Estimation of synthetic flood design hydrographs using a distributed rainfall–runoff model coupled with a copula-based single storm rainfall generator

Candela, Angela; Brigandì, Giuseppina; Aronica, Giuseppe Tito

doi:10.5194/nhess-14-1819-2014

Cited by 43 publications

(35 citation statements)

References 55 publications

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“…The idea to use Huff curves to generate an internal storm structure has also been adopted by Candela et al (2014). Given the 105-year time series at hand, empirical Huff curves can be obtained by partitioning each storm in the time series in e.g.…”

Section: Historical Time Series Characteristicsmentioning

confidence: 99%

A continuous rainfall model based on vine copulas

Vernieuwe

Vandenberghe

Baets

et al. 2015

Hydrol. Earth Syst. Sci.

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Abstract.Copulas have already proven their flexibility in rainfall modelling. Yet, their use is generally restricted to the description of bivariate dependence. Recently, vine copulas have been introduced, allowing multi-dimensional dependence structures to be described on the basis of a stage by stage mixing of 2-dimensional copulas. This paper explores the use of such vine copulas in order to incorporate all relevant dependences between the storm variables of interest. On the basis of such fitted vine copulas, an external storm structure is modelled. An internal storm structure is superimposed based on Huff curves, such that a continuous time series of rainfall is generated. The performance of the rainfall model is evaluated through a statistical comparison between an ensemble of synthetical rainfall series and the observed rainfall series and through the comparison of the annual maxima.

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Section: Historical Time Series Characteristicsmentioning

confidence: 99%

A continuous rainfall model based on vine copulas

Vernieuwe

Vandenberghe

Baets

et al. 2015

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Candela et al (2014) applied a bivariate Archimedean copula-based distribution for characterising rainfall duration and intensity, in order to generate single synthetic rainfall events to be used as input in a conceptual fully distributed rainfall-runoff model based on the curve number method. The copula approach was then applied to the peak flow and hydrograph volume series of 5000 events synthetically generated from such a procedure, to obtain the flood design hydrograph related to a given joint return period.…”

Section: Introductionmentioning

confidence: 99%

Extension of observed flood series by combining a distributed hydro-meteorological model and a copula-based model

Requena

Flores

Mediero

et al. 2015

Stoch Environ Res Risk Assess

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Long flood series are required to accurately estimate flood quantiles associated with high return periods, in order to design and assess the risk in hydraulic structures such as dams. However, observed flood series are commonly short. Flood series can be extended through hydro-meteorological modelling, yet the computational effort can be very demanding in case of a distributed model with a short time step is considered to obtain an accurate flood hydrograph characterisation. Statistical models can also be used, where the copula approach is spreading for performing multivariate flood frequency analyses. Nevertheless, the selection of the copula to characterise the dependence structure of short data series involves a large uncertainty. In the present study, a methodology to extend flood series by combining both approaches is introduced. First, the minimum number of flood hydrographs required to be simulated by a spatially distributed hydro-meteorological model is identified in terms of the uncertainty of quantile estimates obtained by both copula and marginal distributions. Second, a large synthetic sample is generated by a bivariate copula-based model, reducing the computation time required by the hydro-meteorological model.The hydro-meteorological modelling chain consists of the RainSim stochastic rainfall generator and the Real-time Interactive Basin Simulator (RIBS) rainfall-runoff model. The proposed procedure is applied to a case study in Spain. As a result, a large synthetic sample of peak-volume pairs is stochastically generated, keeping the statistical properties of the simulated series generated by the hydro-meteorological model. This method reduces the computation time consumed. The extended sample, consisting of the joint simulated and synthetic sample, can be used for improving flood risk assessment studies.

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“…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 synthetic flood design hydrographs using a distributed rainfall–runoff model coupled with a copula-based single storm rainfall generator

Cited by 43 publications

References 55 publications

A continuous rainfall model based on vine copulas

A continuous rainfall model based on vine copulas

Extension of observed flood series by combining a distributed hydro-meteorological model and a copula-based model

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

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