Using FloodRisk GIS freeware for uncertainty analysis of direct economic flood damages in Italy

Albano, Raffaele; Sole, Aurelia; Adamowski, Jan; Perrone, Antonio; Inam, Azhar

doi:10.1016/j.jag.2018.06.019

Cited by 24 publications

(28 citation statements)

References 35 publications

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“…For the NPV estimates comparing action to in-action, uncertainties associated with input runoff volume, threshold criteria, unit costs, and discounting rate demonstrate the most significant impacts. The two largest uncertainty contributions are related to the damage cost functions, thereby confirming the results of previous studies that highlight the importance of this uncertainty contribution [12,15]. Climate factors and investment costs are relatively less important in this case study.…”

Section: Resultssupporting

confidence: 89%

“…They find that the damage costs are dominating the overall uncertainty. Several other studies have confirmed that this uncertainty is high [13,14], and is also compared to the uncertainty of modelling the hazards [15]. Löwe et al [16] explored the overall uncertainty by defining a number of scenarios and possible variable outcomes and from that calculate both the overall uncertainty and the efficiency of different strategies by presenting resulting flood risk indicators as box plots as a measure of resulting resilience.…”

Section: Introductionmentioning

confidence: 98%

“…Löwe et al [16] explored the overall uncertainty by defining a number of scenarios and possible variable outcomes and from that calculate both the overall uncertainty and the efficiency of different strategies by presenting resulting flood risk indicators as box plots as a measure of resulting resilience. Albano et al [15] used the same method for exploring the uncertainty, but focused on attributing the risk in relation to the uncertainty of the variables. Since they study a particular event, they considered the runoff volume as known, and hence the hazard uncertainty was only quantified by DEM resolution and the roughness of the surface.…”

Section: Introductionmentioning

confidence: 99%

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Uncertainty Assessment of Climate Change Adaptation Options Using an Economic Pluvial Flood Risk Framework

Zhou

Arnbjerg‐Nielsen

2018

Water

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Identifying what, when, and how much adaptation is needed to account for increased pluvial flood risk is inherently uncertain. This presents a challenge to decision makers when trying to identify robust measures. This paper presents an integrated uncertainty analysis to quantify not only the overall uncertainty of individual adaptation scenarios, but also the net uncertainty between adaptation alternatives for a direct comparison of their efficiency. Further, a sensitivity analysis is used to assess the relative contribution of inherent uncertainties in the assessment. A Danish case study shows that the uncertainties in relation to assessing the present hazards and vulnerabilities (e.g., input runoff volume, threshold for damage, and costing of floods) are important to the overall uncertainty, thus contributing substantially to the overall uncertainty in relation to decisions on action or in-action. Once a decision of action has been taken, the uncertainty of the hazards under the current climate, and also the magnitude of future climate change, are less important than other uncertainties such as discount rate and the cost of implementing the adaptation measures. The proposed methodology is an important tool for achieving an explicit uncertainty description of climate adaptation strategies and provides a guide for further efforts (e.g., field data collection) to improve decision-making in relation to climate change.

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Section: Resultssupporting

confidence: 89%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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Uncertainty Assessment of Climate Change Adaptation Options Using an Economic Pluvial Flood Risk Framework

Zhou

Arnbjerg‐Nielsen

2018

Water

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“…e outcomes of the study confirm that the knowledge of the magnitude and source of uncertainties helps to improve assessments and leads to better inform decisions on flood risk mitigation alternatives [14]. Moreover, numerical models need to be controlled, for example, through a calibration process that adjusts model parameters, assumptions, or equations to optimize concordance between observed data and model predictions [15].…”

mentioning

confidence: 72%

“…e results showed that poor-resolution DEMs might produce a global high feature agreement score with historical data but may fail to provide good flood extent estimations locally, particularly in flat areas. Instead, high-resolution DEMs (1 to 5 m) remain advantageous for modelling as they represent better the topography of the study area but it is important to carefully calibrate the models by the use of the roughness parameter.e outcomes of the study confirm that the knowledge of the magnitude and source of uncertainties helps to improve assessments and leads to better inform decisions on flood risk mitigation alternatives [14]. Moreover, numerical models need to be controlled, for example, through a calibration process that adjusts model parameters, assumptions, or equations to optimize concordance between observed data and model predictions [15].In this context, remote sensing is a low-cost technology that represents an important source of information in the water-related hazards and in water resource management fields [16].…”

mentioning

confidence: 77%

Computational Methods and Applications to Simulate Water-Related Natural Hazards

Albano

Manenti

Domínguez

et al. 2020

Mathematical Problems in Engineering

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anks to the availability of high-performance computers, in the last few years, Computational Fluid Dynamics (CFD) has been widely applied to simulate natural hazards in the field of environmental and civil engineering [1]. In order to explore different risk scenarios and potential risk-reduction options and to address hazard related uncertainty, the development of numerical models represents an important task in supporting emergency response agencies, water resource managers, insurance companies, and other decision-makers [2]. e application purpose of CFD modeling requires contextual attention to the output variables of predictive interest and their time and space scales, the level of accuracy required considering eventually real-time data assimilation, and computational efficiency demands [3,4]. e main aim of this special issue is to highlight the most recent advances in CFD modeling and its application related to water-related natural hazards and discusses future directions. Special focus is devoted to the modeling, handling of uncertainty, and the applications related to relevant natural hazard problems of practical and theoretical interest. A brief summary of all accepted papers is provided below.In the paper by Y. Shi et al., they have investigated, through the numerical CFD test, the influence of bed surface roughness on the flow structure in an open channel. In particular, they have developed a CFD meshless method, such as a weakly compressible smoothed particle hydrodynamics (WCSPH) [5], for open-channel turbulence simulation. e proposed rough bed model is based on the ghost boundary particles (GBPs) [6]; it uses wall function for a small-scale rough boundary. e results outperform the traditional mixed-length-based subparticle scale (SPS) turbulence model [7] by obtaining small numerical errors in the mainstream and near-surface region but it is found that errors varied widely for the inner region; the authors showed that the latter error is positively correlated with the channel bed slope and the equivalent roughness. On the basis of these results, the study proposes empirical formulae to calculate the ghost particle velocity under different hydraulic conditions using data mining.C. Zhen et al. have investigated the fatigue failure for trimaran ship, which is actually considered as a good alternative to monohulls in high-speed transportation and in naval applications [8]. In particular, they have presented a simplified fatigue analysis of trimaran cross-deck structure based on three-dimensional (3D) linear potential flow theory and global finite element (FE) analysis for wave loads and stress transfer functions calculation; at the same time, a stochastic spectral fatigue analysis is carried out considering Hindawi Mathematical Problems in Engineering Volume 2020, Article ID 4363095, 3 pages https://doi.org/10.1155/2020/4363095 the weighted wave heading factors. en, the authors have demonstrated the application of the proposed method by simulating the fatigue lives of a few hot spots. e outcome of the stu...

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Enhancing Flood Susceptibility Modeling: a Hybrid Deep Neural Network with Statistical Learning Algorithms for Predicting Flood Prone Areas

Ghobadi,

Ahmadipari

2024

Water Resour Manage

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Using FloodRisk GIS freeware for uncertainty analysis of direct economic flood damages in Italy

Cited by 24 publications

References 35 publications

Uncertainty Assessment of Climate Change Adaptation Options Using an Economic Pluvial Flood Risk Framework

Uncertainty Assessment of Climate Change Adaptation Options Using an Economic Pluvial Flood Risk Framework

Computational Methods and Applications to Simulate Water-Related Natural Hazards

Enhancing Flood Susceptibility Modeling: a Hybrid Deep Neural Network with Statistical Learning Algorithms for Predicting Flood Prone Areas

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