Memorias de investigación
Artículos en revistas:
Extension of observed flood series by combining a distributed hydro-meteorological model and a copula-based model
Año:2015

Áreas de investigación
  • Ingenieria civil

Datos
Descripción
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.
Internacional
Si
JCR del ISI
Si
Título de la revista
Stochastic Environmental Research And Risk Assessment
ISSN
1436-3240
Factor de impacto JCR
2,673
Información de impacto
Datos JCR del año 2013
Volumen
DOI
10.1007/s00477-015-1138-x
Número de revista
Desde la página
1
Hasta la página
16
Mes
SIN MES
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Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Hidroinformática y Gestión del Agua
  • Departamento: Ingeniería Civil: Hidráulica, Energía y Medio Ambiente