Displays

Infrastructure is considered as the fundamental facilities and systems serving a country or other area to ensuring the functioning of its economy. The term infrastructure refers to public and private facilities and systems such as transport (including roads, railways, bridges, tunnels, ports, airports, etc.), water supply, sewers, electrical grids, and telecommunication lines. Throughout the area of Russia, almost all of the listed infrastructure facilities are exposed to the undesirable impacts of adverse natural processes and phenomena, as well as natural hazards of various origins such as geophysical, hydro-meteorological, and others. Adverse impacts of natural hazards may trigger accidents and failures; disrupt the normal operation of infrastructure facilities. In their turn, these negative consequences of natural hazard impacts on the infrastructure cause multiple social problems. Using the information collected by the author in the database of technological and natural-technological accidents, contributions of natural factors to accidents and failures in the infrastructure facilities are assessed. Database includes more than 21 thousand events from 1992 to 2019. Among all the identified types of natural hazards, the largest contributions to accidents and infrastructure disruptions have hydro-meteorological hazards such as heavy snowfalls and rains, floods, and ice phenomena. Electrical grids are the most vulnerable to adverse impacts of natural hazards. Regional differences in the risk of accidents and infrastructure disruptions between Russian federal regions were found. All the federal regions were grouped by their risk levels of accidents and infrastructure disruptions. The resulting maps were created and analyzed.

How to cite: Petrova, E.: Natural hazard impacts on infrastructure in Russian regions, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10634, https://doi.org/10.5194/egusphere-egu2020-10634, 2020.

Critical infrastructures, such as energy, water and ICT supply are the backbone of societies. Especially in urban contexts, peoples’ dependency on the increasingly complex and interdependent network of critical infrastructures is daunting. However, a majority of inhabitants is rather unaware of related implications and risks, leaving individuals largely unprepared and highly vulnerable to potential critical infrastructure disruptions or failures. This is particularly true for developed countries with high supply security.

In addition, current discourses on safe and affordable operations of CI are mostly limited to the engineered part such as roads or electricity lines while hardly dealing with the soft components, namely coping capacities to overcome potential outages. With more frequent and intense occurrence of natural hazards the combination of CI complexity, dependency and unawareness poses a growing threat to urban populations with major implications for local disaster management actors and emergency services.

Based on comprehensive literature and policy analyses and this contribution will elaborate on challenges and opportunities of reducing natural hazards’ impacts on urban areas by extending assessments of critical infrastructure exposure to “soft” components, focusing on impacts on end users. Data from a major household survey conducted in a German city will be used to present and discuss damage impact types, their interlinkages as well as potential pathways towards risk reduction.

How to cite: Sandholz, S. and Sett, D.: Urban preparedness for critical infrastructures disruptions from an end user perspective, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21701, https://doi.org/10.5194/egusphere-egu2020-21701, 2020.

The Horizon2020 project RESISTO (Resilience enhancement and risk control platform for communication infrastructure operators) aims to reduce the risk as well as the impact of an anomalous incident for the telecommunication infrastructure. Incidents here can be natural hazards such as floods, earthquakes etc., but also cyber attacks, physical attacks or a combination of the latter two.

The approach uses a short-term control loop (STCL) that detects anomalies via various sensors or factors: internal remote sensors such as cameras, external sensing such as weather data, social media data mining, etc.. By doing so, the STCL is a risk predictor, but it also predicts effects of countermeasures and simulates short-term effects of failure with respect to performance degradation. This real-time risk and resilience assessment and the integrated interdependency analysis (among virtual and physical domains) lead to an effective Decision Support System (DSS) that detects critical situations and supports their management.

A risk and resilience analysis of the system is performed on a regular basis by the long term control loop (LTCL). It is used to generally evaluate the resilience of the system via network simulation techniques, to identify weak points and test effects of various improvement measures. The resilience management process is based on the risk management process defined in the ISO 31000 and refined to the specific needs of RESISTO. The outcome of the LTCL analysis can be compared to the measured values of the STCL to validate and improve the simulation model.

The functionality, modularity and adaptability of the DSS is validated by nine use cases with various sub-scenarios, led by the telecommunication providers in the consortium. The use cases apply differing combinations of real and virtual parts, posing a specific threat to the infrastructure. An example for the added value to the resilience and recovery strategies of a telecommunication infrastructure and its provider is given by a use case where an unspecified natural disaster hits a rural area:

Because the RESISTO system interfaces with specific national sensing platforms such as weather and seismic ones, it is aware of the natural disaster and its severity. Simultaneously, RESISTO receives the congestion events from the provider’s Network Management Center (NMC) and monitoring tools. It responds by “ordering” an Unmanned Aerial Vehicle (UAV) to make a damage inspection in the area. With the UAV, the platform identifies the affected critical network assets (antennas, switches, routers etc.) as the potential cause of the congestion, and correlates the loss of the network resources with the congestion events. RESISTO then suggests suitable mitigation actions, i.e. traffic redirection and or activation of auxiliary network resources. Also conceivable is the direct dispatch of technical / maintenance personnel, depending on safety aspects.

Telecommunication nowadays is crucial for the functioning of a society, on the corporate as well as on the private level. During the response and recovery phases of disasters, telecommunication infrastructures also play a central role. The RESISTO platform aims to be another step towards more resilient societies.

How to cite: Bach, S., Fehling-Kaschek, M., and Baldoni, S.: Resilience Enhancement of Communication Infrastructures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-18788, https://doi.org/10.5194/egusphere-egu2020-18788, 2020.

In recent years, lots of major disasters happened in the industrial parks. As a critical infrastructure, it become an urgent issue to tackle the disaster prevention and vulnerability assessment of the industrial parks. This study reviews the theory of vulnerability, regional resilience, disaster prevention system for industrial parks and related literature to establish the vulnerability assessment framework. Therefore, by utilizing the fuzzy Delphi method to screen the indicators in four dimensions such as physical, social, exposure and economic, and also the AHP expert panel to set the related weights and the correlation between their indicators. And, follow up with Dynamic ANP Process to extract the decision-making structures in 2019, and 2030. In total, 63 industrial parks were evaluated by this evaluation framework and categorized by different vulnerable types. Therefore, responding disaster adaptation strategies were proposed for different parks as a reference for government.

How to cite: Pai, J.-T. and Chen, H.-J.: Vulnerability assessment and Disaster Prevention Adaptation Planning Strategies for Industrial Parks, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-2487, https://doi.org/10.5194/egusphere-egu2020-2487, 2020.

In recent years airports have demonstrated sensitivity to climate hazards, raising various safety, environmental and socio-economic concerns. Evidence from the literature indicates that the occurrence of climate hazard events, including sea-level rise, extreme heat, precipitation changes and convective weather, is likely to become more frequent as a result of climatic change. This, in turn, is likely to place additional stress on airports infrastructure and threatening its ability to maintain their social and economic function. While climate adaptation and hazard impacts are more established in other major sectors, in the case of airports this issue has only more recently emerged as a risk.

By examining the key challenges airports face in different geographical regions and climate zones, this study examines how climate extremes and hydrological hazards affect the airport system and, presents best practices to improve the resilience of airport infrastructure. The key objective of this contribution is to provide a better understanding of the direct and indirect impact of climate hazards and to outline some of the aspects that could be included in climate hazard risk reduction strategies in the future.

How to cite: Voskaki, A., Budd, T., and Mason, K.: An overview of climate hazard impacts to the global airport system, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6014, https://doi.org/10.5194/egusphere-egu2020-6014, 2020.

The Austrian Federal Railways (ÖBB) are operating about 4800 kilometers of railway track in all regions of Austria. Most parts of this infrastructure are exposed to various natural hazards like landslides, debris flows, rockfalls, floodings and avalanches but also extreme weather events like strong winds or extreme heat can disrupt railway traffic. The frequency of their occurrence is changing due to recent climate change.

We use over 2000 events from 1990 to 2018 and a principal component approach to create an event space which lets us combine events and meteorological data on a fine spatial grid. This is necessary to detect characteristic climate-indices (CIs) in temporal series of meteorological parameters, like temperature or precipitation, that have negative effects on railway operation or trigger natural hazards that do so. The results are evaluated using various multivariate statistic methods to quantify the quality of the found CIs.

After these steps we can estimate the frequency of CI occurrence in near (2036-2065) and remote future (2071-2100) by analyzing ensembles of downscaled GCM projections for different climate scenarios. The result are hazard-development-corridors that are a relative measure for the number of predicted hazard events during the two periods of time along the considered railway tracks.

How to cite: Wally, C., Lehner, S., Matulla, C., Enigl, K., Müller, H., Rauch, H. P., Fian, T., Hauger, G., Rachoy, C., and Salinger, F.: Derivation of climate-indices and establishment of hazard-development-corridors along the ÖBB rail network, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10890, https://doi.org/10.5194/egusphere-egu2020-10890, 2020.

Abstract: Rainfall-induced disaster is the most frequent disaster affected Chinese Railway System. Climate change will lead to more extreme rainfall in the future. A better understanding of extreme precipitation in the future and the exposure of railway infrastructures to extreme precipitation will facilitate railway planning and disaster risk management. This paper employs climate model simulations to calculate the changes of the extreme precipitation under different global warming scenarios. The return periods of the present 50-yr/100-yr return-period precipitation amount in the future are obtained. Based on this, the changes of the exposure of Chinese railways to extreme precipitation are analyzed. The results reveal that 58.61% (55.46) of China’s region will experience an increase in the 50-yr(100-yr) return-period precipitation under 1.5°C warming in comparison with the present period (2001–2020), the value will be 64.44% and 59.53% due to the additional 0.5°C warming. By calculating the exposure of Chinese railways, we found that 28.49% (32.15) of China's railways are in the region where 50-yr return-period rainfall at this stage will occur less than 20 years under 1.5°C (2.0°C) warming, and 36.85% (41.39)of China's railways are in the region where 100-yr return-period rainfall at this stage will occur less than 50 years under 1.5°C (2.0°C) warming in the future. This study quantified the exposure of China’s railway to extreme precipitation under the 1.5°C/2.0°C global warming. The results provided in this study have profound significance for the fortification planning of China's railway system for rainfall-induced disasters and provide useful experience for other countries.

How to cite: Zhao, J., liu, K., and Wang, M.: Exposure analysis of Chinese railways under the Change of Extreme-Precipitation in the future , EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12428, https://doi.org/10.5194/egusphere-egu2020-12428, 2020.

Short term flood intervention planning includes identifying how the limited resources should be allocated to the most appropriate affected locations. The water level is an important factor for temporary flood protection planning for which adaptability of the plan to its changing future condition is regarded valuable. Moreover, flexibility in activation, delaying and replacement of the existing plans should be considered to mitigate the damages caused by future unknown condition. This research applies real options analysis which incorporates adaptability and flexibility in addressing “least-cost alternative”  location selection via multi-stage stochastic programming. We apply the proposed model to a case study in Eden catchment with nine different flood-affected cities with different degrees of uncertainty along Eden River in England. A multi-objective and mixed integer optimization model was formulated to solve on a scenario tree capable to choose most appropriate locations for deploying intervention measures of temporary flood protection. We examine the solution under various model parameters uncertainty and compare the results with the business as usual case presenting the benefits of proposed formulation in terms of expected damage and cost.

How to cite: Ni, M. and Erfani, T.: How an adaptive and flexible short-term flood planning can be beneficial - a UK case study application, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20619, https://doi.org/10.5194/egusphere-egu2020-20619, 2020.

The soil erosion is the most serious environmental problem in watershed areas in Bhagirathi River. The main factors affecting the amount of soil erosion include vegetation cover, topography, soil, and climate. In order to describe the areas with high soil erosion risks and to develop adequate erosion prevention measures in the watersheds of dams, erosion risk maps should be generated considering these factors. “Reduction in the capacity and life of Tehri dam Reservoir was became a major concern. Remote Sensing (RS) and Geographic Information System (GIS) technologies were used for erosion risk mapping in the catchment area of Bhagirathi River. The principal aim of this paper is to utilize spatial-based soil erosion information to assess land suitability at a watershed level. The model integrated with RS and GIS technologies has great potential for producing accurate and inexpensive erosion risk maps.

Data on Climate (Total precipitation and its frequency and intensity), Geomorphology (Land form, Physiography, Slope and Drainage Characteristics), Soil characteristics (Texture, structure), Land Use/ Land cover (Density of forest or grassland, plant residue, crops etc.) and Soil management were calculated using standard reported methods (Naqvi et al., 2015). Total 6 parameters were calculated i.e. Slope, Slope length, Soil texture, Drainage density, landuse/landcover and Rainfall erosivity. Weightage of each parameters on the basis of value and classes were assign. At last SYI value were calculated using weightage map, Delivery ratio, area of watershed. The sub-watersheds 10, 11 were identified as being very high risk. Intense rainfall and reservoir area of dam coupled with poor soil structure and steep slopes are the main drivers of soil erosion in this area. Therefore, the proper designing of integrated watershed management and conservation strategies is a crucial element to reduce the current rate of environmental degradation and boost up agricultural production in the sub-watersheds.

How to cite: Nain, G.: Estimation of Soil Loss at Tehri Dam Catchment in Uttarakhand, India., EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-5115, https://doi.org/10.5194/egusphere-egu2020-5115, 2020.

1712 Swabian immigration started to Sathmar county on today's Romania territory. This followed closing the Sathmar peace 1711 after a war which left lands empty without work force. The colonists came from Upper Swabia, which is today Baden-Württemberg in Germany. The immigration took about one century. The colonists came by means of ships called Ulmer Schachtel from Ulm on the Danube, for which reason these are the first Danube Swabians. The later waves of colonists were brought by Emperor Maria Theresia to further areas in Banat and Hungary. Within a DOMUS scholarship in the home country, the author investigated how patterns of architecture were brought by the migrants from their old to their new home, including church and vernacular architecture. The colonists came from an area where much of the land belonged to monasteries, and following the end of the 30 years war an intense construction activity started, in Baroque style, which led to what is today the Upper Swabian Baroque Street. Investigation of Zsiros assessed the magnitude of the 1834 Érmellék earthquake, which affected this area, by effects on vernacular architecture. But also churches displayed earthquake damage, as research of Julia Bara shows, including destruction of towers and vaults. Churches were built by foreign architects such as Josef Bittheuser from Würzburg and Franz Sebastian Rosenstingl from Vienna. The churches of the later in Vienna displayed damages with time as well. Within the research of the author these damages were mapped and connected to patters of earthquake safe construction in the home country, which is also affected by moderate earthquakes. Particularly in case of vernacular architecture, the houses of the colonists are related to other typologies of Danube Swabians but not to those which can be observed in the houses conserved in village museums, from which some date from before the migration. This can be explained by their destruction. The oldest identified one is one of the ancestors of the author, dated by genealogy data to be built around 1840. The in situ conserved museum house is of a more recent date. The vernacular housing typology was investigated employing the GEM taxonomy based on the World Housing Encyclopedia questionnaire. Relevant for the session is how migration patterns result in architectural shape patterns, for which the author also participated in building a society game. Migration has been mapped by means of story maps as well, but also using Gephi network analysis. The effects of the anthropic hazard of war on letting large amounts of population move (migration) are also relevant for the session.

How to cite: Bostenaru Dan, M.: The 1834 Ermellek earthquake effects and the architecture of migration after war in Baroque times, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6825, https://doi.org/10.5194/egusphere-egu2020-6825, 2020.

Between the Ion Mincu University of Architecture and Urbanism in Bucharest, Romania and the Szechenyi Istvan University in Gyor, Hungary a cooperation agreement was concluded between the first and fourth author regarding disaster management. A first step was taken in January 2020 starting the reciprocical visits by a visit of the third author to the Romanian university. Exchange encompassed participation to master level courses at the Master Urban Design (urban prospective: urban vulnerability and protection of localities against risks, the later taught by the second author, who is also a titular member of the doctoral school) and a lecture at the doctoral school with discussions moderated by the first and third authors. The conclusions were discussed with the master students as well. The innovative in the cooperation is that it regards how urban planners can contribute to disaster management and infrastructures in a field where they can best plan. Master students learn how to design urban projects while doctoral candidates do research in this, and are thereof complementary. Cooperation will continue by various national and bilateral schemes. This contribution shows the conclusions of the discussions.

How to cite: Bostenaru Dan, M., Gociman, C. O., Anghelache, M. A., and Kegyes-Brassai, O.: Romanian-Hungarian cooperation in the field of reduction of seismic risk to infrastructures, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-21156, https://doi.org/10.5194/egusphere-egu2020-21156, 2020.

Abstract: Power grids are one of the most important and complex infrastructure systems in our society. The components of power grid systems are susceptible to damage due to natural hazards and may lead to cascading failures of the system. Here, for the first time, we propose an integrated risk assessment framework for power grid system that combines: (1) geospatial and voltage level information of Chinese power grid and corresponding location of transmission towers; (2) stochastic earthquake scenarios that are generated based on a seismicity model and the Monte Carlo method and (3) cascading failure model to analyze the number of affected population under various power grid initial loads and capacities. This methodology is employed to evaluate the seismic risk of Chinese power grid system, where affected population is regarded as vulnerability metrics. The results show that Beijing, Hebei province and central area of Shandong and Qinghai province, eastern area of Sichuan province as well as southern area of Xinjiang province have higher seismic risk, which indicates high-aseismic measures should be adopted in the aforementioned areas. Meanwhile, we also found that the increase of capacity of the whole power grid will result in and increasing robustness of the power grid system and decreasing affected population.

How to cite: Li, K., Liu, K., and Wang, M.: Risk and Vulnerability Assessment of Power grid under Seismic Hazards, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-6512, https://doi.org/10.5194/egusphere-egu2020-6512, 2020.