scholarly journals Interactive comment on “Large-scale application of the flood damage model Railway Infrastructure Loss (RAIL)” by Patric Kellermann et al.

2016 ◽  
Author(s):  
Anonymous
Keyword(s):  
Large Scale ◽  
Damage Model ◽  
Flood Damage ◽  
Railway Infrastructure

scholarly journals Large-scale application of the flood damage model RAilway Infrastructure Loss (RAIL)

2016 ◽  
Vol 16 (11) ◽  
pp. 2357-2371 ◽  
Author(s):  
Patric Kellermann ◽  
Christine Schönberger ◽  
Annegret H. Thieken
Keyword(s):  
Risk Management ◽  
Risk Aversion ◽  
Flood Risk ◽  
Structural Damage ◽  
Large Scale ◽  
Damage Model ◽  
Flood Damage ◽  
Railway Infrastructure ◽  
Increased Risk ◽  
The Impact

Abstract. Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.

scholarly journals Large-scale application of the flood damage model Railway Infrastructure Loss (RAIL)

2016 ◽  
Author(s):  
Patric Kellermann ◽  
Christine Schönberger ◽  
Annegret H. Thieken
Keyword(s):  
Risk Management ◽  
Risk Aversion ◽  
Flood Risk ◽  
Structural Damage ◽  
Large Scale ◽  
Damage Model ◽  
Flood Damage ◽  
Railway Infrastructure ◽  
Increased Risk ◽  
The Impact

Abstract. Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than one hundred million euros due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate 1) the expected structural flood damage, and 2) the resulting repair costs of railway infrastructure due to a 30-year, 100-year and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.

scholarly journals Estimating flood damage to railway infrastructure – the case study of the March River flood in 2006 at the Austrian Northern Railway

2015 ◽  
Vol 3 (4) ◽  
pp. 2629-2663
Author(s):  
P. Kellermann ◽  
A. Schöbel ◽  
G. Kundela ◽  
A. H. Thieken
Keyword(s):  
Damage Model ◽  
Flood Damage ◽  
Water Levels ◽  
Railway Track ◽  
Future Research ◽  
Natural Risk ◽  
Railway Infrastructure ◽  
River Flood ◽  
Flood Losses

Abstract. Models for estimating flood losses to infrastructure are rare and their reliability is seldom investigated although infrastructure losses might contribute considerably to the overall flood losses. In this paper, a statistical modelling approach for estimating direct structural flood damage to railway infrastructure and associated financial losses is presented. Via a combination of empirical data, i.e. photo-documented damage on the Northern Railway in Lower Austria caused by the March river flood in 2006, and simulated flood characteristics, i.e. water levels, flow velocities and combinations thereof, the correlations between physical flood impact parameters and damage occurred to the railway track were investigated and subsequently rendered into a damage model. After calibrating the loss estimation using recorded repair costs of the Austrian Federal Railways, the model was applied to three synthetic scenarios with return periods of 30, 100 and 300 years of March river flooding. Finally, the model results are compared to depth-damage curve based approaches for the infrastructure sector obtained from the Rhine Atlas damage model and the Damage Scanner model. The results of this case study indicate a good performance of our two-stage model approach. However, due to a lack of independent event and damage data, the model could not yet be validated. Future research in natural risk should focus on the development of event and damage documentation procedures to overcome this significant hurdle in flood damage modelling.

scholarly journals Estimating flood damage to railway infrastructure – the case study of the March River flood in 2006 at the Austrian Northern Railway

2015 ◽  
Vol 15 (11) ◽  
pp. 2485-2496 ◽  
Author(s):  
P. Kellermann ◽  
A. Schöbel ◽  
G. Kundela ◽  
A. H. Thieken
Keyword(s):  
Damage Model ◽  
Flood Damage ◽  
Water Levels ◽  
Railway Track ◽  
Future Research ◽  
Natural Risk ◽  
Railway Infrastructure ◽  
River Flood ◽  
Flood Losses

Abstract. Models for estimating flood losses to infrastructure are rare and their reliability is seldom investigated although infrastructure losses might contribute considerably to the overall flood losses. In this paper, an empirical modelling approach for estimating direct structural flood damage to railway infrastructure and associated financial losses is presented. Via a combination of event data, i.e. photo-documented damage on the Northern Railway in Lower Austria caused by the March River flood in 2006, and simulated flood characteristics, i.e. water levels, flow velocities and combinations thereof, the correlations between physical flood impact parameters and damage occurred to the railway track were investigated and subsequently rendered into a damage model. After calibrating the loss estimation using recorded repair costs of the Austrian Federal Railways, the model was applied to three synthetic scenarios with return periods of 30, 100 and 300 years of March River flooding. Finally, the model results are compared to depth-damage-curve-based approaches for the infrastructure sector obtained from the Rhine Atlas damage model and the Damage Scanner model. The results of this case study indicate a good performance of our two-stage model approach. However, due to a lack of independent event and damage data, the model could not yet be validated. Future research in natural risk should focus on the development of event and damage documentation procedures to overcome this significant hurdle in flood damage modelling.

scholarly journals Comparative flood damage model assessment: towards a European approach

2012 ◽  
Vol 12 (12) ◽  
pp. 3733-3752 ◽  
Author(s):  
B. Jongman ◽  
H. Kreibich ◽  
H. Apel ◽  
J. I. Barredo ◽  
P. D. Bates ◽  
...  
Keyword(s):  
Large Scale ◽  
Best Practice ◽  
Damage Model ◽  
Flood Damage ◽  
Model Assessment ◽  
Care Needs ◽  
Damage Functions ◽  
Damage Models ◽  
European Approach ◽  
Asset Values

Abstract. There is a wide variety of flood damage models in use internationally, differing substantially in their approaches and economic estimates. Since these models are being used more and more as a basis for investment and planning decisions on an increasingly large scale, there is a need to reduce the uncertainties involved and develop a harmonised European approach, in particular with respect to the EU Flood Risks Directive. In this paper we present a qualitative and quantitative assessment of seven flood damage models, using two case studies of past flood events in Germany and the United Kingdom. The qualitative analysis shows that modelling approaches vary strongly, and that current methodologies for estimating infrastructural damage are not as well developed as methodologies for the estimation of damage to buildings. The quantitative results show that the model outcomes are very sensitive to uncertainty in both vulnerability (i.e. depth–damage functions) and exposure (i.e. asset values), whereby the first has a larger effect than the latter. We conclude that care needs to be taken when using aggregated land use data for flood risk assessment, and that it is essential to adjust asset values to the regional economic situation and property characteristics. We call for the development of a flexible but consistent European framework that applies best practice from existing models while providing room for including necessary regional adjustments.

Study on Deformation and Damage of Rock Mass Subject to High In Situ Stress by Using a Elastoplastic Damage Model and Considering the Impact of Weak Planes

2013 ◽  
Vol 838-841 ◽  
pp. 705-709
Author(s):  
Yun Hao Yang ◽  
Ren Kun Wang
Keyword(s):  
Rock Mass ◽  
Large Scale ◽  
Damage Model ◽  
Back Analysis ◽  
In Situ Stress ◽  
Surrounding Rock ◽  
High In Situ Stress ◽  
Underground Caverns ◽  
The Impact

Large scale underground caverns are under construction in high in-situ stress field at Houziyan hydropower station. To investigate deformation and damage of surrounding rock mass, a elastoplastic orthotropic damage model capable of describing induced orthotropic damage and post-peak behavior of hard rock is used, together with a effective approach accounting for the presence of weak planes. Then a displacement based back analysis was conducted by using the measured deformation data from extensometers. The computed displacements are in good agreement with the measured ones at most of measurement points, which confirm the validities of constitutive model and numerical simulation model. The result of simulation shows that damage of surrounding rock mass is mainly dominated by the high in-situ stress rather than the weak planes and heavy damage occur at the cavern shoulders and side walls.

scholarly journals Gradient Nonlocal Enhanced Microprestress-Solidification Theory and Its Finite Element Implementation

2021 ◽  
Vol 8 ◽  
Author(s):  
Teng Tong ◽  
Changqing Du ◽  
Xiaofan Liu ◽  
Siqi Yuan ◽  
Zhao Liu
Keyword(s):  
Finite Element ◽  
Large Scale ◽  
Deformation Gradient ◽  
Damage Model ◽  
Reinforced Concrete Beams ◽  
Chain Model ◽  
Finite Element Software ◽  
Order Deformation ◽  
Implicit Solver

Time-dependent responses of cracked concrete structures are complex, due to the intertwined effects between creep, shrinkage, and cracking. There still lacks an effective numerical model to accurately predict their nonlinear long-term deflections. To this end, a computational framework is constructed, of which the aforementioned intertwined effects are properly treated. The model inherits merits of gradient-enhanced damage (GED) model and microprestress-solidification (MPS) theory. By incorporating higher order deformation gradient, the proposed GED-MPS model circumvents damage localization and mesh-sensitive problems encountered in classical continuum damage theory. Moreover, the model reflects creep and shrinkage of concrete with respect to underlying moisture transport and heat transfer. Residing on the Kelvin chain model, rate-type creep formulation works fully compatible with the gradient nonlocal damage model. 1-D illustration of the model reveals that the model could regularize mesh-sensitivity of nonlinear concrete creep affected by cracking. Furthermore, the model depicts long-term deflections and cracking evolutions of simply-supported reinforced concrete beams in an agreed manner. It is noteworthy that the gradient nonlocal enhanced microprestress-solidification theory is implemented in the general finite element software Abaqus/Standard with the implicit solver, which renders the model suitable for large-scale creep-sensitive structures.

scholarly journals Ice shelf fracture parameterization in an ice sheet model

2017 ◽  
Vol 11 (6) ◽  
pp. 2543-2554 ◽  
Author(s):  
Sainan Sun ◽  
Stephen L. Cornford ◽  
John C. Moore ◽  
Rupert Gladstone ◽  
Liyun Zhao
Keyword(s):  
Enhancement Factor ◽  
Large Scale ◽  
Damage Model ◽  
Ice Sheet ◽  
Ice Shelf ◽  
Ice Flow ◽  
Ice Shelves ◽  
Order Of Magnitude ◽  
Eventual Loss ◽  
Spatially Varying

Abstract. Floating ice shelves exert a stabilizing force onto the inland ice sheet. However, this buttressing effect is diminished by the fracture process, which on large scales effectively softens the ice, accelerating its flow, increasing calving, and potentially leading to ice shelf breakup. We add a continuum damage model (CDM) to the BISICLES ice sheet model, which is intended to model the localized opening of crevasses under stress, the transport of those crevasses through the ice sheet, and the coupling between crevasse depth and the ice flow field and to carry out idealized numerical experiments examining the broad impact on large-scale ice sheet and shelf dynamics. In each case we see a complex pattern of damage evolve over time, with an eventual loss of buttressing approximately equivalent to halving the thickness of the ice shelf. We find that it is possible to achieve a similar ice flow pattern using a simple rule of thumb: introducing an enhancement factor ∼ 10 everywhere in the model domain. However, spatially varying damage (or equivalently, enhancement factor) fields set at the start of prognostic calculations to match velocity observations, as is widely done in ice sheet simulations, ought to evolve in time, or grounding line retreat can be slowed by an order of magnitude.

Analysis of potential flood damage on crops at global scale

2020 ◽  
Author(s):  
Antonio Annis ◽  
Davide Danilo Chiarelli ◽  
Fernando Nardi ◽  
Maria Cristina Rulli
Keyword(s):  
Food Security ◽  
Flood Risk ◽  
Large Scale ◽  
Flood Hazard ◽  
Strong Support ◽  
Flood Damage ◽  
Natural Ecosystems ◽  
Remotely Sensed Data ◽  
Regulated Rivers ◽  
Cropland Area

<p>Most of the food production connected to crops is located in fluvial corridors because of their suitable morphology and fertile soils. The knowledge and large scale quantification of the agricultural resources at flood risk has a crucial importance for improving urban and regional planning. Recent advances in satellite derived products related to land use, digital terrain and hydrologic variables can give a strong support on extensive analyses on cropland areas in floodplains and their interactions with natural ecosystems and human activities. In this work, we present a global assessment of cropland at flood risk in terms of extension, productivity and the related calories adopting the Global Cropland Area Database (GCAD), the Global Floodplain Dataset (GFPLAIN250m), the Global flood hazard maps (GFHM) in conjunction with continental remotely-sensed data representing free flowing (versus artificially regulated) rivers and urban density maps. Spatially distributed and aggregated results of the research allow to identify the most critical areas in terms of food security and floods, thus allowing to support intervention strategies for food security management at large scale and for different socio-economic contexts.</p>

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