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A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

Authors :
Requena, A. I.
Mediero Orduña, Luis Jesús
Garrote de Marcos, Luis
Requena, A. I.
Mediero Orduña, Luis Jesús
Garrote de Marcos, Luis
Source :
Hydrology and Earth System Sciences, ISSN 1027-5606, 2013-08, Vol. 17, No. 8
Publication Year :
2013

Abstract

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping

Details

Database :
OAIster
Journal :
Hydrology and Earth System Sciences, ISSN 1027-5606, 2013-08, Vol. 17, No. 8
Notes :
application/pdf, English
Publication Type :
Electronic Resource
Accession number :
edsoai.ocn885149816
Document Type :
Electronic Resource