NH9.4 | Costs of Natural Hazards

NH9.4

EDI

Assessing the costs of the overall economic impacts, the costs of prevention and the costs of responses and measures to foster resilience to natural hazards supplies crucial information for decision-making practices in the fields of risk management and climate change adaptation. However, the lack of empirical impact data as well as the significant diversity in methods that are currently applied in costs assessments of different natural hazards and impacted systems make it difficult to establish comprehensive, robust and reliable cost figures. This also hinders comparisons of associated costs across countries, hazards and impacted sectors.
This session aims to highlight the challenges and advances on costs of various natural hazards (e.g. floods, droughts, earthquakes) around three main themes: post-event data collection, assessment methods and economic evaluation of natural risk management policies. The session will cover methodological and empirical aspects for the data collection and assessment of the various cost types (direct damage, indirect damage, health impacts, risk reduction costs as well as environmental). In particular, it may be interesting to discuss methods that take into account the dynamics of processes related to vulnerability and resilience. Also, we are interested in contributions that focus on the economic appraisal (e.g. Cost-Benefit Analysis) of risk reduction to natural hazards, risk transfers and adaptation to increasing weather risks that are due to climate change. Presentations are welcome for instance on model development, validation, uncertainty analysis, risk assessment frameworks as well as presentations about the application of damage models in case studies. Abstracts are sought from those involved in both the theoretical and practical aspects related to these topics.

Convener: Pauline Bremond | Co-conveners: Veit BlauhutECSECS, Frédéric Grelot, Viktor RözerECSECS, Lukas SchoppaECSECS
Orals
| Thu, 27 Apr, 08:30–10:15 (CEST)
 
Room 1.34
Posters on site
| Attendance Thu, 27 Apr, 14:00–15:45 (CEST)
 
Hall X4
Posters virtual
| Attendance Thu, 27 Apr, 14:00–15:45 (CEST)
 
vHall NH
Orals |
Thu, 08:30
Thu, 14:00
Thu, 14:00

Orals: Thu, 27 Apr | Room 1.34

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
Chairpersons: Pauline Bremond, Viktor Rözer, Lukas Schoppa
08:30–08:35
Data collection
08:35–08:45
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EGU23-13584
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On-site presentation
Jiwon Son, Eunbeen Park, Jiwon Kim, and Woo-Kyun Lee

Climate change is becoming a serious global problem every year as it intensifies, and increasing uncertainty and frequency of extreme weather is part of the problem that is getting worse. The Earth is getting warmer overall, but the frequency of extreme cold waves is not decreasing, which can be a risk in many sectors. On February 2021, the worst cold outbreak in the United States has stopped the electricity supply to 5.5 million households in 18 states including factories as Samsung Austin Semiconductor. Factories, especially semiconductor-chip-factories, are sensitive to stabilized power supply, and unstable power supply might cause huge financial losses. Those unexpected extreme climate events hinder the estimation of future electricity demand, which can lower the accuracy of expected demand and interfere with secure power supply. Also, sudden snowfall and cold temperature can cause roads to freeze, disturbing the smooth transportation of materials and products. In this study, the unpredictability of cold waves was assumed as a hazard, and evaluating the adequacy of data to assess vulnerability to abnormal cold wave in industrial sector was done. The study was conducted in South Korea.

This study was done by first defining the abnormal cold wave using the difference between normal and observed temperatures during winter season in Korea (November to April). Then, the relations between the power supply reserve ratio and the degree of abnormal cold wave was identified using regression models. The degree was decided as distance of observed from normal temperature data. Also, chronically frozen section of roads provided by Ministry of the Interior and Safety(ROK), was also included as data for assessing vulnerability. Categorizing an assessment was approached by following the IPCC risk assessment methodology, which classified chronically frozen sections of roads as ‘exposure’, the degree of abnormal cold wave as ‘vulnerability’ from stable power supply, and cold weather itself as ‘climate.’ As a result, compared to SSP1-2.6 scenario, frequency and degree of abnormal cold wave has slightly increased overall in the scenario SSP5-8.5. Also, chip factories in Cheongju, Yongin and Icheon for example, has at least three chronically frozen sections within 5 kilometers from the factories, average 7 sections within 10 kilometers. This study has a point in focusing on the non-decreasing, unusual cold waves despite the increasing temperature and reviewing data before assessing vulnerability of cold wave in industry. The result may be useful by offering additional methods and categories in evaluating vulnerabilities and risks to the party concerned, which can be used by working groups in making climate change adaptation plans in industrial sectors.

 

Keywords: climate change, cold wave, IPCC risk assessment, vulnerability, industrial sector, stable power supply, SSP scenario

Acknowledgements: This work was supported by Korea Environment Industry & Technology Institute (KEITI) through “Climate Change R&D Project for New Climate Regime (RE202201934)”, Funded by Korea Ministry of Environment (MOE).

How to cite: Son, J., Park, E., Kim, J., and Lee, W.-K.: Data Review for Assessing Vulnerability to Abnormal Cold Wave in Industrial Sector due to Climate Change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13584, https://doi.org/10.5194/egusphere-egu23-13584, 2023.

08:45–08:55
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EGU23-13743
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On-site presentation
Daniela Molinari, Chiara Arrighi, Francesca Da Porto, Alessio Domeneghetti, and Annarita Scorzini

Floods are growing phenomena both in terms of intensity and frequency, due to climate change and rapid urbanization. In fact, several extreme flood events hit populations and assets around the Globe in recent years; one example is the exceptional flood that it the Marche region (Central Italy) between the 15th and 16th of September 2022, with rainfall reaching local cumulated peaks of 400mm. The intense precipitation triggered widespread landslides, as well as the flooding of several rivers; the short warning that characterized the event prevented the implementation of mitigation measures, causing 12 fatalities and severe damages to activities and buildings.

In the aftermath of the event, several Italian universities and private companies mobilized to conduct an intensive field survey, to collect data enabling a better understanding of the causes of the event, the involved physical phenomena as well as factors leading to damage (https://sites.google.com/view/misa2022/home-page). This contribution describes the activity carried out by 6 of them (i.e., 5 universities and an engineering company) aimed at the survey of the damage occurred to the various exposed assets (such as residential buildings, economic and agricultural activities, infrastructure, and cultural heritage). The survey campaign was carried out between October and December 2022 in the municipalities of Senigallia, Ostra and Tre Castelli, where 126 residential buildings, 135 economic activities (manufacturing and commercial), 12 cultural heritage sites and a little number of agricultural activities were investigated. A preliminary descriptive analysis of collected data shows that the water depths recorded in correspondence of the exposed elements frequently exceeded 1 m and, in some cases, reached 3 m, causing severe damage. The most affected buildings are, almost 3 months after the event, still uninhabited and damaged; while some economic activities are not able to reopen. Most of them suffered widespread damage to buildings, stock, and equipment and were not insured. With respect to agriculture, mainly fruit and vegetable companies suffered damage, while fields of cereal and oleaginous plants production were bare, limiting the damage to the soil. For what concern the cultural heritage, the damage was concentrated in assets such as churches, Roman bridges, and examples of industrial archaeology. However, more quantitative results will be available at the time of the conference. Data collected in this project will be used in future analyses both for understanding the main vulnerabilities of the affected area and for developing and improving damage models for more effective risk management, in planning and emergency phases.

Acknowledgement: authors acknowledge with gratitude all the researcher involved in the field survey campaign and data analysis that were not nominated due to space issues.

How to cite: Molinari, D., Arrighi, C., Da Porto, F., Domeneghetti, A., and Scorzini, A.: The record-breaking flood in Central Italy in September 2022: preliminary impacts analysis from a field survey campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13743, https://doi.org/10.5194/egusphere-egu23-13743, 2023.

Economic appraisal
08:55–09:05
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EGU23-7503
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ECS
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Virtual presentation
Stefano Bruzzese, Simone Blanc, Filippo Brun, Battista Taboni, Gessica Umili, and Anna Maria Ferrero

Forests can effectively mitigate rockfall risk in mountainous contexts, acting as “nature-based solutions” (NBS). However, the use of artificial structures, for example, rockfall barriers, is usually necessary and complementary to ensure continuous and effective protection of specific elements at risk. In this work, we evaluate the forest protection service and the complementary effectiveness between NBS and rockfall barriers. The case study analysed, known as Alpe di Bazena, is located in the Italian Alps (municipality of Breno); it is a coniferous forest of about 8 hectares that, together with existing flexible barriers, protect from recurrent rockfall phenomena the underlying provincial road SP 345. At present, the forest partly fulfils its protective role, having been damaged by storm Vaia in 2018. Results from recent studies focused on the identification of rockfall source areas and block volume distribution were used for characterizing rockfall phenomena. For the economic evaluation of the forest protection service, the ASFORESEE model was used and a scenario analysis was carried out with four different levels of protection desired by stakeholders: 25, 50, 75 and 100%. The results show the effectiveness of the forest protection for all scenarios, with an estimated annual unit value of approximately 7,000 € ha-1 y -1 for both the first three scenarios, where the role played by the forest is sufficient, and in the last scenario, where an undersized rockfall barrier is required to complement the forest's action. This study proves quantitatively that the integration of green and grey measures could represent an optimization strategy in terms of costs and environmental benefits when dealing with rockfall phenomena.

How to cite: Bruzzese, S., Blanc, S., Brun, F., Taboni, B., Umili, G., and Ferrero, A. M.: Integrating green and grey measures for rockfall protection: technical and economic aspects, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7503, https://doi.org/10.5194/egusphere-egu23-7503, 2023.

09:05–09:15
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EGU23-2832
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On-site presentation
Ronny Klæboe and Unni Eidsvig

A prototype tool (DynEcon) for dynamic societal cost benefit analyses was used to produce simple estimates of future costs of traffic disruption caused by one or more rail and road bridge failures from 100-year flooding(s) in the Santarem Region. The focus was on quantification of different types of consequences. A project period until year 2100 was chosen to include adverse events in the far future. Future private and professional vehicle flows before and after disruptions were calculated for 36 scenarios considering declining rural and semi-rural populations destinations and increasing GDP over time. Potential cascading effects from detours and mode transfer at future time points were estimated. The additional fuel and vehicle costs for personal cars and trucks, time losses for professional and private drivers, and external costs for rural and semi-rural population subjected to increased traffic were estimated. The sizes of these costs, depend on the size and composition of the vehicle fleets at time of each disruption. Local and global emissions from fossil fuels the next twenty years will be reduced as the older most polluting vehicles in the vehicle fleets are phased out and newer vehicles must satisfy even more stringent emission and design standards. In addition, EC greening policies and electrification will reduce the amounts of combustion related pollutants dramatically. Prices of Diesel and Petrol were assumed to increase over time. The costs of accidents have decreased due to improved protection from the vehicles and is predicted to continue to decrease due to more intelligent vehicles and smart road infra-structure. Noise, air-pollution due to road wear, and road maintenance costs per km were assumed to remain stable. Costs of CO2-emissions and time delay costs of private and professional drivers were modelled as increasing over time. The additional disability-adjusted life years(DALYs) from local air pollution and noise, were estimated using exposure effect relationships and DALY impact estimates from WHO. A monetary DALY-value was assigned, and the sum costs calculated. To harmonize cost estimates for Portugal having a lower GDP than Norway, costs were scaled down.

The dynamic cost benefit tool applies Monte Carlo simulations in a two-step procedure. In the first step a population of e.g. 1000 sets of 100-year flooding events occurring between 2021 and 2100 are generated using knowledge on climate change, flooding characteristics, scour etc. Future annual costs until 2100 are generated using growth models. Since all parameters and growth models are associated with uncertainties, the second step derives the uncertainty distribution of economic result indicators and confidence intervals. An online web-based Monte Carlo framework such as DynEcon could enable researchers to cooperate on different parts of the patchwork necessary for analyses of resilience policies that include hazards occurring late century.

How to cite: Klæboe, R. and Eidsvig, U.: Using a Monte Carlo framework for assessing future costs of major transport disruptions from seldom occurring natural hazards, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2832, https://doi.org/10.5194/egusphere-egu23-2832, 2023.

09:15–09:25
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EGU23-15423
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ECS
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On-site presentation
Jan Hassel, Thomas Vogt, and Christian Otto

Tropical cyclones are among the meteorological and climatological extreme events with the largest economic impact worldwide, although they only affect coastal areas in certain geographical latitudes. At the same time, anthropogenic climate change affects the characteristics of tropical cyclones: they move more slowly, achieve greater intensities and reach higher latitudes more frequently.

In view of these complex changes, there is great demand for models assessing the economic impact of tropical cyclones that are not based on simple macroscopic indicators. In a so-called event-based approach, a spatially and temporally resolved representation of a single tropical cyclone is blended with spatially resolved data on the distribution of economic capital. Thus, even complex changes in storm characteristics can be included in the impact assessment.

The vulnerability of affected regions is expressed through impact functions that relate loss of economic capital to a storm’s local wind speed. These impact functions are calibrated against historic damage databases and then applied to hypothetical storm scenarios for risk analysis or climate change forecasting.

This research aims at the calibration of impact functions that explicitly depend on the per capita income of the affected region. For this purpose, a United States damage database identifying impacts at the county level is introduced, allowing the investigation of the statistical relationship between vulnerability and per capita income of affected counties.

A quantitative formulation of the income dependence of vulnerability will not only improve the overall predictive quality of event-based models, but also enhance the understanding of the impact of tropical cyclones on social inequality.

We find that vulnerability is highest in the poorest affected regions, indicating the extraordinary relevance of tropical cyclones on low-income coastal communities. Furthermore, we can show that vulnerability mostly declines with per capita income.

How to cite: Hassel, J., Vogt, T., and Otto, C.: Income-Specific Vulnerability in Event-Based Models for the Impact Assessment of Tropical Cyclones, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15423, https://doi.org/10.5194/egusphere-egu23-15423, 2023.

09:25–09:35
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EGU23-5795
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ECS
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Highlight
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On-site presentation
Vanessa Völz and Jochen Hinkel

There is wide consensus that many adaptation decisions are multi-stage decisions shaped by future learning through observations, as the growing literature of adaptation pathways shows [1]. However, most methods for economic appraisal of adaptation decisions (e.g. cost-benefit analysis) do not consider future learning through observations. Methods that do consider future learning through observations (e.g. real-option analysis [2] and optimal control studies [3]) require specific projections of critical variables (e.g. sea level rise or precipitation), which we will call learning scenarios [4]. Learning scenarios are a generalisation of static projections (used by cost-benefit analysis) in that they do not only provide trajectories of values of future critical variables as seen from today, but also as seen from future moments in time (e.g., sea level trajectories from 2050 onwards assuming that, e.g., 40 cm of sea level rise has been experienced until 2050). Such learning scenarios are not publicly available, instead, scientists independently generate them based on static projections. The consideration of learning scenarios in adaptation decision-making results in adaptive adaptation strategies, which plan future adaptation decisions conditional on actual future observations. The crucial benefit of such methods, in contrast to traditional cost-benefit analysis, is that they quantify the value of future learning in combination with flexible adaptation options and thereby justify whether implementing flexible adaptation options today are worth the extra costs, or if waiting for further knowledge is beneficial [5]. This can lead to reduced adaptation costs compared to traditional methods that ignore future learning through observations. This contribution i) presents a novel method to generate learning scenarios; ii) applies this method to generate learning scenarios for sea level rise based on AR6 and iii) applies this learning scenario within a case study in Lübeck at the Baltic sea to evaluate adaptation and flood damage costs.

 

References

[1] Werners, S., Wise, R., Butler, J., Totin, E. and Vincent, K. (2021). Adaptation pathways: A review of approaches and a learning framework. Environmental Science & Policy, Volume 116, Pages 266-275. https://doi.org/10.1016/j.envsci.2020.11.003.

[2] Ginbo, T., Corato, L.D. & Hoffmann, R. (2020). Investing in climate change adaptation and mitigation: A methodological review of real-options studies. Ambio, 50(1):229–241.

[3] Herman, J.D., Quinn, J.D., Steinschneider, S., Giuliani, M., Fletcher, S. (2020). Climate adaptation as a control problem: Review and perspectives on dynamic water resources planning under uncertainty. Water Resources Research, 56. doi:10.1029/2019wr025502.

[4] Hinkel, J., Church, J.A., Gregory, J.M., Lambert, E., Cozannet, G.L., Lowe, J., McInnes, K.L., Nicholls, R.J., Pol, T.D., Wal, R. (2019). Meeting user needs for sea level rise information: A decision analysis perspective. Earth's Future 7, 320–337. doi:10.1029/2018ef001071.

[5] Kind, J. M., Baayen, J. H., & Botzen, W. J. W. (2018). Benefits and limitations of real options analysis for the practice of river flood risk management. Water Resources Research, 54 (4), 3018–3036. doi:10.1002/2017wr022402.

How to cite: Völz, V. and Hinkel, J.: Learning Scenarios: A New Method for the Economic Appraisal of Adaptation Decisions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5795, https://doi.org/10.5194/egusphere-egu23-5795, 2023.

09:35–09:45
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EGU23-17207
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ECS
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On-site presentation
Mara Ruf, Amelie Hoffmann, Daniel Koutas, and Daniel Straub

Floods are one of the most hazardous natural phenomena in Germany, which calls for thorough and comprehensive flood risk mitigation strategies. Considering this, a series of controlled flood detention basins, so-called flood polders, are planned along the Danube as one part of the Bavarian flood protection program 2020plus. By means of a reduction of the peak discharge of large flood events, flood polders can reduce the load on downstream located flood protection structures and therewith lower the probability of dike breaches.

A cost-benefit analysis is used to evaluate the economic efficiency of a flood polder location. Therein, the costs of construction and maintenance of the polder are compared with the expected monetarized flood risk reduction over the lifetime of the polder. However, assessing the economic consequences of flood risk on a trans-regional level to quantify the benefit of the flood protection measure is challenging and subject to significant uncertainties. These include uncertainties on the characteristics of the hydrological inputs and their occurrence probability in the future, on the material characteristics and resistances of the dike structures, on population and asset developments, on the economic impacts of flooding, on the discount rate as well as on model choices and simplifications.

This highlights the necessity of conducting a thorough uncertainty and sensitivity analysis. Since our model serves to support decision-making, it seems natural that the sensitivity of the benefit-cost ratio to input and model uncertainties should be measured in the context of this decision. Decision sensitivity measures have been proposed [1], however, to our knowledge they have not been applied to the assessment and management of natural hazards. In this contribution, we utilize the expected value of information for sensitivity analysis on the cost-benefit analysis of a flood polder at theDanube River in Bavaria.

[1] Felli, J. C., & Hazen, G. B. (1998). Sensitivity Analysis and the Expected Value of PerfectInformation. Medical Decision Making, 18(1), 95–109.

How to cite: Ruf, M., Hoffmann, A., Koutas, D., and Straub, D.: Decision-related sensitivity analysis of a flood risk model assessing the benefit-cost ratio of a flood polder at the Bavarian Danube, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17207, https://doi.org/10.5194/egusphere-egu23-17207, 2023.

09:45–09:55
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EGU23-3034
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ECS
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Highlight
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Virtual presentation
Szu-Yun Lin and Chia-Hung Wang

Owing to the aging of built environment, many cities are facing the increasing of disasters impact and risk. Reinforcing the existing buildings is one common strategy. This study aims to provide a reference for the reinforcement plan of private buildings through life cycle cost and benefit analysis from the perspective of the society as a whole. First, the seismic reinforcement strategies in different countries are reviewed for identifying suitable target buildings. The total annual earthquake loss related to the characteristics of building is assessed through the capacity spectrum method, fragility curves, and probabilistic seismic hazard analysis. The construction cost and reinforcement cost are estimated by historical data, and then the equivalent uniform annual cost method is used to analyze the life cycle cost of a certain reinforcement strategy. The privately owned buildings in Taipei City, Taiwan were analyzed to demonstrate the proposed method. The priority of reinforcement was determined by different vulnerability and risk measures of each building, and four different reinforcement strategies were compared in the case study. The results show that the proposed method can provide an objective reference for arranging the reinforcement order and economic-effectively reducing the impact of earthquakes on the whole community.

How to cite: Lin, S.-Y. and Wang, C.-H.: Life Cycle Cost Analysis of Seismic Reinforcement Plans, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3034, https://doi.org/10.5194/egusphere-egu23-3034, 2023.

Multi-hazard
09:55–10:05
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EGU23-13001
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ECS
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On-site presentation
Tara Evaz Zadeh, Laurens Jozef Nicolaas Oostwegel, Lars Lingner, Simantini Shinde, Fabrice Cotton, and Danijel Schorlemmer

Effects of a hazard can be expressed in terms of the losses and damages caused by it. These risk assessments help decision makers and disaster managers to better prepare for and cope with the disasters arising from hazards in all three phases (preparation, response and recovery) of disaster risk reduction and resilience. With the growth of disaster risk globally (GAR, 2022), and also the related research on different components of risk (hazard, exposure, vulnerability), there is a rising demand to compute risk for multi-hazard events, for which an integrated tool is very beneficial, but most of the tools used for multi-hazard risk assessment purposes are not available for public use (Cees J. van Westen and Stefan Greiving, 2017).

The ‘risk-calculator’ is an open-source Python program that enables users to do multi-hazard scenario risk assessments. This program is  capable of assessing loss and damage for different sets of discrete or continuous vulnerability or fragility functions for different concurrent hazards, such as floods, earthquakes and tsunamis.

The three main inputs are: (1) hazard, expressed as an intensity field (e.g ShakeMap for earthquakes or inundation field for tsunamis and floods), (2) the exposure model provided in a geospatial database or as CSV files to be imported, and (3) vulnerability/fragility functions describing the level of loss or damage at different intensity measure levels dependent on the asset taxonomy and the hazard type. The tool works on basis of the standard taxonomy as defined by the Global Earthquake Model. This taxonomy can also be expanded to include damage states of previous events for a loss computation of cascading events such an earthquake followed by a tsunami.

Apart from using the program directly, users can connect to the API designed for this program to run loss assessments. The resulting losses and damages are provided in a geospatial database (SpatiaLite or GeoPackage), for sake of easier handling and plotting. This user-friendly program provides database views, connecting data in a meaningful way from different tables to allow for various ways of analyzing and visualizing the loss and damage assessments.

How to cite: Evaz Zadeh, T., Oostwegel, L. J. N., Lingner, L., Shinde, S., Cotton, F., and Schorlemmer, D.: ‘risk-calculator’: a tool for multi-hazard risk assessments, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13001, https://doi.org/10.5194/egusphere-egu23-13001, 2023.

10:05–10:15
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EGU23-8868
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On-site presentation
Derya Deniz, Ahmet Buğra Ceyhan, Yasamin Moaiyedfar, and Ramin Sheikhi Garjan

Floodings and debris flows (mudflows) are the most frequent natural disasters provoked by heavy rainfalls, leading to significant physical damage to the built environment, severe economic losses, and social disruptions in communities. To promote disaster resilience of communities, sophisticated models are needed to support citizens in assessment of potential hazard losses and taking proper disaster mitigation actions. This study thus develops a framework to support the "multi-hazard resilience" of EU residential building stocks under rainfall-triggered floods and mudflows. It considers two levels of resolution for resilience assessment: at the local level of individual buildings versus at the level of building portfolios in a community. First, a typical EU residential building set was created and disassembled into components. The damage potential of each structural, nonstructural, and content component of the buildings was examined for various hazard depths and velocities of flooding and mudflow actions. Repair cost and time for each damaged component were obtained considering the individual failure limit of the components. Then, all components and associated variabilities were probabilistically assembled to estimate the total losses and repair times on residential buildings. Next, the developed impact models for individual buildings were extended into models for building portfolios, considering a virtual EU community under multi-hazard scenarios of flooding and mudflow. The effects of uncertainties associated with building and hazard properties were considered, and spatial correlations in hazard demand and common building configurations and practices were reflected in an aggregated impact and resilience assessment of building portfolios. Lastly, several retrofit actions were explored to understand their effects on flood or mudflow impacts for residential buildings. The "optimum retrofit strategies" were investigated for both individual buildings and building portfolios by performing benefit analyses on repair costs and times.

Results show that, while water/mud contact can cause severe damage to the interior building and content items, physical flood and mudflow load actions may cause significant damage to the exposed exterior building components. They may lead to high hazard losses and long repair times, especially for buildings with finished basements. The impact models developed for building portfolios show that neglecting spatial correlation in losses and repair times due to commonality in hazard demand and building performance may underestimate the overall loss and recovery time assessments for the lower probabilities of exceedance, the region of significance for public safety and insurance underwriting purposes. Moreover, benefit analyses on retrofit actions to reduce hazard impacts show that most of these actions cannot perform adequately on their own, but if grouped together as a package, they may be more effective and useful solutions. To conclude, this study brings an innovative resilience framework that greatly contributes to different stakeholders, including building owners seeking to mitigate their homes, reinsurance companies seeking to improve insurance portfolio risk policy, and government or research agencies seeking to improve disaster response and management plans.

ACKNOWLEDGEMENTS: One of the authors, Dr. Derya Deniz, acknowledges the support provided by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 893147.

How to cite: Deniz, D., Ceyhan, A. B., Moaiyedfar, Y., and Sheikhi Garjan, R.: A Multi-Hazard Resilience Framework for Residential Building Stocks subjected to Floods and Debris Flows, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8868, https://doi.org/10.5194/egusphere-egu23-8868, 2023.

Posters on site: Thu, 27 Apr, 14:00–15:45 | Hall X4

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Chairpersons: Lukas Schoppa, Viktor Rözer, Pauline Bremond
X4.68
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EGU23-27
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ECS
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On-site presentation
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Thijs Endendijk, Wouter Botzen, Hans de Moel, Jeroen Aerts, Kymo Slager, and Matthijs Kok

Natural disasters, such as flood events, are expected to increase in their frequency and severity, which results in higher flood risk without additional adaptation measures. The information gained from flood risk models is essential in flood risk management. However, vulnerability model components in the form of depth-damage curves are often a large driver of uncertainty and empirical vulnerability curves are rarely estimated due to a lack of damage data from flood events. This study uses a unique dataset with experienced damages and the implementation of flood damage mitigation (FDM) measures on the household level, collected after the flood event in the Netherlands in 2021. Two main findings emerge from an analysis of this dataset. First, depth-damage curves that control for several hazard, exposure and vulnerability indicators are estimated. These curves serve as an update to current input in flood risk models, where previous vulnerability estimates from the Netherlands are based from a flood event in the 1950s. Second, it is found that previous studies on the effectiveness of FDM measures are prone to a selection bias, as households that do and do not take FDM measures systematically differ in their risk profiles. By using an Instrumental Variable (IV)-estimation, this study overcomes this selection bias and finds significant reductions in flood damage to both buildings and household contents due to FDM measures.

How to cite: Endendijk, T., Botzen, W., de Moel, H., Aerts, J., Slager, K., and Kok, M.: Flood vulnerability curves and household flood damage mitigation measures: an econometric analysis of survey data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-27, https://doi.org/10.5194/egusphere-egu23-27, 2023.

X4.69
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EGU23-12202
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ECS
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On-site presentation
Natasha Petruccelli, Alessio Domeneghetti, Ludovica Marinelli, Maria Chiara Molino, and Armando Brath

Floods are one of the most frequent and widespread natural hazards globally. Over the past 20 years, the number of floods has more than doubled from the previous two decades, resulting in annual losses of around $40 billion worldwide. Among the various sectors exposed, agriculture is certainly the most vulnerable to events of this type, given its close dependence on weather conditions. However, although floods constitute the second most serious threat to agricultural areas, causing total production losses of up to 20%, their impacts are still difficult to assess. The perceived minor importance of agricultural losses compared to those of other assets (e.g. infrastructures, residential and industrial buildings, cultural assets), together with a lack of observations, have led to development of few approaches for crop damage assessment in case of floods, in most of the cases also characterized by considerable imprecisions.In compliance with the requests of the Floods Directive (Directive 2007/60/EC), a model has been developed to quantify the direct and tangible flood-related damages to the multi-year crops (such as vineyards and orchards). The loss of perennial plant material in the years following the flood and thus, the expected damage, is evaluated based on hazardous variables (e.g., water depth, inundation duration, season of occurrence, etc.), crop (e.g., typology, technological solutions, yield, etc.) and economic conditions (product price, production costs, etc.). The model relies on several damage curves, by means of which it is possible to estimate the total absolute damage for each flooded agricultural portion.The expert-based model has been developed referring to the Emilia-Romagna region (Northern Italy) and validated using real damage records collected after the flood of the Secchia river (2014). Results are convincing, reproducing the damage suffered by farmers with a good approximation (errors of about 12-20%).

How to cite: Petruccelli, N., Domeneghetti, A., Marinelli, L., Molino, M. C., and Brath, A.: Development, application and validation of a flood damage model for multi-year crops (vineyards and orchards)., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12202, https://doi.org/10.5194/egusphere-egu23-12202, 2023.

X4.70
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EGU23-3322
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On-site presentation
Florent Lobligeois and Guillaume Magnan
Natural hazards are a systemic risk for the insurance industry and the assesment of the stochastic losses covered by the underwritten policies is fundamental to ensure the insurance company solvability and the protection of its customers. AXA Group develops and operationnaly uses complex sophisticated modeling platorms to quantify the impact of natural events in terms of insured losses: from hazard physical-modeling to risk vulnerability and financial computations. Unfortunately, in practice, the loss assesments are strongly impacted by the model uncertainties (theoretically challenging and computationally expensive) and the quality of the input data.
A basic framework to quantify the impact of data quality on modeled loss results has been developed within AXA Group to produce pragmatic and operational loss best-estimates taking into account low-quality or unknown input data. This Data Quality Risk (DQR) framework which relies on four pillars, (i) availibility (ii) granularity (iii) completeness and (iv) reliability, is applied on a list of predefined risk drivers (risk characteristics, geocoding ...) and then loads the model results. The DQR methodology is operationally used for a financial solvability model and serves as an essential input to natural event loss assesment and (re)insurance protection purposes.

How to cite: Lobligeois, F. and Magnan, G.: How to deal with uncertain data for property loss assesment due to Natural Hazards ?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3322, https://doi.org/10.5194/egusphere-egu23-3322, 2023.

X4.71
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EGU23-6308
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Highlight
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On-site presentation
Morgane Terrier
LiveCat is a disaster response tool operationally used at AXA to provide impact assessment at group level within 24 hours of a natural event occurrence. It covers several natural catastrophe perils at a global scale: earthquakes, floods, cyclones, European windstorms, etc. Providing a rapid loss estimation is essential for operational purposes such as claims management and communication to key stakeholders, to quickly deliver a response proportional to the event’s magnitude and likely impact.
The overall methodology consists of (1) recovering or generating an alert according to a predefined threshold, (2) defining the event spatial characteristics and intensity, (3) identifying AXA customers and insured value within the event footprint, (4) modeling destruction rates and applying contractual terms (co-insurance, deductibles, limits, etc.), (5) estimating the claims number and associated losses and (6) generating the appropriate reporting and communication supports.
LiveCat is directly integrated within the modelling ecosystem deployed at AXA and its internal R&D and expertise on natural hazards. Several internal AXA tools are supporting this impact assessment platform: a global insurance contract database gathering 40m+ insured risks (with detailed physical, financial and coverage descriptions), an internal hazard and financial modeling platform (running internal cat models at event scale and producing loss estimates per risk), and our internal geospatial solution for Nat Cat underwriting.
Finally, LiveCat estimates are refined post-event and archived to consolidate the assessment of model backtesting and modelling methodology by matching actual collected claims and field feedback.

How to cite: Terrier, M.: LiveCat : Development of an internal global real-time disaster loss estimation tool, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6308, https://doi.org/10.5194/egusphere-egu23-6308, 2023.

X4.72
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EGU23-8379
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ECS
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On-site presentation
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Harriet E. Thompson, Bruce D. Malamud, Faith E. Taylor, Joel C. Gill, Robert Šakić Trogrlić, and Melanie J. Duncan

Reporting of hazard impacts in international disaster databases predominantly focuses on single hazard events and their direct impacts. Moreover, impacts on the urban poor are often excluded from these databases despite the disproportionate burden experienced by these communities. Here we describe a systematic approach to extract multi-hazard impact information from DesInventar Sendai. The study focuses on urban poor-centred impacts, in this case impacts on slums and squatter settlements, of past multi-hazard events that have affected Kathmandu Valley, Nepal.

First, we identified the main primary natural hazards of study: earthquake, fire, flood, and landslide. These hazards represent four of the five main hazard types (the fifth being epidemic which is categorised as a biohazard and is therefore omitted from this study) that could occur in Nepal as defined in the Nepal Ministry of Home Affairs Disaster Report 2017. The choice of these hazard types was affirmed by seven scoping interviews conducted in October and November 2022 with Kathmandu-based stakeholders working in academia, NGOs and the private sector. We then searched DesInventar Sendai for Nepal case study examples of past hazard events. We selected the region as “central region” and the districts as those comprising the Kathmandu Valley (“Bhaktapur”, “Lalitpur” and “Kathmandu”).

We created a database of single hazard and multi-hazard events divided into the following categories: earthquake, fire, flood and landslide. The location was supplemented by quantitative (e.g., indirectly affected, missing) and qualitative (e.g., comments about the event) impacts. Where available, the cause(s) and description of cause(s) were listed and categorised by group to enable an assessment of whether the event was multi-hazard and had cascading impacts.

Our results illustrate which impacts are associated with different single and multi-hazard types within slums and squatter settlements in Kathmandu Valley. Reporting of hazard impacts in DesInventar Sendai are focused on quantitative direct impacts, such as fatalities and losses in $USD, rather than indirect, intangible and/or qualitative descriptions of impacts which are limited to brief comments. Recorded hazard events are often limited to single hazards, or simple multi-hazard events (e.g., primary hazard triggering secondary hazard). This is reflected in a lack of reporting of interconnected or cascading impacts. Equally as important is the missing or incomplete data, and what this suggests about bias within the Nepal region database.

Our ongoing research will compare these DesInventar Sendai results with secondary loss and damage datasets documenting earthquake, fire, flood, and landslide events and their impacts on urban poor communities in Kathmandu Valley. These loss and damage datasets, collected by Kathmandu-based organisations, will be analysed using a systematic approach such as content analysis in NVivo. The comparison between the DesInventar Sendai and loss and damage datasets will assess to what extent it is possible to disaggregate these data by social groups within the urban poor, and whether these data sources can present a nuanced account of multi-hazard impacts.

How to cite: Thompson, H. E., Malamud, B. D., Taylor, F. E., Gill, J. C., Šakić Trogrlić, R., and Duncan, M. J.: Systematic extraction of urban poor-centred multi-hazard impacts from DesInventar Sendai: a case study of Kathmandu Valley, Nepal, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8379, https://doi.org/10.5194/egusphere-egu23-8379, 2023.

X4.73
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EGU23-15018
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ECS
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On-site presentation
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Lucile Bruhat, Hugo Rakotoarimanga, and Maxime Hersent

The insurance industry faces highly complex P&C challenges, among which natural catastrophe risk, also labeled as “CAT” risk. Among disasters, climatic and seismic events show large variability in size and frequency, with devastating consequences; not to mention climate change which brings added uncertainty for the future. Global insurance groups, such as AXA, must develop a sound understanding of the frequency, intensity, and impacts of natural hazard events, to protect their economic capital and ensure their solvency.

At the AXA Group Risk Management, the CAT modeling process consists in 1) collecting CAT exposure data (geographical, physical, and financial information) on a per-entity (AXA France, AXA Mexico…) and per-location basis (houses, factories, vehicles…) and 2) assessing the risk on a per-entity per-peril per-geography basis (cyclones, earthquakes, floods, hailstorms...) to finally aggregate it at Group level. This process constitutes a technical challenge through the data collection of 50 million of policies, the combination of multiple modeling solutions, and the production of millions of stochastic event losses. Alongside this process, the collection and analysis of “scenarios”, either historical events, or potential future disasters, improves the robustness and understanding of risk assessment. However, there is currently no unified and consistent database recording the characteristics of natural events (a unique identifier, their spatial and temporal extent, their intensities, and the location affected) and their actualized economic and industry impacts. This work aims at developing a database for that would first gather an exhaustive inventory of historical natural events (cyclones, storms, floods, earthquakes…) and, throughout the integration within the existing CAT modeling ecosystem, automatize model validation, back-testing, and risk analysis with respect to market and as-if losses. 

How to cite: Bruhat, L., Rakotoarimanga, H., and Hersent, M.: Developing a unified and consistent database for historical natural events, and subsequent losses, within a catastrophe modeling framework, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15018, https://doi.org/10.5194/egusphere-egu23-15018, 2023.

X4.74
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EGU23-7473
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On-site presentation
Pauline Bremond, Frédéric Grelot, Maxime Modjeska, David Nortes Martinez, and Justine Panégos
The analysis of impacts of climatic events on socioeconomic systems is based on the collection of post-event data. However, this method rarely describes the processes and the decisions that generated the impacts. Yet, counting on thorough descriptions of those processes and decisions, although very time-consuming, takes on its full meaning when several climatic phenomena follow one another on complex economic systems.

In the Mediterranean context, and moreover in the context of climate change, it is not uncommon for several climatic hazards to follow one another. For agricultural activities, whose harvests and thus added value are produced over several months, this implies that a production campaign can be affected by different events (e.g. frost, hail, drought, flooding, etc.), causing the strategy of the various actors involved to be readjusted.

We propose to address the problem of the analysis of the succession of two climatic events for the estimation of the impacts on a complex economic system through the case study of a wine cooperative located in the department of Aude in the South-West of France which was affected during the 2021 production campaign by a frost in March and a flood in September at the time of the harvest.

We are interested in three questions: (i) are there impacts resulting specifically from the succession of both climatic events?; (ii) are there impacts resulting from the organisational links between the winegrowers (individual level) and the wine-making cooperative (collective level)?; (iii) which indicators are relevant to highlight them?

In our case study, the cooperative winery brings together 128 winegrowers representing 1100 ha and has three vinification sites. 65 winegrowers out of the 128 were impacted by at least one of the events. To analyse the impacts of both events on the cooperative, we carried out a questionnaire-type survey among the affected winegrowers. We obtained 57 responses to the preliminary questionnaire and 33 exhaustive interviews. Three interviews were also conducted with the managers in charge of the winery during this campaign. After an initial analysis of the results, we presented and discussed these results with the representatives and some of the winegrowers surveyed.

The consolidation of the analyses is still in progress. However, this work already shows that there are cross-effects resulting from the succession of both events. For instance, our surveys enable us to discern the loss of quality or yield due to biophysical processes (e.g. frost, berries' rotting or bursting) from loss of quality due to organizational impacts at the winegrower level (e.g. inaccessibility of the plots at the time of harvesting due to flooding that aggravates the loss of quality). We also show that the succession of events generated specific impacts linked to collective readjustment decisions taken at the winery level. We will discuss the scope of this analysis and the interest of this approach to consider possible adaptations to be implemented.

 

How to cite: Bremond, P., Grelot, F., Modjeska, M., Nortes Martinez, D., and Panégos, J.: Impacts of successive climatic events on a wine cooperative system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7473, https://doi.org/10.5194/egusphere-egu23-7473, 2023.

X4.75
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EGU23-13295
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On-site presentation
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Mathis Joffrain
Since the early 90s, natural catastrophe models have been mainly used by the re/insurance industry for pricing and risk management purposes.
These rely on a catalogue of plausible yet so far unseen events called the “stochastic events catalogue”. For each of these events a loss and a frequency is calculated leading to an industry standard output called YLT (Year Loss Table).
Based on the YLT, insurers can calculate a wide range of risk measures such as the Value at Risk or the annual average loss. They also can modify the YLT to incorporate impacts by Climate Change.
 
This poster sets out to:
(i) Explain the concept of Year Loss Table (YLT)
(ii) Show the derivation of key risk measures.
(iii) Describe how the YLT can be modified to take into account the impacts by climate change, with a focus on the North Atlantic hurricane wind risk.
(iv) Present the results obtained by the approach in (iv).

How to cite: Joffrain, M.: An industry framework to estimate changes in hurricanes wind risk due to climate change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13295, https://doi.org/10.5194/egusphere-egu23-13295, 2023.

Posters virtual: Thu, 27 Apr, 14:00–15:45 | vHall NH

The posters scheduled for virtual presentation are visible in Gather.Town. Attendees are asked to meet the authors during the scheduled attendance time for live video chats. If authors uploaded their presentation files, these files are also linked from the abstracts below, but only on the day of the poster session. The button to access Gather.Town appears just before the time block starts.
vNH.4
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EGU23-3020
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ECS
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Virtual presentation
Ayat Al Assi, Rubayet Bin Mostafiz, Carol J. Friedland, Robert V Rohli, and Md Adilur Rahim

In the United States, the Federal Emergency Management Agency (FEMA) delineates 100-year flood zones (special flood hazard area (SFHA) in the U.S.A.) to define flood risks and insurance rates. Quantifying flood risk in the SFHA which is the area of high risk of flooding is vital for individual, communities, and decision makers to minimize flood consequences. Flood risk is assessed as the product of the probability of flooding and the consequences associated with its occurrence. The unavailability of the modeled flood depth data for 100- year return period or for all return periods in most of SFHA’s areas make quantifying flood risk is challenging. This research develops a systematic approach that generates a synthetic flood parameter to quantify flood risk in A Zone- portion of the SFHA in which the potential base flood wave height is between 0.0 and 3.0 feet. The synthetic flood hazard parameters are generated in 100-year floodplain considering different flooding scenarios, and the flood risk is quantified in terms of average annual loss (AAL) at 100-year flood elevation (E100), and with an additional elevation above E100 for single-family home with different attribute located in A Zone. The results reveal that the AAL for single-family home (i.e., one vs. two-plus stories, with vs. without basement), at E100  and located in A Zone ranging of 0.27–0.98 percent of replacement cost value. The methodology and results generated in this research will benefit homeowners, engineers, surveyors, and community planners in enhancing resilience to the flood hazard in A Zone.

How to cite: Al Assi, A., Mostafiz, R. B., Friedland, C. J., Rohli, R. V., and Rahim, M. A.: Flood Risk Assessment for Single-Family Home in A Zone, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3020, https://doi.org/10.5194/egusphere-egu23-3020, 2023.

vNH.5
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EGU23-7544
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On-site presentation
Urbanisation in flood-prone areas, hydraulic infrastructures and economic evaluation
(withdrawn)
Frédéric Grelot, David Nortes Martinez, and Pauline Brémond