Comment on "INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis"

Author(s):  
Anonymous
Author(s):  
Francesco Dottori ◽  
Rui Figueiredo ◽  
Mario Martina ◽  
Daniela Molinari ◽  
Anna Rita Scorzini

Author(s):  
Francesco Dottori ◽  
Rui Figueiredo ◽  
Mario Martina ◽  
Daniela Molinari ◽  
Anna Rita Scorzini

Abstract. Methodologies to estimate economic flood damages are increasingly important for flood risk assessment and management. In this work, we present a new synthetic flood damage model based on a component-by-component analysis of physical damage to buildings. The damage functions are designed using an expert-based approach with the support of existing scientific and technical literature, and have been calibrated with loss adjustment studies and damage surveys carried out for past flood events in Italy. The model structure is designed to be transparent and flexible, and therefore it can be applied in different geographical contexts and adapted to the actual knowledge of hazard and vulnerability variables. The model has been tested in a recent flood event in Northern Italy. Validation results provided good estimates of post-event damages, with better performances than most damage models available in the literature. In addition, a local sensitivity analysis has been performed, in order to identify the hazard variables that have more influence on damage assessment results.


2016 ◽  
Vol 16 (12) ◽  
pp. 2577-2591 ◽  
Author(s):  
Francesco Dottori ◽  
Rui Figueiredo ◽  
Mario L. V. Martina ◽  
Daniela Molinari ◽  
Anna Rita Scorzini

Abstract. Methodologies to estimate economic flood damages are increasingly important for flood risk assessment and management. In this work, we present a new synthetic flood damage model based on a component-by-component analysis of physical damage to buildings. The damage functions are designed using an expert-based approach with the support of existing scientific and technical literature, loss adjustment studies, and damage surveys carried out for past flood events in Italy. The model structure is designed to be transparent and flexible, and therefore it can be applied in different geographical contexts and adapted to the actual knowledge of hazard and vulnerability variables. The model has been tested in a recent flood event in northern Italy. Validation results provided good estimates of post-event damages, with similar or superior performances when compared with other damage models available in the literature. In addition, a local sensitivity analysis was performed in order to identify the hazard variables that have more influence on damage assessment results.


Hydrology ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 110
Author(s):  
Carlos Martínez ◽  
Zoran Vojinovic ◽  
Arlex Sanchez

This paper presents the performance quantification of different green-grey infrastructures, including rainfall-runoff and infiltration processes, on the overland flow and its connection with a sewer system. The present study suggests three main components to form the structure of the proposed model-based assessment. The first two components provide the optimal number of green infrastructure (GI) practices allocated in an urban catchment and optimal grey infrastructures, such as pipe and storage tank sizing. The third component evaluates selected combined green-grey infrastructures based on rainfall-runoff and infiltration computation in a 2D model domain. This framework was applied in an urban catchment in Dhaka City (Bangladesh) where different green-grey infrastructures were evaluated in relation to flood damage and investment costs. These practices implemented separately have an impact on the reduction of damage and investment costs. However, their combination has been shown to be the best action to follow. Finally, it was proved that including rainfall-runoff and infiltration processes, along with the representation of GI within a 2D model domain, enhances the analysis of the optimal combination of infrastructures, which in turn allows the drainage system to be assessed holistically.


2012 ◽  
Vol 502 ◽  
pp. 451-457
Author(s):  
Jiang Bo Wang ◽  
Qing Ming Zhang ◽  
Cheng Liang Feng ◽  
Wei Bing Li ◽  
Heng Wang

By building up a debugging method about material parameters of concrete impact damage model based on DOE (Design of Experiments) analysis, this paper studies the influence of material parameters of concrete targets on the results of numerical simulation based on quantitative analysis, when the impact velocity is 300m/s and 850m/s respectively. It concludes that when the impact velocity of 300m/s, 5 parameters have considerable effect on the residual velocity of warhead, they are , , , and . Of all 5 parameters, , and can be obtained by calculation therefore it only needs to debug two parameters and according to experiments. Finally, when the impact velocity is 300m/s or so, debug combining the experiments to get a set of concrete impact damage model material parameters to make the results of simulation and experiment anastomosis well.


2016 ◽  
Vol 16 (11) ◽  
pp. 2357-2371 ◽  
Author(s):  
Patric Kellermann ◽  
Christine Schönberger ◽  
Annegret H. Thieken

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.


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