the severity and frequency of climate-change-induced natural disasters, building critical infrastructure resilience has become a prominent policy issue globally for reducing disaster risks. Sustainable measures and procedures to strengthen preparedness, response, and recovery of infrastructures are urgently needed, but the standard for measuring such resilient elements has yet to be consensually developed. This study was undertaken with an aim to quantitatively measure transportation infrastructure robustness, a proactive dimension of resilience capacities and capabilities to withstand disasters; in this case, floods. A four-stage analytical framework was empirically implemented: (1) specifying the system and disturbance (i.e., road network and flood risks in Chiang Mai, Thailand), (2) illustrating the system response using the damaged area as a function of floodwater levels and protection measures, (3) determining recovery thresholds based on land use and system functionality, and (4) quantifying robustness through the application of edge- and node-betweenness centrality models. Various quantifiable indicators of transportation robustness can be revealed; not only flood-damaged areas commonly considered in flood-risk management and spatial planning, but also the numbers of affected traffic links, nodes, and cars are highly valuable for transportation planning in achieving sustainable flood-resilient transportation systems.