Global Sensitivity and GLUE-Based Uncertainty Analysis of a 2D-1D Dual Urban Drainage Model

Fraga, Ignacio; Cea, Luís; Puertas, Jerónimo; Suárez, Joaquín; Jiménez, Vicente; Jácome, Alfredo

doi:10.1061/(asce)he.1943-5584.0001335

Cited by 49 publications

(56 citation statements)

References 43 publications

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“…The parameters of the hydrological models shown in Table 3 were calibrated within the well-established GLUE framework (Beven & Binley, 1992). The GLUE methodology has been successfully applied to the calibration of hydrological models, including semi and fully distributed models, such as the ones used in this paper (Blasone et al, 2008;Shen et al, 2012;Cea, Legout, Grangeon, & Nord, 2016;Fraga et al, 2016;Lehbab-Boukezzi, Boukezzi, & Errih, 2016).…”

Section: Models Parameters and Calibrationmentioning

confidence: 99%

“…The parameters shown in Table 3 were sampled using the Latin hypercube sampling (LHS) technique. This technique has been successfully used for model calibration in many hydrological studies (Zhao, Chen, Wang, & Tong, 2012;Kim et al, 2015;Fraga et al, 2016). The ranges of variation of the three potential infiltration rates, the soil porosity, and the river's Manning coefficient, were estimated from the HEC-HMS reference manual (Scharffenberg & Fleming, 2006 In order to limit the computational burden of the simulations, 200…”

Section: Models Parameters and Calibrationmentioning

confidence: 99%

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Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

Fraga

Cea

Puertas

2018

Hydrological Processes

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This paper analyses the effect of rain data uncertainty on the performance of two hydrological models with different spatial structures: a semidistributed and a fully distributed model. The study is performed on a small catchment of 19.6 km2 located in the north‐west of Spain, where the arrival of low pressure fronts from the Atlantic Ocean causes highly variable rainfall events. The rainfall fields in this catchment during a series of storm events are estimated using rainfall point measurements. The uncertainty of the estimated fields is quantified using a conditional simulation technique. Discharge and rain data, including the uncertainty of the estimated rainfall fields, are then used to calibrate and validate both hydrological models following the generalized likelihood uncertainty estimation (GLUE) methodology. In the storm events analysed, the two models show similar performance. In all cases, results show that the calibrated distribution of the input parameters narrows when the rain uncertainty is included in the analysis. Otherwise, when rain uncertainty is not considered, the calibration of the input parameters must account for all uncertainty in the rainfall–runoff transformation process. Also, in both models, the uncertainty of the predicted discharges increase in similar magnitude when the uncertainty of rainfall input increase.

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Section: Models Parameters and Calibrationmentioning

confidence: 99%

Section: Models Parameters and Calibrationmentioning

confidence: 99%

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

Fraga

Cea

Puertas

2018

Hydrological Processes

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“…Los algoritmos implementados en el modelo han sido validados y aplicados por diversos autores en diferentes estudios hidrodinámicos y de inundación en ríos, estuarios y zonas urbanas (Bermúdez et al, 2017;Bodoque et al, 2016;Cea y Bladé, 2015;Cea y French, 2012;Fraga et al, 2016).…”

Section: Modelado Numéricounclassified

Determinación de la inundación en tramos de ríos afectados por marea basada en la simulación continúa de nivel

Sopelana¹,

Cea

Ruano

2017

ing.agua

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Sopelana et al. | Determinación de la inundación en tramos de ríos afectados por marea basada en la simulación […] RESUMENLas desembocaduras, estuarios y tramos de ríos costeros son elementos hidrodinámicamente complejos debido a la interacción de varias dinámicas generadoras de inundación como la marea astronómica, la marea meteorológica, el oleaje y el caudal del río, entre otras. La marea astronómica es una onda larga que se propaga aguas arriba llegando a afectar a tramos de río situados a decenas de kilómetros de la costa. En estos tramos de río, el mismo nivel del agua puede ser el resultado de diferentes combinaciones de las dinámicas mencionadas. Los estudios de peligrosidad y riesgo de inundación en tramos de ríos afectados por la marea se han basado hasta ahora en la aplicación de una condición de contorno de nivel de marea fijada de forma más o menos arbitraria. En España, la Guía metodológica para el desarrollo del Sistema Nacional de Cartografía de Zonas Inundables (Ministerio de Medio Ambiente y Medio Rural y Marino, 2011), consciente de la complejidad de los procesos y en aras de simplificar, aconseja aplicar una condición de contorno de nivel correspondiente al mismo periodo de retorno que el de la avenida que se esté modelizando. Esta forma de proceder no tiene en cuenta la probabilidad de ocurrencia de varios eventos extremos al mismo tiempo. En este artículo se propone una metodología híbrida de simulación continua que combina la generación de series sintéticas a largo plazo de las variables implicadas, un modelado hidrodinámico bidimensional de alta resolución espacial de la zona de estudio, y técnicas estadísticas de muestreo de datos e interpolación de resultados. La metodología propuesta se ha aplicado a la ciudad costera de Betanzos (noroeste de España), localizada en la confluencia de dos ríos y en la cola de un estuario. Históricamente Betanzos ha tenido problemas de inundación por lo que está catalogada como un Área de Riesgo Potencial Significativo de Inundación (ARPSI) fluvial y costera. Los resultados se han comparado con los obtenidos aplicando la propuesta de la

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“…There have been several previous works on 1D-2D dual drainage simulation models (coupling of 1D sewer network with 2D surface overland flow) in the literature [22][23][24][25][26][27][28][29]. In this kind of approach, the numerical model takes into account the flow through both surface and sewer system domains and establishes a communication between them at certain points, such as culverts or manholes.…”

Section: Introductionmentioning

confidence: 99%

Development of a New Simulation Tool Coupling a 2D Finite Volume Overland Flow Model and a Drainage Network Model

Fernández-Pato

García‐Navarro

2018

Geosciences

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Numerical simulation of mixed flows combining free surface and pressurized flows is a practical tool to prevent possible flood situations in urban environments. When dealing with intense storm events, the limited capacity of the drainage network conduits can cause undesirable flooding situations. Computational simulation of the involved processes can lead to better management of the drainage network of urban areas. In particular, it is interesting to simultaneuously calculate the possible pressurization of the pipe network and the surface water dynamics in case of overflow. In this work, the coupling of two models is presented. The surface flow model is based on two-dimensional shallow water equations with which it is possible to solve the overland water dynamics as well as the transformation of rainfall into runoff through different submodels of infiltration. The underground drainage system assumes mostly free surface flow that can be pressurized in specific situations. The pipe network is modeled by means of one-dimensional sections coupled with the surface model in specific regions of the domain, such as drains or sewers. The numerical techniques considered for the resolution of both mathematical models are based on finite volume schemes with a first-order upwind discretization. The coupling of the models is verified using laboratory experimental data. Furthermore, the potential usefulness of the approach is demonstrated using real flooding data in a urban environment.

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Global Sensitivity and GLUE-Based Uncertainty Analysis of a 2D-1D Dual Urban Drainage Model

Cited by 49 publications

References 43 publications

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

Effect of rainfall uncertainty on the performance of physically based rainfall–runoff models

Determinación de la inundación en tramos de ríos afectados por marea basada en la simulación continúa de nivel

Development of a New Simulation Tool Coupling a 2D Finite Volume Overland Flow Model and a Drainage Network Model

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