Computational Aspects of Dam Risk Analysis: Findings and Challenges

Escuder‐Bueno, Ignacio; Mazzà, Guido; Morales-Torres, Adrián; Castillo-Rodríguez, Jesica T.

doi:10.1016/j.eng.2016.03.005

Cited by 21 publications

(7 citation statements)

References 1 publication

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“…In 2013 the International Committee of Large Dams organized a numerical benchmark where the participants were invited to predict the breach outflow hydrograph of a hypothetical dam failure; that is, the true outcome was not known (Zenz & Goldgruber, 2013). The results demonstrate that the variations between the predicted hydrographs of different dam breach models/modelers are large and can significantly influence the result of hydrodynamic calculations (Escuder-Bueno et al, 2016). The origin of the discrepancies in the resulting hydrographs of the benchmark participants can be mainly attributed to variability of the erodibility of embankment material as a result of different soil types, compaction effort, and water content (Morris et al, 2008).…”

Section: Introductionmentioning

confidence: 93%

Development of Probabilistic Dam Breach Model Using Bayesian Inference

Peter

Siviglia

Nagel

et al. 2018

Water Resources Research

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Dam breach models are commonly used to predict outflow hydrographs of potentially failing dams and are key ingredients for evaluating flood risk. In this paper a new dam breach modeling framework is introduced that shall improve the reliability of hydrograph predictions of homogeneous earthen embankment dams. Striving for a small number of parameters, the simplified physics‐based model describes the processes of failing embankment dams by breach enlargement, driven by progressive surface erosion. Therein the erosion rate of dam material is modeled by empirical sediment transport formulations. Embedding the model into a Bayesian multilevel framework allows for quantitative analysis of different categories of uncertainties. To this end, data available in literature of observed peak discharge and final breach width of historical dam failures were used to perform model inversion by applying Markov chain Monte Carlo simulation. Prior knowledge is mainly based on noninformative distribution functions. The resulting posterior distribution shows that the main source of uncertainty is a correlated subset of parameters, consisting of the residual error term and the epistemic term quantifying the breach erosion rate. The prediction intervals of peak discharge and final breach width are congruent with values known from literature. To finally predict the outflow hydrograph for real case applications, an alternative residual model was formulated that assumes perfect data and a perfect model. The fully probabilistic fashion of hydrograph prediction has the potential to improve the adequate risk management of downstream flooding.

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Section: Introductionmentioning

confidence: 93%

Development of Probabilistic Dam Breach Model Using Bayesian Inference

Peter

Siviglia

Nagel

et al. 2018

Water Resources Research

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“…1 Risk assessments of concrete gravity dam have been performed for several decades. 2 Some of the early applications are purely based on qualitative assessment, engineering judgment, and expert opinions. 3 Some others use logical modeling techniques for risk quantification such as event tree 4,5 or fault tree 6 methods.…”

Section: Introductionmentioning

confidence: 99%

Analytical failure probability model for generic gravity dam classes

Hariri-Ardebili

2017

Proceedings of the Institution of Mechanical Engineers, Part O:

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Risk analysis of concrete dams and quantification of the failure probability are important tasks in dam safety assessment. The conditional probability of demand and capacity is usually estimated by numerical simulation and Monte Carlo technique. However, the estimated failure probability (or the reliability index) is dam-dependent which makes its application limited to some case studies. This article proposes an analytical failure model for generic gravity dam classes which is optimized based on large number of nonlinear finite element analyses. A hybrid parametric–probabilistic–statistical approach is used to estimate the failure probability as a function of dam size, material distributional models and external hydrological hazard. The proposed model can be used for preliminary design and evaluation of two-dimensional gravity dam models.

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“…For a reliable probabilistic analysis, the emphasis must be placed on the quality of the input parameters and in particular the uncertainties. However, probabilistic assessment, no matter how sophisticated, can still lead to very different solutions for a given problem because of the complex choices of random variables (RVs), characteristic values, PDFs, and bounds, which can largely influence final results [25][26][27]. Consequently, the analysis is generally not updated in light of new information due to the time-consuming re-evaluation and the lack of flexibility in the methods regarding including modified PDFs and bounds.…”

Section: Related Workmentioning

confidence: 99%

Accounting for Uncertainties in the Safety Assessment of Concrete Gravity Dams: A Probabilistic Approach with Sample Optimization

Segura

Miquel

Paultre

et al. 2021

Water

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Important advances have been made in the methodologies for assessing the safety of dams, resulting in the review and modification of design guidelines. Many existing dams fail to meet these revised criteria, and structural rehabilitation to achieve the updated standards may be costly and difficult. To this end, probabilistic methods have emerged as a promising alternative and constitute the basis of more adequate procedures of design and assessment. However, such methods, in addition to being computationally expensive, can produce very different solutions, depending on the input parameters, which can greatly influence the final results. Addressing the existing challenges of these procedures to analyze the stability of concrete dams, this study proposes a probabilistic-based methodology for assessing the safety of dams under usual, unusual, and extreme loading conditions. The proposed procedure allows the analysis to be updated while avoiding unnecessary simulation runs by classifying the load cases according to the annual probability of exceedance and by using an efficient progressive sampling strategy. In addition, a variance-based global sensitivity analysis is performed to identify the parameters most affecting the dam stability, and the parameter ranges that meet the safety guidelines are formulated. It is observed that the proposed methodology is more robust, more computationally efficient, and more easily interpretable than conventional methods.

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Computational Aspects of Dam Risk Analysis: Findings and Challenges

Cited by 21 publications

References 1 publication

Development of Probabilistic Dam Breach Model Using Bayesian Inference

Development of Probabilistic Dam Breach Model Using Bayesian Inference

Analytical failure probability model for generic gravity dam classes

Accounting for Uncertainties in the Safety Assessment of Concrete Gravity Dams: A Probabilistic Approach with Sample Optimization

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