Dependence Between Extreme Rainfall Events and the Seasonality and Bivariate Properties of Floods. A Continuous Distributed Physically-Based Approach

Gabriel-Martín, Ivan; Sordo‐Ward, Álvaro; Garrote, Luís; García, Juan Pascual

doi:10.3390/w11091896

Cited by 3 publications

(3 citation statements)

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“…Although some modern extensions of this event-based concept account for variable initial conditions prior to the event through sensitivity tests (Filipova et al, 2019), most of the work using event-based simulations assume default initial conditions. Indeed, such event-based simulation is still in use, in particular in the context of probable maximum flood (PMF) estimation based on probable maximum precipitation (PMP) (Beauchamp et al, 2013;Gangrade et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…An example is the work of Arnaud and Lavabre (2002), who use a continuous simulation framework to generate an ensemble of possible extreme hydrographs, which are then used as individual scenarios for hazard management. Another option is to summarize all simulated flood hydrographs into probability distributions for peak flow and flood volume (Gabriel-Martin et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Downsizing parameter ensembles for simulations of rare floods

Sikorska‐Senoner

Schaefli

Seibert

2020

Nat. Hazards Earth Syst. Sci.

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Abstract. For extreme-flood estimation, simulation-based approaches represent an interesting alternative to purely statistical approaches, particularly if hydrograph shapes are required. Such simulation-based methods are adapted within continuous simulation frameworks that rely on statistical analyses of continuous streamflow time series derived from a hydrological model fed with long precipitation time series. These frameworks are, however, affected by high computational demands, particularly if floods with return periods > 1000 years are of interest or if modelling uncertainty due to different sources (meteorological input or hydrological model) is to be quantified. Here, we propose three methods for reducing the computational requirements for the hydrological simulations for extreme-flood estimation so that long streamflow time series can be analysed at a reduced computational cost. These methods rely on simulation of annual maxima and on analysing their simulated range to downsize the hydrological parameter ensemble to a small number suitable for continuous simulation frameworks. The methods are tested in a Swiss catchment with 10 000 years of synthetic streamflow data simulated thanks to a weather generator. Our results demonstrate the reliability of the proposed downsizing methods for robust simulations of rare floods with uncertainty. The methods are readily transferable to other situations where ensemble simulations are needed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Downsizing parameter ensembles for simulations of rare floods

Sikorska‐Senoner

Schaefli

Seibert

2020

Nat. Hazards Earth Syst. Sci.

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show abstract

“…Furthermore, the rainfall-runoff and hydrodynamic models should be fully coupled to allow for representing the flood generation and routing processes with satisfactory accuracy, thus making the whole approach extremely difficult, if not prohibitive, for the engineering community and practicians [18]. For this reason, continuous simulation and stochastic event-based methods are often tackled as alternative approaches [19]. Other alternatives are based on "semi-continuous" schemes, where synthetic rainfall events are inserted into continuous historical rainfall records, and then used in hydrological models [20].…”

mentioning

confidence: 99%

Revisiting Flood Hazard Assessment Practices under a Hybrid Stochastic Simulation Framework

Efstratiadis

Dimas

Pouliasis³

et al. 2022

Water

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We propose a novel probabilistic approach to flood hazard assessment, aiming to address the major shortcomings of everyday deterministic engineering practices in a computationally efficient manner. In this context, the principal sources of uncertainty are defined across the overall modeling procedure, namely, the statistical uncertainty of inferring annual rainfall maxima through distribution models that are fitted to empirical data, and the inherently stochastic nature of the underlying hydrometeorological and hydrodynamic processes. Our work focuses on three key facets, i.e., the temporal profile of storm events, the dependence of flood generation mechanisms on antecedent soil moisture conditions, and the dependence of runoff propagation over the terrain and the stream network on the intensity of the flood event. These are addressed through the implementation of a series of cascade modules, based on publicly available and open-source software. Moreover, the hydrodynamic processes are simulated by a hybrid 1D/2D modeling approach, which offers a good compromise between computational efficiency and accuracy. The proposed framework enables the estimation of the uncertainty of all flood-related quantities, by means of empirically derived quantiles for given return periods. Lastly, a set of easily applicable flood hazard metrics are introduced for the quantification of flood hazard.

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Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve

Sordo‐Ward

Gabriel-Martín

Bianucci

et al. 2021

Water

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This study proposes a methodology that combines the advantages of the event-based and continuous models, for the derivation of the maximum flow and maximum hydrograph volume frequency curves, by combining a stochastic continuous weather generator (the advanced weather generator, abbreviated as AWE-GEN) with a fully distributed physically based hydrological model (the TIN-based real-time integrated basin simulator, abbreviated as tRIBS) that runs both event-based and continuous simulation. The methodology is applied to Peacheater Creek, a 64 km2 basin located in Oklahoma, United States. First, a continuous set of 5000 years’ hourly weather forcing series is generated using the stochastic weather generator AWE-GEN. Second, a hydrological continuous simulation of 50 years of the climate series is generated with the hydrological model tRIBS. Simultaneously, the separation of storm events is performed by applying the exponential method to the 5000- and 50-years climate series. From the continuous simulation of 50 years, the mean soil moisture in the top 10 cm (MSM10) of the soil layer of the basin at an hourly time step is extracted. Afterwards, from the times series of hourly MSM10, the values associated to all the storm events within the 50 years of hourly weather series are extracted. Therefore, each storm event has an initial soil moisture value associated (MSM10Event). Thus, the probability distribution of MSM10Event for each month of the year is obtained. Third, the five major events of each of the 5000 years in terms of total depth are simulated in an event-based framework in tRIBS, assigning an initial moisture state value for the basin using a Monte Carlo framework. Finally, the maximum annual hydrographs are obtained in terms of maximum peak-flow and volume, and the associated frequency curves are derived. To validate the method, the results obtained by the hybrid method are compared to those obtained by deriving the flood frequency curves from the continuous simulation of 5000 years, analyzing the maximum annual peak-flow and maximum annual volume, and the dependence between the peak-flow and volume. Independence between rainfall events and prior hydrological soil moisture conditions has been proved. The proposed hybrid method can reproduce the univariate flood frequency curves with a good agreement to those obtained by the continuous simulation. The maximum annual peak-flow frequency curve is obtained with a Nash–Sutcliffe coefficient of 0.98, whereas the maximum annual volume frequency curve is obtained with a Nash–Sutcliffe value of 0.97. The proposed hybrid method permits to generate hydrological forcing by using a fully distributed physically based model but reducing the computation times on the order from months to hours.

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Dependence Between Extreme Rainfall Events and the Seasonality and Bivariate Properties of Floods. A Continuous Distributed Physically-Based Approach

Cited by 3 publications

References 53 publications

Downsizing parameter ensembles for simulations of rare floods

Downsizing parameter ensembles for simulations of rare floods

Revisiting Flood Hazard Assessment Practices under a Hybrid Stochastic Simulation Framework

Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve

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