Rank tests for changepoint problems

Landry

Labrèche

et al. 2014

Water

Abstract:Although climate models predict that the impacts of climate change on the temporal variability of water levels in the St. Lawrence River will be seasonally-dependent, such a seasonal effect on the current variability of extreme water levels has never been analyzed. To address this, we analyzed the temporal variability of three hydrological variables (monthly daily maximums and minimums, as well as their ratio) of water levels in the St. Lawrence River measured at the Sorel station since 1912, as they relate to climate indices. As for stationarity, the shifts in the mean values of maximum and minimum water levels revealed by the Lombard method took place prior to 1970 for spring water levels, but after that year, for winter water levels. Changes in the winter stationarity are thought to mainly relate to the decreasing snowfall observed in the St. Lawrence River watershed after 1970. In contrast, for spring, these changes are likely primarily related to human activity (digging of the St. Lawrence Seaway and construction of dams). Two shifts in the mean values of fall minimum extreme water levels were highlighted. The first of these shifts, which occurred in the first half of the 1960s decade, can also be linked to human activity (digging of the St. Lawrence Seaway and construction of dams), whereas the second shift, observed after the 1970s for the months of November and December, can be linked to decreasing amounts of snow in winter. AMO (Atlantic Multidecadal Oscillation) is the climate index that is most frequently correlated negatively with the hydrologic variables, mainly in winter and spring.

Section: + = T Tmentioning

confidence: 89%

Section: Statistical Analysis Of Extreme Monthly Daily Water Levelsmentioning

confidence: 99%

See 1 more Smart Citation

Temporal Variability of Monthly Daily Extreme Water Levels in the St. Lawrence River at the Sorel Station from 1912 to 2010

Landry

Labrèche

et al. 2014

Water

“…This method allows the detection of shifts (sharp or gradual) in mean and variance values of series and the determination of the precise dates of these shifts. The mathematical basis for this method was described by [21] as well as [22]. Its application to the analysis of hydroclimate data was documented, among others, by [23].…”

Section: Statistical Analysis Of Hydroclimate Seriesmentioning

confidence: 99%

Comparison of the Spatio-Temporal Variability of Annual Minimum Daily Extreme Flow Characteristics as a Function of Land Use and Dam Management Mode in Quebec, Canada

Sylvain

Landry

et al. 2015

Water

This study presents a comparison of the spatio-temporal variability of characteristics (magnitude, duration and timing) of annual minimum daily extreme flows (AMEF) as a function of land use and the mode of management of dams. Streamflow measured at stations not affected by dams at Joliette, along the L'Assomption River (agricultural watershed, 1340 km 2 ), and at Saint-Michel-des-Saints, on the Matawin River (forested watershed, 1390 km 2 ) on one hand, and downstream from the Rawdon dam (regulated natural-type management mode), on the Ouareau River (1260 km 2 ), which is the main tributary of the L'Assomption River, and from the Matawin dam (inverted-type management mode), on the Matawin River (4070 km 2 ), on the other hand, were compared over the period from 1930 to 2010. As far as the spatial variability of natural rivers is concerned, the magnitude and duration of AMEF are higher in the forested watershed than in the agricultural watershed. In regulated rivers, AMEF magnitude is higher downstream from the dam characterized by a natural-type management mode than downstream from the dam characterized by inversion-type management. However, downstream from the latter, AMEF occur much more OPEN ACCESSWater 2015, 7 1233 frequently and very early in the year. As for temporal variability, the Lombard method did not reveal any influence of land use differences on the stationarity of series of AMEF characteristics. In contrast, differences in dam management mode result in occurrences of AMEF downstream from the inversion-type dam progressively earlier in the year. The duration and timing of AMEF are not correlated with the same climate variables, be it in natural rivers or downstream from dams.

“…Significant longitudinal changes in mean reflectance values were precisely constrained to specific zones (i.e., spatial breakpoint) using the Lombard method (Figure 2). Detailed information on this method can be found in Lombard [1987] and Quessy et al [2011].…”

Section: Image Processingmentioning

confidence: 99%

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

Massicotte

Water Resources Research

Gratton

et al. 2013

[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.