Estimation of flood inundation probabilities using global hazard indexes based on hydrodynamic variables

Aronica, Giuseppe Tito; Candela, Angela; Fabio, Pamela; Santoro, Mario

doi:10.1016/j.pce.2011.04.001

Cited by 49 publications

(43 citation statements)

References 34 publications

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“…A comparison between the probabilistic and deterministic formulations of the problem made on such a basis allows us to raise the question of how the risk related to the river discharge is affected by the model uncertainty. To our knowledge, in recent times only Aronica et al (2012) have dealt with a similar problem, although they assumed the independence of roughness coefficients from flows. Apart from the probability maps conditioned on a design flood, a marginal probability of flood inundation is also derived as a result of integration over the flow of a joint probability of flow magnitude and maximum water levels.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Maximising the usefulness of flood risk assessment for the River Vistula in Warsaw

Kiczko

Romanowicz

Osuch

et al. 2013

Nat. Hazards Earth Syst. Sci.

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Abstract. The derivation of the flood risk maps requires an estimation of maximum inundation extent for a flood with a given return period, e.g. 100 or 500 yr. The results of numerical simulations of flood wave propagation are used to overcome the lack of relevant observations. In practice, deterministic 1-D models are used for that purpose. The solution of a 1-D model depends on the initial and boundary conditions and estimates of model parameters based on the available noisy observations. Therefore, there is a large uncertainty involved in the derivation of flood risk maps using a single realisation of a flow model. Bayesian conditioning based on multiple model simulations can be used to quantify this uncertainty; however, it is too computer-time demanding to be applied in flood risk assessment in practice, without further flow routing model simplifications. We propose robust and feasible methodology for estimating flood risk. In order to decrease the computation times the assumption of a gradually varied flow and the application of a steady state flow routing model is introduced. The aim of this work is an analysis of the influence of those simplifying assumptions and uncertainty of observations and modelling errors on flood inundation mapping and a quantitative comparison with deterministic flood extent maps. Apart from the uncertainty related to the model structure and its parameters, the uncertainty of the estimated flood wave with a specified probability of return period (so-called 1-in-10 yr, or 1-in-100 yr flood) is also taken into account. In order to derive the uncertainty of inundation extent conditioned on the design flood, the probabilities related to the design wave and flow model uncertainties are integrated. In the present paper that integration is done whilst taking into account the dependence of roughness coefficients on discharge. The roughness is parameterised based on maximum annual discharges. This approach allows for the relationship between flood extent and flow values to be derived, thus giving a cumulative assessment of flood risk. The methods are illustrated using the Warsaw reach of the River Vistula as a case study. The results indicate that deterministic and stochastic flood inundation maps cannot be quantitatively compared. We show that the proposed simplified approach to flood risk assessment can be applied even when breaching of the embankment occurs, with the condition that the flooded area is small enough to be filled rapidly.

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Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

Maximising the usefulness of flood risk assessment for the River Vistula in Warsaw

Kiczko

Romanowicz

Osuch

et al. 2013

Nat. Hazards Earth Syst. Sci.

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show abstract

“…Damage functions are expressed as functions of the flood water level H . Of course, the calibration of the governing parameters also influences the damage probability P f functions, used for this global approach, should be performed by developing and running a complete reliability analysis: probabilistic description of the hazard, probabilistic description of the conditional vulnerability and convolution integral providing the risk of failure (Aronica et al, 2011;Schumann et al, 2007).…”

Section: New Global Methods: Probabilistic Development and Proposalmentioning

confidence: 99%

Flood hazards and masonry constructions: a probabilistic framework for damage, risk and resilience at urban scale

Mébarki

Valencia

Salagnac

et al. 2012

Nat. Hazards Earth Syst. Sci.

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Abstract. This paper deals with the failure risk of masonry constructions under the effect of floods. It is developed within a probabilistic framework, with loads and resistances considered as random variables. Two complementary approaches have been investigated for this purpose:-a global approach based on combined effects of several governing parameters with individual weighted contribution (material quality and geometry, presence and distance between columns, beams, openings, resistance of the soil and its slope. . . ),-and a reliability method using the failure mechanism of masonry walls standing out-plane pressure.The evolution of the probability of failure of masonry constructions according to the flood water level is analysed. The analysis of different failure probability scenarios for masonry walls is conducted to calibrate the influence of each "vulnerability governing parameter" in the global approach that is widely used in risk assessment at the urban or regional scale.The global methodology is implemented in a GIS that provides the spatial distribution of damage risk for different flood scenarios. A real case is considered for the simulations, i.e. Cheffes sur Sarthe (France), for which the observed river discharge, the hydraulic load according to the Digital Terrain Model, and the structural resistance are considered as random variables. The damage probability values provided by both approaches are compared. Discussions are also developed about reduction and mitigation of the flood disaster at various scales (set of structures, city, region) as well as resilience.

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“…All normalised hydrographs were extended to a common duration (for comparison purposes) and cluster analysis with the Ward method and Euclidean distances was implemented (Aronica et al, 2012).…”

Section: Hydrograph Selectionmentioning

confidence: 99%

“…In the relatively recent literature, there is a wide application of the copula functions to model the natural variability of hydrometeorological variables, ranging from rainfall (De Michele and Salvadori, 2003;Zhang and Singh, 2007;Balistrocchi and Bacchi, 2011;Singh and Zhang, 2007;Ariff et al, 2012) to floods (Aronica et al, 2012;Balistrocchi et al, 2014;Candela et al, 2014;Domeneghetti et al, 2013;Gräler et al, 2013;Ganguli and Reddy, 2013). …”

Section: Introductionmentioning

confidence: 99%

Dealing with uncertainty in the probability of overtopping of a flood mitigation dam

Michailidi

Bacchi

2017

Hydrol. Earth Syst. Sci.

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Abstract. In recent years, copula multivariate functions were used to model, probabilistically, the most important variables of flood events: discharge peak, flood volume and duration. However, in most of the cases, the sampling uncertainty, from which small-sized samples suffer, is neglected. In this paper, considering a real reservoir controlled by a dam as a case study, we apply a structure-based approach to estimate the probability of reaching specific reservoir levels, taking into account the key components of an event (flood peak, volume, hydrograph shape) and of the reservoir (rating curve, volume-water depth relation). Additionally, we improve information about the peaks from historical data and reports through a Bayesian framework, allowing the incorporation of supplementary knowledge from different sources and its associated error. As it is seen here, the extra information can result in a very different inferred parameter set and consequently this is reflected as a strong variability of the reservoir level, associated with a given return period. Most importantly, the sampling uncertainty is accounted for in both cases (single-site and multi-site with historical information scenarios), and Monte Carlo confidence intervals for the maximum water level are calculated. It is shown that water levels of specific return periods in a lot of cases overlap, thus making risk assessment, without providing confidence intervals, deceiving.

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Estimation of flood inundation probabilities using global hazard indexes based on hydrodynamic variables

Cited by 49 publications

References 34 publications

Maximising the usefulness of flood risk assessment for the River Vistula in Warsaw

Maximising the usefulness of flood risk assessment for the River Vistula in Warsaw

Flood hazards and masonry constructions: a probabilistic framework for damage, risk and resilience at urban scale

Dealing with uncertainty in the probability of overtopping of a flood mitigation dam

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