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In effort to understand and reduce flood consequences more effectively and strategically, flood risk assessment has been a cornerstone of a long-term flood management. One component of flood risk assessment is the estimation of a range of possible damage to an area exposed to flooding, that is, the vulnerability curve. The vulnerability curve can be depicted by a stage–damage relationship. This study attempts to investigate how vulnerability to flooding can be quantitatively assessed using a micro-scale approach in Malaysia’s vulnerable areas. A residential area in Kota Bharu was chosen as the case study area. Depth–damage relationships from a multiple regression function of Department of Irrigation and Drainage Malaysia and spatial variability of residential buildings were used for the micro-scale assessment. Final estimates of expected annual damage were then calculated for each building type at 1-, 3- and 5-day flood durations. Results show that the methodology adopted is feasible to be applied for local-scale assessment flood risk assessment in Malaysia. The results also suggest that applying the methodology is possible when given wider availability of resources and information. This is particularly important for a robust end-to-end flood risk assessment for long-term effective flood management in Malaysia.

The government-led public healthcare services in Sri Lanka became a major strength in managing the COVID-19 comparatively well. However, natural hazards are a major threat to this healthcare system, as they cause severe damages, especially to curative healthcare infrastructures such as hospitals. Floods have been the major contributor to the economic loss of the Sri Lankan healthcare system. Therefore, the purpose of this study is to develop a proper flood risk assessment framework for Sri Lankan hospitals.

This research study has attempted to develop a flood vulnerability assessment tool for hospitals using the concept of Depth Damage Functions (DDFs). Flood vulnerability curves have been developed for identified critical units of hospitals considering the damage caused to building contents which are predominantly expensive medical equipment. The damage caused only by wetting was considered in generating vulnerability curves. Structured interviews were conducted with government officials in the healthcare sector to gather details on the cost and damages of medical equipment. Pilot studies were carried out in two hospitals identified as located in flood-prone areas and have previous experiences of flooding, to acquire data regarding building contents of the critical units.

The developed vulnerability curves indicate that no major damage would occur to building contents in critical units (other than the labor room) until the inundation depth reaches a value of 0.6–0.9 m (varies for each type of unit). It is also noteworthy that after a certain range in the inundation depth, the damage increases drastically, and building contents would incur total damage if the inundation depth passes a value of 1.2–1.5 m.

This study explains the initial phase of developing a flood vulnerability assessment framework for Sri Lankan hospitals. Not many studies had been carried out to assess the vulnerability of hospitals specifically for floods using vulnerability curves. The study recommends a zoning system with pre-defined vulnerability levels for critical units during a flood, which can be associated with evacuation planning as well. Further studies must be carried out to verify this system for hospitals in Sri Lanka.

Damage functions constitute an essential part of the modelling of critical infrastructure (CI) performance under the influence of climate events. This paper aims to compile and discuss publications comprising damage functions for transport assets.

The research included the collection of contemplable literature and the subsequent screening for damage functions and information on them. In conclusion, the derived damage curves and formulae were transferred to a unified design.

Damage functions for the transport sector are scarce in the literature. Although specific damage functions for particular transport assets exist, they mainly consider infrastructure or transport in general. Occasionally, damage curves for the same asset in different publications vary. Major research gaps persist in wildfire damage estimation.

The study scope was restricted to the hazards of fluvial floods and wildfires. Despite all efforts, this study did not cover all existing literature on the topic.

This publication summarises the state of the art of research concerning transport asset damage functions, and hence contributes to the facilitation of prospective research on CI performance, resilience and vulnerability modelling.

The purpose of this paper is twofold: first, to investigate the flood impact on a detached dwelling based on physical attributes related to the positioning, form and orientation of the house, and second, to investigate the effectiveness of property-level protection (PLP) to mitigate the direct structural damage of the house and the degree of floodwater ingress within the house.

The methods included modelling and simulation within the ANSYS Fluent® computational fluid dynamics software. Flooding scenarios with constrained parameters using theoretical modelling methods/tools were used to test the research hypotheses. Therefore, the results obtained will match the what-if scenarios considered if/based on the standard equations and assumptions made in the idealised model.

It was found that the position, orientation and form of an individual dwelling with brick and block construction informs the impact of the applied pressure on the structure and water ingress. Increase in pressure on the structure was noted from 0.3 m. All examined PLP mitigated the risk of structural damage if applied in consideration with other interventions e.g. mortar sealing. The use of non-return valves could potentially increase the pressure on the structure, but was also found to be effective in reducing water ingress. Findings should be considered in conjunction with the assumptions and exceptions of this study.

The limitations of this study are that the findings are based on an idealised model of a single detached house, with no landscape obstruction to the watercourse. This mathematical approach concerned with developing the normative models may therefore not fully describe the real-world complex phenomena. But it provides the first vision and an objective basis to answer the questions under study, and to propose usable outputs. Flooding caused from internal sources (e.g. bursting of pipes, roof leaks) or seepage from the ground and moisture through the walls were excluded. Building content was not modelled.

Common property-level flood interventions are typically tested to mitigate water ingress to the house. This study extends this approach to include the prevention of structural damage to the external walls; this can help to avoid the indiscriminate use of property-level flood prevention solutions without full understanding of their degree of effectiveness or impact on the building’s structural integrity. This study is practically significant because it provides outputs and means to examine which intervention(s) are better for delivering flood protection to a standard brick/block detached house type. This knowledge is highly beneficial for relevant stakeholders who can use it to deliver effective property-level flooding resilience measures.

The study provides useful insights for property owners and building professionals to explore suitable, cost-effective single property-level protection against flooding. Furthermore, the effective implementation of interventions can be used to achieve a customised, “fit for purpose” resilience retrofit.

The purpose of this paper is to investigate the functionality and main results of the ImmoRisk tool. The aim of the project of the Federal Ministry for Transport, Building and Urban Development (BMVBS), in corporation with the Federal Institute for Research on Building, Urban Affairs and Spatial Development (BBSR), was to develop a user-friendly tool that provides a sound basis with respect to the risk situation caused by extreme weather events.

The tool calculates the annual expected losses (AEL) for different types of extreme weather hazard and the damage rate as the proportion of AEL on building value, based on a trinomial approach: natural hazard, vulnerability and the value of the property.

The paper provides property-specific risk profiles of both the present and future risk situation caused by various extreme weather events.

The approach described in the paper can serve as a model for the realization of subsequent tools in further countries bound with other climatic risks.

The real estate industry is affected by a significant rise in monetary damages caused by extreme weather events. Accordingly, the approach is suitable for implementation in the companies’ real estate risk management systems.

The tool offers homeowners a profound basis for investment decisions with regard to adaptation measures.

The approach pioneers fourfold: first, by meeting the needs of the housing and real estate industry based on a trinomial approach; second, by using a property-specific bottom-up approach; third, by offering both a comprehensive risk assessment of the hazards storms, flood and hailstorm and finally, by providing results with respect to the future climatic risk situation.

This study aims to combine information about sea level rise (SLR), the probability distribution of storm surge, a flood damage function and the value of property by elevation along the coast of selected cities to measure expected flood damage. The selected six cities all have nearby long-term tidal stations that can be used to estimate the probability distribution of floods. The model is calibrated to each city. The study then compares the cost of building higher seawalls today along the coast versus the benefit of each wall (the reduction in expected flood damage).

The combination of coastal storms and SLR has led to extensive flood damage across American cities. This study creates a simple generic model that evaluates whether seawalls would be effective at addressing this flooding problem. The paper develops an approach that readily measures the expected flood benefits and costs of alternative coastal seawalls. The approach takes account of near term SLR and the probability distribution of storm surge. The model finds seawalls are effective only in cities where many buildings are in the 25-year flood plain.

Cities with many buildings built on land below 2 m in elevation (the 25-year flood plain) have high expected flood damage from storms and SLR. Cities which already have many buildings in this flood plain would benefit from seawalls. Assuming seawalls are built above the high tide line, the optimal wall height that maximizes net benefits is between 0.9 to 1.2 m. These relatively low seawalls block 70%–83% of expected flood damage in these cities. Fair flood insurance is the least cost strategy for handling the remaining damages that overtop the optimal seawalls.

The analysis evaluates whether or not to build a seawall the length of each city at high tide lines. However, the analysis also finds several long stretches of coast in two cities where a wall is not warranted because there are few vulnerable buildings. Future analyses should consider seawalls in more spatially detailed sections of each city. Each section could then be analyzed independently. Whether or not more complex hydrodynamic models are needed to evaluate coastal resilience planning should also be explored. Alternative solutions such as planned retreat and nature-based solutions should be compared with seawalls in future studies as well.

Cities should be careful to avoid development in the 25-year flood plain because of high expected flood damage. Cities that have low elevation areas subject to frequent flooding should consider seawalls to reduce frequent flooding. Because they are very costly and have low expected benefits, high walls that can stop a one-hundred-year storm are generally not worth building.

The analysis reveals that the most important factor determining the vulnerability of cities along the eastern coastline of the USA is the number of buildings built below 2 m in elevation (the 25-year flood plain). Cities should use zoning to discourage further development in the 25-year flood plain. Cities which already have many buildings in this flood plain would benefit from city-wide seawalls. Assuming these walls are built at mean high-high tide, the optimal height of current seawalls should be relatively modest – averaging about 0.9–1.2 m above ground. Using fair insurance for the remaining risk is less expensive than building taller walls. In particular, the cost of seawalls that protect against a major hurricane surge are over three times the expected benefit and should not be built. As decades pass and observed sea level progresses, seawalls and the boundary of the 25-year flood plain should be reevaluated.

This paper develops a coastal flood model that combines SLR and the probability distribution of storm surges with the value of property by elevation to estimate the expected damage from storm surge. The model is relatively easy to calibrate making it a practical tool to guide city flood planning. The authors illustrate what insights such a model gives about coastal resilience to flooding across six cities along the Eastern US coastline.

The purpose of this work is the development of a structured case study design process for developing case studies in humanitarian logistics, in particular for short-term predictable disaster situations like floods and hurricanes. Moreover, useful public sources are presented in order to enable researchers to find relevant data for their case studies more easily.

A structured framework for case study design is set up, splitting the process into different steps and phases.

The framework is applied to an illustrative example, where case studies with different numbers and levels of detail of scenarios are designed based on the three-day forecast for hurricane Harvey in 2017. The corresponding solutions demonstrate the relevance of using as much forecast information as possible in case study building, and in particular in scenario design, in order to get useful and appropriate results.

The case study design process is mostly suitable for short-term predictable disasters, but can also be adapted to other types of disasters. The process has been applied to one specific hurricane here which serves as an example.

Also for practitioners, the results of this work are highly relevant, as constructing realistic cases using real data will lead to more useful results. Moreover, it is taken into account in the case study design process that relief agencies are regularly confronted with disasters in certain areas and hence need to define the basic planning situation and parameters “once and for all” and on a long-term basis, whereas disaster specific data from forecasts are only available within a short time frame.

The new design process can be applied by researchers as well as practitioners, and the publicly available data sources will be useful to the community.

The overall objective of this study is envisaged to provide decision makers with actionable insights and access to multi-risk maps for the most in-danger stave churches (SCs) among the existing 28 churches at high spatial resolution to better understand, reduce and mitigate single- and multi-risk. In addition, the present contribution aims to provide decision makers with some information to face the exacerbation of the risk caused by the expected climate change.

Material and data collection started with the consultation of the available literature related to: (1) SCs' conservation status, (2) available methodologies suitable in multi-hazard approach and (3) vulnerability leading indicators to consider when dealing with the impact of natural hazards specifically on immovable cultural heritage.

The paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. The results highlight the danger at which the SCs of Røldal, in case of floods, and of Ringebu, Torpo and Øye, in case of landslide, may face and stress the urgency of increasing awareness and preparedness on these potential hazards.

The contribution for the first time aims to homogeneously collect and report all together existing spread information on architectural features, conservation status and geographical attributes for the whole group of SCs by accompanying this information with as much as possible complete 2D sections collection from existing drawings and novel 3D drawn sketches created for this contribution. Then the paper contributes to a better understanding of place-based vulnerability with local mapping dimension also considering future threats posed by climate change. Then it highlights the danger of floods and landslides at which the 28 SCs are subjected. Finally it reports how these risks will change under the ongoing impact of climate change.

The purpose of this paper is to provide an effective and simple technique to structural damage identification, particularly to identify a crack in a structure. Artificial neural networks approach is an alternative to identify the extent and location of the damage over the classical methods. Radial basis function (RBF) networks are good at function mapping and generalization ability among the various neural network approaches. RBF neural networks are chosen for the present study of crack identification.

Analyzing the vibration response of a structure is an effective way to monitor its health and even to detect the damage. A novel two‐stage improved radial basis function (IRBF) neural network methodology with conventional RBF in the first stage and a reduced search space moving technique in the second stage is proposed to identify the crack in a cantilever beam structure in the frequency domain. Latin hypercube sampling (LHS) technique is used in both stages to sample the frequency modal patterns to train the proposed network. Study is also conducted with and without addition of 5% white noise to the input patterns to simulate the experimental errors.

The results show a significant improvement in identifying the location and magnitude of a crack by the proposed IRBF method, in comparison with conventional RBF method and other classical methods. In case of crack location in a beam, the average identification error over 12 test cases was 0.69 per cent by IRBF network compared to 4.88 per cent by conventional RBF. Similar improvements are reported when compared to hybrid CPN BPN networks. It also requires much less computational effort as compared to other hybrid neural network approaches and classical methods.

The proposed novel IRBF crack identification technique is unique in originality and not reported elsewhere. It can identify the crack location and crack depth with very good accuracy, less computational effort and ease of implementation.