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Disasters are occurring worldwide, and Sri Lanka has also become a victim of multiple disasters. Though there is a disaster management mechanism from the national level to the local level in Sri Lanka, several gaps are identified in pre- and postdisaster management activities. Among them, the responsibilities of local-level stakeholders in flood management activities are not performing at a satisfactory level. Therefore, the flood damage from the previous events was too great. Accordingly, the purpose of this study is to assess the roles, responsibilities and performance of stakeholders involved in local-level flood risk management activities.

The Deduru Oya basin in Sri Lanka was selected as the study area. The study hypothesized that “ineffective roles, responsibilities and performance of local level stakeholders have weakened the flood risk management in the Deduru Oya basin.” The stratified random sampling method selected the sample (n = 425) from the flood-vulnerable population. Primary data were collected through a questionnaire survey, key informant interviews and field observations. Secondary data were collected from reports, work plans, journal papers and published maps. Descriptive data analysis methods and thematic data analysis methods were used in the study.

About 69% of the respondents state that they are not satisfied with the involvement of government agencies in local-level flood risk management activities, while 10% of the respondents state that they are satisfied. The thematic analysis reveals several gaps, such as the lack of reservations in the Deduru Oya, improper land use practices, no inundation areas are identified and mapped out and the effects of illegal sand mining in the Deduru Oya. In addition to that, the lack of legal power vested in local governments in disaster management and the weaknesses of current legislation on flood risk management are the other major courses of local-level ineffectiveness.

The current research was limited to studying the involvement of local-level stakeholders in flood risk management, but the involvement of subnational and national-level stakeholders should be studied in future research.

This paper examines the involvement of local-level stakeholders in flood risk management. The results of the study confirm that the roles and responsibilities of local-level stakeholders are not well-defined and mandated, and therefore, the performance of stakeholders involved is minimal. Therefore, the results highlight the need for a well-established community-based flood risk management mechanism.

The study aims to investigate the nomenclature of structural versus non-structural building adaptation measures taken by occupants of residential properties located in flood-prone areas of Port Harcourt, Nigeria, to verify whether they are adapted or maladapted relative to their level of flood exposure and underscore the role of disaster resilience in property management.

Using the survey research strategy, the uptake of structural and non-structural adaptation measures in spatially distributed areas of Port Harcourt was descriptively analyzed and tested to identify significant variation in the uptake of adaptation measures relative to increasing flooding levels, using a one-way ANOVA.

The study outcome reveals that there are some distinctive features of buildings in Port Harcourt which provide wet-proofing structural adaptation qualities while dry-proofing structural adaptation measures are not adequate. However, although some key structural adaptation measures were adapted relative to the levels of flood exposure, most structural features of the buildings do not vary relative to flooding levels, indicating maladaptation even with increasing flood risk. The uptake of non-structural measures is also inadequate and maladapted relative to changes in the level of flood exposure, despite their non-intrusive and low-cost nature. Overall, the findings imply that maladaptation is more prevalent.

The study provides a descriptive snapshot of the nomenclature of property-level flood risk adaptation in residential buildings, while highlighting the maladaptive tendencies/behavior of property occupants, within a metropolitan setting in the developing world, necessary to inform policy and provide sensitization for fostering disaster resilience in property management.

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.

In an era overshadowed by the alarming consequences of climate change and the escalating peril of recurring floods for communities worldwide, the significance of proficient disaster risk management has reached unprecedented levels. The successful implementation of disaster risk management necessitates the ability to make informed decisions. To this end, the utilization of three-dimensional (3D) visualization and Web-based rendering offers decision-makers the opportunity to engage with interactive data representations. This study aims to focus on Thiruvananthapuram, India, where the analysis of flooding caused by the Karamana River aims to furnish valuable insights for facilitating well-informed decision-making in the realm of disaster management.

This work introduces a systematic procedure for evaluating the influence of flooding on 3D building models through the utilization of Web-based visualization and rendering techniques. To ensure precision, aerial light detection and ranging (LiDAR) data is used to generate accurate 3D building models in CityGML format, adhering to the standards set by the Open Geospatial Consortium. By using one-meter digital elevation models derived from LiDAR data, flood simulations are conducted to analyze flow patterns at different discharge levels. The integration of 3D building maps with geographic information system (GIS)-based vector maps and a flood risk map enables the assessment of the extent of inundation. To facilitate visualization and querying tasks, a Web-based graphical user interface (GUI) is developed.

The efficiency of comprehensive 3D building maps in evaluating flood consequences in Thiruvananthapuram has been established by the research. By merging with GIS-based vector maps and a flood risk map, it becomes possible to scrutinize the extent of inundation and the affected structures. Furthermore, the Web-based GUI facilitates interactive data exploration, visualization and querying, thereby assisting in decision-making.

The study introduces an innovative approach that merges LiDAR data, 3D building mapping, flood simulation and Web-based visualization, which can be advantageous for decision-makers in disaster risk management and may have practical use in various regions and urban areas.

This paper aims to clarify the resistance degree of group road logistics to flood disaster resilience. The paper measures the resilience of group road logistics by establishing network structure model. The purpose of this study is to improve the resilience of road log.

This paper adopts Delphi method to collect data, interviews mainly flood management experts and supply chain risk management experts, and then analyzes the data through the network structure model combined with interpretative structure model (ISM) and analytical network process (ANP).

The results show that flood frequency and drainage systems are the main factors affecting the resilience of road transport logistics in urban areas. These research results provide useful guidance for the effective planning and design of urban road construction and infrastructure.

However, the main factors affecting the resilience of road transport logistics are likely to change with the development of factors such as climate, economy and environment. Therefore, in future work, the authors' research will focus on the further application of this evaluation method.

The results show that the impact of flooding on the four dimensions of road logistics resilience varies. This shows that in deciding what intervention measures are to be taken to improve the resilience of the road network to flooding, various measures need to be considered.

This paper provides a more scientific analysis of the risk management ability of the road network in the face of floods. In addition, it also provides a useful reference for urban road planners.

This paper addresses a clear need to study how to build models to improve the resilience of road logistics in flood risk.

This study aims to determine the key indicators affecting the resilience of the construction supply chain to flooding and calculate the resilience of the urban construction supply chain in three cases city.

This study combines expert opinions and literature review to determine key indicators and establish a fuzzy EWM-GRA-TOPSIS evaluation model. The index weight was calculated using the entropy weight method, and GRA-TOPSIS was used for comprehensive evaluation.

The results of the study show that the three cities are ranked from the high to low in order of Hangzhou, Hefei and Zhengzhou.

The innovative method adopted in this study comprising EWM-GRA-TOPSIS reduced the influence of subjectivity, fully extracted and utilized data, in a way that respects objective reality. Further, this approach enabled the absolute and relative level of urban construction supply chain resilience to be identified, allowing improvements in the comprehensiveness of decision-making. The method is relatively simple, reasonable, understandable, and computationally efficient. Within the approach, the entropy weight method was used to assign different index weights, and the GRA-TOPSIS was used to rank the resilience of the construction supply chain in three urban cities. The development of resilience provides a robust decision-making basis and theoretical reference, further enriching research methods, and having strong practical value. The study serves to improve risk awareness and resilience, which in turn helps to reduce losses. It also provides enhanced awareness regarding the future enhancement of supply chain resilience for urban construction.

The survivorship of firms under extreme weather poses an essential question about the local economy's health. Over 90% of agricultural banks are categorized as community banks, which are important financial institutions promoting local growth. While previous studies suggest that climate change and weather shocks adversely impact community banks' resiliency, studies on whether these institutions engage in risk-reducing management strategies have been limited. In this study, the authors examine strategic choices of local community banks when facing flood events which include (1) safety net increase, (2) portfolio diversification, and (3) branch opening. These strategic choices are the coping mechanisms banks can take to survive while affecting the local competitive lending market.

The authors use panel-fixed effect regressions based on the storm data from National Oceanic and Atmospheric Administration (NOAA)'s National Weather Service (NWS) and the call reports from the Federal Deposit Insurance Corporation (FDIC). The authors focus on community banks' account variable characteristics and the number of offices to examine whether community banks take an active role in managing flood risk.

Results suggest that community banks do employ the selected strategic choices to a certain degree, as it is found that there is an increase in the core capital that absorbs shocks and portfolio diversification. However, the magnitudes of these activities are rather small and not large enough to fully mitigate the climate risk. Also, the authors do not find any evidence of branch expansion associated with local floods.

This study contributes to the literature by examining different strategic choices of community banks in the face of natural uncertainty. Even though concerns of climate risk have been raised in the regulatory setting, a lack of guidance or assessment tools could contribute to the passive action of these community banks, even though climate risks can have a significant economic impact. Thus, the evidence documented from this study calls for further guidelines and the importance of highlighting climate risks on community banks so that they can actively engage in risk-reducing strategies.

The ineffectiveness of flood control in climate-impacted majority-world cities like Jakarta highlights the need for policies that integrate local knowledge and embrace water harmony rather than resistance. This study explores flood adaptation in North Jakarta's kampungs (urban informal settlements), aiming to enhance the efficacy of current flood disaster management. The outcomes of the participatory planning mechanism simulation that we propose are expected to provide valuable insights for the urban planning approach in that city.

We employed focus groups and design charrettes with a bottom-up approach to explore how local knowledge can enhance spatial flood management and urban planning policies. In total, 17 diverse participants, covering various ages and professions, engaged in these activities. Our methods aimed to be culturally sensitive and inclusive, embracing indigenous values like musyawarah and gotong royong. The research methodically examined flood implications and adaptations in informal settlements, progressing through preliminary understanding, data triangulation, and a reflective synthesis of the findings.

Amid worsening global changes like sea level rise, community-focussed, collaborative planning can help create tailored flood-resilience solutions. The research reveals that partnerships between communities and organisations promote city-wide, flood-adapted environments, aligning policy with the needs and goals of those most affected by flooding. This collaboration enhances flood disaster management and planning policies.

This research focusses on Jakarta's flood adaptation and urban planning, reflecting on historical situations relevant to urbanising majority-world countries. Whilst specific to Jakarta, it offers perspectives on managing global environmental challenges such as sea level rise. Subsequent research should prudently consider each locale's distinct geographic and social milieu and the trust in planning systems in applying these findings, methodologies and approaches.

This study clarifies the relationship between disaster management, policy and flood adaptation, focussing on local knowledge in North Jakarta, pertinent to urbanising majority-world nations. Jakarta's historical and modern dynamics, including globalisation, reveal specific prospects and obstacles to applying vernacular knowledge to planning and disaster response. It highlights crucial points for policymakers in the majority of the world to address growing flood risks and create strategies that integrate local and traditional wisdom.

The purpose of this study is to explore multiple stakeholders managing the different type of knowledge in a flood-prone area. Different stakeholders hold different types of knowledge in their area of interest, and both knowledge streams have their intrinsic potentials and limitations. In this paper, the issue of knowledge complementarity is explored in the context of flood hazards. Hazards such as floods may appear messy, unpredictable, with unsorted and unorganised forms of data, information and knowledge on the part of diverse stakeholders.

Case study design had been used in this study to explore how stakeholders: Orang Asli, Malay, and humanitarian organisations manage the differences in terms of type of knowledge each of them have. To illicit the response from participants from each of the stakeholders, in-depth interviews had been used.

This research has led to the development of a conceptual framework based on the case study. The lessons learned from the framework is discussed, together with the barriers to their implementation.

This paper presents a research case study on multiple stakeholders in the district of Pekan, the state of Pahang, Malaysia, and how these multiple stakeholders manage flood hazards with their different types of knowledge.

This study aims to review the features and challenges of the flood relief chain, identifies administrative measures during and after the flood occurrence and prioritizes them using two machine learning (ML) and analytic hierarchy process (AHP) methods. This paper aims to provide a prioritization program based on flood conditions that optimize flood management and improves society’s resilience against flood occurrence.

The collected database in this paper has been trained by using ML algorithms, including support vector machine (SVM), Naive Bayes (NB) and k-nearest neighbors (kNN), to create a prioritization program. Furthermore, the administrative measures in two phases of during and after the flood are prioritized by using the AHP method and questionnaires completed by experts and relief workers in flood management.

Among the ML algorithms, the SVM method was selected with 91.37% accuracy. The prioritization program provided by the model, which distinguishes it from other existing models, considers five conditions of the flood occurrence to prioritize actions (season, population affected, area affected, damage to houses and human lives lost). Therefore, the model presents a specific plan for each flood with different occurrence conditions.

The main limitation is the lack of a comprehensive data set to determine the effect of all flood conditions on the prioritization program and the relief activities that have been done in previous flood disasters.

The originality of this paper is the use of ML methods to prioritize administrative measures during and after the flood and presents a prioritization program based on each flood’s conditions. Therefore, through this program, the authority and society can control the adverse impacts of flood more effectively and help to reduce human and financial losses as much as possible.