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.

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.

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.

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.

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.

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.

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.

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.

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.

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.