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The purpose of this paper is to explore flood-prone area residents' preferences of flood-resilient housing technologies (HTs), to understand the factors influencing their choices. Flood-resilient HTs can reduce damage and disruption at a household level, particularly in areas where large-scale community schemes are not available or feasible. People’s perception of floods and their preferences of flood-resilient HTs are among many very important factors influencing the adoption of these technologies. Therefore, these perceptions and preferences must be well understood before implementation of these technologies can occur. However, studies on these two important factors are lacking in literature, particularly in the sub-Saharan African context.

Nigerian residents’ preferences of flood-resilient HTs were explored by focusing on five frequently flooded areas around the Niger and Benue river basins in Kogi State, Nigeria. Thirty-eight chat, video and voice call interviews were conducted with participants across five case study areas: Lokoja, Idah, Bassa, Ajaokuta and Koton Karifi. The interviews, informed through an illustrated brochure, covered residents’ experiences and perceptions of floods. This was done to gain an understanding of the factors influencing the choice of flood-resilient HTs adopted and those preferred.

This study confirms that residents in these five focus areas show similar characteristics to other floodplain residents as encapsulated in protection motivation theory. The flood-resilient HTs discussed in this study include flood-avoidance, flood-recoverability and flood-resistance strategies, as well as neighbourhood-scale approaches. Flood-resistance and flood-recoverability strategies rated highly in terms of suitability and envisaged efficiency in mitigating flooding in Kogi State. Although the measures were mostly agreed to be potentially effective and successful on a household scale, there were concerns as to flood mitigation on a neighbourhood scale.

Pre-existing flood-resilient HTs were not extensively discussed in the literature review but were included to have a sense of the participants’ mitigation behaviour, as well as their potential to adopt (or not) new measures after adopting previous ones.

The results provide supporting evidence of the factors influencing the choice of and/or intention to adopt flood-resilient HTs, highlighted in literature. Results also contribute to literature by providing further insight into flood-resilient measures already adopted by residents, as well as their preferred HTs from the options presented. The implications of these findings and methodological considerations in this research are fully discussed in this paper.

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.

Flood preparedness and response from the perspective of community engagement mechanisms have been studied in scholarly articles. However, the differences in flood mitigation may expose social and behavioural challenges to learn from. This study aimed to demonstrate how text mining can be applied in prioritising existing contexts in community-based and government flood mitigation and management strategies.

This investigation mined the semantics researchers ascribed to flood disasters and community responses from 2001 to 2022 peer-reviewed publications. Text mining was used to derive frequently used terms from over 15 publications in the Scopus database and Google Scholar search engine after an initial output of 268 peer-reviewed publications. The text-mining process applied the topic modelling analyses on the 15 publications using the R studio application.

Topic modelling applied through text mining clustered four (4) themes. The themes that emerged from the topic modelling process were building adaptation to flooding, climate change and resilient communities, urban infrastructure and community preparedness and research output for flood risk and community response. The themes were supported with geographical flood risk and community mitigation contexts from the USA, India and Nigeria to provide a broader perspective.

This study exposed the deficiency of “communication, teamwork, responsibility and lessons” as focal themes of flood disaster management and response research. The divergence in flood mitigation in developing nations as compared with developed nations can be bridged through improved government policies, technologies and community engagement.

Despite the present focus on improving the resilience of homes to flooding in UK flood risk management policy and strategy, a general measurement framework for determining levels of flood resilience in UK homes does not exist. In light of this, the aim of this study was to develop a means to evaluate the levels of resilience in flood-prone homes from the perspective of homeowners'.

A quantitative research methodology was employed, with empirical data obtained through a postal survey of homeowners who had experienced flooding. The responses received were then analysed using a combination of statistical techniques including agreement/reliability tests and multiple regression to develop a model of flood resilience.

A predictive model was developed that allows the resilience of a property to be quantified and measured as perceived by homeowners. The findings indicate that the main factors found to influence the level of flood resilience were: property type (PT), presence of cellar/basement (C/B), property wall type (PWT), property ground floor type (PGFT), kitchen unit type (KU), flood experience (FE), flood source (FS) and flood risk level (FRL).

The resulting model provides unique insights into resilience levels to the benefit of a range of stakeholders including policy makers (such as Defra/Environment Agency), Local Authority flood teams, property professionals, housing associations and homeowners. As a result, homeowners will be in a better position to determine which interventions should be prioritised to ensure better flood protection.

This is the first study of its kind to have rigorously quantified the level of flood resilience for individual homes. This study has quantified the effectiveness of individual resilience measures to derive the first reliable means to measure the overall levels of resilience at the individual property level. This is regarded as a significant contribution to the study of flood risk management through the quantification of resilience within individual UK homes, enabling the prioritisation of interventions and the overall monitoring of resilience.

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.

This paper aims to quantitively assess the resilience of residential properties to urban flooding in Port Harcourt, Nigeria, and assess whether they vary at spatially aggregated scales relative to the level of flood exposure.

The study synthesizes theoretical constructs/indicators for quantifying property level resilience, as a basis for measuring resilience. Using a two-stage purposive/stratified randomized sampling approach, 407 questionnaires were sent out to residents of 25 flood-prone areas, to solicit information on the resilience constructs as indicated by the adaptation behaviors of individual households and their property attributes. A principal component analysis approach is used as a mechanism for weighting the indicators, based on which aggregated spatial-scale resilience indices were computed for the 25 sampled areas relative to their levels of flood exposure.

Area 11 located in the moderate flood zone has the lowest resilience index, while Area 20 located in the high flood zone has the highest resilience index. The resilience indices for the low, moderate and high flood zone show only minimal and statistically insignificant differences indicating maladaptation even with incremental levels of flood exposure.

The approach to resilience measurement exemplifies a reproducible lens through which the concept of “living with floods” can be holistically assessed at the property level while highlighting the nexus of the social and technical dimensions.

The study moves beyond theoretical conceptualization, to empirically quantify the complex concept of property-level flood resilience.

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.

The purpose of the paper is to predict mapping of areas vulnerable to flooding in the Ourika watershed in the High Atlas of Morocco with the aim of providing a useful tool capable of helping in the mitigation and management of floods in the associated region, as well as Morocco as a whole.

Four machine learning (ML) algorithms including k-nearest neighbors (KNN), artificial neural network, random forest (RF) and x-gradient boost (XGB) are adopted for modeling. Additionally, 16 predictors divided into categorical and numerical variables are used as inputs for modeling.

The results showed that RF and XGB were the best performing algorithms, with AUC scores of 99.1 and 99.2%, respectively. Conversely, KNN had the lowest predictive power, scoring 94.4%. Overall, the algorithms predicted that over 60% of the watershed was in the very low flood risk class, while the high flood risk class accounted for less than 15% of the area.

There are limited, if not non-existent studies on modeling using AI tools including ML in the region in predictive modeling of flooding, making this study intriguing.

Sustainable and resilient infrastructure projects aim to reduce flooding impacts and improve community adaptability. For instance, flood-resistant stilts elevate structures, mitigating flood damage. Comprehensive consideration is crucial when adding elements to housing projects, incurring costs for all involved parties. This study aims to assess the viability of concrete stilts for cost-effective flood mitigation in Malaysian terrace housing.

The study evaluates cost implications through a comparative 5D building information modeling (BIM) cost analysis of stilted and conventional (standard) housing models. This assesses the percentage increase in total cost. Furthermore, a survey of construction professionals was undertaken. The study used online convenience and stratified sampling techniques. Out of the 222 emails that were sent, 27 construction professionals located in Johor, Sabah and Selangor within Malaysia participated in the research survey. Their perspectives on stilt housing prospects and factors for costing such structures were analyzed through a descriptive analysis using SPSS.

The case study models revealed that the incorporation of stilts could lead to a 21.64% increase in the overall cost per unit. This cost increase was primarily attributed to the additional reinforcement required. However, the survey findings highlighted that a majority of construction professionals perceived the cost increment to fall within the range of 10%–20%. Consequently, it becomes imperative to meticulously consider cost factors such as foundational requirements, staircases, and the extended construction duration to effectively curtail expenditures. The prospect of heightened costs potentially posing a threat to profit margins and discouraging developers necessitates careful financial management. Notwithstanding these challenges, the survey's insights underscored that professionals in the construction industry indeed recognize the potential of stilt technology in the realm of flood mitigation and management, particularly within housing projects.

This research has significant practical implications. It provides a precise financial contrast between housing categories using 5D BIM and incorporates construction experts’ viewpoints on raised housing. Enhanced design considerations for raised housing can make it economically viable, offering a cost-effective, nature-based approach to flood mitigation. This approach can bring substantial benefits to residents by reducing flood-related damages and enhancing community resilience.

One of the notable aspects of this research is its originality. It uses a dual quantitative methodology involving modeling and survey techniques to address its objectives effectively. This approach contributes significantly to the relatively limited body of research focused on stilt housing and the application of 5D BIM. By combining these methodologies, the study explores a relatively uncharted area, making a valuable contribution to the field.

Understanding the technical and socioeconomic dimensions to resilience is core to making a business case for property-level flood risk adaptation. The study investigates the socioeconomic factors that impact the technical dimensions to property-level flood risk adaptation, and whether there is a typology of households adopting similar adaptation measures in Port Harcourt.

Exploratory and inferential statistical analysis of data collated from 407 questionnaires was carried out. Using chi-square analysis, significant bivariate associations were sought between the level of uptake of different categories of property level adaptation and the socioeconomic characteristics of households. A two-step cluster analysis was used to explore discernible patterns of households implementing similar adaptation measures. Logistic regression analysis was further used to evaluate the extent to which socioeconomic parameters impact residents' willingness to undertake adaptation measures given the option of relocation.

The chi-square analysis highlighted a lack of significant association between some socioeconomic parameters and the uptake of individual adaptation measures. The regression analysis however showed that the socioeconomic parameters exert varying degrees of influence on the residents' willingness to undertake adaptation measures. Two homogeneous groups of residents with similar socioeconomic characteristics were identified via the cluster analysis but did not translate into strongly discernible adaptation differences/patterns.

The study shows that although socioeconomic parameters to some extent underlie the technical dimensions to flood resilience, there is no distinctive typology of households in Port Harcourt adopting a similar combination of measures.

The study offers insights into understanding property-level flood risk adaptation responses within the context of the developing world.