Purpose This research explored the current views and experiences of commercial property owners and users towards the practice of property flood resilience (PFR) to identify the barriers and develop improved implementation strategies. Design/methodology/approach The research adopted an exploratory approach using six recently flooded commercial properties as case studies and examined them through site visits, interviews and documentary evidence to achieve triangulation of the enquiry. Findings The findings revealed that while PFR measures had thus far been sparsely implemented, where PFR had been installed, these had been designed to meet particular business needs and had brought about positive outcomes in reducing the impact of flooding and speeding up the recovery process. However, businesses were found to be lacking a coherent strategy and lacked the required understanding and support for PFR implementation. Research limitations/implications This research provides robust evidence for commercial property owners and other stakeholders to facilitate improved decision-making in the design and implementation of PFR measures. This research was conducted based on six commercial properties from two UK regions and therefore the findings are limited in this respect. Practical implications This research extends current insights into PFR and presents a much-needed in-depth understanding of issues in PFR implementation in commercial properties. This not only provides valuable lessons for commercial properties owners on how to implement PFR for effective flood risk management but also allows policymakers such as governments and professional bodies to better design incentives and support mechanisms for businesses. Originality/value The application and implementation of PFR has focused on residential properties, and there has been a dearth of research on its application to commercial property. This paper presents the commercial property owners’ flood experience and explores the potentials of PFR and the barriers to its implementation.

With increasing global urbanization and climate change, urban flooding has become more frequent, making urban flood resilience (UFR) a critical research focus. This study assesses UFR in the Yangtze River Delta (YRD) region by extending the Pressure-State-Response model with a 'Recovery' dimension, integrating Nature, Economy, Society, and Infrastructure systems. Using data from 27 YRD cities (2014-2023), a CRITIC-TOPSIS model evaluates UFR, while Moran's I and LISA analyses reveal spatiotemporal patterns. The XGBoost-SHAP model identifies key influencing factors. Results show: (1) YRD's UFR is medium-to-high, steadily rising, with disparities narrowing and values concentrating at 0.4-0.5 by 2023; (2) A 'high southeast, low northwest' spatial pattern emerges, with high-high clusters (e.g. Jinhua, Shaoxing) and low-low clusters (e.g. Yancheng, Taizhou-JS); (3) slope and population density primarily drive UFR differences, supported by ecological, economic, and social factors. This study informs targeted flood resilience strategies and regional governance in the YRD.

Flooding is an increasing climate risk in the UK, yet schools remain marginal in resilience planning. Flood events disrupt education, heighten pupil anxiety, increase staff workload and unsettle communities, but these experiences are rarely documented in ways that inform policy. This study examines how schools in the East and West Midlands regions of the UK have experienced and adapted to flooding. Eight qualitative case studies were undertaken in flood-affected schools using semi-structured interviews with key staff, site visits and documentary evidence. Interview transcripts were thematically analysed using NVivo to explore past flood events, levels of preparedness, and readiness for measures such as Property Flood Resilience, Sustainable Drainage Systems and Climate Action Plans. Findings show wide variation in awareness, emergency procedures and engagement with local authorities. Most schools had faced flooding or near misses but lacked formal guidance or flood-specific plans, leading to improvised responses led internally by staff. Despite limited funding, inconsistent communication and exclusion from wider planning, schools demonstrated adaptive potential and willingness to support community preparedness. The study offers evidence to guide headteachers, policymakers and local authorities in strengthening school-based flood resilience and supporting the development of a resilience innovation blueprint for flood-prone schools in the UK.

Flood risk management (FRM) strategies in many developed countries increasingly focus on building flood resilience at property, community, and national levels. However, existing research on community flood resilience (CFR) has thus far inadequately addressed the social dynamics underpinning interactions among key resilience dimensions. Despite limited recognition of the social dimension, factors such as social capital and sociocultural dynamics remain insufficiently explored, warranting further investigation. This study employs a modified preferred reporting items for systematic reviews and meta-analyses (PRISMA) to critically review and synthesize research gaps, before presenting an innovative social capital oriented framework to evaluate CFR. While infrastructure, economic, environmental, human, and governance dimensions play significant roles, the proposed framework emphasizes the foundational role of social capital and sociocultural factors, including norms, values, and identities, in shaping resilience outcomes and actions. These factors influence the success or failure of resilience-building efforts, particularly in diverse, deprived communities, such as those with nonnative speaking populations. This innovative framework offers insights for multisectoral stakeholders, including flood risk managers, engineers, surveyors, property owners, and local authorities, to address persistent challenges in resilience-building activities and improve intervention outcomes.

Flood and drought risks in river basins are driven by a complex interplay of natural and anthropogenic factors, making their assessment and management particularly challenging. This paper presents a novel approach to systematically identify and evaluate the most influential parameters contributing to these risks. We employed Interpretive Structural Modelling (ISM) and Causal Loop Diagrams (CLD) to construct a comprehensive framework of 116 interconnected parameters. By applying 11 network metrics, including betweenness centrality, PageRank, and closeness centrality, we identified the key parameters that act as critical influencers within the system [4]. The Cross-Entropy method was then utilized to refine this set, pinpointing the most significant 30 percent of parameters across all metrics. This analysis led to the development of causal networks for flood and drought risks, highlighting the dynamic relationships and critical drivers in each context. The findings provide a robust foundation for decision-makers to prioritize resources, optimize risk management strategies, and predict future risks. This work offers valuable insights for policymakers and river basin managers to converge socio-environmental planning and transboundary water management, while also supporting the proactive mitigation of flood and drought impacts.

Urban flooding represents a major long-standing and historical challenge that has become more severe in recent years due to the intensification of climate change and rapid urbanization. This study establishes a new comprehensive framework for assessing urban flood resilience based on a novel combination of the 'pressure-state-response' theory and through consideration of natural, social, economic and infrastructure dimensions. Through an analysis of both the static and the dynamic considerations, a more comprehensive evaluation system is developed. This new framework is then used to evaluate the flood resilience levels of three flood prone cities in China. The results show that Wuhan has the highest level of flood resilience, Nanchang ranks second, while Changsha has the lowest level of flood resilience. This study provides new insights to support the development of understanding of urban flood resilience at the macro scale and will be useful to policy makers and in shaping new strategic approaches to flood risk management.

Purpose In view of the increasing threat of flooding across the world and specifically the vulnerability of the Pearl River Delta region to these risks, this study undertakes a spatial and temporal evolution of flood risk in the region, including an assessment of urban flood resilience. Design/methodology/approach By combining the pressure-state-response (PSR) model and the nature-economy-society-infrastructure (NESI) framework, an urban flood resilience index system is constructed. The order relation analysis method, Criteria Importance Through Intercriteria Correlation method and the VlseKriterijumska Optimizacija Kompromisno Resenje evaluation method, they were then combined to quantify urban flood resilience and reveal the hierarchical relationships that exist between key factors. Using ArcGIS software, the resilience levels of each city are dynamically tracked and compared to reveal the trends in flood resilience over a three-year period. Findings The results show that annual precipitation and impervious areas are the key factors impacting environmental pressure, while the sewage treatment rate is found to be the key response measure. The cities of Guangzhou and Shenzhen were shown to have maintained high flood resilience indexes (FRI), while Zhaoqing City was the weakest. Flood resilience levels across the Pearl River Delta were found to vary significantly, with the central and southern cities having higher levels than those in the eastern and western regions. Originality/value This study constructs a new combined method for assessing urban flood resilience, which is suitable for quickly and accurately assessing the short-term spatial and temporal evolution trend of urban flood resilience.

Community Engagement (CE) is crucial for building flood resilience and empowering communities to participate actively in disaster preparedness, response, and recovery. However, many existing CE approaches neglect key social dimensions, such as inclusivity, social vulnerabilities, and community-driven strategies. This oversight often limits community ownership and reduces effectiveness. This research critically examines the social drivers of community engagement in flood resilience, emphasising the need for a Social Network approach to strengthen social connections, enhance participation, and foster sustained resilience. A review and synthesis of existing literature, spanning disaster risk management, flood resilience, social networks, behavioural science, and community engagement, identifies key internal and external drivers. The main internal drivers include social cohesion, leadership, education and local knowledge. Key external drivers include government support, partnerships, and technological resources. The findings highlight the importance of integrating internal and external drivers through Social Network Analysis (SNA) to foster foster cohesion, adaptability, and sustainability in community engagement. The research provides valuable theoretical insights for policymakers, practitioners, and researchers to improve collaboration, resource allocation, and community-led engagement. It advances knowledge by analysing key social drivers and introducing SNA as a framework to integrate these drivers for more effective community engagement. Future research will develop a theoretical framework and test the applicability of SNA in various contexts.

In light of frequent flood risks in Guangdong Province and the lack of recent research, this study developed a four-dimensional assessment system with 16 indicators covering disaster risk, environmental sensitivity, vulnerability of disaster-bearing bodies, and disaster prevention capabilities. Weights were assigned using the ANP and EWM, and flood risks in 21 prefecture-level cities were ranked using the TOPSIS method. Risk maps were generated with ArcGIS. Results reveal uneven flood risk distribution, with high-risk areas concentrated in the Pearl River Delta, western, and northern regions, influenced by multiple factors. Vulnerability and disaster prevention capabilities were identified as critical considerations. The study verifies the feasibility of the method, offering a scientific basis for flood risk management in Guangdong and supporting sustainable urban development.

Existing Community Flood Resilience (CFR) frameworks often integrate a range of dimensions to measure flood resilience, but social indicators are often overlooked or neglected due to the challenges involved in gathering information and quantifying these aspects. This research presents a novel methodology towards the development of a more comprehensive CFR framework. The methodology presented combines quantitative and qualitative insights through a participatory mixed-methods approach. Initially, the Delphi process is used to co-develop resilience indicators with professional experts drawn from key stakeholders including the Environment Agency, Local Authorities and National Flood Forum, as well as a range of community representatives. This new methodology argues for initiating earlier stakeholder input and sustaining this to enhance relevance and applicability of the framework. Grounding the framework in multiple stakeholder perspectives creates an opportunity to capture local and culturally relevant resilience indicators which thus far have received scant treatment in earlier frameworks. The intention is to apply the new methodology in vulnerable UK communities, using GIS mapping and regression analysis to visualise and quantify resilience levels. This new approach can bridge the gap in traditional flood resilience measurement by providing a flexible tool for policymakers to identify specific resilience needs. It contributes to the growing field of CFR assessment, provides practical solutions for adaptive flood management and supports United Nations Sustainable Development Goals (SDGs) Goal 16 by enabling local stakeholder engagement in resilience planning.

Purpose Flooding is China’s most frequent and catastrophic natural hazard, causing extensive damage. The aim of this study is to develop a comprehensive assessment of urban flood risk in the Hubei Province of China, focusing on the following three issues: (1) What are the factors that cause floods? (2) To what extent do these factors affect flood risk management? (3) How to build an effective comprehensive assessment system that can be used to reduce flood risk? Design/methodology/approach This study combines expert opinion and evidence from the extent literature to identify flood risk indicators across four dimensions: disaster risk, susceptibility, exposure and prevention and mitigation. The Criteria Importance Through Intercriteria Correlation (CRITIC) and the Grey Relational Analysis (RA)-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) decision-making approach were applied to calculate the weighting of factors and develop a model of urban flood risk. Then, ArcGIS software visualizes risk levels and spatial distribution in the cities of Hubei Province; uncertainty analysis verified method accuracy. Findings The results show that there are significant differences in the level of urban flood risk in Hubei Province, with cities such as Tianmen, Qianjiang, Xiantao and Ezhou being at high risk, while cities such as Shiyan, Xiangyang, Shennongjia, Yichang, Wuhan and Huanggang are at lower flood risk. Originality/value The innovative method of combining CRITIC-GRA-TOPSIS reduces the presence of subjective bias found in many other flood risk assessment frameworks. Regional data extraction and uncertainty analysis enhance result reliability, supporting long-term decision-making and urban planning. Overall, the methodological approach developed provides an advanced, highly effective and efficient analysis and visualization of flood risk. This study deepens the understanding of flood risk assessment mechanisms and more broadly supports the development of resilient cities.

This Introduction presents the collection of chapters in this Handbook - chapters that emphasize urban flood management on city, neighbourhood, local and property scales. The chapters propose that the goal of risk management, to minimize the risk to populations, can be enhanced through better understanding of the impacts on people and their risk behaviours. Such understanding can be developed through collaboration involving communities and other urban stakeholders at all stages and in multiple ways. Furthermore, they indicate the immense variety of research beginning to evaluate the effect of involving wider stakeholders and communities in designing and implementing mitigation, preparedness and emergency actions towards more informed and socially connected flood risk management.

In recent years, large-scale flood events have occurred more frequently, and the concept of resilience has become a prevalent approach to managing flood risk in many regions. This has led to an increased interest in how to effectively measure a city’s flood resilience levels. This study proposes a novel modeling approach to quantify urban flood resilience by developing D-number theory and analytical hierarchy process (AHP) models, which are applied to three cities in China using the VIse Kriterijumski Optimizacioni Racun (VIKOR) method. The findings reveal that Hefei City has the most effective level of flood resilience, Hangzhou City was ranked second, while Zhengzhou City has the least effective level of flood resilience. This study provides a new scientific basis on how to quantify flood resilience at the city scale and provides a useful reference for these three specific cities. The methods and approaches developed in this study have the potential to be applied to other cities and in the related aspects of disaster prevention, recovery, and reconstruction.

Urban flooding is one of the main challenges affecting sustainable urban development worldwide, threatening the safety and well-being of communities and citizens. The aim of this study is to assess the development and trends in urban flood resilience at the city scale, as well as to improve the resilience of cities to these risks over time. The study constructs a model for assessing urban flood resilience that incorporates economic, social, ecological, and managerial aspects and assesses them through a range of indicators identified in the literature. The comprehensive evaluation model of Network Analysis Method–Entropy Weight Method–The Distance between Excellent and Inferior Solutions (ANP-EWM-TOPSIS) was used to empirically investigate the flood resilience characteristics of Nanjing from 2010 to 2021. There are two main findings of the study: firstly, the flood resilience of Nanjing gradually improves over time, as the economic flood resilience steadily increases, while the social, ecological, and management flood resilience decreases; and secondly, during the study period, barriers caused by economic and regulatory factors in Nanjing decreased by 33.75% and 23.72%, respectively, while barriers caused by social and ecological factors increased by 32.69% and 24.68%, respectively. The novelty of this study is the introduction of a “barrier degree” model, which identifies and highlights barriers and obstacles to improving urban flood resilience and provides new insights into improving urban flood resilience at the city scale.

PurposeIn modern urban governance, rescue materials storage points (RMSP) are a vital role to be considered in responding to public emergencies and improving a city's emergency management. This study analyzes the siting of community-centered relief supply facilities.Design/methodology/approachCombining grey relational analysis, complex network and relative entropy, a new multi criteria method is proposed. It pays more attention to the needs of the community, taking into account the use of community hospitals, fire centers and neighborhood offices to establish small RMSP.FindingsThe research results firstly found suitable areas for RMSP site selection, including Hanyang, Qiaokou, Jiangan and Wuchang. The top 10 nodes in each region are found as the location of emergency facilities, and the network parameters are higher than ordinary nodes in traffic networks. The proposed method was applied in Wuhan, China and the method was verified by us-ing a complex network model combined with multi-criteria decision-making for emergency facility location.Practical implicationsThis method solves the problem of how to choose the optimal solution and reduces the difficulty for decision makers. This method will help emergency managers to locate and plan RMSP more simply, especially in improving emergency siting modeling techniques and additionally in providing a reference for future research.Originality/valueThe method proposed in this study is beneficial to improve the decision-making ability of urban emergency departments. Using complex networks and comprehensive evaluation techniques, RMSP is incorporated into the urban community emergency network as a critical rescue force. More importantly, the findings highlight a new direction for further research on urban emergency facilities site selection based on a combination of sound theoretical basis as well as empirical evidence gained from real life case-based analysis.Highlights:Material reserve points are incorporated into the emergency supply network to maintain the advantage of quantity.Build emergency site selection facilities centered on urban communities.Use a complex network model to select the location of emergency supplies storage sites.