Temporal Regionalization of 7-Day Low Flows in the St. Lawrence Watershed in Quebec (Canada)

Assani, Ali A.; Chalifour, Alain; Légaré, Guillaume; Caza-Szoka, Manouane; Leroux, Denis

doi:10.1007/s11269-011-9870-6

Cited by 26 publications

(18 citation statements)

References 57 publications

(67 reference statements)

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“…In an international level, this affirmation can be ascertained through the development of several studies aiming hydrological generalization (ASSANI et al, 2011;MWALE et al, 2011;SAMUEL et al, 2011;ENGELAND & HISDAL, 2009;CASTIGLIONI et al, 2009). …”

Section: Introductionmentioning

confidence: 98%

Multivariate statistical analysis to support the minimum streamflow regionalization

Elesbon¹,

Silva²,

Sediyama³

et al. 2015

Eng. Agríc.

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This study aimed to develop a methodology based on multivariate statistical analysis of principal components and cluster analysis, in order to identify the most representative variables in studies of minimum streamflow regionalization, and to optimize the identification of the hydrologically homogeneous regions for the Doce river basin. Ten variables were used, referring to the river basin climatic and morphometric characteristics. These variables were individualized for each of the 61 gauging stations. Three dependent variables that are indicative of minimum streamflow (Q 7,10 , Q 90 and Q 95 ). And seven independent variables that concern to climatic and morphometric characteristics of the basin (total annual rainfall -P a ; total semiannual rainfall of the dry and of the rainy season -P ss and P sc ; watershed drainage area -A d ; length of the main river -L p ; total length of the rivers -L t ; and average watershed slope -S L ). The results of the principal component analysis pointed out that the variable S L was the least representative for the study, and so it was discarded. The most representative independent variables were A d and P sc . The best divisions of hydrologically homogeneous regions for the three studied flow characteristics were obtained using the Mahalanobis similarity matrix and the complete linkage clustering method. The cluster analysis enabled the identification of four hydrologically homogeneous regions in the Doce river basin. KEYWORDS: principal component analysis, cluster analysis, homogeneous regions. ESTATÍSTICAS MULTIVARIADAS COMO SUPORTE À REGIONALIZAÇÃO DE VAZÕES MÍNIMAS1 RESUMO: Este trabalho teve por objetivo propor uma metodologia baseada em análises estatísticas multivariadas de componentes principais e de agrupamento, com o intuito de identificar as variáveis mais representativas em estudos de regionalização de vazões mínimas e otimizar a obtenção das regiões hidrologicamente homogêneas para a bacia hidrográfica do Rio Doce. Foram utilizadas 10 variáveis referentes às características climáticas e morfométricas da bacia. Essas variáveis foram individualizadas para as 61 estações fluviométricas adotadas, sendo três variáveis dependentes e indicativas das vazões mínimas (Q 7,10 , Q 90 e Q 95 ) e sete independentes (precipitação total anual -P a ; precipitação total do semestre seco -P ss e chuvoso -P sc ; área de drenagem da bacia -A d ; comprimento do rio principal -L p ; comprimento total dos cursos d'água da bacia -L t ; e declividade média da bacia -S L ). O resultado da análise de componentes principais apontou a variável independente S L como a menos representativa e foi excluída do estudo. As variáveis independentes mais representativas foram A d e P sc . As melhores divisões de regiões hidrologicamente homogêneas para as três vazões características estudadas foram obtidas utilizando-se conjuntamente da matriz de similaridade de Mahalanobis e do método de agrupamento do vizinho mais distante. A análise de agrupamento possibilitou a identificação de quatro re...

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Section: Introductionmentioning

confidence: 98%

Multivariate statistical analysis to support the minimum streamflow regionalization

Elesbon¹,

Silva²,

Sediyama³

et al. 2015

Eng. Agríc.

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show abstract

“…The influence of this index on the interannual variability of hydroclimatic variables (temperature, precipitation, and river flow) is largely documented in North America [e.g., Enfield et al, 2001;McCabe et al, 2004;Sutton and Hodson, 2005;Curtis, 2008]. For instance, this index revealed a negative correlation with Assani et al, 2010aAssani et al, , 2010bAssani et al, , 2011Assani et al, , 2012. Accordingly, when this index is in a positive phase, precipitation and river flow (water level) diminished.…”

Section: Discussionmentioning

confidence: 99%

“…Water-level measurements are recorded from Lake Ontario since 1918. The climate indices selected are related to the interannual and interdecadal variability of streamflow in the Great Lakes watershed in North America, in general, and Quebec, in particular [e.g., Enfield et al, 2001;Anctil and Coulibaly, 2004;Wood, 2004, 2005;McCabe et al, 2004;Coulibaly and Burn, 2004;Kingston et al, 2006;Shabbar, 2006;Curtis, 2008;Assani et al, 2010aAssani et al, , 2010bAssani et al, , 2011. They are the following: the Arctic oscillation (AO), the Atlantic multidecadal oscillation (AMO), the North Atlantic oscillation (NAO), and the southern oscillation (SOI).…”

Section: Sources Of Hydroclimatic Data and Statistical Analysismentioning

confidence: 99%

“…All studies looking at water color in rivers to date have focused on measurement methods, processes, and factors that affect this color [e.g., Kirk, 1988Kirk, , 1994DaviesColley and Nagels, 2008;Thorp et al, 2006;Frenette et al, 2003Frenette et al, , 2006Frenette et al, , 2012Stomp et al, 2007;Julian et al, 2008a;Bukata, 1995;. Although the existence of a link between climate indices and flow (or water levels) in rivers has been demonstrated by many authors (e.g., Assani et al [2010aAssani et al [ , 2010bAssani et al [ , 2011 for Quebec), to our knowledge, no study has examined the relationship between water color in rivers and water levels, so the present study aims to fill this gap. More specifically, it aims to determine whether or not the color of SLR waters is directly sensitive (i) to water-level fluctuations and/or indirectly sensitive to climate variability using well-described climate indices.…”

Section: Introductionmentioning

confidence: 99%

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Relationship between water color, water levels, and climate indices in large rivers: Case of the St. Lawrence River (Canada)

Massicotte

Assani

Gratton

et al. 2013

Water Resources Research

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[1] The relationship between the color (measured with Landsat Thematic Mapper and Enhanced Thematic Mapper sensors in bands 1, 2, and 3) of St. Lawrence River (SLR) water and water levels (in SLR and Lake Ontario) was first analyzed, followed by the analysis of the relationship between water levels and four climate indices for the period from 1984 to 2009. Although there is a statistically significant relationship between these first two variables, this link depends on the strength of two factors: the type of color (band) and inflows from tributaries. Bands 1 (blue) and 2 (green) were negatively correlated with water levels. This correlation, however, is spatially influenced by water inflows from tributaries. Band 3 (red) showed no significant correlation with either water level. Over the same period, water levels were negatively correlated with the Atlantic multidecadal oscillation index. Results suggest that the color of waters in the SLR may be used as an indicator to monitor environmental and climate changes in its watershed.

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“…The following formula was used for linear regression: However, the linear regression method does not yield information on the nature of changes (abrupt or smooth) affecting the arithmetic mean (average) and variance values of time series, nor the precise dates of such changes. The Lombard method, described by Assani et al (2011) among others, was therefore used to obtain this information. Let a series of observations, noted X 1 ,…,X n , where X i is the observation taken at time T=i.…”

Section: Choice Of Hydrologic Variables and Statistical Methodsmentioning

confidence: 99%

Reservoirs Effects on the Interannual Variability of Winter and Spring Streamflow in the St-Maurice River Watershed (Quebec, Canada)

Assani

Landry

Daigle

et al. 2011

Water Resour Manage

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The aim of this study was to test three main hypotheses about the interannual variability of streamflow downstream from dams: (1) an almost similar long-term trend in interannual variability, (2) low variability of flow, and (3) its independence (no link) from climate variability. To test these hypotheses, the interannual variability of winter and spring streamflow downstream from three reservoirs (Gouin, Manouane, and Matawin) which induce an inversion of the natural cycle of streamflow (maximum flows in winter and minimum flows in spring) was compared to the interannual variability of streamflow in natural rivers (measured at the Matawin and Vermillon stations) over the period from 1932 to 2008 in the St-Maurice River watershed. As far as the interannual variability of flow is concerned, its long-term trend is not homogeneous downstream from the three reservoirs in both seasons. However, downstream from two reservoirs, changes in streamflow were observed to be different from those in natural rivers (no significant trend downstream from the Taureau reservoir, on the Matawin River, and significant decrease in spring flow downstream from the Manouane reservoir). Finally, coefficient of variation values for minimum flows are higher downstream from reservoirs than in natural rivers, despite the fact that watershed surface area is larger for regulated rivers than for natural ones. As for the link with climate variability, analysis of the correlation between climate variables (temperature and precipitation) and mean winter and spring daily streamflow reveals that winter streamflow downstream from the Taureau reservoir is not correlated with any climate variable, whereas spring streamflow is positively correlated with rainfall and negatively Water Resour Manage (2011) 25:3661-3675 correlated with maximum temperature. Thus, downstream from reservoirs, the interannual variability of streamflow depends on climate during the spring, but not during winter.

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Temporal Regionalization of 7-Day Low Flows in the St. Lawrence Watershed in Quebec (Canada)

Cited by 26 publications

References 57 publications

Multivariate statistical analysis to support the minimum streamflow regionalization

Multivariate statistical analysis to support the minimum streamflow regionalization

Relationship between water color, water levels, and climate indices in large rivers: Case of the St. Lawrence River (Canada)

Reservoirs Effects on the Interannual Variability of Winter and Spring Streamflow in the St-Maurice River Watershed (Quebec, Canada)

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