An overview of methods to evaluate uncertainty of deterministic models in decision support

Uusitalo, Laura; Lehikoinen, Annukka; Helle, Inari; Myrberg, Kai

doi:10.1016/j.envsoft.2014.09.017

Cited by 447 publications

(286 citation statements)

References 68 publications

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“…In addition, the current approach could be extended to the full geographical scale of LISCoAsT (Vousdoukas et al, 2018a, b). Finally, the selection of uncertainty sources can be deemed subjective, as with any nonexhaustive analysis (Uusitalo et al, 2015), and in the following paragraphs we try to underline the aspects which could be interesting for further investigation in future research. The accuracy of ESL projections is affected by the atmospheric and ocean model resolution (Cavaleri and Bertotti, 2004;Calafat et al, 2014) as well as including (or not) nonlinear interactions between ESL components (Arns et al, 2015) and waves in the analysis (Serafin and Ruggiero, 2014;Vitousek et al, 2017).…”

Section: Discussionmentioning

confidence: 99%

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policymaking, and harmonization of climate change adaptation strategies. There is, however, limited insight into the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the coastal flood risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea level (ESL), (ii) the underlying uncertainty in the digital elevation model (DEM), (iii) flood defence information, (iv) the assumptions behind the use of depth-damage functions that express vulnerability, and (v) different climate change projections. The impact of these uncertainties on estimated expected annual damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal, and on the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, and their absolute and relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large datasets with sufficient resolution and accuracy, the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.

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Section: Discussionmentioning

confidence: 99%

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Vousdoukas

Bouziotas

Giardino

et al. 2018

Nat. Hazards Earth Syst. Sci.

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“…Knowledge of the type and magnitude of the uncertainties is crucial to understand and interpret a model's results. Therefore, uncertainty analysis, conducted to quantify the uncertainty in the model's outputs values induced by the uncertainty in the inputs, increases the confidence in hydraulic model predictions [4].…”

Section: Introductionmentioning

confidence: 99%

Uncertainty Analysis of a Two-Dimensional Hydraulic Model

Oubennaceur

Chokmani

Nastev

et al. 2018

Water

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Abstract:A reliability approach referred to as the point estimate method (PEM) is presented to assess the uncertainty of a two-dimensional hydraulic model. PEM is a special case of numerical quadrature based on orthogonal polynomials, which evaluates the statistical moments of a performance function involving random variables. When applied to hydraulic problems, the variables are the inputs to the hydraulic model, and the first and second statistical moments refer to the mean and standard deviation of the model's output. In providing approximate estimates of the uncertainty, PEM appears considerably simpler and requires less information and fewer runs than standard Monte Carlo methods. An example of uncertainty assessment is shown for simulated water depths in a 46 km reach of the Richelieu River, Canada. The 2D hydraulic model, H2D2, was used to solve the shallow water equations. Standard deviations around the mean water depths were estimated by considering the uncertainties of three main input variables: flow rate, Manning's coefficient and topography. Results indicate that the mean standard deviation is <27 cm for the considered flow rates of 759, 824, 936, 1113 m 3 /s. Higher standard deviations were obtained upstream of the topographic shoal at the municipality of Saint-Jean-sur-Richelieu. The PEM method adds further value to the H2D2 model predictions as it indicates the magnitude and the spatial variation in uncertainties. The effort required to complete an uncertainty analysis using the PEM method is minimal and the resulting insight is meaningful. This knowledge should be incorporated into decision-making in the context of flood risk assessment.

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“…In transportation engineering, despite considerable information can be derived from new technologies and can be incorporated into the traditional performance measurements (see e.g. [2][3][4][5][6][7][8]), the effect of variability and uncertainty in input parameters on outputs is not often taken into account in the capacity analysis of roads and intersections. The assessment of the effects of a design choice on one or more parameters that are used when an operational analysis is being carried out, requests information on the sources of uncertainty that have affected them and the relation among them [9].…”

Section: The Backgroundmentioning

confidence: 99%

Exploring the uncertainty in capacity estimation at roundabouts

Giuffrè

Granà

Tumminello

2017

Eur. Transp. Res. Rev.

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Purpose In gap-acceptance theory the critical and the followup headways have a significant role in determining roundabout entry capacities which in turn depend on circulating flow rates under a specified arrival headway distribution. Calculation considers single mean values of the gap-acceptance parameters, neglecting the inherent variations in these random variables and providing a single value of entry capacity. The purpose of this paper is to derive the entry capacity distribution which accounts for the variations of the contributing (random) variables and suggest how to consider this issue in the operational analysis of the roundabouts. Methods We performed a Monte Carlo simulation to get the distribution of entry capacity and found Crystal Ball software effective for performing the random sampling from the probability density functions of each contributing parameter. A steady-state model of capacity was used for performing many runs; in each run, the values of each contributing parameter were randomly drawn from the corresponding distributions. Results The paper presents the first simulations and the entry capacity distributions at roundabouts, once the probability distributions of the headways were assumed. The results of the analysis were expressed probabilistically, meaning that the probability distributions of capacity rather than the simple point estimates were obtained. Conclusions Comparing the capacity values based on a metaanalytic estimation of critical and follow-up headways and the capacity functions based on the probability distributions of the model parameters, more insights in developing an appropriate approach to capacity estimation at roundabouts can be gained.

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An overview of methods to evaluate uncertainty of deterministic models in decision support

Cited by 447 publications

References 68 publications

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

Uncertainty Analysis of a Two-Dimensional Hydraulic Model

Exploring the uncertainty in capacity estimation at roundabouts

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