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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.

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.

Cities across the globe, particularly those of the less developed world, face long-term challenges associated with floods which impact negatively on the resilience of city systems and their inhabitants. In the city of Maroua, most urban management stakeholders have been unable to integrate flood resilience research into urban development issues. It is against this background that the purpose of this paper is to evaluate the governance issues constraining the deployment of flood resilience strategies implemented by residents in flood-prone zones and those used by the government via administrative authorities and institutions charged with urban development to flood-related risks in the city of Maroua, Far North Region of Cameroon.

Field surveys, participant observations, interviews, and on-the-spot appraisals were carried out with residents in flood-prone neighbourhoods and municipal authorities on the state of recurrent floods including mitigating strategies being implemented.

The results revealed that Maroua has a fragile ecological setting which has increased the vulnerability of the town to flood-related risks. This is further aggravated by the fact that municipal authorities are yet to have a thorough mastery of such recurrent flood incidences due to their limited planning horizons, rendering the urban poor disproportionately susceptible to flood-related stresses. This exposes them to unavoidable flood associated hazards such as water borne diseases (typhoid and cholera) as they are bogged down by physical and financial limitations. Besides, decision-making processes in relation to managing urban systems are not guided by good governance as efforts to enhance and integrate the local population for flood resilience are neither participatory nor inclusive, ushering the urban environment of Maroua into a frivolous path to profligacy.

For resilience to be deeply entrenched, the paper proffers for the mainstreaming of flood resilience strategies into urban development plans through multi-stakeholder involvement across different sectors and departments, as well as the setting up of a practical time table for monitoring the progress of these measures through geospatial technologies such as remote sensing and geographical information systems.

Flood resilience is emerging as a major component of an integrated strategic approach to flood risk management. This approach recognizes that some flooding is inevitable and aligns with the concept of “living with water.” Resilience measurement is a key in making business case for investments in resilient retrofits/adaptations, and could potentially be used to inform the design of new developments in flood prone areas. The literature is, however, sparse on frameworks for measuring flood resilience. The purpose of this paper is to describe the development of a fuzzy logic (FL)-based resilience measuring model, drawing on a synthesis of extant flood resilience and FL literature.

An abstraction of the flood resilience system followed by identification and characterization of systems’ variables and parameters were carried out. The resulting model was transformed into a fuzzy inference system (FIS) using three input factors: inherent resilience, supportive facilities (SF) and resident capacity.

The resulting FIS generates resilience index for households with a wide range of techno-economic and socio-environmental features.

It is concluded that the FL-based model provides a veritable tool for the measurement of flood resilience at the level of the individual property, and with the potential to be further developed for larger scale applications, i.e. at the community or regional levels.

Flood resilience is a critical concept in flood risk management (FRM). Meanwhile, flood resilience measurement has become vital for making the business case for investment in FRM. However, information is sparse on measuring the level of resilience of flood-prone communities in Nigeria. Therefore, this study aims to develop a fuzzy logic-based model for measuring the resilience of flood-prone communities towards achieving the United Nations Sustainable Development Goals (SDGs) 11 and 13.

This study describes the development of a fuzzy logic-based flood resilience measuring model, drawing on a synthesis of fuzzy logic literature and extant flood resilience. A generalisation of the flood system for a typical Nigerian community was made. It was followed by an identification and characterisation of the variables and parameters of the system based on SDGs 11 and 13. The generated data was transformed into a fuzzy inference system (FIS) using three input community flood resilience dimensions: natural, socio-technical and socio-economic factors (SEF). The model was then validated with primary data obtained from selected flood-prone communities in Ibadan, Southwest Nigeria. Expert opinions were used in rating the input dimensions for the selected communities.

In spite of various inputs from experts in the same study area (Apete, Ibadan, Nigeria), the resulting FIS generated consistent resilience indices for various natural, socio-technical and SEF. This approach can strengthen flood resilience measurement at the community level.

Although previous attempts have been made to measure flood resilience at the individual property level (Oladokun et al., 2017; Adebimpe et al., 2020), this research focuses on measuring flood resilience at the community level by adapting the fuzzy logic approach. The fuzzy logic-based model can be a tool for flood resilience measurement at the community level. It can also be developed further for regional and national level applications.

This paper aims to investigate aspects of flood experience, attitudes and responses of micro-, small- and medium-sized enterprises (MSMEs) in Greece and to indicate a typology of strategies associated with their relative effort to build flood resilience capacity.

A qualitative study protocol was used, based on pertinent literature that considers how business entities withstand, adapt and/or recover from non-linear climate change impacts, natural hazards and extreme weather. Data was obtained by conducting semi-structured interviews with 82 MSMEs’ owners-managers who had recently experienced flooding.

The study reports limited activities of MSMEs towards flood resilience capacity despite the threat of relevant disasters. Findings suggest that most owners-managers of these enterprises are not adequately preparing their businesses for the impacts of flooding.

The findings call for multi-level and dynamic perspectives to be examined in assessing MSME resilience capacity to floods. It is attitudinal, managerial, organisational, behavioural and regulatory (as well as other institutional) factors that merit further investigation. Such an investigation would allow a better understanding as to whether these factors hinder or enable conditions for microeconomic flood preparedness and resilience as well as how they may interact with each other or create feedback loops.

The study carries managerial implications and policy recommendations in terms of nurturing opportunities towards awareness-raising campaigns for reducing deficits in managerial knowledge and competencies. It also encapsulates practical implications in terms of emphasising supporting mechanisms from key institutional stakeholders to allow MSMEs scan available options they have in effectively reinforcing the business premises from the forces of rising waters.

Most of the related studies have examined flood impacts, responses and/or resilience capacity at the household- or community-level. Empirical work that is conducted to ascertain how MSMEs cope with flooding remains thin on the ground. In response to this, the current study and the typology of MSMEs’ strategic postures that are suggested seek to contribute to this under-researched topic.

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.

Recent changes in climate, rainfall patterns, snow melt and rising sea levels coupled with an increase in urban development have increased the threat of flooding. To curb these threats and mitigate these damages, property-level approaches to improving resilience are now being encouraged as part of an integrated approach to flood risk management. This raises questions such as, what are the flood resilient attributes within individual properties, what is their importance and how can these be quantified. This research sought to develop a quantitative approach for the measurement of property-level flood resilience.

A synthesis of literature was undertaken to establish the main resilient attributes and their relevant sub-attributes. This process led to the development of a new method, named the Composite Flood Resilient Index (CFRI) to weight the attributes and sub-attributes of flood resilience based on their importance. The approach adopts the use of the fuzzy-analytic hierarchy process (F-AHP) approach to quantify flood resilience.

The implications of the proposed methodology in determining the flood resilience of individual property, including the potential use in retrofitting activities, and the benefits to a range of stakeholders are considered.

The methodology offers the potential to support the measurement of flood resilience of individual properties, allowing the identification and prioritisation of specific interventions to improve the resilience of a property.

Whereas previous attempts to quantify flood resilience have adopted qualitative approaches with some level of subjectivity, this proposed methodology represents an important advancement in developing a scientific and quantitative approach.

Existing literature on how social learning stemming from flood experience influences management and adaptation to flood-risks, and resilience-building is scant. In this context, the purpose of this study is to map the processes and examine the application of social learning in formulating coping measures and adaptation strategies in Bangladesh's wetland communities.

To bridge this research gap, conceptually, we formulated the Social Learning from Disasters (SLD) Framework to explain the process of social learning from flood experience and the mechanism of its influence on community resilience. Applying a qualitative research approach, the empirical investigation was carried out in the Fenarbak Union of Sunamganj District, Bangladesh. Using a participatory approach and qualitative techniques, the required primary data were procured.

The results of the study yielded three key findings: (1) social learning and memory have often enabled wetland communities to adopt diverse coping and adaptive measures in response to flash floods; (2) social learning-based actions have resulted in reduced flood-risk and enhanced community resilience to flash floods, especially when these actions were supported by both local and external innovations and (3) the aforementioned social learning stemmed primarily from first-hand experience of flash floods, which was shared via various collective learning platforms.

The study followed a participatory methodology and the data were procured from two communities in the union level unit of Bangladesh. Therefore, generalization to apply to the larger context should be made with caution. Also, the study represents a cross-sectional study, and thus understanding of the long-term trend is not possible.

The findings of the study have direct and profound implications for local community-level disaster-risk planning. As there are serious deficiencies in documenting and preserving social learning for community resilience and development planning, this study offers a conceptual framework, along with empirical evidence, for transforming these lessons learned into practical actions for change.

The findings of the study highlight the importance of social learning as a collective effort and provide empirical evidence of innovative adaptations to change. These results are critical to formulating societal strategies for disaster-risk management as well as to enhance community resilience.

Limited efforts have hitherto been made to determine (1) how the actual process of social learning from disaster shocks takes place, and (2) how innovative adaptation strategies lead vulnerable communities to take up social learning-based actions. Our research attempts to fill these knowledge gaps by providing an evidence-based account of community resilience-building responses to flash flood disasters.

Floods are among the most frequent urban disasters in cities of the global south where capacity and resource limitations collude with rapid urbanization to force many poor people to live in flood prone settlements. This paper investigated the impact of flood disasters on social resilience of low-income communities in Mzuzu City, Malawi.

Using a quantitative design, 345 households were interviewed in Zolozolo West and Mzilawaingwe Wards in Mzuzu City. The survey instrument achieved a 100% response rate. A reliability test using Cronbach’s alpha showed internal consistency of survey instrument at 0.711 for Zolozolo West Ward and 0.730 for Mzilawaingwe Ward.

Out of the eleven indicators of social resilience used in this study, six indicators showed no correlation with the outcome expectancy of social resilience. Of the five indicators that showed relationship with social resilience, only improvisation and inventiveness (r_s = 0.356, p = 0.000 at two-tailed, n = 213; r_s = 0.610, p = 0.000 at two-tailed, n = 132) had a strong relationship with the outcome expectancy of social resilience.

The study was only conducted in two settlements; caution should be observed when generalizing the results.

Practitioners should ensure that social resilience strengthening mechanisms are incorporated in flood risk management as they strive to achieve SDG 11 of making cities inclusive, safe, resilient and sustainable.

The study showed how floods can negatively impact the social resilience of low-income communities, which is different from common knowledge that floods can enhance community social resilience.