Search Results (1,628)

Coastal urban environments are increasingly exposed to natural hazards, including storm surges, tsunamis, coastal erosion, and flooding, which threaten lives, livelihoods, and infrastructure. Despite their widespread use, conventional hard and soft engineering measures have often proved insufficient to address the escalating risks posed by climate change and rapid urbanisation. This study explores the potential of Nature-Inspired Solutions (NiS) as a complementary pathway to advance resilience in architecture, urban design, and planning. Unlike Nature-Based Solutions that utilise existing ecosystems directly, NiS draw design principles from both biotic and abiotic natural systems, offering innovative models for resilient settlements, coastal infrastructure, and adaptive urban planning. Using a mixed-methods approach that includes systematic and narrative reviews, semi-structured expert interviews, analysis of urban development plans, a panel discussion, and expert brainstorming, this research examines how natural coastal systems inform design interventions. Sri Lanka was selected as the primary case study context due to its exceptional coastal vulnerability, significant climate adaptation policy gaps, and status as a small island developing state representative of the coastal challenges faced by similar contexts globally. Furthermore, Sri Lanka was selected as the case study in accordance with the original research proposal submitted to the University of Huddersfield, which identified the country as a suitable context due to its significant vulnerability to coastal hazards, as outlined above. Field investigations in the Lunawa coastal area documented community-based adaptive practices emerging from multi-generational environmental observation. Analysis reveals how dune morphologies, root structures, living shorelines, and rock pool formations translate into architectural and engineering applications. Findings identify critical implementation challenges, including context-specific requirements, technical knowledge gaps, insufficient policy frameworks, limited practitioner awareness, and uncertainties about economic feasibility, as well as key enablers such as demonstrated ecological effectiveness and the potential of multifunctional infrastructure. The study demonstrates that embedding NiS into risk-informed planning and resilient urban design contributes to climate change adaptation, ecological sustainability, and inclusive governance, while highlighting persistent barriers that require strategic intervention. By bridging ecological wisdom and architectural innovation, NiS offers transformative opportunities to reimagine resilient coastal cities and communities facing escalating climate-induced hazards. Full article

Urban flooding poses escalating threats to high-density cities, yet the nonlinear mechanisms linking rainfall characteristics and urban morphology to waterlogging severity remain poorly understood. This study proposes a rainfall-stratified explainable machine learning framework to distinguish deep from shallow inundation at the block scale, taking Shanghai as a case study. Four models (XGBoost, random forest, SVM, and logistic regression) were compared via nested cross-validation and Bayesian optimization, with XGBoost identified as the optimal model. Three physically distinct rainfall dimensions and multi-dimensional urban morphological indicators were incorporated as predictive features. SHAP-based attribution and PDP were employed to unveil the driving mechanisms behind inundation severity, characterizing scenario-dependent shifts in driver dominance and nonlinear threshold effects. Urban morphology primarily governs spatial risk under non-extreme rainfall, with building shape coefficient (BSC) remaining the primary driver overall. Meteorologically, waterlogging severity surges beyond critical thresholds for maximum hourly rainfall (>18.40 mm/h) and total volume (>139 mm), while duration exhibits an inverted U-shaped response. Morphologically, a high BSC (>0.39 m⁻¹) is consistently associated with elevated deep inundation probability, whereas higher SDBV (>54,155 m³) and greater DR (>582 m) are associated with a severity-attenuating effect. These findings provide threshold-driven insights for integrating morphological resilience into urban renewal and sustainable flood adaptation strategies in high-density metropolises. Full article

Quantifying the impact of land use changes on the threat of flash-floods is a critical consideration in flood hazard planning and risk reduction, and is an area of active research. Here, a coupled Weather Research and Forecasting model hydrological extension package (i.e., WRF-Hydro) modeling approach is applied to simulate flash-flooding processes for short-duration, localized, intense precipitation events. To better understand the effect of urbanization on flash floods, a series of numerical experiments is performed surrounding Ellicott City, Maryland, a location which has experienced both significant heavy rainfall events and suburban development over the past several decades. Two intense rainfall events occurring on 30 July 2016 and 27 May 2018 are investigated, respectively, to first calibrate the hydrologic model performance and then quantify the sensitivity of flash flooding to varying degrees of urbanization. Performing the same experiments using observed historical land use states is of more limited insight, as the thrust of suburban development in the Ellicott City region significantly predates satellite-derived land use datasets. Results confirm that urbanization produces larger river streamflow, higher water stages, faster hydrologic responses to achieve peak flow discharge, and shorter recession limbs, even for very intense, short-duration events. The collective findings suggest that WRF-Hydro is applicable for both watershed flash flood prediction and hypothesis testing, and demonstrates potential utility to urban development decision-makers in locations such as Ellicott City, which could face future increases in catastrophic flooding. Full article

Due to climate change and rapid urbanization, cities worldwide face the dual challenge of improving flood resilience and providing accessible green space within limited land resources. Sponge City parks offer a landscape-based approach for integrating stormwater management with park services. However, how park morphology structures this combined performance remains insufficiently understood. This study examines 26 Sponge City parks in Shanghai and evaluates how node-, line-, and patch-type morphologies are linked to stormwater storage and service provision. Using geospatial analysis, DEM-derived catchment delineation, land-cover interpretation, and statistical analysis, this study compares estimated stormwater storage, storage efficiency, local park availability, and land-cover composition across different park morphologies. The results show that estimated performance of stormwater management and park service provision vary across morphological types, but these differences do not follow a simple node–line–patch hierarchy. Rather, the observed patterns are jointly shaped by park morphology, catchment setting, land-cover allocation, and surrounding urban context. These findings suggest that Sponge City parks should not only be evaluated by total stormwater storage. Their contribution depends on morphology, scale, catchment setting, land-cover allocation, and urban context. The study provides a morphology–performance perspective to support more differentiated planning of multifunctional green infrastructure. Full article

Worldwide, flash floods are among the most unpredictable and hazardous hydrological phenomena, particularly in arid and semi-arid regions such as the Kingdom of Saudi Arabia, where sudden heavy rainfall follows prolonged periods of drought. This work presents an effective integrated model for flood hazard evaluation in the Hanefah Catchment, a socioeconomically vital area in the central part of Saudi Arabia that includes the capital city, Riyadh. Using high-resolution ALOS PALSAR 12.5 m Digital Elevation Model spatial data, we extracted and investigated indicative linear, areal, and relief morphometric keys of 64 sub-catchments. This paper employs a dual-method concept that integrates a multi-criteria ranking method and the El-Shamy approach in conjunction with morphotectonic analysis to model flood-susceptibility zones. Furthermore, this paper suggests a comparative assessment of low-cost morphometric models under data-scarce conditions, assessing the multi-criteria ranking method against El-Shamy’s approach, using the topographic position index (TPI) as an internal terrain scale benchmark. The ranking method successfully assigned 85.7% of the historically recorded flood locations to the high-hazard zone that covers ~24.22% of the Hanefah catchment. In contrast, the El-Shamy approach systematically underestimated flood susceptibility because regional tectonic activity increases bifurcation ratios, resulting in just ~42.9% of the historical floods being assigned to the high-hazard zone. The final results highlight the northern and northwestern parts of the catchment as high-hazard zones, characterized by high drainage density and steep relief. This study provides a refined, cost-effective model that aligns with the strategic objectives of Saudi Vision 2030 for sustainable water resources management and significant urban development. Full article

As the development and utilization of underground spaces in coastal cities receive growing emphasis and continue to expand, the secondary disasters of underground flooding triggered by storm surges have become increasingly frequent in recent years. Consequently, the need for emergency evacuation in these spaces has grown more urgent, making the challenge of safe evacuation increasingly critical. However, the classical social force model shows notable limitations in simulating such scenarios, particularly in its lack of characterization of hydrodynamic resistance, heterogeneous pedestrian mobility, and organized guidance mechanisms. Therefore, this paper proposes an improved social force model for more realistically simulating the microscopic dynamics of pedestrians in underground floodwater environments. By extending the classical model, a flood resistance force term is introduced. Furthermore, the model comprehensively considers the varying speeds of pedestrians with heterogeneous attributes—such as age, height, and gender—under different water depths, quantifying the impact of the flood environment on pedestrian mobility. Simultaneously, a leader–follower guidance mechanism is integrated to simulate the influence of organized command behavior on group movement. Simulation experiments in typical underground flood scenarios were conducted to validate the proposed model. Simulation results indicate that flood resistance significantly reduces evacuation efficiency, and heterogeneous pedestrian factors such as age distribution also have a considerable impact. The quantitative findings are as follows: flood resistance increased total evacuation time by 9.3% (from 37.5 to 41.0 s) and decreased the average evacuation rate by 8.6%; similarly, raising the proportion of elderly pedestrians from 20% to 30% prolonged total evacuation time by 9.4% and reduced the average evacuation rate by 8.6%. These outcomes verify the effectiveness of the improved model in characterizing heterogeneous pedestrian behavior in underground flooding scenarios. This study provides a more refined theoretical model and simulation tool to support the development of emergency evacuation plans for underground spaces during floods. Full article

To reveal the overtopping dam-break mechanism under extreme rainfall conditions and assess downstream flood risk, a series of dam-break flume tests, flood routing simulations and inundation risk assessments were conducted. Using the Hubuling Reservoir in Rizhao City, Shandong Province as a case study, a circulating extreme rainfall dam-break flume system with a controllable reservoir water level was constructed at a geometric similarity scale of 1:70. Four test conditions were designed: no rainfall and 50-year, 100-year and 2000-year rainfall return periods. Pore water pressure, earth pressure and water content sensors were embedded in critical dam sections to monitor real-time internal dynamic responses. The results show that, due to the combined effect of the highest rainfall intensity, rapid reservoir water-level rise, progressive infiltration-induced weakening and concentrated surface erosion, a dam-break occurs only under the 2000-year rainfall return period. The failure process is divided into four stages: initial infiltration, slope surface scour, overtopping initiation and rapid breach development. Based on dam-break parameters obtained by physical model tests, a two-dimensional numerical using HEC-RAS was conducted. The results show that, under the 2000-year rainfall return period, the flood reaches the downstream area at 80 min after dam failure. The maximum inundation area reaches 15.20 km² at 200 min, with a maximum inundation depth of 11.80 m and a maximum inundation duration of 144 h. By integrating the maximum inundation depth, inundation duration and land use conditions, the expected economic loss is estimated to be 690 million yuan. The results provide important support for dam-break early warnings, emergency management and disaster mitigation of similar small- and medium-sized reservoirs. Full article

Multisource remote sensing data is utilised for the purpose of monitoring annual and interannual changes associated with climate change in the water bodies of the Chotts of Merouane and Melrhir, which are located in the Zone of Chotts in North Africa. These endorheic depressions are distinguished by recurrent flooding events of varying magnitude and frequency, which are contingent on fluctuations in climate parameters. It has been determined that certain cities located within the surrounding watersheds, such as Biskra, are subject to the intermittent threat of severe flooding. This has been shown to result in land degradation and soil salinisation during the drying-up process. A detailed examination of chronological data from the 1960s onwards reveals a decline in the frequency of flooding in Chott Melrhir in recent years. It is noteworthy that the region has not experienced any substantial flooding since 2020. This phenomenon is concomitant with the marked decline in precipitation levels observed in the region. Since 1980, there have been at least ten significant floods, resulting in varying degrees of damage and disruption. In contrast, Chott Merouane exhibits a more consistent hydrological pattern, with water flowing almost year-round due to wastewater and the drainage of the palm groves by the Oued Righ. Until the 1970s, the occurrence of flooding in the region was exclusively attributable to the direct overflow of the Biskra River and its tributaries. However, from the 1980s onwards, a new type of flooding emerged, linked to insufficient infiltration and drainage capacity in the soil and sewage systems during rainfall that was sometimes considered normal. The hydrological regime in the area has severe ramifications for the water supply and the state of the oases, which are vulnerable to salinisation. Full article

The escalating frequency and intensity of extreme rainfall events driven by climate change threaten infrastructure resilience and societal safety, underscoring the urgent need for robust models to predict these events. Previous studies on the integration of Extreme Value Theory (EVT) and machine learning in modelling extreme rainfall events have not explored the use of a time-varying threshold. This study introduces a novel time-varying threshold Generalised Pareto (GP) regression tree for modelling extreme rainfall in Durban, South Africa. The proposed hybrid model combines EVT with covariate-driven regression tree partitioning, allowing the threshold to evolve dynamically with meteorological conditions. Using daily rainfall and meteorological covariate data from 1981 to 2025, the model was developed, pruned, and benchmarked against a static-threshold GP regression tree and a time-varying threshold Generalised Pareto Distribution (GPD). Evaluation based on the Bayesian Information Criterion (BIC) and log-likelihood demonstrated the superior performance of the proposed model in capturing covariate-driven heterogeneity and temporal variability of rainfall extremes. Four distinct climatic regimes with different tail behaviours and return levels were identified. This study provides the first meteorological application of a time-varying threshold GP regression tree and offers practical insights into flood risk assessment and climate resilience planning in the city of Durban. Full article

Urban areas are increasingly vulnerable to climate-related stresses such as heatwaves, flooding, and resource inefficiencies, requiring integrated, data-driven strategies to enhance resilience and sustainability. This study presents a modular assessment and planning framework that combines Geographic Information Systems (GIS), Building Information Modeling (BIM), City Information Modeling (CIM), microclimate simulations (ENVI-met, SWMM), Life Cycle Assessment (LCA), and remote sensing within a unified decision support interface (DSI). The framework operates across multiple spatial scales—from individual buildings to entire cities—to assess climate vulnerability, support evidence-based urban regeneration, and inform sustainable renovation strategies. It enables the identification of multifunctional interventions that reduce climate risks while improving energy efficiency, resource management, and environmental quality. Urban areas are classified based on their exposure and sensitivity to climate stressors, providing a systematic basis for prioritizing adaptation and mitigation measures. The approach is validated through a case study in Daegu, Republic of Korea, a city facing an aging building stock and increasing climatic pressures. The framework is presented as a conceptual design operating at Technology Readiness Level (TRL) 3–4, indicating that it has passed its proof-of-concept, with key components including ENVI-met microclimate simulations and Sentinel-2/Landsat remote sensing processing demonstrably operational for the Daegu context. Illustrative performance benchmarks drawn from the peer-reviewed literature demonstrate that framework-guided interventions can achieve urban heat island reductions of 1.5–4.0 °C via green roof and reflective surface combinations; stormwater runoff reductions of 30–60% through sustainable urban drainage systems; and building energy savings of 25–45 kWh/m²/yr from deep façade renovation. Its modular and transferable design ensures applicability across diverse urban contexts with similar climatic and infrastructural challenges. Full article

Urbanization and climate change are increasing pluvial flooding risks, thereby intensifying the need for more adaptive stormwater governance in Chinese Sponge City projects. Although public participation is widely recognized as important, current research frequently conceptualizes it as a simplified or static attribute and seldom provides explicit criteria for identifying representative projects in large urban portfolios. This study develops a life cycle-sensitive framework for evaluating public participation in Sponge City projects by conducting a cross-city comparison in China. The study integrates project inventory construction, evidence-based representative project selection, and a multidimensional participation measurement tool covering breadth, depth, identity, and potential across planning, design, construction, and maintenance using five national pilot cities: Jinan, Shanghai, Xiamen, Shenzhen, and Wuhan. The results show that the five representative projects display distinct life cycle participation profiles, rather than a single participation pattern, influenced by project type and governance arrangement. Maintenance emerges as the strongest documented stage, whereas design is the weakest, suggesting stronger documented governance continuity after project delivery than in front-end co-design. Recurrent weaknesses remain in substantive inclusion and feedback-adoption closure. Overall, the study frames participation as a structured governance capability, providing an auditable comparative framework for identifying participation strengths and weaknesses in Sponge City governance. Full article

Urban forests and green spaces provide important ecosystem services that support climate adaptation, public health, and urban sustainability. Despite growing evidence from individual Portuguese cities, nationwide data on how citizens perceive, use, and support the governance of urban green spaces remain limited. This study addresses that gap through a nationwide online survey conducted in Portugal in 2024, gathering 927 valid responses from Portuguese adults across metropolitan, intermediate-density, and low-density municipalities, to investigate public perceptions of ecosystem services, patterns of green space use, management challenges, and attitudes toward urban forestry governance policies. Results revealed strongly positive perceptions of urban trees and green spaces across all sociodemographic groups, with over 95% of respondents acknowledging that urban green spaces positively influence physical and mental health. Regulating services, including air quality improvement, urban noise reduction, climate change mitigation, and flood mitigation, received the highest levels of agreement, while cultural ecosystem services were positively perceived but with comparatively lower agreement. Accessibility emerged as a critical determinant of visitation frequency: 85% of respondents could reach a green space within 15 min, and 82% of daily users lived within 300 m of one, broadly consistent with the 3 + 30 + 300 principle. Frequent visitation was primarily associated with relaxation, physical activity, and social interaction. Conversely, only 6% considered that trees cause more damage than benefits, with pavement damage and superficial roots cited as the more significant management challenges. Support for public investment was broad, with over 90% of respondents favouring allocating municipal tax revenues to urban tree management. However, 68% remained unfamiliar with Law No. 59/2021, revealing a gap between public support and policy awareness. These findings establish a national baseline to support municipalities in developing more resilient, inclusive, and health-promoting urban environments in the face of climate change, as they align urban forestry practices with citizens’ expectations. Full article

In recent years, multi-criteria group decision-making (MCGDM) methods have attracted widespread attention in the academic community. However, most existing MCGDM approaches suffer from limitations in decision-makers’ expressive capacity and the loss of uncertain information. To address these issues, this study proposes a novel multi-criteria group decision-making (MCGDM) framework. First, we developed an evaluation information representation method called the hybrid probabilistic information set (HPIS), which allows DMs to fully express their opinions based on individual cognition using the most suitable form of representation. Second, the criteria importance through inter-criteria correlation (CRITIC) and the combined compromise solution (CoCoSo) methods are extended into the cloud model environment, ensuring that the rich uncertainty information is fully preserved and transmitted throughout the entire evaluation process. Finally, we apply the proposed MCGDM framework to a practical case study evaluating urban flood resilience within an urban agglomeration, to identify its vulnerable components. The results indicate that Baoding, Zhangjiakou, and Chengde are identified as the most vulnerable cities, necessitating immediate and targeted measures to bolster their flood defense capabilities. At the same time, decision-makers can select both qualitative and quantitative comments simultaneously and carry uncertainty information throughout the entire calculation process. Furthermore, the sensitivity and comparative analyses demonstrate the robustness and practical utility of the proposed method under the tested scenarios. Full article

Amid rapid urbanisation and the associated environmental challenges, such as increased flood risk, the urban heat island effect, and ecosystem degradation, Blue–Green Infrastructure (BGI) has emerged as a vital sustainable development strategy. Some countries have successfully implemented BGI projects, shaped by their unique geographical conditions, socioeconomic contexts, and governance structures. Although the BGI concept is highly relevant worldwide, strategies for integrating BGI into urban environments vary significantly across regions and countries due to their distinct urban structures and spatial planning systems. This study provides a comparative study of BGI implementation into spatial planning systems of Ljubljana (Slovenia) and Kraków (Poland), as Central European cities, and Shanghai and Guangzhou, as Chinese cities. Through a systematic analysis of semi-structured interviews with key stakeholders, the study evaluates how different enablers, i.e., (1) guidelines, strategies, and actions, (2) land-use strategy for BGI, and (3) potential of factors for BGI implementation, including planning scale, financial, technical, and spatial, facilitate BGI implementation. This comparative study reveals contrasting yet complementary BGI paradigms, most notably related to top-down versus bottom-up implementation and different prioritisation of BGI functions. These varying paradigms are shaped by specific urban challenges, governance, and spatial planning systems. Full article

Natural hazards and their negative impacts on assets are increasing because of a variety of causes, including climate change, population expansion, and urbanization. Moreover, several areas are susceptible to multiple hazards that interact spatially and/or temporally, necessitating a multi-hazard assessment to adequately mitigate their effects. The goal of this study is to investigate the direct monetary losses produced by the simultaneous interaction of two independent hazards in Lisbon’s city centre, i.e., earthquake and pluvial flood. Seismic hazard has been assessed in terms of macro-seismic intensity, while flood scenario allows for the prediction of water depth for different return periods through a hydrologic-hydraulic model in HEC-RAS software. The seismic and flood vulnerability of the urban investigated compound was evaluated through MCDM methodology—specifically, AHP and TOPSIS methods. A framework for multi-hazard analysis was subsequently developed, explicitly accounting for the interaction between the two hazards and their joint occurrence probabilities based on historical data from the case study area. The results demonstrate that multi-hazard losses are 108 M€ for a 2-year return period and 232 M€ for a 475/500-year scenario, emphasizing that floods contribute more across all return periods in the research area; however, for longer return periods, the earthquake contribution increases significantly. Full article