Canada Research Chair on the Estimation of Hydro meteorological Variables

Que, Canada

Canada Research Chair on the Estimation of Hydro meteorological Variables

Que, Canada
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Ben Aissia M.-A.,Canada Research Chair on the Estimation of Hydro meteorological Variables | Chebana F.,Canada Research Chair on the Estimation of Hydro meteorological Variables | Ouarda T.B.M.J.,Canada Research Chair on the Estimation of Hydro meteorological Variables | Ouarda T.B.M.J.,Masdar Institute of Science and Technology | And 3 more authors.
Journal of Hydrology | Year: 2014

Generally, hydrological event such as floods, storms and droughts can be described as a multivariate event with mutually dependent characteristics. In the literature, two types of studies are performed focusing either on the evolution of one variable or more but separately, or on the joint distribution of two or more variables on a fixed window period. The main aspect in multivariate analysis is the dependence between the studied variables. It is important to study the evolution of this dependence over a long period especially in studies dealing with climate change (CC). The aim of the present study is to evaluate and analyze the dependence evolution between hydrological variables with an emphasis on the following flood characteristics, peak (. Q), volume (. V) and duration (. D). This analysis includes confidence interval determination, stationarity analysis and change-point detection over a moving window series of three dependence measures. Two watersheds are considered along with observed and simulated flow data, obtained from two hydrological models. Results show that the dependence between the main flood characteristics over time is not constant and not monotonic. The corresponding behavior is sensitive to the choice of hydrological model, to climate scenarios and to the global climate model being used. The dependence of (. Q,. V) decreases when that of (. V,. D) increases. Moreover, the two considered hydrological models generally overestimate the dependence of (. Q,. V) and underestimate the dependence of (. V,. D) and (. Q,. D). All simulated dependence series are stationary over the whole period and present several break-points corresponding to short trends. This study allows also to check the ability of hydrological models, and if necessary, to recalibrate them to correctly simulate the dependence historically and in the future. © 2014 Elsevier B.V.


Lekina A.,Canada Research Chair on the Estimation of Hydro meteorological Variables | Lekina A.,HEC Montréal | Chebana F.,Canada Research Chair on the Estimation of Hydro meteorological Variables | Ouarda T.B.M.J.,Canada Research Chair on the Estimation of Hydro meteorological Variables | Ouarda T.B.M.J.,Masdar Institute of Science and Technology
Stochastic Environmental Research and Risk Assessment | Year: 2014

Parametric models are commonly used in frequency analysis of extreme hydrological events. To estimate extreme quantiles associated to high return periods, these models are not always appropriate. Therefore, estimators based on extreme value theory (EVT) are proposed in the literature. The Weissman estimator is one of the popular EVT-based semi-parametric estimators of extreme quantiles. In the present paper we propose a new family of EVT-based semi-parametric estimators of extreme quantiles. To built this new family of estimators, the basic idea consists in assigning the weights to the k observations being used. Numerical experiments on simulated data are performed and a case study is presented. Results show that the proposed estimators are smooth, stable, less sensitive, and less biased than Weissman estimator. © 2013 Springer-Verlag Berlin Heidelberg.

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