Factors such as human activity and climate change are contributing to an increase in the frequency and intensity of wildfires. This problem has challenged society's knowledge, response capacity, and resilience, revealing its inadequacy to cope with the new wildfire regime characterized by extreme wildfire events (EWE). Policies on wildfire management mainly focus on suppression and managing emergencies, which may be insufficient to reduce EWE's incidence and cope with its impact. Consequently, there is a lack of tools to support decision-making in wildfire management in other important aspects, such as prevention and protection. This study examines global wildfire policies specifically in the Iberian Peninsula (Portugal and Spain), including cross-border policies. A GIS-based tool to evaluate different normal and extreme wildfire management policies is applied to a cross-border case study, paying attention to the impact on critical land-based transport systems. A relevant outcome of the tool application is that suppression must be complemented with other wildfire management strategies in the analyzed area. The gained insights can help stakeholders to improve decision-making in wildfire management to successfully address EWE.

@en

Climate change is causing an increase in the frequency and intensity of wildfires, demonstrating that our capacity to respond to them is insufficient. Therefore, it is necessary to reconsider wildfire management policies, practices, and decision-support tools, extending beyond emergency measures. This study presents the extension of a GIS-based methodology for fire analysis, providing decision-making support for the implementation of new fire-related policies for road transportation infrastructure. It represents a novel contribution that facilitates the transition towards proactive wildfire policies. The framework is demonstrated to support informed decision-making, addressing both reactive actions, i.e., emergency response, and the evaluation of proactive adaptation measures at a system level. The results suggest that landscape management policies can play an important role in improving the resilience of road networks to wildfires.@en

The severe effects of extreme wildfire events in recent years have shown that the fire suppression approach is not enough to solve the problem. An alternative to dealing with this issue is to accept the impossibility of eliminating wildfire hazards and focus on preparing systems to be more resilient. However, existing decision-making tools based on resilience present important drawbacks that make them inadequate for this task. This paper proposes a new approach and methodology for the resilience assessment of road traffic networks to wildfires that overcomes the main drawbacks, paying attention to the different functions of the system and the acceptance of a specific loss of performance. The latter is done through the introduction of dynamic thresholds that reflect the different requirements of the system under different wildfire conditions, including normal and extreme fires. The methodology is exemplified for five traffic networks. The results support the relevance of appropriate wildfire management through the adaptation of the natural and built environment to increase the capacity of the traffic networks to cope with wildfires.@en

Wildfires are becoming more intense and frequent. This problem has tested the knowledge, response capacity, and resilience achieved by society throughout history, making it clear that they are insufficient to face this new wildfire regime. The effectiveness of the related policies mainly focused on fire suppression rather than prevention is increasingly insufficient and questionable. Consequently, there is a clear lack of tools to assess the impact of wildfire preventive actions. Therefore, it is imperative to review wildfire management practices, policies, and the tools used to support decision-making in this regard. This study performs an analysis of wildfire policies applied in the Iberian Peninsula case (Portugal and Spain), including cross-border policies and the role of road transport networks. A novel simplified methodology is included to evaluate different normal and extreme forest fire management policies in road transport infrastructures. The methodology includes different parameters related to wildfires, such as sources of exposure, identification of natural and artificial barriers, and traffic conditions that capture the economic characteristics of the studied area. The information provided by the tool is useful for strategic investment planning, resource prioritization, and evacuation time management. In addition, due to its simplicity of application, it is a useful tool for cross-border areas.@en

Wildfires have become a source of concern for society due to the increase in frequency, intensity, and unpredictability. This has caused serious impacts all over the world, even in areas where this type of problem did not occur before. Studies on the adaptation of critical infrastructure have been conducted to reduce the impacts of this type of hazard influenced by climate change. However, there are currently no tools to evaluate adaptation measures and their influence on the resilience of transport infrastructure to wildfires. Therefore, this paper proposes the application of a simplified methodology to assess the priority level in interventions on bridge networks and the effectiveness of different adaptation measures. The methodology is applied to a case study in Portugal. In that sense, the results show that adaptation measures such as changing vegetation management policy and implementing wildfire spread barriers effectively reduce the exposure of bridges. Therefore, this tool can be very useful for stakeholders and practitioners supporting wildfire management in terms of adaptation measures.

@en

Climate change is leading to a rise in the occurrence and intensity of wildfires, exacerbated by the growing encroachment of communities into the natural environment, posing challenges to our global capacity to respond to wildfires. During wildfire events, road transport infrastructure becomes crucial for the evacuation of people and accessibility to an emergency by first responders. Nevertheless, resilience management of transportation infrastructure affected by wildfires is poorly considered, despite its relevant role and high exposure to wildfires. Therefore, this study proposes a new methodology to estimate the priority level for wildfire preparation by combining exposure and criticality of road transportation infrastructure to wildfire hazards with consideration of different wildfire categories. The analysis is conducted at the system level considering interdependencies and redundancies among infrastructure components and using a geographic information system (GIS) to automate the modelling process and visualization of results. The proposed methodology is applied to a case study in the Leiria region of Portugal, demonstrating its utility in prioritizing economic resources and decision-making for areas requiring preparation. This approach can serve as a resilience-based tool for decision-making, supporting the implementation of effective adaptation strategies to enhance wildfire resilience.@en

The severe effects of extreme wildfire events in recent years have shown that the fire suppression approach is not enough to solve the problem. An alternative to dealing with this issue is to accept the impossibility of eliminating wildfire hazards and focus on preparing systems to be more resilient. However, existing decision-making tools based on resilience present important drawbacks that make them inadequate for this task. This paper proposes a new approach and methodology for the resilience assessment of road traffic networks to wildfires that overcomes the main drawbacks, paying attention to the different functions of the system and the acceptance of a specific loss of performance. The latter is done through the introduction of dynamic thresholds that reflect the different requirements of the system under different wildfire conditions, including normal and extreme fires. The methodology is exemplified for five traffic networks. The results support the relevance of appropriate wildfire management through the adaptation of the natural and built environment to increase the capacity of the traffic networks to cope with wildfires.

@en

Structural reliability has become a widely accepted performance indicator for infrastructures over the past decade, providing valuable information about their structural condition. As a result, it has been assessed in combinationwith deterioration prediction, aiming at defining optimal maintenance, and rehabilitation strategies for bridge networks. In that case, reliability values need to be updated based on collected data. To this purpose, there has been a rapid development of advanced bridge condition assessment techniques, both in the fields of structural health monitoring as well as on non-destructive assessment techniques. Most of the sophisticated non-destructive methods are the preferred option but sometimes are not possible. Thus, visual inspection is still the predominant bridge condition assessment technique being adopted within the majority of Bridge Management Systems (BMS). However, there is a procedural gap when incorporating information obtained from visual inspections into a reliability assessment. Therefore, this paper describes a methodology for a time-dependent reliability-based condition evaluation of existing bridges. The procedure is applied to a pre-stressed reinforced concrete railway bridge located in Portugal, in which prediction of reliability levels are calculated for different periods assuming corrosion initiation, causing a reduction in the cross-section area of the steel reinforcement and residual strength reduction, based on onsite inspection evidence. Finally, the updating is made through a Bayesian approach to compute the posterior bridge reliability based on inspection results. This approach may apply to other types of structures considering information obtained from visual inspection concerning the actual deterioration state in a quantitative way.@en

Assessing flood risks on road infrastructures is critical for the definition of mitigation strategies and adaptation processes. Some efforts have been made to conduct a regional flood risk assessment to support the decision-making process of exposed areas. However, these approaches focus on the physical damage of civil infrastructures without considering indirect impacts resulting from social aspects or traffic delays due to the functionality loss of transportation infrastructures. Moreover, existing methodologies do not include a proper assessment of the uncertainties involved in the risk quantification. This work aims to provide a consistent quantitative flood risk estimation and influence factor modelling for road infrastructures. To this end, a Flood Risk Factor (FRF) is computed as a function of hazard, vulnerability, and infrastructure importance factors. A Bayesian Network (BN) is constructed for considering the interdependencies among the selected input factors, as well as accounting for the uncertainties involved in the modelling process. The proposed approach allows weighting the relevant factors differently to compute the FRF and improves the understanding of the causal relations between them. The suggested method is applied to a case study located in the region of Santarem Portugal, allowing the identification of the sub-basins where the road network has the highest risks and illustrating the potential of Bayesian inference techniques for updating the model when new information becomes available.

@en

Road infrastructures are crucial for societies daily life due to the dependency of other critical infrastructures upon it. Therefore, society expects an uninterrupted availability of the road network. However, maintain this constant availability is often a difficult task as, in the last decades, climate change has significantly affected transport networks, especially due to the occurrence of extreme natural events leading to their disruption. Those events include floods, wild fires, landslides and others, and all of are varying both in frequency and intensity presently and in the coming years. Therefore, there is a clear need for timely adaptation. Regarding these adaptability measures, an important step is needed to quantify how the transport network is directly and indirectly affected by extreme weather events, which can be obtained within a risk assessment. Nonetheless, there are many questions and variability about this topic such as uncertainties in projections of future climate, cause-effects assessment, and how it can be an integration of all these aspects into a single decision-making process. In that scope, this work describes a risk assessment methodology having account the cause, effect, and consequences of extreme events in road networks to identify the major risks and therefore the assets that may be suitable to be analyzed within a selection of adaptation measures aiming at a holistic decision-making support tool.@en