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Article

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

1
Department of Civil Engineering, Hydraulics, Energy and Environment, Universidad Politécnica de Madrid, 28040 Madrid, Spain
2
School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ 85281, USA
3
School of Earth and Space Exploration, Arizona State University, Tempe, AZ 85287, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Yves Tramblay
Water 2021, 13(14), 1931; https://doi.org/10.3390/w13141931
Received: 28 May 2021 / Revised: 1 July 2021 / Accepted: 9 July 2021 / Published: 13 July 2021
(This article belongs to the Special Issue Planning and Management of Hydraulic Infrastructure)
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. View Full-Text
Keywords: flood frequency analysis; stochastic approach; AWE-GEN; tRIBS; distributed continuous model; distributed event-based model; initial soil moisture; maximum peak-flow; maximum hydrograph volume flood frequency analysis; stochastic approach; AWE-GEN; tRIBS; distributed continuous model; distributed event-based model; initial soil moisture; maximum peak-flow; maximum hydrograph volume
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MDPI and ACS Style

Sordo-Ward, A.; Gabriel-Martín, I.; Bianucci, P.; Mascaro, G.; Vivoni, E.R.; Garrote, L. Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve. Water 2021, 13, 1931. https://doi.org/10.3390/w13141931

AMA Style

Sordo-Ward A, Gabriel-Martín I, Bianucci P, Mascaro G, Vivoni ER, Garrote L. Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve. Water. 2021; 13(14):1931. https://doi.org/10.3390/w13141931

Chicago/Turabian Style

Sordo-Ward, Alvaro, Ivan Gabriel-Martín, Paola Bianucci, Giuseppe Mascaro, Enrique R. Vivoni, and Luis Garrote. 2021. "Stochastic Hybrid Event Based and Continuous Approach to Derive Flood Frequency Curve" Water 13, no. 14: 1931. https://doi.org/10.3390/w13141931

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