Potential themes include:
-Multi-hazard profiles of urban centres: compiling case studies and theoretical evidence for potential hazard interrelationships at the city scale
-Smart sensing and digital twins: exploring the use of AI, crowd-sourced data and big data to understand urban risk dynamics
-Urban expansion and adaptation: understanding how both formal and informal growth of cities interact with the urban hazardscape
-Policy, governance and management aspects of urban risk and resilience
-Early warning systems and anticipatory action: methods to combine local knowledge and predictive capabilities to issue effective early warnings in cities
We welcome interdisciplinary approaches, including:
-Case studies
-Modelling
-Empirical data collection and monitoring
-Inclusive methods such as stakeholder engagement, citizen science and participatory approaches
-Innovative methods in AI and machine learning
-Frameworks and tools for measuring risk and resilience
This session provides an interdisciplinary forum for researchers, policy-makers, and practitioners to share cutting-edge research and practical insights, highlighting diverse approaches to understanding and reducing urban risk.
Orals: Thu, 7 May, 14:00–18:00 | Room D2
Landslides in urban areas inhabited by socioeconomically vulnerable populations frequently result in high-magnitude disasters. In such settings, landslide hazard and social vulnerability are intrinsically coupled. Informal settlements (favelas), widespread in the Global South and often established on hillslopes, exemplify this condition due to unplanned occupation and persistent deficiencies in public services and infrastructure. In these contexts, risk reduction strategies must go beyond interventions exclusively focused on slope stabilization.
This paper presents and discusses a participatory project developed in 2023 in an informal settlement in Rio de Janeiro, Brazil, aimed at integrating landslide risk reduction with urban upgrading as a pathway to strengthening urban resilience. The project adopted an interdisciplinary and intersectoral approach, combining architecture and urban planning, sociology, and geotechnical engineering, with the active involvement of researchers and students from the Federal University of Rio de Janeiro, local civil society organizations, and municipal government agencies. Consistent with the principles of the Sendai Framework for Disaster Risk Reduction, local residents actively participated in defining the intervention area, conducting a socio-environmental diagnosis, and co-developing improvement proposals.
The study area, Travessa Laurinda, comprises more than 100 dwellings and is characterized by steep slopes (≈35°), intensely fractured weathered rock outcropping or underlying a thin soil layer, influenced by groundwater flow with spring points, strong anthropogenic modification related to housing construction, and past landslides.
The project began with a participatory socio-environmental diagnosis based on interviews with residents (62 households), local organizations, and consultations with municipal agencies related to geology, solid waste management and environmental issues. This process enabled the identification of physical and social vulnerabilities, local capacities, priority demands, and risk perception patterns. Urban intervention concepts initially proposed by the academic team were discussed and refined through dialogue with residents, reinforcing co-production of knowledge and solutions.
Results indicate that residents’ main demands are closely linked to landslide risk drivers, including inadequate sewage and drainage systems, waste disposal, lack of vegetation, and the absence of slope stabilization measures. Accessibility emerged as the most critical issue, recognized as a key factor for emergency evacuation, disaster response, and everyday urban resilience. The participatory process also supported the development of thematic maps, including the integration of residents’ perceived landslide hazard levels with the presence of structural cracks in dwellings, contributing to the identification of critical risk areas by municipal authorities.
Based on the diagnosis, an integrated project for structural urban improvement measures was proposed, combining risk reduction measures such as surface and subsurface drainage, solid waste management, stairway construction, and access paving. The outcomes were consolidated into a “Participatory and Propositive Socio-environmental Diagnosis” and an “Urban Proposals Booklet for Travessa Laurinda,” delivered to local organizations as an advocacy tool to support the implementation of collectively defined actions. The experience highlights the role of participatory, place-based approaches in addressing urban risk dynamics and enhancing resilience in rapidly changing cities. After the success of this experiment, the work continues, focusing on a different area of the favela each year.
How to cite: Mendonça, M. B., Carvalho, S. A., and Pinheiro, A. B.: Participatory Urban Upgrading as a Pathway to Landslide Risk Reduction in Informal Settlements: A Case Study from Rio de Janeiro, Brazil, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4260, https://doi.org/10.5194/egusphere-egu26-4260, 2026.
Rapid urbanization and climate change jointly shape future flood exposure in coastal cities, particularly in the Global South, where urban growth rates are high and adaptive capacity is often constrained. While scenario-based frameworks such as the Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) provide consistent narratives of socioeconomic and climatic change, their integration into spatially explicit urban growth modelling and flood exposure analysis remains limited.
This study applies the SLEUTH urban growth model to project high-resolution (30 m) urban expansion trajectories up to 2050 for nine coastal urban agglomerations across Africa, Asia, and Latin America under SSP1, SSP2, and SSP5. SSP-based urban population projections were translated into scenario-specific SLEUTH parameters, enabling consistent representation of divergent socioeconomic pathways. Model calibration was supported by harmonized historical settlement data from the World Settlement Footprint and enhanced through a kernel density–based zonation and spatial tiling approach to capture heterogeneous urban–rural growth dynamics across large study areas. Projected urban extents were overlaid with RCP-based coastal, fluvial, and pluvial flood hazard maps to assess future flood exposure at the 50th and 83rd percentiles for a 100-year return period.
Results reveal pronounced inter-city and inter-scenario variability in both urban expansion and flood exposure. Four cities (Dar es Salaam, Ho Chi Minh City, Khulna, and Surat) are projected to expand by more than 50% by 2050 under SSP1 and SSP5. Flood exposure is driven by the combined effects of climate forcing and urban development patterns: high radiative forcing scenarios amplify hazard extent, while socioeconomic pathways strongly influence where and how cities expand into flood-prone areas [1]. In several cities, newly developed urban areas exhibit disproportionately higher exposure than existing settlements, particularly for fluvial and pluvial flooding. However, exposure patterns are highly city-specific, underscoring the limitations of generalized assumptions.
The findings demonstrate that future urban flood exposure cannot be explained by climate change alone, but emerges from the interaction between climate scenarios and socioeconomic pathways shaping urban growth. By combining SSP/RCP frameworks with spatially explicit urban growth modelling across multiple cities, this study provides comparative insights relevant for scenario-based urban planning and flood risk management in rapidly urbanizing coastal regions of the Global South.
[1] Bachofer, F., Wang, Z., Huth, J., Eisfelder, C., Reimuth, A., & Kuenzer, C. (2026). Urban growth prediction along Shared Socioeconomic Pathways (SSPs) for future flood exposure risk assessment: a cross-continental analysis of coastal cities. Anthropocene Coasts, 9(1). https://doi.org/10.1007/s44218-025-00109-6
How to cite: Bachofer, F., Reimuth, A., Huth, J., Eisfelder, C., and Künzer, C.: Modelling Future Urban Flood Exposure: The Combined Role of Socioeconomic Pathways and Climate Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19127, https://doi.org/10.5194/egusphere-egu26-19127, 2026.
Urban ground subsidence represents a growing natural hazard in densely populated cities, driven by aging underground infrastructure, intensive land use, and increasing hydro-meteorological extremes. Ground Penetrating Radar (GPR) surveys are widely adopted as a preventive tool for detecting subsurface cavities beneath roadways. However, despite their widespread use, the absence of standardized performance criteria for GPR equipment has limited the consistency and comparability of survey outcomes across different urban contexts. This lack of technical standardization constrains the effective integration of subsurface survey results into preventive subsidence risk management and public decision-making processes.
This study proposes a performance-based technical framework for standardizing GPR systems used in urban road cavity detection, with the explicit aim of enhancing preventive subsidence risk management. The framework follows a three-step approach integrating hazard analysis, physical detectability, and governance relevance. First, a forensic analysis of 14 major sinkhole incidents that occurred in South Korean metropolitan areas between 2022 and 2024 was conducted to define a target cavity size associated with significant public safety risk. These observations were combined with established overburden depth–to–cavity size relationships to derive a risk-informed detection threshold, focusing on early-stage hazard identification rather than post-collapse response.
Second, minimum technical requirements for GPR systems were derived to ensure the reliable detection of target cavities under typical urban road conditions. Key parameters include center frequency thresholds based on horizontal resolution theory, operational survey speed limits required to maintain sufficient spatial sampling density, and multi-channel system configurations to ensure survey coverage and positional reproducibility. Emphasis is placed on performance outcomes relevant to hazard prevention rather than on manufacturer-specific specifications.
Third, the proposed framework was evaluated through benchmarking against international technical guidelines for near-surface geophysical investigations. This comparison demonstrates that the proposed standards are broadly consistent with global practices while explicitly addressing urban-specific constraints such as traffic conditions, spatial re-identification requirements for follow-up investigations, and administrative usability of survey outputs.
By translating physical detection capability into risk-relevant performance metrics, this framework provides a common technical reference for public agencies, survey operators, and urban risk managers. The proposed standard supports the integration of subsurface survey data into preventive urban hazard governance and contributes to strengthening the resilience of cities against ground subsidence hazards.
How to cite: hwang, S., hur, C., kim, H., and lee, S.: A GPR Performance Standardization Framework for Mitigation Urban Road Subsidence Risk, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15912, https://doi.org/10.5194/egusphere-egu26-15912, 2026.
Landslides are among the deadliest natural hazards. Their impact is the highest in urban areas, where human exposure peaks. However, in addition to increasing exposure, multiple human-induced landscape alterations may also increase the probability of landslide occurrence. Hence, when we consider landslide risk in urban areas, not only does elevated exposure increase risk, but the exposed elements may also alter the frequency and intensity of the hazard.
This relationship between exposure and hazard has already been demonstrated in physics-based hazard models that explore landslide potential in informal neighbourhoods. There is also ample evidence of landslides along intercity roads, linking hillslope modification to landslide occurrences. However, the number of observations is limited in urban areas. Here, we discuss the Granizal Landslide that occurred in June 2025, killing 27 people in the Metropolitan Area of the Aburrá Valley, Colombia. The rainfall-induced Granizal Landslide occurred in the steepest section of the urban zone, as could be expected. However, the landslide’s source area coincides with a road and a potentially malfunctioning sewage system, indicating that the exposed elements may have contributed to the landslide[1].
The Granizal Landslide is alarming, as such incidents may increase as climate change intensifies. Especially in the tropical urban centres, more extreme rainfall events may overburden water infrastructure, not only informal infrastructure but also infrastructure that complies with the design standards. The statistical thresholds used to design the infrastructure may become inadequate due to shifts in rainfall patterns. Hence, we could broadly argue that climate change may be eroding the knowledge base that we used to design infrastructure. Perhaps not in the Aburrá Valley, but in other places we have already observed landslides in locations with little or no prior experience and risk awareness. This poses an additional risk due to the lack of knowledge among the newly exposed population about effective behavioural responses[2].
[1] Ozturk, U., Braun, A., Gómez-Zapata, J. C., and Aristizábal, E.: Urban poor are the most endangered by socio-natural hazards, but not exclusively: the 2025 Granizal Landslide case, Landslides, https://doi.org/10.1007/s10346-025-02680-y, 2025.
[2] Bubeck, P., Ozturk, U., Aristizabal, E., Thieken, A. H., and Wagener, T.: Mortality reduction despite changing climate extremes requires better understanding of human behavioral response to warnings, Environmental Research Letters, 20, 101004, https://doi.org/10.1088/1748-9326/ae034f, 2025.
How to cite: Ozturk, U., Bubeck, P., Braun, A., Gómez‑Zapata, J. C., and Aristizábal, E.: Climate Stress, Infrastructure Limits, and Urban Landslide Risk, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3841, https://doi.org/10.5194/egusphere-egu26-3841, 2026.
Hydrogeological risk is a persistent and intricate global concern, particularly in Italy, where hydro-geomorphological disasters have inflicted substantial damage upon infrastructure and urban areas, and in severe instances, resulted in human fatalities. While climate change is widely recognized as a key driver of the frequency, intensity, and duration of these events, the magnitude of their impacts also depends on a wide range of environmental and anthropogenic factors. This study investigates the drivers that shape the spatial extent and temporal persistence of hydro-geomorphological disasters. The analysis draws on the Italian Civil Protection database of emergency states, which was reprocessed to derive, for each province and for the period 2013–2024, two key indicators: the cumulative number of emergency states (CES) and their duration in months (MES). These variables provide insight into the recurrence and persistence of hydro-geomorphological impacts. Spatial analysis shows that the distribution of these indicators, especially duration, is non-random and displays clear spatial patterns. To explore the determinants of these patterns, the indicators were incorporated into a model assessing correlations with a set of environmental and anthropogenic variables. Two publicly available datasets were used, from which roughly sixty variables were selected after filtering. For each model iteration, four statistical parameters were computed to evaluate the strength of the correlations. The results reveal a strong positive correlation between soil sealing in areas classified as having intermediate hydrogeological risk and the temporal persistence of disaster impacts. A further temporal analysis indicates that soil sealing in these areas is still increasing by about 1% per year. These findings highlight the critical role of land use and urbanization processes in amplifying the effects of hydrogeological hazards and underscore the need for more effective planning and territorial management strategies to mitigate future risks.
How to cite: Gatto, A., Clo', S., Martellozzo, F., Ciulla, L., and Segoni, S.: Interplay between soil sealing and hydrogeological disaster impacts in Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7519, https://doi.org/10.5194/egusphere-egu26-7519, 2026.
Exposure is a key aspect of the risk assessment framework. If we know the assets and people that are exposed to hazards, we can better estimate damage and losses in case of a disaster. Recently, building footprint datasets such as OpenBuildingMap have become available, that enable the quantification of exposure on a high resolution. While such datasets are nearing a global footprint coverage, the completeness of semantic information related to the buildings, such as occupancy type, is lower.
Machine Learning (ML) methods can be used to infer semantic information about buildings. Typically, a remote sensing approach is taken, where image-based ML techniques are used on satellite imagery. Such techniques require high-resolution imagery for good results, that are not widely openly available, and use a high amount of computing resources when covering large areas.
Rather than satellite imagery, we have used morphometrics to predict building information. Morphometrics are quantitative features that explain the structure of the built environment. They are calculated using solely building footprints and the street network; both are commonly available. The morphometrics exist on three building scales: the individual building (e.g. footprint size); the building plot (e.g. distance between neighboring buildings); and building block (e.g. building footprint coverage compared to the area of the block). There are also morphometrics related to the street network (e.g. network density). As each feature is a single value, the dimensionality of the feature space is much lower than for image-based methods, reducing the need for computing power. Using this method, we can predict building properties like its height, occupancy type and construction year.
This approach fills information gaps in existing building footprint datasets and can be integrated into high-resolution exposure modeling efforts like the Global Dynamic Exposure Model. It allows for the augmentation of heterogeneous building exposure in data-scarce regions where other methods, such as crowd-sourcing are not available. It can substantially reduce the otherwise high uncertainties in exposure modeling. Consequently, it supports decision-making at local, regional, and national levels, where authorities in civil protection must act despite incomplete or uncertain information.
How to cite: Oostwegel, L. J. N., Schorlemmer, D., Çalliku, D., Evaz Zadeh, T., Lingner, L., de la Mora, P., Nie, W., Rafiezadeh Shahi, K., Rao, C., and Guéguen, P.: Explaining building exposure using urban morphology and AI, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10682, https://doi.org/10.5194/egusphere-egu26-10682, 2026.
How to cite: Limones, N., Serrano-Acebedo, P., Sánchez-Rodríguez, E., García-Martínez, B., Aguilar-Alba, M., and Ojeda-Zújar, J.: Swimming pools as dual urban infrastructures: water resources pressure and heat-risk modulation under climate change in a Mediterranean context, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15127, https://doi.org/10.5194/egusphere-egu26-15127, 2026.
Cities significantly affect tropical cyclone (TC)-induced rainfall through land–atmosphere interactions. While extensive modeling analyses have demonstrated that urban land surface produces more TC rainfall over cities, direct observational evidence across multiple cities remains limited, particularly in inland areas where the risks of TC-induced extreme flooding are increasing. Here, using the high spatio-temporal resolution Stage IV gridded rainfall product, we analyze TC rainfall distributions associated with 84 landfalling TCs over 112 cities in the Contiguous United States. Our analyses revealed that in over 88% of cities, intense TC rainfall occurs predominantly outside urban cores, primarily in the left-side suburban regions relative to the dominant wind within urban boundary layer. This distinct spatial pattern emerged as a robust feature across diverse urban geographic settings. However, the preferred location of urban rainfall anomalies in suburbs varies with the urban geographic setting, owing to difference in urban dynamic turbulence conditions (such as, horizontal wind and vertical velocity). Enhanced TC rainfall tends to occur upwind areas in simple and mountainous cities but downwind areas in coastal cities. Further, we reconstructed three-dimensional TC wind fields for representative cities using radar data. We find that increased urban surface roughness weakens tangential winds and strengthens radial inflow, thereby enhancing convergence and rainfall in the left quadrants of urban core region. This urban influence tends to weaken, along with larger mean rainfall and lower spatial variability under strong ambient wind. These findings highlight an urgent need for risk management and spatial planning strategies that explicitly target vulnerable peri-urban regions, and call for the integration of aerodynamic principles into risk and urban planning frameworks to enhance resilience in future cities.
How to cite: Shen, Y., Huang, H., and Yang, L.: Under the shadow: urbanization displaces tropical cyclone rainfall to the peri-urban regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8724, https://doi.org/10.5194/egusphere-egu26-8724, 2026.
Environmental risk assessments require spatially explicit information on how people and assets are concentrated within the built environment. However, exposure metrics based solely on 2D building footprints or population grids fail to capture the vertical dimension that strongly influences heat exposure, air‑pollution accumulation, flood impacts, and infrastructure vulnerability. Leveraging the newly released Global Building Atlas (GBA)—a harmonized and globally consistent dataset of building footprints and height estimates, and currently the most comprehensive source of building information available—we introduce a global Building Density Index (BDI) that integrates key building parameters, including footprint area, building volume, height and distances, to quantify built‑up intensity as an indicator of environmental risk hotspots. The consistent global coverage of the GBA enables direct comparison of vertical density patterns across regions.
The BDI reveals pronounced regional contrasts in built‑volume concentration and illustrates how cities balance horizontal expansion, vertical growth, and the availability of land for settlement. Land-scarce regions, particularly in East and Southeast Asia, exhibit strong vertical densification, resulting in extremely high built volume concentrations even where horizontal extent is limited. In contrast, many rapidly expanding cities in Africa and South Asia primarily rely on horizontal expansion, consuming large areas of developable land while maintaining low vertical density. Latin American cities typically achieve high density through compact mid-rise forms, reflecting a distinct interplay between limited land availability and moderate vertical growth.
The BDI substantially improves the identification of zones where heat exposure, air‑pollution susceptibility, and built-up intensity combine to elevate environmental risks. By capturing the three-dimensional structure of the built environment, it offers a more realistic representation of how urban morphology amplifies or moderates these risks. As a globally consistent measure, the BDI provides a robust foundation for examining how land availability, horizontal expansion, and vertical growth interact to shape environmental vulnerability across diverse urban regions.
How to cite: Reimuth, A., Chen, Y., and Zhu, X.: Mapping Global 3D Building Density with the Global Building Atlas: Implications for Environmental Risk Hotspots, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17536, https://doi.org/10.5194/egusphere-egu26-17536, 2026.
Future risk is expected to rapidly increase in coastal urban areas in Southeast Asia. The case of Jakarta (Indonesia) shows intense urban development, land subsidence, and increased risks of floods and storm surges. Climate adaptation seeking to prevent the impacts of these risks has so far been disconnected from urban planning and land use policies, setting the stage for a largely unchecked real estate market and a highly unequal development process that increases exposure and fosters increased climate vulnerability. In our research, we fill this gap by combining the participatory development of metropolitan-scale shared socioeconomic pathway narratives for the Jakarta metropolitan region (also known as Jabodetabek) with cross-analysis of path dependency factors influencing future urban development. From this primarily qualitative research foundation, we then perform semi-quantitative estimation of key development indicators that are input into an agent-based model of urban development to simulate future urban growth scenarios under each SSP. The results include three SSP narratives for the megacity-sized metropolitan region (with ca. 32 million inhabitants) and estimations for indicators that include population growth, urbanisation compactness, economic inequality, informal and precarious work, and informal and precarious settlements. We also present urban growth simulations for 2050 at 150 m resolution that incorporate the differentiation of socioeconomic profiles based on location preferences and real estate market simulation. We then analyse the growth trends versus known patterns of exposure to riverine flood and coastal storm surge and provide an outlook for future risk in the region. The novelty of this approach is threefold. First, we integrate qualitative, semi-quantitative, and simulation methods to generate future scenarios of urban growth. The potential is to lay out a clear framework for similar future-oriented work in data-scarce and highly complex urban environments in the Global South. Second, we provide medium-term socioeconomic pathways along with estimates of key socioeconomic variables, which are helpful for future risk modelling studies in the region, notably those integrating urban development. Finally, we implement an agent-based modelling approach that is flexible and accessible to scholars focusing on megacities in the Global South. Our methods are based on robust previous research and require only open data (e.g., OpenStreetMap, Global Human Settlement Layer, WorldPop, among others) and local export elicitation for their parameters and inputs. Ultimately, we hope our research supports disaster risk reduction and climate adaptation policies in the complex metropolitan regions of the Global South by reducing uncertainties and integrating risk and urban analysis.
How to cite: Pereira Santos, A., Mirbach, C., and Ketut Surtiari, G. A.: Future risk pathways for a Southeast Asian megacity: Coupling socioeconomic scenarios and agent-based modelling to integrate exposure, vulnerability, and hazards in Jakarta (Indonesia), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18575, https://doi.org/10.5194/egusphere-egu26-18575, 2026.
While urbanization is traditionally associated with economic growth and improved food security outcomes, many African countries have urbanized without concurrent economic growth, and, in turn, case studies suggest that as many as 70% of urban households are food insecure. Climate change stands to exacerbate these challenges, with, for example, increased instances of heat waves decreasing urban labor productivity and decreasing the ability of urban residents to purchase food. Despite these concerns, food security research has historically been rural-focused, and little research has systematically assessed how urban food security varies over time compared to rural food security. Indeed, food security is a highly under-researched and under-appreciated emerging urban risk across Africa.
To enhance our understanding of this risk, this study examines national-level differences in childhood food insecurity between urban and rural areas across thirty-six African countries, using child stunting and wasting as indicators of chronic and acute undernutrition. Using Demographic Health Survey (DHS) data from the 1990s through 2020, we aggregate household-level observations to national urban and rural prevalence rates. We assess the influence of climatic, agricultural, economic, and demographic predictors on urban and rural stunting and wasting using a suite of generalized linear models. Preliminary results suggest that rates of rural and urban food insecurity are not only converging over time, but in some instances, urban food insecurity rates are higher than rural insecurity rates. These findings underscore the need for context-specific policies that address the distinct mechanisms driving urban and rural childhood undernutrition in rapidly urbanizing, low-income settings. This can help inform policy-making to respond more appropriately to childhood food insecurity crises across Africa.
How to cite: Concannon, D. and Tuholske, C.: Urban-Rural Disparities and Predictors of Childhood Undernutrition across Africa , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5811, https://doi.org/10.5194/egusphere-egu26-5811, 2026.
Drafting a governance framework for urban resilience is merely the first step; validating its operational feasibility under dynamic disruption is where the real challenge lies. This study addresses the critical gap between policy planning and operational practice within the Taipei City Government (TCG).
First, we constructed a high-granularity Business Continuity Plan (BCP) predicated on a worst-case scenario: a Magnitude 6.6 earthquake along the Shanchiao Fault. Aligned with ISO 22320 and the Sendai Framework, the plan categorizes mission-critical functions into nine operational chapters with prioritized recovery timelines. It incorporates Naismith’s Rule for realistic personnel mobilization and establishes a multi-tier resource reserve system.
To rigorously measure the resilience of these protocols, we implemented the U.S. HSEEP guidelines, aggregating outcomes from 17 diverse tabletop exercises (TTX) conducted across Taipei (2024-2025). This comprehensive dataset includes six critical sessions focused on compounding disruptors: acute manpower shortages and communication blackouts.
Addressing the limitation of subjective feedback in traditional governance assessments, we propose a novel quantitative framework. We integrated semantic text mining (SentenceTransformer) with Self-Organizing Maps (SOM) to process 636 unstructured feedback entries. This data was projected onto a topological map, distilling complex responses into quantifiable spatial clusters.
The AI-driven analysis revealed a critical divergence: while the BCP policy emphasized physical redundancies (multi-site backups), the neural network identified "Information Systems and Tools" as the dominant bottleneck in the cognitive map of participants. This finding highlights a hidden vulnerability in inter-agency data integration that traditional reporting missed. By coupling rigorous BCP formulation with unsupervised machine learning, this research offers a reproducible methodology for transforming subjective observations into objective, actionable data for urban risk governance.
How to cite: Pan, T.-Y., Chen, L.-Y., Wang, J.-T., and Cheng, C.-C.: Quantifying the "Planning-Practice Gap" in Urban Resilience: Validating Taipei’s Disaster Governance via HSEEP and Unsupervised Neural Networks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7559, https://doi.org/10.5194/egusphere-egu26-7559, 2026.
Municipalities face increasing challenges in adapting to climate change while operating under limited financial and human resources. Climate impacts such as heat stress, pluvial flooding or low water levels affect multiple urban sectors simultaneously and interact with existing planning goals, responsibilities and socio-economic priorities. This complexity creates a strong need for integrated, transparent and comparable information that can support evidence-based prioritisation of adaptation measures across departments and policy fields.
Within the research project R2K-Klim+, the web-based, GIS-supported decision support system KLAUS (KLimaAnpassung Urbaner Systeme) has been developed and implemented in close cooperation with Duisburg in Germany. KLAUS is integrated into the municipal geodata infrastructure and bundles decision-relevant information in a map-based environment. It combines spatial assessments of climate signals with an evaluation of vulnerabilities and potential effects of adaptation measures, making heterogeneous information accessible in a way easier to understand.
A core component of KLAUS is a dedicated assessment methodology that translates climate impacts such as heat and flooding into transparent and comparable indicators. These indicators reflect both physical exposure and social vulnerability, enabling the identification of areas where negative climate effects accumulate and where adaptation measures can generate the greatest benefit. The system is designed as a cross-sectoral tool that supports transdisciplinary use by different municipal actors from urban planning, water management, environmental protection and public health.
The presentation demonstrates the practical application of KLAUS using screenshots from the web service and concrete municipal use cases from Duisburg. Examples include the identification of suitable locations for new drinking water wells considering climate impacts and vulnerable population groups, the spatial identification of deficit areas as a basis for targeted funding measures, and the use of pluvial flood simulations to support settlement drainage planning. These use cases illustrate how scientific assessments can be translated into actionable knowledge for day-to-day municipal decision-making.
The contribution focuses on two questions that are highly relevant for many cities: Where do climate impacts spatially accumulate, and how can they be represented in a way that is understandable and comparable across sectors? How can limited resources be allocated to measures that promise the highest overall benefit? In addition, the presentation discusses key conditions for successful implementation in municipal practice, including compatibility with existing workflows, comprehensibility of visualisations and transparency of the underlying evaluation.
The KLAUS prototype is publicly accessible and currently populated with data for the City of Duisburg. Its modular structure allows transferability and further development for other municipalities and application contexts, contributing to the science–policy–practice interface in climate change adaptation.
How to cite: Braun, M. and Roth, T.: From climate data to municipal decisions: a GIS-based decision support system for prioritising urban adaptation measures, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5651, https://doi.org/10.5194/egusphere-egu26-5651, 2026.
The increasing frequency and intensity of extreme rainfall events highlight the need to advance pluvial flood risk analysis toward more integrated and comprehensive assessment frameworks. While hydraulic modelling is a well-established tool for analysing urban drainage systems, an effective evaluation of urban resilience requires coupling hydraulic behaviour with the characteristics and vulnerability of the built environment.
This study focuses on the Sampierdarena district in the city of Genoa, Italy, an area characterised by high urban density and a documented exposure to multiple natural hazards. The research investigates how pluvial flood risk can be modelled and systematically integrated within a multi-hazard framework that also considers seismic risk, with the aim of supporting urban resilience assessment and planning.
The proposed approach adopts an area-based methodology that enables the comparison and integration of different hazards through a common spatial framework. Multiple vulnerability dimensions, including population exposure and building use, are incorporated to assess the potential impacts associated with each hazard. With specific reference to pluvial flooding, the study employs an open-source modelling framework that couples two-dimensional surface flow simulations with one-dimensional sewer network modelling, allowing a detailed representation of interactions between overland runoff and urban drainage infrastructure.
Pluvial flood simulations were conducted using a synthetic rainfall event with a 10-year return period. The resulting surface water depth maps were subsequently integrated with building-scale vulnerability indicators, enabling a spatially explicit assessment of flood impacts across the study area. This integration facilitates the identification of areas where hydraulic insufficiencies intersect with high levels of exposure or vulnerability, thereby enhancing the interpretability of flood risk results in an urban context.
In contrast, the seismic risk component of the study follows a different methodological approach, primarily focused on the identification and analysis of strategic elements relevant to emergency planning. The present work builds upon this existing seismic assessment by extending the framework to include pluvial flood risk, thereby contributing to a more comprehensive multi-risk perspective.
This approach enables a more robust performance analysis of strategic buildings and the strategic connections defined within the Emergency Plan of Genoa. By intersecting hydraulic vulnerabilities with the urban emergency network, the study represents a significant step forward in defining targeted Civil Protection actions for an area where pluvial flooding constitutes the primary risk, ensuring that strategic accessibility and functionality are preserved during extreme events.
Overall, this research forms part of broader efforts aimed at developing effective decision-support tools for urban risk management. By framing the relationship between hydraulic system performance, building vulnerability, and multi-hazard exposure, the study contributes to advancing integrated methodologies for assessing and enhancing urban resilience. Specifically, the integration of pluvial flood risk into the strategic framework of Genoa’s Emergency Plan provides a practical instrument for Civil Protection authorities to prioritize mitigation measures and optimize emergency response. Ultimately, this work demonstrates how a multi-risk perspective can transform technical hydraulic modelling into actionable knowledge, strengthening the safety and functionality of strategic urban networks under increasing climatic and environmental pressures.
How to cite: Lazzati, M., Acquilino, M., Cattari, S., and Boni, G.: From Hydraulic Simulation to Decision Support: A Multi-Risk Framework for Pluvial Flood and Seismic Risk in Urban Genoa , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15287, https://doi.org/10.5194/egusphere-egu26-15287, 2026.
In recent decades, Venice has experienced increasing frequency of extreme high-tide events, driven by a combination of land subsidence, eustatic sea-level rise, and changes in climatic forces. To mitigate flood risk, an adaptation strategy was implemented in 2019 at the three inlets (Lido, Malamocco, and Chioggia) connecting the Venice Lagoon with the Adriatic Sea: the Mo.S.E. (Modulo Sperimentale Elettromeccanico) storm-surge barrier system. The barriers are activated when the sea level is expected to exceed 1.10 m a.P.S. (“above Punta della Salute”), being the 1.10 value a compromise between effective flood protection and the economic impacts due to the stop of maritime traffic during barrier closure.
Nevertheless, by the time this level is reached, about 12% of Venice is already flooded, including the iconic St. Mark’s Square (ground elevations between 0.60 and 1.10 m a.P.S.). During flooding episodes, surface runoff from the Square is conveyed into the historic drainage network (gàtoli). When high tide conditions also occur, the runoff interacts with the backwater effect within the gàtoli as saltwater rises from the Lagoon. As flooding progresses, water ponds in front of St. Mark's Basilica (0.6 m a.P.S.) and gradually expands to the rest of the Square.
Following the extreme event of 2019, a first intervention (installation of glass barriers to protect the Basilica) was implemented in 2022. However, a more comprehensive series of targeted interventions has been planned since 2020. This holistic approach extends beyond the Basilica, encompassing the entire Square to preserve the integrity of the whole area. During high tide events, the Square will thus be isolated from the Lagoon when the water level exceeds 0.7 m a.P.S. While water entering the gàtoli system through precipitation runoff, lagoon wave overtopping, and subsurface infiltration, is actively managed by the new flood defence system, efficiently conveying and discharging water outside the Square. The multi-faceted strategy includes the permanent sealing of minor gàtoli-lagoon connections and the controlled operation of major ones, as well as localized elevation of the Square's pavement. Additionally, floating breakwaters are installed to limit wave overtopping discharge, while the gàtoli tunnels are restored to enhance their conveyance capacity. A pumping station, whose strategic position allows easy maintenance procedures, ensures the required outlet discharge.
In this study, the hydraulic processes affecting St. Mark’s Square are analysed using InfoWorks ICM (Integrated Catchment Model), which couples a 1D model of the drainage network with a 2D representation of flooding dynamics over the Square. Water inputs (rainfall, groundwater infiltration, and lagoon wave overtopping) are quantified using a combination of theoretical and experimental approaches, and the overall discharge capacity of the Square is evaluated to assess the current performance of the drainage system. Subsequently, the study investigates the effects of various restoration and adaptation scenarios to assess their effectiveness in mitigating flooding under different forcing conditions.
How to cite: Mazzarotto, G. and Salandin, P.: Challenges and Strategies in Urban Adaptation to Climate Risks: The Case of St. Mark's Square (Venice, Italy), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12176, https://doi.org/10.5194/egusphere-egu26-12176, 2026.
Long-term monitoring of post-disaster reconstruction is essential for evaluating recovery processes, improving urban resilience, and reducing future vulnerability in regions and population exposed to recurrent extreme events. This contribution presents a remote sensing framework for assessing reconstruction dynamics using multi-temporal Very High-Resolution (VHR) optical satellite imagery, such as WorldView-2 and WorldView-3. The methodology is designed to provide detailed, building-level reconstruction assessment over multiple years, supporting quantitative analysis and trend evaluation.
The framework that is proposed consists of manual photointerpretation with a structured classification schema to determine the reconstruction status of individual buildings. To enhance efficiency and consistency, the process is supported by AI-detected buildings which act as a foundational layer. Buildings are categorized into classes such as unchanged, removed, under reconstruction, reconstructed, newly built, or not applicable. These classes are presented as photointerpretation keys, that are developed based on observable indicators in VHR imagery, including structural integrity, roofing, facades, presence of construction materials, and signs of ongoing repair. It is widely acceptable that manual photointerpretation is time-consuming. However, for post-disaster monitoring, it is essential to accurately classify buildings, and the AI-supported workflow streamlines the initial building identification.
On top of that, a proper temporal consistency was achieved with image acquisition in a necessary seasonal window across multiple years. In that way, interpretation bias caused by illumination, vegetation phenology, or coastal conditions, are minimized. Temporal analysis is performed by comparing building classifications year by year, allowing the identification of reconstruction progress, new construction, or abandonment. In terms of ambiguous building statuses are detected, multi-date interpretation is applied.
Additionally, a multi-image manageable strategy is described, when uncertainty associated with illumination, cloud cover, atmospheric effects, or visual obstructions is raised. Thus, in cases where persistent cloud cover limits visibility, carefully selected alternative acquisition periods are used to maintain analytical continuity.
To sum up, this framework demonstrates the value of VHR satellite-based, building-level reconstruction monitoring, combining methodological rigor with practical applicability for long-term recovery assessment and hazard-informed planning. Providing transferability and scalability, for long-term monitoring of post-disaster recovery, in which urban planning, resilience evaluation, and disaster risk reduction effort, can be supported.
How to cite: Stasinos, N., Salas, E., Tsoutsos, M.-C., Paroni, K.-A., Pissaridi, K., and Kontoes, C. (.: A multi-temporal Very High-Resolution optical satellite remote sensing framework for post-disaster reconstruction monitoring, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18665, https://doi.org/10.5194/egusphere-egu26-18665, 2026.
Accelerating urbanization and climate change have intensified urban flood risks, rendering underground spaces—critical hubs of modern infrastructure—inherently vulnerable to rapid inundation. Unlike surface flooding, underground inundation is characterized by the funneling effect and high-velocity inflows, often resulting in supercritical flows that cause catastrophic damage. Despite the widespread deployment of physical interventions such as flood barriers and watertight doors, a unified global standard for evaluating their performance remains absent. This study comprehensively reviews the mechanisms of underground flooding and critically analyzes the performance evaluation standards of nations: the USA (ANSI/FM 2510), the UK (BS 851188), Japan (JIS A 4716), and South Korea (KS F 2639).
The comparative analysis reveals that while existing standards possess distinct strengths—ranging from comprehensive reliability verification (USA) and strict water exclusion targets (UK) to practical performance grading systems (Japan)—they predominantly rely on hydrostatic pressure testing. This static approach fails to adequately represent the hydro-complex dynamics of underground flooding, specifically the dynamic surge pressures and debris impacts generated at steep entrances. Furthermore, some regulations exhibit a regulatory lag, failing to reflect the actual hydrodynamic loads (e.g., velocities exceeding 3.0 m/s) or the advanced capabilities of modern technologies.
To address these gaps, this paper proposes an integrated performance evaluation framework tailored to the unique risks of underground spaces. Key recommendations include: (1) a transition from static to Dynamic Hydro-Complex Load scenarios to simulate high-velocity surges; (2) the implementation of a Risk-Based Performance Grading System commensurate with facility criticality; and (3) the mandatory verification of lifecycle durability for equipment. This study provides a theoretical foundation for establishing international standards to enhance urban flood resilience.
Keywords: Underground Flood; Flood Protection Equipment; Performance Evaluation
Acknowledgements: This research was support by a (RS-2025-02218717) of Cooperative Research Method and Safety Management Technology in National Disaster funded by Ministry of Interior and Safety(MOIS, Korea).
How to cite: Lee, E. S., Kim, B. M., and Park, S. M.: A review of Performance Evaluation Methods for Underground Flood Protection Equipment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15202, https://doi.org/10.5194/egusphere-egu26-15202, 2026.
Posters on site: Fri, 8 May, 10:45–12:30 | Hall X3
Constantine is one of Algeria’s major metropolitan centers and is recurrently affected by landslides due to its complex geomorphological context, characterized by steep slopes, deeply incised valleys, and mechanically weak lithological formations. Over recent decades, rapid population growth, land scarcity, and the expansion of informal settlements have significantly intensified exposure to slope instability. Previous studies have largely focused on hazard identification, susceptibility mapping, and engineering mitigation measures, while limited attention has been given to how these risks intersect with social practices, residential choices, and everyday urban life. In response to increasing landslide risk and related urban challenges in Constantine, the new city of Ali Mendjeli was developed as a large-scale resettlement project intended to reduce exposure by relocating vulnerable populations. However, despite the technical rationale behind this intervention, a noticeable proportion of relocated households have gradually returned to risk-prone areas within the historic city. This study addresses this gap by integrating landslide susceptibility assessment with a social-geographical analysis of resettlement outcomes. A landslide susceptibility map for Constantine was produced using Geographic Information Systems, integrating topographic, geological, hydrological, and anthropogenic conditioning factors through an Analytic Hierarchy Process (AHP). This spatial analysis was complemented by qualitative methods, including the review of planning documents, field observations, and semi-structured interviews to examine perceptions of risk, place attachment, and daily spatial practices. The results show that urban saturation and informal housing in Constantine strongly influenced the decision to create Ali Mendjeli as a resettlement site. However, the relocation process was implemented with a primary focus on quantitative housing provision, without adequate consideration of social networks, social attachment to the historic city center, and everyday spatial practices. The regrouping of households by original neighborhoods, combined with limited urban connectivity and weak functional diversity, contributed to early social fragmentation. Consequently, Ali Mendjeli evolved as a socially fragile urban space where pre-existing vulnerabilities were reproduced rather than mitigated, encouraging some residents to return to risk-prone areas. These findings demonstrate the limitations of purely technocratic, hazard-driven resettlement strategies and highlight the need for integrated approaches that align geohazard management with social sustainability, urban cohesion, and long-term resilience.
Keywords: Landslide susceptibility, Urban resettlement, Informal housing, Urban resilience, Social Geography, Urban attachment.
How to cite: Saidi, I., Abdelkader, M., and Czimre, K.: Urban Growth and Geohazards Constraints as Drivers of New City Creation: The Case of Ali Mendjeli and Constantine, Algeria, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13605, https://doi.org/10.5194/egusphere-egu26-13605, 2026.
Urban flooding in rapidly growing cities is undergoing significant changes in both its driving mechanisms and spatial patterns. In many historic cities of South Asia, flooding was traditionally associated with river overflow during the monsoon season. In recent years, however, frequent flood events have been reported in urban areas located far from river channels, indicating an increasing role of rainfall-driven pluvial flooding. This shift is closely linked to rapid urban expansion, increased impervious surface coverage, and the degradation of natural drainage systems. Despite its growing relevance, the transition from riverine to pluvial flooding remains insufficiently documented, particularly in historic cities. This study investigates the evolution of urban flooding under rapid urbanization in Varanasi, a historic city located in the Middle Ganga Plain, India. Urban growth was analyzed using multi-temporal satellite imagery from 2000 to 2025, including Landsat and Sentinel data, to quantify changes in built-up areas and land-surface characteristics. Information on past flood events was compiled from historical records, satellite-derived flood observations, and reported urban flooding locations. Flood events were classified as riverine or pluvial based on their proximity to river channels and local drainage conditions. The spatial distribution of flood events was analyzed over time in relation to urban expansion patterns and distance from the river network. Event-based rainfall data were examined to assess the role of short-duration intense rainfall in recent flooding episodes, while changes in drainage density and land-surface conditions were considered to support the interpretation of flooding mechanisms. The results indicate a clear temporal shift in flooding patterns. Earlier flood events were predominantly concentrated near river corridors, reflecting riverine flooding, whereas recent flood events increasingly occur within newly urbanized areas away from rivers. This shift highlights the growing dominance of pluvial flooding associated with rapid urban expansion, increased impervious surfaces, and reduced drainage efficiency. The findings emphasize the need to move beyond river-focused flood management approaches and to strengthen urban drainage planning, land-use regulation, and climate-resilient urban design. The approach presented here is transferable to other rapidly urbanizing historic cities facing similar flood challenges.
How to cite: Sarkar, S. and Verma, N.: Transition from Riverine to Pluvial Flooding under Rapid Urbanization: Evidence from Varanasi, India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7599, https://doi.org/10.5194/egusphere-egu26-7599, 2026.
Pluvial flood risks and impacts have been extensively studied; however, floods triggered by cloudbursts have received comparatively less attention. Cloudbursts are frequent, short-lived extreme precipitation events that often trigger flash floods. Due to their short duration and highly localized nature, cloudbursts are difficult to detect and monitor. Moreover, the lack of high-resolution data to adequately represent affected areas significantly limits impact assessment.
This study addresses this gap by using high-resolution cloudburst flood hazard data from a Copenhagen cloudburst event as a reference case, which are intersected with detailed building footprints, road network data, and gridded population datasets. Using an impact-based approach, the analysis focuses on the accessibility of critical facilities, such as hospitals and healthcare centers, in Karlstad municipality, Sweden. Network analysis demonstrates that disruptions to the road network caused by flooding can indirectly compromise access to critical facilities, even in the absence of direct flooding at those locations.
The results highlight the need for a deeper understanding of cloudburst-related flooding and its indirect impacts on urban systems and accessibility, emphasizing the importance of impact-based early warning systems and inclusive urban flood adaptation strategies.
How to cite: Chantziara, A.-N. and Karagiorgos, K.: Impact-Based Assessment of Cloudburst Flooding on Access to Critical Infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8297, https://doi.org/10.5194/egusphere-egu26-8297, 2026.
Climate change is increasing the frequency and intensity of pluvial (rainwater-induced) flooding, creating emerging risks for small urban settlements with historic fabric and limited adaptive capacity. Across the Mediterranean, many coastal towns with significant heritage assets are exposed to short-duration, high-intensity rainfall events. Çeşme, located on the Karaburun Peninsula, represents a relevant case where hydro-meteorological hazards intersect with cultural heritage conservation. Designated as an “Urban Conservation Area,” the historic settlement contains built and archaeological heritage, while its coastal and topographical setting renders it highly sensitive to cloudburst-like episodes.
Analysis of precipitation data (1994-2025) indicates a marked rise in intense rainfall events, particularly after 2010. Extreme episodes expected to have long return periods are now recurring in rapid succession. Documented pluvial floods in 2015 (166 mm), 2024 (82 mm), and late 2025 (132 mm) repeatedly affected the settlement. In addition, even moderate precipitation triggered surface flooding. This sensitivity is amplified by rapid tourism-driven development, the expansion of impervious surfaces, and shoreline modifications.
To assess flood dynamics and heritage exposure, this study conducts a basin-scale GIS-based flood risk assessment using ArcGIS Pro, integrating topography, drainage patterns, geological and hydrogeological background, CORINE land cover, historical aerial imagery and building-scale impervious surface data. Flood-related indicators were spatially analysed and subsequently downscaled to the historic core to evaluate exposure and vulnerability at street and building levels. The assessment was developed through interdisciplinary collaboration between geologists, architects and cultural heritage conservation specialists. The resulting multi-scale analysis identifies flood-prone zones, vulnerable heritage structures and critical micro-topographic runoff pathways, providing a spatial basis for future pluvial flood risk management and heritage-sensitive mitigation and adaptation strategies in small coastal historic settlements under ongoing climate change.
How to cite: Özkaya İlbey, Z., Uzelli, T., and Yüceer, H.: Pluvial Flood Risk Assessment in a Small Coastal Historic Settlement: The Case of Çeşme, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10952, https://doi.org/10.5194/egusphere-egu26-10952, 2026.
Urban areas are increasingly exposed to flood risk under climate change, where evacuation planning based on fixed inundation depth thresholds may inadequately capture spatial uncertainty and the needs of vulnerable populations. This study investigates how shifting from a depth-based to a probability-based flood risk perspective can improve urban evacuation and shelter planning. Using a dense urban district in New Taipei City, Taiwan, as a case study, we integrate urban drainage modelling with multi–return-period rainfall analysis to construct probabilistic flood distributions under an end-of-century RCP8.5 climate change scenario, and examine their implications for evacuation decision-making and urban risk governance.
Probabilistic flood maps are developed by overlaying inundation extents simulated for multiple rainfall return periods, allowing flood risk to be expressed in terms of likelihood rather than as a single deterministic outcome. Changes in flood hazard patterns under climate change are further assessed using composite hazard indicators, including flood depth, flow velocity, and water level rise rate. To evaluate decision-level impacts, probabilistic flood information is incorporated into urban road network analysis to compare evacuation strategies based on a conventional depth threshold (50 cm inundation) and a probability-based decision threshold (70% flood likelihood).
Results indicate that under climate change conditions, areas characterized by high flood probability and moderate hazard levels expand significantly within the urban fabric, affecting neighborhoods not readily identified by depth-based criteria alone. The comparison of evacuation strategies reveals substantial differences in priority evacuation zones, routing options, and shelter allocation for vulnerable populations. Probability-based planning reduces the risk of over-evacuation while enabling earlier and more targeted evacuation actions in high-likelihood risk areas.
The findings demonstrate that integrating probabilistic flood risk into urban evacuation planning can enhance anticipatory decision-making and support more adaptive and equitable urban risk governance. By reframing flood risk from static depth thresholds to probabilistic decision logic, this approach contributes to strengthening urban resilience and improving disaster preparedness for vulnerable populations under climate change.
How to cite: Ke, K. Y., Li, C. L., Lin, J.-H., Chang, H. K., and Lin, Y. J.: From Flood Depth to Flood Probability: Improving Urban Evacuation Planning for Vulnerable Populations under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3581, https://doi.org/10.5194/egusphere-egu26-3581, 2026.
Climate change has intensified extreme wind events, posing growing threats to human safety, infrastructure, and urban resilience. These risks are amplified in densely populated and highly urbanized regions, where increasing intensity and unpredictability of tropical cyclones, frontal wind systems, and tornadic phenomena interact with complex built environments. Urban areas are particularly vulnerable due to the so-called urban corridor effect, in which densely arranged buildings locally accelerate and channel wind flow. Although observational networks and numerical weather prediction (NWP) models have achieved notable success in forecasting large-scale wind events, their performance remains limited in urban settings because of insufficient horizontal and vertical resolution. To overcome these limitations, computational fluid dynamics (CFD) has been increasingly coupled with NWP models, offering enhanced representation of urban-scale wind fields. However, CFD applications require prescribed boundary and initial conditions, and extreme wind events—such as cyclones, downbursts, and tornadoes—exhibit diverse temporal and spatial characteristics that must be identified in advance. In this study, the temporal features of observed wind speeds along the southern coast of the Korean Peninsula, a region frequently affected by various extreme wind events, were systematically analyzed. Wind events were classified into representative wind scenarios using meteorological pattern recognition based on K-means clustering. By identifying common atmospheric patterns, refined wind fields can be pre-simulated using CFD for each representative scenario. These precomputed wind scenarios enable rapid application to real-time events, facilitating high-resolution estimation of urban wind fields under extreme conditions. The proposed framework supports timely risk assessment and mitigation strategies for urban wind disasters. This research was supported by the Technology Development Program for Strengthening Resilience Against Urban Wind Disasters (Grant No. RS-2025-02220682), funded by the Ministry of the Interior and Safety (MOIS), Republic of Korea.
How to cite: Lee, S.: Identification of Extreme Urban Wind Hazards in Complex Built Environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8491, https://doi.org/10.5194/egusphere-egu26-8491, 2026.
Landslides may be mainly controlled by terrain steepness, but population exposure on hazardous slopes is shaped by human settlement decisions. Yet, despite growing recognition of landslide risk under a changing climate, we still lack a clear global picture of who is settling in steep terrain, how fast this exposure is changing, and where new hotspots are emerging. In this study, we take a global perspective on this challenge by combining terrain, population, and settlement datasets to explore how population exposure on steep hillslopes (≥10°) has evolved over the past five decades.
We find that the number of people living on steep hillslopes has increased by nearly 350 million since 1975. This growth is highly variable in terms of geography, socio-economic status and settlement types. The largest increases are seen in parts of South and Southeast Asia, tropical East Africa, and Central America. Our results show that low- and lower-middle-income countries account for almost 60% of the population living on steep hillslopes. Much of the growth appears to be driven by peri-urban and expanding urban settlements that are pushing outward into more marginal terrain. Broader structural drivers such as rapid population growth, land scarcity, and institutional fragility also seem to play a role. For example, three-quarters of the top 20 hotspots (by absolute exposure growth) fall in countries ranking lowest on the World Bank defined ‘Political Stability and Absence of Violence’ index.
These patterns suggest that the geography of landslide exposure is not just a function of physical terrain but is being actively reshaped by human dynamics, particularly at the urban fringe. As population pressure continues to rise in regions with limited flat land, and extreme rainfall events become more frequent, landslide risk on steep terrain is likely to keep growing. We identify hotspots of rapid growth and the potential drivers. These results provide a global baseline for more targeted landslide risk assessment and urban resilience planning.
How to cite: Gururani, C., Ozturk, U., and Wagener, T.: Unequal Rise of Population Exposure on Steep Terrain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5247, https://doi.org/10.5194/egusphere-egu26-5247, 2026.
The escalating frequency of extreme heatwaves and rapid urbanization pose unprecedented challenges to urban thermal environments. While current UHI research has established robust static mitigation strategies, it remains limited in capturing the dynamic pathways of urban systems during and after acute thermal shocks. Specifically, the post-disturbance recovery and non-linear thresholds that govern systemic resilience under extreme heat remain largely under-explored. To bridge this gap, we establish a resilience-oriented framework grounded in Press–Pulse Disturbance (PPD) theory, which we operationalize via a Pulse Intensity Index (PII) to quantify acute Pulse disturbances. Within this framework, we evaluate the system’s dynamic response through three dimensions: Resistance (the max temperature deviation from the thermal baseline during the peak Pulse period), Recovery (the restoration rate of LST toward the baseline post-disturbance), and Adaptation(the thermal baseline represents a long-term structural adjustment aimed at addressing long-term urbanization pressure).
The research focuses on the Seoul Metropolitan Area (SMA) during 26years (2000–2025). (1) We utilized Google Earth Engine to retrieve Land Surface Temperature from multi-temporal Landsat imagery, fused multi-source remote sensing and meteorological data. (2) The PII integrates heatwave frequency (>= 33°C, KMA standards) with cumulative excess perceived heat, providing a robust physical baseline for evaluating systemic responses to acute shocks. (3) We constructed a multi-dimensional indicator system across these categories: Built-up structures, GI and road composition. These indicators were processed through unsupervised clustering to urban morphological typologies. (4) An explainable machine learning model (LightGBM) integrated with SHAP values was employed to decouple the nonlinear and marginal effects of these morphological categories on resilience metrics.
Findings reveal significant spatial heterogeneity in thermal resilience across SMA. 1) During 2025 heatwave, areas under intense thermal load demonstrated a notable resilience decay as green infrastructure reached its critical threshold in cooling efficiency, especially PII was 41.9 in Seoul compared to only 2.3 in 2010. 2) High-density urban cores exhibited a difference in Resilience and Recovery. Although the shading effect enhanced immediate resilience, canyon heat retention led to a sharp decline in resilience compared to medium-density areas. 3) LightGBM model identified a critical threshold for GAC; below this morphological limit, adaptation capacity diminishes abruptly regardless of built-up and GI configurations.
This study underscores that urban thermal resilience is a dynamic response shaped by the synergy between chronic urbanization pressures and acute climatic shocks. The identified nonlinear relationships and threshold effects indicate that undifferentiated urban greening strategies are insufficient for mitigating extreme heat risks across diverse urban fabrics. Our findings establish a methodological workflow—linking urban expansion to resilience identification—thereby providing spatially targeted optimization strategies. This research provides a scientific basis for urban planners to shift from general mitigation to targeted structural interventions, ensuring enhanced climate-adaptive capacity for future extreme scenarios.
This work was supported by Korea Environment Industry &Technology Institute (KEITI) through "Climate Change R&D Project for New Climate Regime.", funded by Korea Ministry of Environment (MOE) (RS-2022-KE002123).
How to cite: Wang, Y., Li, Y., Kanniah, K. D., and Lee, J.: Decoupling the Nonlinear Effects of Urban Morphology on Thermal Resistance, Recovery, and Adaptation under Press–Pulse Disturbances, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8598, https://doi.org/10.5194/egusphere-egu26-8598, 2026.
Posters virtual: Wed, 6 May, 14:00–18:00 | vPoster spot 3
EGU26-16181 | ECS | Posters virtual | VPS13
Physics-Based Flood Fragility Modeling of CLT Shear WallsWed, 06 May, 14:09–14:12 (CEST) vPoster spot 3
In this study, a physics-based, performance-oriented framework to estimate the probability of failure of a cross-laminated timber (CLT) shear wall has been proposed. In low-lying coastal regions, residential buildings are becoming more exposed to both the pluvial and fluvial flooding. In previous studies, most structural analysis has been done emphasizing either solely on masonry-wall structures or entire building structures made of wood. In this study, the CLT shear wall has been subjected to flood-induced load. The wall demand is expressed in terms of a combination of hydrostatic and hydrodynamic forces, with the water depth acting as the intensity measure. Structural resistance has been computed at the component level by combining the in-plane and out-of-plane resistance models. Among the in-plane, bracket sliding, and rocking capacities, along with their combination has been considered. Whereas for out-of-plane bending resistance, the bending strength of CLT has been considered. Based on the demand and the resistance value, a limit state function has been formulated. Using a series of crude Monte Carlo simulations, the uncertainties in flood depth that lead to the damage state have been calculated. Overall, the results demonstrate that for all the given water depths, the CLT shear wall can withstand the load and avoid structural failure.
How to cite: Khan, N. M., Kameshwar, S., and Bin Mostafiz, R.: Physics-Based Flood Fragility Modeling of CLT Shear Walls , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16181, https://doi.org/10.5194/egusphere-egu26-16181, 2026.
EGU26-22962 | Posters virtual | VPS13
Implementation of a Congolese observatory of urban gullies for research, governance, and early warning systemWed, 06 May, 14:12–14:15 (CEST) vPoster spot 3
Urban gullies are an emerging geo-hydrological hazard of the Anthropocene, particularly in rapidly urbanizing tropical cities. In the Democratic Republic of the Congo (DRC), intense rainfall, steep slopes, erodible soils, and uncontrolled urban expansion combine to create highly favorable conditions for the formation and rapid expansion of UGs. Recent national-scale inventories reveal that more than half of Congolese cities are significantly affected, with nearly 3,000 urban gullies mapped. These features can reach tens of meters in depth and width within a few years, causing widespread destruction of housing, roads, and infrastructure, and leading to population displacement, injuries, and fatalities.
Recent analyses estimate that approximately 118,000 people were displaced by urban gullies in the DRC between 2004 and 2023, with displacement rates more than doubling after 2020. Currently, about 3.2 million people live within potential gully expansion zones, a number expected to increase dramatically as urbanization continues. Despite this growing risk, major knowledge gaps persist regarding the socio-economic impacts, rainfall thresholds, and short-term dynamics controlling gully initiation and expansion, severely limiting disaster risk management and early warning capacities.
This project aims to address these gaps through the implementation of a Congolese observatory of urban gullies, focusing on the cities of Kinshasa and Bukavu. Building on previous achievements, the project combines geomorphological research, citizen science, and policy advocacy to provide a proof of concept for an operational observatory.
The project adopts a participatory citizen science approach, engaging at-risk communities as “citizen observers” to collect in-situ data on gully dynamics, rainfall events, and socio-economic impacts. Community information sessions support risk awareness, co-development of data collection tools, and validation of observations. Data are collected using mobile applications, complemented by high-resolution geomorphological monitoring through rain gauge networks, GPS surveys, and drone imagery. These datasets enable improved characterization of gully expansion processes and identification of rainfall thresholds associated with hazardous events.
Beyond data generation, the project emphasizes governance and advocacy by translating scientific results into policy briefs and stakeholder workshops involving communities, authorities, NGOs, and urban planners. The project ultimately seeks to strengthen disaster risk management, inform sustainable urban planning, and demonstrate the feasibility and necessity of a dedicated national observatory for urban gullies in the DRC.
How to cite: Ilombe Mawe, G., Lutete Landu, E., Mugaruka Bibentyo, T., Makanzu Imwangana, F., Nzolang, C., Poesen, J., Dewitte, O., Bielders, C., Vanmaercke, M., and Michellier, C.: Implementation of a Congolese observatory of urban gullies for research, governance, and early warning system, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22962, https://doi.org/10.5194/egusphere-egu26-22962, 2026.
EGU26-23167 | Posters virtual | VPS13
Stabilisation of urban gullies by managing rainwater at parcel scaleWed, 06 May, 14:15–14:18 (CEST) vPoster spot 3
Urban gullies (UGs) are an increasingly urgent concern in many cities of the Global South. Rapid and largely unplanned urban expansion, combined with inadequate drainage infrastructure, erodible soils, and intense rainfall, have led to the formation of thousands of large UGs —often several tens of meters wide and deep and extending over hundreds of meters— in cities across the Democratic Republic of the Congo. These gullies cause loss of life, destroy housing and critical infrastructure, and further exacerbate the vulnerability of already marginalized populations. The situation is particularly severe in Kinshasa, where more than 800 UGs have already been recorded, threatening over one million people.
A wide range of initiatives has been implemented to stop UG expansion. These include large-scale engineering interventions led by the state or non-governmental organizations, such as concrete reinforcement of gully heads and canalizing the gully channel. However, many measures are expensive and/or often fail.
Nevertheless, emerging evidence highlights promising strategies for urban gully prevention and control. A key principle is to prevent rainwater from leaving individual parcels by installing water retention structures, as the accumulation of runoff along roads is a primary driver of gully initiation and expansion. A critical requirement for success is that a majority of households actively participate in such initiatives. Improving risk awareness and creating synergies between UG control and water accessibility will therefore be crucial to achieving this.
Here we aim to demonstrate the effectiveness of such a strategy. For this purpose, we installed water retention structures in a representative catchment in Kinshasa affected by UGs. This is done in close collaboration with local stakeholders. By monitoring and studying participation rates as well as the resulting hydrological effects (e.g., through the involvement of local students), we will develop actionable guidelines to this growing problem in Kinshasa and elsewhere, thereby enhancing both urban resilience and water security in vulnerable neighborhoods.
How to cite: Lutete Landu, E., Ilombe Mawe, G., Makanzu Imwangana, F., Makonga, L.-O., Lusolamo Nguizani, D., Luemba Luemba, R., Bielders, C., Michellier, C., Dewitte, O., Poesen, J., and Vanmaercke, M.: Stabilisation of urban gullies by managing rainwater at parcel scale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23167, https://doi.org/10.5194/egusphere-egu26-23167, 2026.
