Comparison of the interannual variability of spring heavy floods characteristics of tributaries of the St. Lawrence River in Quebec (Canada)

Mazouz, Rabah; Assani, Ali A.; Quessy, Jean‐François; Légaré, Guillaume

doi:10.1016/j.advwatres.2011.10.006

Cited by 34 publications

(25 citation statements)

References 50 publications

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“…In addition, this method is sensitive to small changes in mean and variance, unlike other tests [16]. Because the Lombard test equations have been presented in several papers (e.g., [16][17][18]), they are not described herein. According to this test, at the 95% confidence interval, one concludes that the mean or variance of the series changes significantly whenever S n > 0.0403.…”

Section: Discussionmentioning

confidence: 99%

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Analysis of the Impacts of Man-Made Features on the Stationarity and Dependence of Monthly Mean Maximum and Minimum Water Levels in the Great Lakes and St. Lawrence River of North America

Assani

2016

Water

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Abstract:Various manmade features (diversions, dredging, regulation, etc.) have affected water levels in the Great Lakes and their outlets since the 19th century. The goal of this study is to analyze the impacts of such features on the stationarity and dependence between monthly mean maximum and minimum water levels in the Great Lakes and St. Lawrence River from 1919 to 2012. As far as stationarity is concerned, the Lombard method brought out shifts in mean and variance values of monthly mean water levels in Lake Ontario and the St. Lawrence River related to regulation of these waterbodies in the wake of the digging of the St. Lawrence Seaway in the mid-1950s. Water level shifts in the other lakes are linked to climate variability. As for the dependence between water levels, the copula method revealed a change in dependence mainly between Lakes Erie and Ontario following regulation of monthly mean maximum and minimum water levels in the latter. The impacts of manmade features primarily affected the temporal variability of monthly mean water levels in Lake Ontario.

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Section: Discussionmentioning

confidence: 99%

“…The method has been described in some of our previous work (e.g., [18,20]). The dependence in a random vector (X, Y) is contained in its corresponding copula function C. Specifically, the theorem of Sklar ensures that there exists a unique C :…”

Section: Discussionmentioning

confidence: 99%

Analysis of the Impacts of Man-Made Features on the Stationarity and Dependence of Monthly Mean Maximum and Minimum Water Levels in the Great Lakes and St. Lawrence River of North America

Assani

2016

Water

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“…Researchers have explored the correlation of a wide range of indices with hydro-climate indicators for North American and Canada-wide influences (Rood et al 2005;Gobena and Gan 2006;Bonsal and Shabbar 2008), and for various regions (Coulibaly et al 2000;Déry and Wood 2005;Fleming et al 2007;Woo and Thorne 2008) and specific watersheds in western, northern and eastern Canada (Burn 2008;Brabets and Walvoord 2009;Thorne and Woo 2011;Déry et al 2012;Mazouz et al 2012;Peters et al 2013). A range of hydro-climate indicators, at different temporal scales, were used, including: snow cover (Brown and Goodison 1996), snow water equivalent (Hamlet et al 2005), nival and glacier-influenced streamflow (Fleming et al 2006), annual streamflow (Anctil and Coulibaly 2004;Déry et al 2012), seasonal streamflow (Coulibaly and Burn 2005) and low-flow and high flow extremes (Ehsanzadeh and Adamowski 2008;Khaliq et al 2008;Assani et al 2010Assani et al , 2012.…”

Section: Hydrology-based Indicatorsmentioning

confidence: 99%

Climate and water availability indicators in Canada: Challenges and a way forward. Part II – Historic trends

Mortsch

Cohen

Koshida³

2015

Canadian Water Resources Journal / Revue canadienne des ressour

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“…The multi-dimensional aspect of this study is essential since most spring floods are consequences of multiple cumulative and simultaneous events/conditions, including primarily snowmelt conditions. The severity of spring floods in North-East America depends mainly on the rate of snowmelt and the snow accumulation from the previous winter, but intense spring rainfall events may also amplify the phenomenon (Lawford et al 1995;Turcotte et al 2010;Villarini et al 2011;Mazouz et al 2012). Such meteorological events can be quantified using indicators developed by the Expert Team on Climate Change Detection Monitoring and Indices (ETCCDMI) and/or by the STAtistical and Regional dynamical Downscaling of EXtremes for European regions project (STARDEX), which were used in previous studies in eastern Canada in Gachon et al (2005).…”

Section: Introductionmentioning

confidence: 99%

A nested multivariate copula approach to hydrometeorological simulations of spring floods: the case of the Richelieu River (Québec, Canada) record flood

Saad

Adlouni

St‐Hilaire

et al. 2014

Stoch Environ Res Risk Assess

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Floods have potentially devastating consequences on populations, industries and environmental systems. They often result from a combination of effects from meteorological, physiographic and anthropogenic natures. The analysis of flood hazards under a multivariate perspective is primordial to evaluate several of the combined factors. This study analyzes spring flood-causing mechanisms in terms of the occurrence, frequency, duration and intensity of precipitation as well as temperature events and their combinations previous to and during floods using frequency analysis as well as a proposed multivariate copula approach along with hydrometeorological indices. This research was initiated over the Richelieu River watershed (Quebec, Canada), with a particular emphasis on the 2011 spring flood, constituting one of the most damaging events over the last century for this region. Although some work has already been conducted to determine certain causes of this record flood, the use of multivariate statistical analysis of hydrologic and meteorological events has not yet been explored. This study proposes a multivariate flood risk model based on fully nested Archimedean Frank and Clayton copulas in a hydrometeorological context. Several combinations of the 2011 Richelieu River flood-causing meteorological factors are determined by estimating joint and conditional return periods with the application of the proposed model in a trivariate case. The effects of the frequency of daily frost/thaw episodes in winter, the cumulative total precipitation fallen between the months of November and March and the 90th percentile of rainfall in spring on peak flow and flood duration are quantified, as these combined factors represent relevant drivers of this 2011 Richelieu River record flood. Multiple plausible and physically founded flood-causing scenarios are also analyzed to quantify various risks of inundation.

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Comparison of the interannual variability of spring heavy floods characteristics of tributaries of the St. Lawrence River in Quebec (Canada)

Cited by 34 publications

References 50 publications

Analysis of the Impacts of Man-Made Features on the Stationarity and Dependence of Monthly Mean Maximum and Minimum Water Levels in the Great Lakes and St. Lawrence River of North America

Analysis of the Impacts of Man-Made Features on the Stationarity and Dependence of Monthly Mean Maximum and Minimum Water Levels in the Great Lakes and St. Lawrence River of North America

Climate and water availability indicators in Canada: Challenges and a way forward. Part II – Historic trends

A nested multivariate copula approach to hydrometeorological simulations of spring floods: the case of the Richelieu River (Québec, Canada) record flood

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