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Dam risk assessment based on univariate versus bivariate statistical approaches: a case study for Argentina
Authors:Ana Claudia Callau Poduje  Aslan Belli  Uwe Haberlandt
Institution:1. Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering, Leibniz University Hannover, Hannover, Germanycallau@iww.uni-hannover.de;3. Institute of Water Resources Management, Hydrology and Agricultural Hydraulic Engineering, Leibniz University Hannover, Hannover, Germany
Abstract:Abstract

Considering floods as multivariate events allows a better statistical representation of their complexity. In this work the relevance of multivariate analysis of floods for designing or assessing the safety of hydraulic structures is discussed. A flood event is characterized by its peak flow and volume. The dependence between the variables is modelled with a copula. One thousand random pairs of variables are transformed to hydrographs, applying the Beta distribution function. Synthetic floods are routed through a reservoir to assess the risk of overtopping a dam. The resulting maximum water levels are compared to estimations considering the peak flow and volume separately. The analysis is performed using daily flows observed in the River Agrio in Neuquén Province, Argentina, a catchment area of 7300 km2. The bivariate approach results in higher maximum water level values. Therefore the multivariate approach should be preferred for the estimation of design variables.
Editor D. Koutsoyiannis; Associate editor S. Grimaldi
Keywords:copula  dam risk assessment  flood frequency  synthetic hydrograph
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