This session aims at gathering researchers interested in the scientific advances related to the multiple facets of natural hazard impacts, i.e., direct, indirect, tangible and intangible losses.
The session welcomes novel approaches to address impact modelling, data analysis, uncertainty analysis, calibration/validation and theoretical frameworks across all natural hazard types, e.g., floods, droughts, earthquakes, wind storms etc.. The topics include but are not limited to:
- comprehensive assessment of the economic impacts of natural hazards, emphasizing the importance of robust cost evaluations for informed decision-making in disaster risk reduction, hazard management, cost-effectiveness and efficiency of risk reduction strategies, and climate change adaptation planning.
- cascading impacts from direct losses to systemic indirect losses, e.g., business interruption, disruptions to critical services or the influence of critical infrastructure interdependencies.
- indirect and intangible impacts of natural hazards, which are increasingly significant in today’s interconnected socio-technological world. These include loss of irreplaceable items or ecosystem services, and the impacts on physical and mental health. Special attention will be given to the effects on specific population groups (e.g., vulnerable communities), and the long-term health impacts of climatic stressors. Given the complex nature of these impacts, the session will also focus on novel systemic approaches to assess the interplay of hazards with social vulnerability, particularly through the use of advanced data analysis techniques (e.g., ML and spatial disaggregation).
- challenges posed by the lack of empirical data and the diversity of methodologies currently applied to assess the costs associated with different natural hazards and impacted sectors, e.g., agriculture, population, buildings etc.
Submissions are encouraged from those engaged in both theoretical and practical aspects of impact assessment, with a view to fostering interdisciplinary dialogue and advancing the field. Outstanding contributions will be highlighted as “solicited talks”.
Orals: Wed, 6 May, 08:30–12:25 | Room E2
Climate warming and increased human activity accelerates the thawing of permafrost, posing considerable threat to infrastructure security and sustainable development. Mitigating infrastructure damage from global permafrost thaw is a grand challenge because of future dramatically increased risks and the constraints to implementing damage-reduction measures. Here, we synthesize field observations worldwide and identify six key measures that can reduce subgrade internal temperature within 15-m depth by 1.5 ± 0.1 °C and extend the useful life of infrastructure by 9.5 ± 3.4 years. Adoption of these integrated measures allows current additional costs decrease by 33% to 57%. The mitigation measures will save global societal cost of 52.6 ± 16.6 billion USD by 2090 under SSP2-4.5, with Alaska (67 ± 12% reduction), Western Siberia (65 ± 12%) and the Qinghai-Tibet Plateau (53 ± 17%) having the highest benefits. Given future demographic projections targeting permafrost areas, per capita infrastructure cost by following the integrated measures up to 2090 is projected to increase by 83% compared to 2050. To reduce future economic burden of infrastructure damage, more efficient mitigation measures such as new and low-cost insulation materials, design and construction concepts could be implemented, where necessary, subsidize the adoption of these measures.
How to cite: Du, X. and Mu, C.: Cost-effective mitigation of infrastructure damage from global permafrost thaw, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19599, https://doi.org/10.5194/egusphere-egu26-19599, 2026.
The efficacy of the flood protection of the Netherlands critically depends on the reliable functioning of six Dutch storm surge barriers. Usually, these barriers are open and they only close in case of severe storm tides. The storm surge barrier performance (i.e. the amount of risk reduction due to their presence) depends roughly on the height, the structural reliability, and the closure reliability. Obviously, hydraulic overload and the probability of structural failure increase with storm severity and tide levels. Yet, it is also likely that a storm tide coincides with meteorological conditions that may harm the closure reliability. This compound event is typically not accounted for in current flood risk assessments, potentially leading to underestimation of the flood risk. This study explores what meteorological conditions may affect the closure reliability and how these conditions may coincide with storm tides that require a closure. We found that storm tides can both coincide with reliability reducing and reliability increasing meteorological conditions. Yet, in general it has a negative impact on the closure reliability. This implies that the actual flood risk may be somewhat higher than usually perceived.
How to cite: Bakker, A.: The conincidence of severe storm tides and weather conditions affecting the closure reliability of storm surge barriers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20998, https://doi.org/10.5194/egusphere-egu26-20998, 2026.
Floods are the most frequent natural disasters, and their frequency and intensity are expected to increase under climate change, leading to heightened vulnerability of critical infrastructure. Such conditions amplify the likelihood of cascading effects, including industrial accidents (e.g., Natech - Natural Hazard Triggering Technological Disasters). Moreover, floods often can transport hazardous contaminants over long distances, generating significant impacts on ecosystems and human health. While numerous models exist for marine oil dispersion, their application to river and floodplain environments remains limited. Available models are often non-open access, computationally intensive, and require extensive input data, restricting their usability for rapid-response scenarios or studies involving multiple simulation runs.
To address this gap, the present study develops a simplified crude oil dispersion module for floodwaters, integrated into the CAESAR-LISFLOOD model (a morphodynamic Landscape Evolution Model). This approach provides a balance between physical reliability, computational efficiency, and ease of use, making it suitable for rapid-response applications, scenario analysis, and large-scale studies.
The model was tested on two case studies with differing levels of hydraulic and topographic complexity and benchmarked against the oil dispersion module implemented in Telemac 2D. Results indicate that CAESAR-LISFLOOD reproduces dispersion patterns, mean concentrations, and contaminated areas with good consistency. Moreover, depending on the spatial and temporal resolution of the simulations, CAESAR-LISFLOOD reduces computational times by 60–80% compared to Telemac 2D while maintaining a sufficiently robust physical representation for lowland floods with subcritical flows. This significant reduction in computational demand, combined with reliable physical performance, highlights the suitability of the model for rapid-response simulations, repeated scenario analyses, and risk assessment studies in flood-prone areas.
How to cite: Di Fluri, P., Wilson, M. D., and Domeneghetti, A.: A Two-Dimensional hydrodynamic framework for simulating oil spills in rivers and floodwaters, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3551, https://doi.org/10.5194/egusphere-egu26-3551, 2026.
River flooding is a major concern in Italy, which has experienced a very long history of disasters. This paper investigates flood risk in River Po basin in northern Italy. The area is highly vulnerable due to rapidly subsiding soils and dense urban concentration in low lands, and hosts a large portion of the Italian population. The complex plane system intertwines high-value industrial areas with an extensive agricultural land that ensures over one third of the national food production yearly. Because of the complex set of services provided and ecosystems that coexist, it is crucial to be able to assess flood risk and its translation to local impacts. The objective of this research is to carry out a probabilistic risk assessment on river flooding. We use a suite of high-resolution (100 m) river flood hazard maps across multiple return periods and combine them with demographic, infrastructural, and socio-economic datasets to estimate potential losses and damages. We identify the most exposed assets and population groups by quantifying productivity reductions and economic losses, while explicitly acknowledging the role of ecosystem services in mitigating impacts. To ensure consistent and fine-scale exposure estimates, we apply a suite of geospatial downscaling techniques that integrate spatial and satellite-derived information with building footprint data, which are subsequently aggregated to the municipal level. The resulting outputs deliver actionable, high-resolution impact data and a set of climate risk indicators designed to support risk assessment, adaptation planning, and evidence-based decision-making.
How to cite: Bovienzo, D., Sarcinella, M., Colucci, M., and Mysiak, J.: An Automated Framework for Probabilistic River Flood Risk Assessment: The Po River Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19970, https://doi.org/10.5194/egusphere-egu26-19970, 2026.
Bosnia and Herzegovina (BiH) is characterized by complex risks induced by natural hazards, particularly floods, landslides, and earthquakes. The recent flood and landslide disaster in the Herzegovina-Neretva Canton in October 2024 underscored the severe adverse impacts of cascading disasters on infrastructure, the economy, environment, and peoples’ wellbeing in BiH. Improved understanding of these cascading impacts, as well as their risk drivers, is hence an integral first step in enhancing climate and disaster risk management. Yet existing disaster risk and impact assessments often focus on single hazards or are tailored to specific, isolated impacts.
Therefore, we applied a comprehensive, mixed-method risk assessment, to identify key risks, risk drivers, including hazard, exposure, and vulnerability factors, potential and observed disaster impacts, as well as cascades and interconnections across risk drivers and impacts. Our study focused on floods, landslides, and earthquakes in the Herzegovina-Neretva Canton in BiH, applying conceptual risk models, including impact chains and impact webs, with data derived from literature, expert interviews, field observations, and a dedicated workshop with local stakeholders.
Our results provide evidence of a multi-hazard risk context, in which floods and earthquakes both increase the potential for landslides – with interconnected impacts. Direct impacts, such as physical damage to housing and infrastructure, represent only a portion of the total burden, while transport disruption and a short-term delay in emergency response reveal cascading impacts. Tangible costs are further compounded by intangible effects, including displacement-related well-being losses as a consequence of destroyed buildings even up to one year after the disaster. At the same time, various risk drivers in the system can critically amplify these impact cascades.
By considering hazard interactions, as well as short- and long-term impacts across diverse sectors, the conceptual risk models provided new evidence that disaster impacts are systematically underestimated when cascading and intangible effects, and the interconnection of risk drivers remain unaccounted for. The development of a multi-hazard conceptual risk model represents an effective approach to move to systemic disaster risk management, while providing specific entry points for interventions.
How to cite: Fricke, N., Das, N., Ortiz-Vargas, A., Smječanin, A., Walz, Y., Sandholz, S., and Sett, D.: Assessing cascading disaster impacts induced by interconnected natural hazards in Bosnia & Herzegovina, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3356, https://doi.org/10.5194/egusphere-egu26-3356, 2026.
Vulnerability analysis is paramount to hazard and risk analysis, and very often is too qualitative and lacks validation. Only the back-analysis of historical data can be used to validate quantitative assessments in certain research contexts. We present a cartographic analysis, doubled by archive analysis, of the settlement network in the Republic of Moldova that is used to establish case studies of hazard and vulnerability scenarios. The cartographic analysis covers the ’20 and ’21 centuries, and uses topographic maps and aerial imagery. Through change detection and overlay analysis, we identified 240 settlements, where parts of settlements were affected by landslides, riverbank erosion, or floods that generated the displacement of the population. Every case study was documented to establish the natural hazard type, the intensity and magnitude of the process, the exposed elements, their vulnerability and the losses. These situations are also complex, because very often the decision of displacement because of the activity of the natural process is taken in conjunction with political and socio-economic contexts. The resulting data was synthesized in model scenarios for every type of natural hazard, climatic and socio-economic pathway that can be used for further modelling, considering the impact of climate change or economic and political changes.
How to cite: Niculita, M., Castraveț, T., Mărgărint, M. C., Dilan, V., Crețu-Văculișteanu, G., Necula, N., Căpățână, L., Suvac, S., Jechiu, I., and Enea, A.: Geomorphological hazards vulnerability at the settlement level in the Republic of Moldova: insights from the cartographic analysis for the last two centuries , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4349, https://doi.org/10.5194/egusphere-egu26-4349, 2026.
Climate change is increasingly experienced as a lived reality by communities living in the Himalayan region, one of the fastest-warming mountain systems globally. While existing research has extensively documented biophysical and economic impacts, comparatively less attention has been paid to the non-economic losses experienced by remote mountain communities, particularly those related to emotional well-being, cultural identity, and sense of place. This paper examines such non-economic losses through a case study of selected Himalayan villages in the Lahaul–Spiti district of Himachal Pradesh, India, with a specific focus on solastalgia which means the distress associated with environmental change in one’s home environment.
This research is a qualitative case study. The data was collected through in-depth interviews. The study explores how climatic changes, including altered snowfall patterns, glacial retreat, increased frequency of extreme weather events, and ecological degradation, are perceived and experienced by local residents. The findings reveal that environmental transformations have disrupted traditional livelihoods, seasonal mobility, and culturally embedded relationships with land and water systems. These changes have generated profound emotional responses, including grief, anxiety, and a sense of loss tied to the erosion of familiar landscapes and ways of life of all the generations differently.
The analysis demonstrates that solastalgia in Lahaul–Spiti is deeply intertwined with place attachment, cultural continuity, and intergenerational knowledge systems. Residents express distress not only over present environmental risks but also over anticipated loss of future possibilities for sustaining life, culture, and identity in the region because of possible climate change induced migration. Such experiences remain largely invisible within climate impact assessments that prioritize quantified economic losses. The paper argues that addressing climate change impacts in mountain regions requires approaches that move beyond economic metrics to incorporate emotional, cultural, and place-based dimensions of loss. Acknowledging these intangible losses is essential for developing more inclusive and context-sensitive climate responses for vulnerable Himalayan communities.
Keywords – Himalayas, Non-economic Loss & Damages, Solastalgia, Vulnerability.
How to cite: Sood, K. and Kumar, A.: Place, Identity, and Loss: Solastalgia as a Non-Economic Impact in Himalayan Communities, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4438, https://doi.org/10.5194/egusphere-egu26-4438, 2026.
In July 2021, extraordinary flooding claimed more than 220 lives in Germany and Belgium, an unprecedented number in recent decades in both countries. To better understand underlying causes, the individual circumstances of 224 fatalities were analyzed based on documents and interviews. Intersections with hazard maps indicate that 58% of the fatal incidents occurred outside officially mapped flood hazard zones. In addition, fatal pathways revealed deficiencies in warning, evacuation and behavior. Around two thirds of the people who died indoors were caught by surprise in souterrain apartments or on the ground and upper floors of their homes, suggesting that these buildings should have been evacuated in time. 22% died in basements mostly while mitigating damage, checking pumps or starting cleanup, pointing towards deficiencies in communicating safe behavior during flooding. The circumstances of outdoor deaths are often less clear, but underline the risks of being outdoors during a flood, even in places that are usually safe to cross a river such as bridges. Despite regional differences between the Walloon Region (Belgium), North Rhine-Westphalia and Rhineland-Palatinate (both Germany), it is generally recommended to clearly communicate appropriate behaviors in warning messages. Evacuation needs to take place in areas where moderate to high water levels are expected, particularly where basement or ground level apartments are expected to be flooded. Special attention should be paid to the safety of elderly people, who are significantly overrepresented among the fatalities of 2021. Finally, the European Floods Directive and its implementation need to better address worst-case scenarios in hazard mapping and risk communication.
How to cite: Thieken, A., Rhein, B., Hosten, E., Zenker, M.-L., Merz, B., Bubeck, P., Kreibich, H., and Guha-Sapir, D.: Analysis of flood fatalities in July 2021: lessons for European flood risk management, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6361, https://doi.org/10.5194/egusphere-egu26-6361, 2026.
Floods generate a wide spectrum of impacts on society, ranging from direct to indirect and from tangible to intangible. While damage models are available for direct and tangible losses (e.g. damage to buildings), there is still a lack of tools capable of capturing the overall impact of floods on people.
To address this gap, we investigated the overall flood impact through an online survey conducted after the September 2022 flood in the Marche region of Italy. The survey collected approximately 700 responses from residents of affected municipalities, including directly exposed, indirectly exposed and non-exposed individuals. Respondents reported a self-assessed overall impact on a 0–6 severity scale. In this study, the overall impact on people is understood as the perceived personal impact resulting from the combined effect of multiple direct and indirect, tangible and intangible flood consequences. The survey collected information on these impact categories, together with data on hazard intensity, exposure conditions, and respondents’ socio-economic and social capital characteristics.
A combination of statistical techniques was employed to analyse the data, including multiple linear regression, factor analysis and cluster analysis. These methods were used to support the conceptualisation of the overall impact, to explore its potential for predictive modelling, and to investigate how different vulnerability characteristics are associated with variations in overall impact and in specific impact dimensions. Among the vulnerability variables considered, social capital indicators were found to play an important role in shaping the reported overall impact.
The results provide empirical insights that can inform policies aimed at reducing the indirect and intangible impacts of floods on people. By highlighting differences in impact experiences and the role of selected vulnerability characteristics, the study supports the design of post-event interventions that address broader social consequences.
How to cite: Rrokaj, S., Barbaccia, E., Azzellino, A., Bubeck, P., and Molinari, D.: Capturing the overall impact of floods on people: evidence from the 2022 Marche Region flood event., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10338, https://doi.org/10.5194/egusphere-egu26-10338, 2026.
In 2025, natural disasters generated substantial global losses, estimated at approximately US$224 billion according to Munich Re’s annual report. While monetary valuation of damages is essential for decision-making and risk management, some categories of loss remain difficult to quantify economically. Cultural heritage is a prime example, as impacts range from physical degradation to disruptions of community identity and sense of belonging. This study advances the assessment of direct tangible losses to cultural heritage from flooding, complementing existing research on indirect and intangible impacts. Direct tangible losses arise from contact between floodwater and artworks or heritage buildings, necessitating restoration. Restoration costs depend strongly on material characteristics, which determine vulnerability to water exposure. We develop new flood vulnerability models for estimating direct cultural heritage losses by integrating (i) historical records of post-flood restoration expenditures adjusted to current prices and (ii) detailed information on the quantity, spatial distribution, and material composition of artworks in heritage structures, including places of worship, museums, and libraries. The methodology is applied to the historic city of Florence, Italy, using data from 48 surveyed cultural heritage buildings to derive mean and percentile vulnerability curves. Under a 500-year flood scenario, average expected direct losses are approximately €2.5 million for building envelopes and €3 million for artworks per asset, resulting in total citywide cultural heritage damages of roughly €550 million. Combining these estimates with existing analyses of indirect and intangible losses provides a more comprehensive basis for risk assessment and management in art cities.
How to cite: Castelli, F., De Lucia, C., and Arrighi, C.: Estimating cultural heritage losses from flooding, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10288, https://doi.org/10.5194/egusphere-egu26-10288, 2026.
Flood risk emerges from dynamic interactions among climate extremes, human systems, and cascading impact pathways that extend into economic, social, and health domains. Traditional risk assessments often inadequately represent these interdependencies. Responding to emerging evidence that flood risk is shaped by interdependencies, health impacts, and evolving vulnerability, my research develops a suite of methodological approaches to advance systemic flood risk modelling. These include system dynamics modelling to capture feedback between hazard, exposure, vulnerability, and human adaptation; hierarchical Bayesian regression and multivariate statistical models to quantify cascading impacts across sectors and scales; and scenario-based simulations that explore how changes in drivers and adaptive responses modulate risk pathways. We further leverage longitudinal survey datasets, probabilistic methods, and open datasets to bridge local empirical findings with broader flood risk dynamics. By integrating health risk metrics which are often missing from conventional frameworks alongside economic and social outcomes, our methods aim to quantify the full cascade of flood impacts and support evidence-based adaptation strategies and inclusive disaster risk management that reflect the complex Human–Flood system.
How to cite: Sairam, N.: Quantifying Cascading Economic, Social, and Health Impacts of Flooding, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13128, https://doi.org/10.5194/egusphere-egu26-13128, 2026.
Damage from natural hazards exacts a heavy toll on society and is expected to increase under climate change. Yet, existing impact datasets remain limited and often biased toward the Global North and monetary loss metrics. This bias constrains our capacity to robustly assess socio-economic consequences, particularly in regions where impacts are most acute and least documented. To help address these gaps, we present ROUGE (Red cross Operations Unified Global Emergency), a new global socio-economic impact database obtained using textual operational reports from the International Federation of Red Cross and Red Crescent Societies (IFRC). These reports are systematically collected and provide extensive coverage of regions that are commonly underrepresented in existing impact datasets.
Using large language models, we extract qualitative and quantitative information from 717 reports spanning 2016-2025. The dataset records 11,370 impacts across 20 socio-economic impact subtypes, reported at both national and sub-national scales. The most frequently reported impacts relate to Water, Sanitation and Hygiene, Agriculture and Access to Food, Affected People, Residential Buildings, and Economy and Livelihood. We validate the database against manually-labelled reports and established disaster impact databases, including EM-DAT or IFRC-GO. Results show that extraction performance varies across impact subtypes, with precision ranging from 0.3 to 0.9 and recall ranging from 0.1 to 0.8. Comparisons with external datasets reveal differences in impact figures, reflecting the inherent challenge associated with quantifying natural disaster impacts. However, for overlapping events, our database more frequently provides quantitative impact values than existing datasets.
Overall, ROUGE opens new avenues for disaster impact research by delivering geographically explicit socio-economic impact data from IFRC reports. The resulting dataset captures the impacts of natural hazards on both populations and the built environment, with spatial resolution extending to the subregional level, capturing impacts that are rarely represented in conventional databases. By doing so, ROUGE enables more precise, inclusive, and globally representative analyses of the socio-economic consequences of natural hazards worldwide.
How to cite: Severino, L., Hasbini, L., de Brito, M. M., Gesualdo, G. C., Rotaru, A. M., Bresch, D. N., Mühlhofer, E., Wang, J., and Carvalho, T. M. N.: ROUGE: A database of disaster impacts in the Global South using Red Cross reports and Large Language Models , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7157, https://doi.org/10.5194/egusphere-egu26-7157, 2026.
Amidst the backdrop of changing climate and increasing disasters, a wide array of mitigation and adaptation responses exist for disaster management. However, residual impacts often arise from insufficient mitigation and inadequate adaptation, known as Loss and Damage (L&D). While existing literature has estimated loss and damage, independently on each capital asset by econometric, or Damage and Loss Assessment, Post Disaster Needs assesment methods, limited research has estimated residual “Loss and Damage” on livelihood assets through vulnerability lenses, and synthesized the linkages among capital assets, and the impacts after adopting mitigation and adaptation measures.
This study addresses this research gap by quantifying economic and non-economic L&D from 2020 super-cyclone Amphan, in South Twenty-Four Parganas, one of India’s highest-risk coastal districts, while accounting for the compounding effects of the concurrent interacting hazard, COVID-19 pandemic. Using the extended Sustainable Livelihoods Approach, a household survey has been conducted across the highest vulnerable community development blocks in this district, to derive the first and second-order economic (human, physical, and financial capital) and non-economic (social and natural capital) L&D estimates across three damage severity levels-low, moderate and high.
While Poisson regression models are used to estimate L&D to human and physical capital, Heckman’s sample selection model is adopted to estimate L&D to financial capital, proxied by change in agricultural income. Non-economic L&D estimates on social and natural capital are quantified using Multivariate Probit model. Regression estimates find that the households faced greatest L&D to human and physical capital in high damage, with second-order estimates being lower than first-order. However, the coping measures bearing high costs, increased second-order L&D to human capital in low and moderate damage. Risk reduction measures effectively minimized L&D to physical capital in low and moderate damage. L&D estimates of financial capital, indicate that the coping measures reduced second-order impacts for low (INR 1140), and high damage (INR 942) households. Among the non-economic L&D estimates, social capital erodes from low to moderate damage [(+93.5) to (+20) percentage-points (first-order); (-3.5) to (-4.5) percentage-points (second-order)]. However, second-order L&D to natural capital exceeds first-order, with relatively lower estimates in moderate damage.
Overall, the findings highlight the crucial and significant role of livelihood diversification in minimizing economic and non-economic L&D. Besides, government support, inter-village trust, and resilient housing significantly reduce economic L&D. Perception of riskiness of house location, household income, and recovery from past cyclone significantly determine non-economic L&D. These insights will guide stakeholders to understand effectiveness of adaption and mitigation measures, necessary to reduce vulnerability and build resilience during overlapping hazards.
How to cite: Bose, D., Mishra, T., and Karmakar, S.: Quantifying Loss and Damage from Disasters: Evidence from Super-cyclone Amphan in Indian east-coastal district, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10704, https://doi.org/10.5194/egusphere-egu26-10704, 2026.
Estimating monetary flood impacts commonly relies on combining hydrodynamic simulations with building-level damage models to compute scenario-specific damages. These losses are then aggregated across multiple flood scenarios to derive the expected annual damage (EAD), which often informs risk-reduction decision-making. While uncertainties related to hydraulic modelling and damage functions have been widely explored, the impact of methodological choices in the aggregation of flow variables at the building scale (also called hazard attribution) has received limited attention.
In high-resolution flood simulations, multiple computational cells typically overlap a single building footprint. To provide input to damage models, a representative value for each flow variable must be assigned to the building, commonly through a statistical operator such as a selected percentile. This study investigates the influence of this choice for water depth, flow velocity, and duration of inundation on the EAD, comparing it to uncertainties arising from modelled flood wave shape and friction parameterization. The analysis is conducted for a residential flood damage model, INSYDE-BE [1], in the city of Theux located in the Vesdre catchment (Belgium) severely affected by the 2021 European flood. A baseline scenario and two risk-reduction configurations (grey vs. hybrid measures) are evaluated.
Results indicate that water depth attribution dominates the uncertainty, with the choice of percentile resulting in up to twice the relative influence on EAD compared to other major uncertainty sources in the hydrodynamic modeling. In contrast, the selection of a particular statistical operator for the attribution of flow velocity and inundation duration has minimal impact, reflecting that particular attention must be paid to the attribution method for water depth. For this reason, the water depths-to-building attribution method was calibrated using surveyed data from the study area in order to determine the most appropriate percentile for obtaining representative water depths.
Furthermore, the study explores the effect of incorporating risk aversion factors to address EAD’s tendency to underweight extreme, but low-probability events. Accounting for this factor increases the contribution of highly damaging scenarios. This potentially alters the ranking of mitigation measures, highlighting the importance of considering monetary indicators with caution.
[1] Scorzini, A. R., Dewals, B., Rodriguez Castro, D., Archambeau, P., and Molinari, D.: INSYDE-BE: adaptation of the INSYDE model to the Walloon region (Belgium), Nat. Hazards Earth Syst. Sci., 22, 1743–1761, https://doi.org/10.5194/nhess-22-1743-2022, 2022.
How to cite: Sansen, D., Rodriguez Castro, D., Archambeau, P., Erpicum, S., Pirotton, M., and Dewals, B.: Uncertainty induced by hazard attribution methods in building-level flood damage and risk assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17235, https://doi.org/10.5194/egusphere-egu26-17235, 2026.
The road subsector is considered one of the key production sub-sectors that tends to be affected by climate and weather variability. Increased precipitation can lead to flooding that may cut-off the network, wash-away sections, and lead to landslides, while increased temperature speeds-up the ageing of materials reducing the overall life of the asset. The Highway Development and Management Model (HDM-4), one of the primary asset management tools used in developing economies was developed in the early 2000’s and used by over 1000 clients for asset investment planning. While valuable for traditional asset management, HDM-4 presents significant limitations when applied to climate resilience planning. Based on static climate assumptions, with inadequate damage assessment, and insufficient economic analysis for climate resilience planning, HDM-4 is unable to capture accelerated deterioration from extreme climates, catastrophic failures, and cascading impacts from climate change.
To tackle these challenges, this research proposes two complementary approaches that address two road failure modes: (1) direct failure and (2) delayed failure. The first approach, dubbed, “Resilience Module” applies a well-known system-of-systems approach to assess the vulnerability of the asset, economically quantify direct and indirect damages from hazard events, and propose adaptation interventions that provide the best returns. The second approach addresses the gradual “delayed failure” modes. Unlike landslides or floods that typically cause sudden damage to assets, extreme heat and some flooding events affect roads through progressive deterioration of the road pavement. This approach addresses these failures through climate-shift factors that were statistically derived to modify the existing deterioration equations. By determining which climate variables are most influential to road pavement deterioration, the research developed a set of multiplier factors that adjust HDM-4’s existing deterioration equations to capture intensifying extreme-heat conditions, flooding, and compound climate stressors.
Together, these approaches build on HDM-4’s strength of prediction, based on historical conditions to create a model that can handle future climates. The framework allows for the quantification of direct and indirect costs from catastrophic events, and accelerated deterioration estimates from changing conditions. It provides a comprehensive risk assessment that integrates exposure analysis, vulnerability evaluation, economic impact estimation, and increased maintenance costs from accelerated degradation across road assets.
By working within existing institutional frameworks and tools, this methodology gives road agencies a practical pathway to integrate climate change into infrastructure planning. This is crucial in ensuring that the limited adaptation resources are invested purposefully where they can deliver the greatest resilience benefits against mounting climate pressures.
How to cite: Acheng, O. P., Pant, R., and Hall, J.: Can Roads Designed Yesterday Survive Tomorrow? Adapting Asset Planning Tools for Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15482, https://doi.org/10.5194/egusphere-egu26-15482, 2026.
Modellers widely use damage (or impact) functions to define the climate's feedback on the economy. Many of these functions are based on econometric theories and are empirically estimated using historical data. However, it is unclear which uncertainties to check for and how these interact in determining the impacts. These robustness checks are pivotal since impact functions are also used to provide policy-relevant insights. We reestimate and analyze four relevant damage functions: Burke, Hsiang, and Miguel (2015), Kalkhul and Wenz (2020), Kotz et al. (2024), and Waidelich et al. (2024). These four functions represent not only different structures, but also different philosophies. We consider three sources of uncertainty: estimation, future scenarios, and internal climate variability. We use a newly developed dataset on climate and climate extremes to reestimate them, performing cross-validation to understand the quality of the fit. We then quantify their uncertainty and perform multivariate sensitivity analysis at the global and regional levels to identify country-specific relevant factors. We gain relevant insights for modellers and policymakers, identifying gaps in our current understanding of climate impacts on our societies.
How to cite: Chiani, L., Mastropietro, M., and Tavoni, M.: What are We Missing in the Relationship between Climate and Economies?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15267, https://doi.org/10.5194/egusphere-egu26-15267, 2026.
Transportation networks, such as roads and bridges, have a fundamental role in the daily economic and social activities, enabling the access to jobs, goods delivery, and social services. However, due to their interconnected nature, these infrastructures are particularly vulnerable to external shocks, especially natural hazards, and therefore it is essential to assess their risk through a systemic approach. Yet, traditional risk assessment methods typically focus only on direct physical damage to infrastructure, often overlooking the cascading effects, especially how this affects firms and households, a crucial limitation for understanding the large-scale economic costs of extreme weather events. In order to address these gaps, we present a comprehensive framework that integrates the novel DisruptSC model, a spatially explicit agent-based model that captures the propagation of infrastructure failures through supply chains, with standard direct impact modeling approaches. By explicitly representing synthetic firms, households, and transport networks within a unified system, the framework allows to quantify both the direct infrastructure damage and the ripple effects that spread through interconnected economic systems can be quantified thanks to this integrated approach.
We applied this framework to Cambodia in order to not only quantify the indirect impacts of critical infrastructure failures but also the effects of sequential or spatially distributed cascading hazards on supply chains. Cambodia is in fact affected by extended heavy rainfall during the wet season leading to multiple flooding phenomena occurring in close succession. The results show that transport disruptions generate substantial indirect economic losses that extend well beyond the directly affected areas. In particular, the model highlights two distinct but interacting mechanisms, namely increases in prices driven by costly rerouting and shortages arising from complete network blockages. While inventories initially buffer these shocks, their depletion over time leads to strongly nonlinear increases in losses, underscoring the importance of disruption duration. Moreover, the analysis reveals that a limited number of critical road segments disproportionately drive aggregate impacts, with relatively small additional disruptions triggering sharp increases in economy wide losses. Overall, the results demonstrate that indirect losses can equal or exceed direct infrastructure damages, and that ignoring cascading effects leads to a systematic underestimation of flood related risks. These findings underline the need for integrated assessment frameworks that explicitly link hazard processes, infrastructure vulnerability, and supply chain dynamics in order to support more effective resilience oriented investment and policy decisions.
How to cite: Nobile, E. G. L., Colon, C., Arosio, M., and Caiani, A.: Cascading economic impacts of critical infrastructure failures on supply chains, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20824, https://doi.org/10.5194/egusphere-egu26-20824, 2026.
Accurate quantification of damage reduction potential from building code enhancements is essential for insurers, investors, and policymakers seeking to prioritize climate adaptation investments. This study develops a tract-level risk assessment framework to estimate the benefits of enhanced building code practices across 708 census tracts within Louisiana's Coastal Zone. Using the National Structure Inventory for exposure data, Hazus-derived damage functions, and ASCE 7-22 wind speed maps, the study calculates expected annual structural damage (EASD) and expected annual damage in dollars (EADD) under baseline and mitigated scenarios.
To identify drivers of spatial variation in mitigation effectiveness, the study links damage reduction estimates to sociodemographic data from the 2018–2022 American Community Survey and the 2020 Decennial Census Demographic and Housing Characteristics file. Spatial regression analysis examines associations between social vulnerability indicators and four damage reduction outcomes: absolute and percentage reductions in both EASD and EADD.
Results reveal substantial spatial variation in damage reduction potential, with tract-level EADD reductions averaging 77%. Key drivers of this variation include building stock characteristics, housing tenure patterns, and population density. Tracts with higher proportions of owner-occupied housing and urban development show larger absolute reductions, while rural tracts demonstrate lower mitigation benefits despite comparable hazard exposure. These patterns suggest that building age, construction quality, and existing code compliance—factors often correlated with sociodemographic characteristics—significantly influence where mitigation investments yield the greatest returns.
This framework provides actionable intelligence for risk-informed decision-making, enabling targeted identification of high-return mitigation zones for insurance loss reduction, public investment prioritization, and resilience planning. The methodology is transferable to other coastal regions facing wind hazards and offers a replicable approach for integrating physical risk modeling with socioeconomic exposure data to support climate adaptation strategies.
How to cite: Mostafiz, R. B., Al Assi, A., Jayasinghe, N., Smiley, K., and Khan, N. M.: Quantifying Wind Risk Reduction Potential Across Diverse Building Stocks: A Census Tract-Level Assessment for Coastal Louisiana, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21948, https://doi.org/10.5194/egusphere-egu26-21948, 2026.
Posters on site: Wed, 6 May, 14:00–15:45 | Hall X3
As flood hazards intensify, many cities adopt partial structural protection rather than comprehensive defenses, reshaping how flood risk is distributed in space and time. Although large-scale analyses suggest that partial levee coverage can reduce overall damage, its spatiotemporal effects remain understudied, particularly in cities of the Global South. Using a 1D-2D coupled hydrodynamic model forced by extreme discharges (100-year return period flood event), together with depth-damage curves and demographic data, we show that partial levee construction in coastal city Surat, India, lowers citywide flood losses by ₹31.24 billion (US$380 million) in core urban wards and by ₹10.34 billion (US$125 million) in suburban neighborhoods. However, both damage and exposure become more inequitable, with the Gini index (0 = perfect equality, 1 = maximum inequality) rising by 20% for damage (0.55 to 0.66) and by about 26% for exposure (0.31 to 0.39). To capture the underlying spatial and temporal mechanisms driving these patterns, we introduce flood stripes and a protection-induced time shift (PITS), revealing that certain near-river wards remain flood-free for up to 12 hours longer, while some downstream areas flood up to 7 hours earlier under partial levee coverage. When ranked by marginal worker share, inequality further intensifies, with the Gini index increasing from 0.19 to 0.23 for damage and from 0.02 to 0.06 for exposure, and the most vulnerable 50% of wards absorbing 60.7% of losses and 56.4% of at-risk residents. Together, these results highlight the importance of evaluating both spatial and temporal consequences of partial flood protection when designing equitable urban adaptation strategies.
How to cite: Kumar, A., Majumder, R., P. Kapadia, V., and Bhatia, U.: Risk redistribution and inequality under partial flood protection in a core- periphery city, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18151, https://doi.org/10.5194/egusphere-egu26-18151, 2026.
Weather conditions affect many areas of human activity, including rail transport. During periods of low air temperatures, steel rails become brittle and may crack. At high air temperatures, rails extend and may buckle. These incidents negatively affect rail traffic and cause train delays. In Czechia, we identified 8,155 broken and 455 buckled rail incidents over a period of 21 years. 78% of broken rails occurred in winter months (between November and March) and 83% of buckled rails in summer (between June and August). To verify the effect of air temperature on the occurrence of these problems, we built a logistic regression model that included several factors such as air temperature, rail traffic intensity, maximum train speed or railway line geometry. We found that air temperature is an important factor as a 1 °C decrease in minimum daily air temperature (Tmin) increased the odds of a broken rail by 13% and a 1 °C increase in maximum air temperature (Tmax) increased the odds of buckled rails by 38%. The results are particularly relevant regarding climate change. It can be expected that if no measures are taken, with increasing average air temperature, the number of broken rails will decrease in the future, and the number of buckled rails will increase in comparison to the current situation. While the first case can be assessed as a positive change, the second cannot. This trend is also obvious from the data. Between 2013 and 2022, there were on average half as many broken rails as between 2002 and 2012. Buckled rails were then mainly linked to temperature extremes, such as heatwaves in 2006 or 2015. The findings may help rail infrastructure managers or other stakeholders better understand the occurrence of these incidents or may serve as a basis for further research.
How to cite: Nezval, V., Andrášik, R., and Bíl, M.: The effect of air temperature on the occurrence of broken and buckled rails, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11096, https://doi.org/10.5194/egusphere-egu26-11096, 2026.
Severe storm events pose a growing threat to urban infrastructures. In particular, falling trees can block streets, which significantly disrupts the functionality of the road network and limits the operability of emergency services. Here we present framework to assess this impact of severe storm scenarios on the road network of the city of Brunswick, Germany.
For our assessment, we apply fragility curves for trees to estimate the probability of failure under a certain storm scenario. We use fragility curves that are parametrized on tree height classes. To translate tree failures into road blockage, we define a closure logic which determines if a fallen tree results in a blocked road segment by combining information on tree height and road width. For this, we use tree height data from the city tree cadaster and estimate road width by measuring the width of representative, single lanes for several road class types in OpenStreetMap.
We construct a probabilistic map of road closures across the urban network for the selected storm scenario using a reliability-based approach by combining the individual failure probabilities of all trees located along a road segment. This probabilistic closure map is converted to a deterministic disruption map by drawing a random sample of open or closed streets based on their calculated probability of failure, resulting in one realization of a disrupted road network for the city. The cascading impact on emergency service response is illustrated by calculating isochrones for ambulance dispatch locations, such as fire stations. Finally, we compare the isochrones of the disrupted network scenario with the normal scenario, which allows us to quantify changes in accessibility of emergency services.
The presented framework provides a quantitative measure of the robustness of the city road network for tree-induced road closures under extreme storm events. It supports the identification of critical roads and thus enables the systematic assessment of cascading effects on emergency service accessibility. Overall, the framework is helpful for risk-informed urban planning, emergency preparedness and adaptation strategies.
How to cite: Bashary, W. and Mager Pozo, A. M.: Storm-Induced Tree Failures and the Effect on Emergency Service Accessibility in Brunswick, Germany, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5357, https://doi.org/10.5194/egusphere-egu26-5357, 2026.
Extreme storms and floods increasingly act not as isolated hazards but as systemic disasters with effects that propagate through interconnected networks of critical infrastructure, generating cascading technological, environmental, and societal disruptions. Within the framework of the new EU Critical Entities Resilience (CER) Directive, which defines eleven essential critical sectors, there is still limited understanding of how flood-storm events trigger cross-sector impact chains rather than single-infrastructure damage.
This work studies multiple European extreme events to identify how impacts propagate across CER sectors, highlighting interdependencies between them. Using a harmonised database of documented disruptions derived from field surveys, scientific publications, operator reports, official bulletins, and post-event studies, impacts are classified in categories and mapped as interdependent impact chains linking energy, transport, water, wastewater, health, digital communications, public administration, food production, and other sectors.
Across extreme events, consistent cascade patterns emerge. Flood- and landslide-induced damage to transport corridors and electricity distribution repeatedly initiates secondary failures in drinking-water supply, wastewater treatment, hospital functionality, telecommunications, food processing, and emergency response. Water-system failures in turn drive public-health crises through environmental contamination and epidemics, while dam damage and long-term inundation propagate into agricultural collapse and food-supply disruption. Environmental effects extend the footprint of disasters beyond flooded areas and have the potential to persist long after waters recede. Evidence shows that even when inundation is spatially limited, networked dependencies allow service outages and socio-economic impacts to spread regionally or nationally.
The results demonstrate that energy, water, and transport repeatedly function as dominant cascade initiators, while they stand together with health, food, public administration, and digital services acting as cascade effect receivers. These findings imply that CER-based risk assessments must move beyond single-sector exposure mapping and classic flood hazard simulation towards a more dependency-aware analysis of cross-sector failure pathways, enabling more realistic preparedness, and resilience planning under a changing climate.
How to cite: Diakakis, M., Besiou, V., Kapris, I., Deligiannakis, G., Falaggas, D., Andriopoulos, P., Gkika, A., and Sarantopoulou, A.: Extreme flood and storm impacts propagation: Multi-event evidence of cascading disruptions and interdependencies across critical entities’ sectors. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5484, https://doi.org/10.5194/egusphere-egu26-5484, 2026.
The resilience of interconnected critical infrastructure systems remains poorly assessed, as are the social and economic impacts of their disruptions. The increase of interdependencies between systems and the emergence of new infrastructure types, such as for renewable energy infrastructure, add further complexity to existing systems. However, a main challenge in addressing the systemic risk of disrupted critical infrastructure is the lack of freely available and consistent data about its impacts. To address this gap, we develop a prototype database on the impacts of infrastructure disruptions in Europe that occurred in the last two decades. We focus on large-scale climate hazards: riverine and coastal floods, severe storms, droughts, heatwaves, and wildfires. For building the database, we leverage an interdisciplinary approach that blends natural language processing with geospatial analysis and network modelling. Our database combines information extracted from scientific publications and newspaper articles by means of an automated framework that orchestrates different language models and their specific tasks. This approach facilitates the extraction of information on infrastructure disruptions within the transport, energy, social, water, and waste treatment sectors, along with their cascading impacts. The reliability of our framework is strengthened by a thorough evaluation of its models and the traceability of the extracted impact data by the user. In addition, we benchmark the ability of our framework to extract such complex information against Google’s LangExtract, a Python library to retrieve structured information from various text sources. The output of our framework is a dataset on the affected critical infrastructure type, its location, and damage type, along with its cascading impacts on other infrastructure components and socioeconomic effects caused by its disruption. In a later step, we enrich our data with information from other state-of-the-art disaster datasets to generate a freely accessible infrastructure impact database comprising climate hazard, exposure, and vulnerability information at a high spatial resolution for Europe. This database will facilitate the analysis and modelling of systemic risks from disrupted critical infrastructure.
How to cite: Buch, A., Kreibich, H., and Cominola, A.: Developing an impact database of climate-related damage to critical infrastructure and cascading socioeconomic effects, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7021, https://doi.org/10.5194/egusphere-egu26-7021, 2026.
Flood risk management commonly relies on structural exposure assessments, with a strong emphasis on the built environment. However, the relationship between exposure and observed flood impacts, such as economic losses, remains uncertain. In particular, the role of population exposure in explaining flood impacts is often underrepresented in large-scale risk assessments.
This study presents an integrated national-scale analysis of flood exposure in Sweden, explicitly comparing the explanatory power of population-based and building-based exposure metrics across two flood hazard scenarios. Using high-resolution geospatial datasets combined with empirical insurance claims data, flood exposure for buildings and populations was quantified and analyzed at municipal and regional scales.
The results show that population exposure exhibits a stronger relationship with observed flood impacts than building exposure, particularly under more severe flood scenarios. Economic losses, represented by total insurance compensation, were better explained by population-based exposure metrics than by structural exposure alone. These findings highlight the importance of human occupancy patterns and dynamic population distributions in shaping flood impacts.
Overall, the study demonstrates that integrating population exposure into flood risk assessments provides more robust insights into observed flood losses, supporting improved risk-informed decision-making, preparedness planning, and resilient flood risk management strategies.
How to cite: Karagiorgos, K.: Population versus Building Exposure in Flood Risk Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6818, https://doi.org/10.5194/egusphere-egu26-6818, 2026.
Since satellite altimetry began in 1993, global mean sea level has risen by approximately 10–11 cm over the past three decades, accelerating coastal erosion and shoreline retreat worldwide. In many coastal regions, the inland migration of shorelines is constrained by fixed artificial structures such as seawalls and urban development, resulting in a phenomenon known as coastal squeeze. Despite its relevance for beach-dependent economies, empirical assessments linking coastal squeeze to tourism dynamics remain limited.
In this backdrop, we aim to quantitatively examine how climate change–induced spatial compression affects beach availability and coastal tourism across island and coastal nations highly dependent on beach tourism over the period 1995–2022. Using monthly Landsat imagery, we construct a Potential Beach Availability Index (PBAI) by identifying water bodies and artificial built-up surfaces based on NDWI and NDBI and excluding them from total land area within 1 km and 10 km inland buffers from national coastlines. The two buffer distances distinguish shoreline-adjacent space directly relevant for beach use from broader inland space reflecting longer-term migration potential under coastal squeeze. We then link the satellite-derived PBAI to tourism statistics from the UN World Tourism Organization (UNWTO), focusing on international tourist arrivals staying at least one night during the same period.
Our results reveal a pronounced decline in PBAI after 2013, indicating a substantial reduction in potentially usable coastal space. In contrast, international tourist arrivals continued to increase until 2019, reflecting a global rise in travel demand. Using two-way fixed-effects panel regressions to control for country-specific heterogeneity and common global time trends, we find that PBAI within the 1 km buffer is positively associated with tourist arrivals, whereas PBAI within the 10 km buffer exhibits a negative relationship. This spatial asymmetry suggests that tourism demand is more sensitive to the availability of land in close proximity to the shoreline than to broader inland space.
By explicitly quantifying coastal squeeze and linking it to tourism outcomes, this study demonstrates that continued growth in tourism demand may mask underlying spatial constraints on beach resources. The findings underscore the importance of accounting for coastal space limitations in sustainable tourism planning and climate adaptation strategies for vulnerable coastal destinations.
How to cite: Baek, S. and Yoon, H.: How Coastal Squeeze Reshapes Beach Availability and Tourism Demand, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8419, https://doi.org/10.5194/egusphere-egu26-8419, 2026.
We present a stochastic hydro-financial modeling framework that produces probabilistic forecasts of post-fire costs attributable to altered watershed hydrology under different wildfire regimes, estimating impacts borne by flood-control infrastructure managers and downstream communities. We then outline a practical framework for mobilizing capital from flood control infrastructure managers to finance forest management strategies that reduce wildfire risk via an Environmental Impact Bond (EIB). Our approach is valuable because economic assessments can emphasize direct wildfire damage while underrepresenting the long-term costs after an event including sedimentation in downstream infrastructure, elevated flood risk, and degraded water quality. This gap is particularly consequential for public entities that manage flood control infrastructure like debris basins and flood control channels and thus shoulder a large portion of post-fire sediment and water-quality management costs. Forest management strategies such as fuels reduction along high-risk corridors offer a pathway to reducing these wildfire costs by lowering fire occurrence and severity. However, entities hoping to implement these strategies can find it difficult to 1) raise the large volumes of capital needed to implement measurable changes and 2) justify the required expenditure without a robust assessment of cost effectiveness. To address these barriers, our model implements historical records of infrastructure maintenance, sediment accumulation and rainfall with wildfire simulation results to generate metrics indicating the benefits of an intervention. We then show how these results can be used to structure an EIB, a financial instrument where private investors provide upfront capital for implementation and are repaid through savings realized by infrastructure managers. We demonstrate the approach by analyzing flood-protection infrastructure operated by the Riverside County Flood Control and Water Conservation District (in Southern California).
How to cite: Mangney, L., Brand, M., Jong-Levinger, A., Maurer, T., Saksa, P., and Raming, W.: Hydro-Stochastic Model to Inform the Design of Environmental Impact Bonds for Wildfire Resilience , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16005, https://doi.org/10.5194/egusphere-egu26-16005, 2026.
When major floods occur, they have an extensive impact across different sectors, such as residential areas, public infrastructure, and commercial properties. The commercial sector poses a particular challenge for damage assessment, as the assets are more heterogeneous than in the residential sector, and less information about flood impacts is available. This study presents novel damage data for the commercial sector, collected from 130 in-person surveys conducted after the 2021 floods in Belgium. This data includes information on hazard, exposure, vulnerability, emergency and precautionary measures, and both direct and indirect damage. After imputation of missing data, statistical analysis was applied including Spearman correlation rank and variance inflation factor.
With a median water depth of around 1.4 m, the analysis indicates that the maximum direct damage is one order magnitude higher than in the residential sector in the same area for the same event. Furthermore, the results show that the median revenue loss corresponds to approximately 25% of the reported direct damage. However, in some cases, revenue losses were even greater than 100% of direct damage, highlighting the importance of accounting for indirect impacts in damage assessments. After the event, the most popular precautionary measure was the adaptation of the use of floors for the exposed assets. In summary, this research combines field-based data collection with subsequent statistical analysis, to identify relationships between observed damage and underlying drivers. It also provides guidance for designing measures to enhance preparedness and resilience to future flood events.
How to cite: Ávila-Guzmán, M. P., Dewals, B., Kreibich, H., Archambeau, P., Erpicum, S., Pirotton, M., and Cools, M.: Flood impacts in the commercial sector: insights from field surveys in Belgium, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19258, https://doi.org/10.5194/egusphere-egu26-19258, 2026.
The impact of natural hazards is one of the most important inputs for assessingthe risk specific to each hazard, as well as for determining multi-risks. The longer the period over which impact assessments can be conducted, the more qualitative the modeling and predictions of the impact of future events will be.
As a part of the transboundary research project “Exploring the paths to cope with hydro-climatic risks in transboundary rural areas along the Prut Valley. A multi-criteria analysis”, this study presents the impact of hydro-climatic hazards on a regional scale, as a database collected from scientific literature, historical maps, regional chronicles, but also from digital archives of newspapers that are now available online. Thus, a database was created containing over 1500 records (between 1860 and 2010) on the impacts of floods, droughts, storms, blizzards, and hail across different social and economic sectors. Each entry represents an event and several associated characteristics, including date (start, end), location, affected sector, mitigating actions, a relative scale of impact magnitude, and data source.
The study area is located along the Prut River, which serves as the natural border between Romania and the Republic of Moldova. The rural spaces of this region possess distinct natural and socio-economic features that set them apart at the eastern border of the European Union, in the so-called „marginal livestock farming”: a farming-based economic profile, an aged population, a consistent rural exodus of young people, low transportation connectivity, high soil quality, and a propensity for soil erosion. The database was cartographically expressed by hazard type and period. For spatial extent, we used the administrative territorial boundaries from different periods in both countries
The complexity of the historical, political, and social evolution of the studied region (during the period between the two world wars, this territory was part of the Kingdom of Romania) resulted in varying levels of vulnerability, leading to different impacts from common hazards. Spatial clusters were identified for each hazard impact, and periods of severe social challenges, associated mainly with droughts, were identified, particularly in the first half of the 20th century.
How to cite: Margarint, M. C., Chiriac, I., Niculita, M., Bejan, I., Chelariu, O.-E., Botnari, A., Fedor, A.-D., and Bunduc, T.: Spatial and temporal patterns of the impact of hydro-climatic hazards in the transboundary Prut River Valley (Romania – Republic of Moldova) for the last 150 years, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16198, https://doi.org/10.5194/egusphere-egu26-16198, 2026.
