Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches

Baldassarre, Giuliano Di; Schumann, Guy; Bates, Paul; Freer, J. E.; Beven, Keith

doi:10.1080/02626661003683389

Cited by 235 publications

(210 citation statements)

References 54 publications

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“…In other words, recent studies point out that roughness coefficients should not be regarded as physically based parameters but rather as statistical parameters that describe riverbed roughness condition and concurrently compensate for the lack of accuracy in the description of riverbed geometry and other simplifying assumptions adopted in practical applications. This compensation may be responsible for unrealistic Manning's coefficients (Horritt and Bates, 2002;Pappenberger et al, 2005;Di Baldassarre et al, 2010). Nevertheless, our analysis showed through a numerical study that adopts as "truth" the output of the same quasi-2-D numerical model for which we then calibrate the roughness coefficients (i.e.…”

Section: Resultsmentioning

confidence: 99%

Assessing rating-curve uncertainty and its effects on hydraulic model calibration

Domeneghetti

Castellarin

Brath

2012

Hydrol. Earth Syst. Sci.

137

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Abstract. This study considers the overall uncertainty affecting river flow measurements and proposes a framework for analysing the uncertainty of rating-curves and its effects on the calibration of numerical hydraulic models. The uncertainty associated with rating-curves is often considered negligible relative to other approximations affecting hydraulic studies, even though recent studies point out that ratingcurves uncertainty may be significant. This study refers to a ∼240 km reach of River Po and simulates ten different historical flood events by means of a quasi-twodimensional (quasi-2-D) hydraulic model in order to generate 50 synthetic measurement campaigns (5 campaigns per event) at the gauged cross-section of interest (i.e. Cremona streamgauge). For each synthetic campaign, two different procedures for rating-curve estimation are applied after corrupting simulated discharges according to the indications reported in the literature on accuracy of discharge measurements, and the uncertainty associated with each procedure is then quantified. To investigate the propagation of rating-curve uncertainty on the calibration of Manning's roughness coefficients further model simulations are run downstream Cremona's cross-section. Results highlight the significant role of extrapolation errors and how rating-curve uncertainty may be responsible for estimating unrealistic roughness coefficients. Finally, the uncertainty of these coefficients is analysed and discussed relative to the variability of Manning's coefficient reported in the literature for large natural streams.

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Section: Resultsmentioning

confidence: 99%

Assessing rating-curve uncertainty and its effects on hydraulic model calibration

Domeneghetti

Castellarin

Brath

2012

Hydrol. Earth Syst. Sci.

137

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“…This approach is suitable for the uncertainty analysis of complex, multiparameter flow routing models and was successfully applied to many flow-routing problems, e.g. Romanowicz and Beven (2003) and Di Baldassarre et al (2010). The method is not statistically efficient but easy to apply.…”

Section: Published By Copernicus Publications On Behalf Of the Europementioning

confidence: 99%

“…There is a substantial difference between the results obtained using both approaches. Di Baldassarre et al (2010) presented a critical discussion of deterministic and probabilistic approaches to flood risk assessment. In their paper the uncertainty of the 1-in-100 yr event was taken into account by sampling from the 1-in-100 yr discharge within a ±15 % range, assuming an equal probability for each sample.…”

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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“…high quality field data and a lidarderived DEM), than a good characterisation of the rainfallrunoff relationship. Current approaches to flood mapping have pointed out that in order to produce a scientifically justifiable flood map, the most physically realistic model should be utilised (Di Baldassarre et al, 2010). Nevertheless, even with these models the amount of uncertainty involved in the determination of an affected area is important and should be quantified.…”

Section: Flood Inundation Modelmentioning

confidence: 99%

Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

Rodríguez-Rincón

Acuña²,

Breña-Naranjo

2015

Hydrol. Earth Syst. Sci.

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Abstract. This investigation aims to study the propagation of meteorological uncertainty within a cascade modelling approach to flood prediction. The methodology was comprised of a numerical weather prediction (NWP) model, a distributed rainfall-runoff model and a 2-D hydrodynamic model. The uncertainty evaluation was carried out at the meteorological and hydrological levels of the model chain, which enabled the investigation of how errors that originated in the rainfall prediction interact at a catchment level and propagate to an estimated inundation area and depth. For this, a hindcast scenario is utilised removing non-behavioural ensemble members at each stage, based on the fit with observed data. At the hydrodynamic level, an uncertainty assessment was not incorporated; instead, the model was setup following guidelines for the best possible representation of the case study. The selected extreme event corresponds to a flood that took place in the southeast of Mexico during November 2009, for which field data (e.g. rain gauges; discharge) and satellite imagery were available. Uncertainty in the meteorological model was estimated by means of a multiphysics ensemble technique, which is designed to represent errors from our limited knowledge of the processes generating precipitation. In the hydrological model, a multi-response validation was implemented through the definition of six sets of plausible parameters from past flood events. Precipitation fields from the meteorological model were employed as input in a distributed hydrological model, and resulting flood hydrographs were used as forcing conditions in the 2-D hydrodynamic model. The evolution of skill within the model cascade shows a complex aggregation of errors between models, suggesting that in valley-filling events hydro-meteorological uncertainty has a larger effect on inundation depths than that observed in estimated flood inundation extents.

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Flood-plain mapping: a critical discussion of deterministic and probabilistic approaches

Cited by 235 publications

References 54 publications

Assessing rating-curve uncertainty and its effects on hydraulic model calibration

Assessing rating-curve uncertainty and its effects on hydraulic model calibration

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

Propagation of hydro-meteorological uncertainty in a model cascade framework to inundation prediction

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