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Several statistical methods were used to analyze the spatio-temporal variability of daily minimum extreme flows (DMEF) in 17 watersheds—divided into three homogenous hydroclimatic regions of southern Quebec—during the transitional seasons (spring and fall), during the 1930–2019 period. Regarding spatial variability, there was a clear difference between the south and north shores of the St. Lawrence River, south of 47° N. DMEF were lower in the more agricultural watersheds on the south shore during transitional seasons compared to those on the north shore. A correlation analysis showed that this difference in flows was mainly due to more agricultural areas ((larger area (>20%) on the south than on the north shore (

Significant changes in regional climates have been observed at the end of the twentieth century, taking place at unprecedented rates. These changes, in turn, lead to changes in global climate zones with pace and amplitude varying from one region to another. Algeria, a country characterized by climate conditions ranging from relatively wet to very dry (desert-like), has also experienced changes in its climate regions, notably in the country’s wet region, which represents about 7% of its total surface area, but is home to 75% of its population. In this study, the pace of climate zone changes as it is defined by Koppen–Geiger was analyzed for the period from 1951 to 2098 using climate data from observation and regional climate simulations over Algeria. The ability of the CORDEX-Africa regional climate models simulations to reproduce the current observed climate zones and their shifts was first assessed. Future changes over the whole of the twenty-first century were then estimated based on two Representative Concentration Pathway (RCP4.5 and RCP8.5) scenarios. Analysis of the shift rate of climate zones from 1951 to 2005 found a gradual but significant expansion of the surface area of the desert zone at an approximate rate of 650 ± 160 km2/year along with the abrupt shrinking, by approximately 30%, at a rate of 1086 ± 270 km2/year, of the warm temperate climate zone surface area. According to projections for the RCP8.5 scenario, the rate of expansion of desert climate will increase in the future (twenty-first century), particularly during the period from 2045 to 2098.

The objective of this study is to use two hydrological indices (coefficients of variation and immoderation) to analyze the impacts of dam management methods on seasonal daily flow rate change downstream of three dams: Manouane (diversion-type management method), Ouareau (natural-type management method) and Matawin (inversion-type management method). The results show that this change is far greater downstream of the Matawin dam (characterized by an inversion-type management method) than downstream of the two other dams. Moreover, downstream of the Matawin dam, this daily flow rate change increases significantly over time, while decreasing downstream of the two other dams and in natural rivers. Lastly, this change is better correlated with climate downstream of the Ouareau dam than downstream of the two other dams. It is positively correlated with winter and spring temperatures as well as summer and fall rain. Contrary commonly accepted hypothesis, this study shows that the impacts of dams generally result in an increase of the seasonal flow rate change in Quebec.

The goal of this study was to analyse the impacts of the sequence of 1 El Nino (2009–2010) and 2 La Nina (2007–2008 and 2010–2011) events on the interannual variability of daily streamflow during the growing season (April to September) and grass species abundance downstream from the Taureau reservoir (4,070 km2) on the Matawin River (Quebec, Canada). This reservoir has inverted the natural annual cycle of streamflow: Maximum flows occur in winter and minimum flows in springtime during snowmelt. Comparison of daily flows over the period from 2006 to 2011 using various statistical tests revealed a significant increase in flows released downstream from the reservoir during the 2 La Nina events, with a particularly large increase in the growing season (April to May) during the 1st La Nina event (2007–2008). In contrast, during the El Nino event (2009–2010), streamflow decreased significantly. As far as the abundance of plant species is concerned, the total number of obligate wetland species increased significantly after the 1st La Nina event and then decreased after the El Nino event, along with the total number of terrestrial species. The study shows that relatively intense El Nino Southern Oscillation events can have significant implications for the management of flows released downstream from reservoirs in Quebec and hence affect plant species abundance on islets.

Many studies have highlighted breaks in mean values of temperature and precipitation time series since the 1970s. Given that temperatures have continued to increase following that decade, the first question addressed in this study is whether other breaks in mean values have occurred since that time. The second question is to determine which climate indices influence temperature and rainfall in the coastal region of Northern Algeria. To address these two questions, we analyzed the temporal variability of temperature and annual and seasonal rainfall as they relate to four climate indices at seven coastal stations in Algeria during the 1972–2013 period using the Mann–Kendall, Lombard, and canonical correlation (CC) analysis methods.The annual and seasonal maximum, minimum and mean temperatures increased significantly over that time period. Most of these increases are gradual, implying a slow warming trend. In contrast, total annual and seasonal rainfall did not show any significant change. CC analysis revealed that annual and seasonal temperatures are negatively correlated with the Western Mediterranean Oscillation (WeMOI) climate index that characterizes atmospheric circulation over the Mediterranean basin. On the other hand, rainfall is positively correlated with a large-scale atmospheric index such as the Southern Oscillation Index.

The increase in drought features in North Africa and Mediterranean regions is one of the most threatening natural hazards related to climate change. The spatial extent of this phenomenon in the North-West of Algeria has caused serious economic, social, and environmental impact with enormous losses. In this study, the return periods of drought events characterized by high severities and the three main droughts characteristics (duration, severity, and intensity) in the future under two Representative Concentration Pathway (RCP4.5 and RCP8.5) over two representative watersheds in North-West Algeria have been estimated In order to plan and manage the water resources under drought conditions.

In this study, we compared the frequency and timing of drought and wetness indices of annual mean water levels in the North American Great Lakes as they relate to teleconnection indices over the period from 1918 to 2012. In terms of timing, drought occurred in the Great Lakes watershed during the 1920, 1930 and 2000 decades, and was very intense in the East during the 1930’s and in the West during the 2000 decade. The main cause of extreme drought episodes in the 1920’s and 1930’s was a decrease in precipitation, while the 2000 decade drought is thought to be caused by increased water temperature (enhanced evaporation) due to a significant decrease in winter ice cover. The 1970 and 1980 decades were very wet over the whole watershed as a result of increased precipitation in the region. The succession of these dry and wet episodes did not have the same impacts on the stationarity of annual mean water levels in the five Great Lakes. Lake Superior shows an abrupt shift in mean in 1999, but a smoothed shift in variance since 1994, whereas Lake Erie shows four abrupt shifts in mean. Lake Ontario also shows the two first abrupt shift in mean and one abrupt change in variance. Extreme drought indices are negatively correlated with the North Atlantic Oscillation (NAO) for the two shallowest lakes (Ontario and Erie). In contrast, extreme wetness indices are positively correlated with PDO (positive correlation) and SOI (negative correlation) for Lake Superior only.

Summary The temporal variability of winter climate in southern Quebec is characterized by increasing temperature and rainfall, but decreasing snowfall. The goal of the study was to analyze the impact of these changes on the magnitude and timing of winter maximum daily flows. Hydrologic series for seventeen tributaries of the St. Lawrence River were analyzed over the period from 1934 to 2010. The most noteworthy result, obtained using the Lombard method, was to highlight a nearly generalized shift in mean values of the series in the early 1970s. This shift reflects a significant increase in the magnitude of winter maximum daily flows after that decade, interpreted to result primarily from snowmelt, which is increasingly frequent at the end of winter. The frequency of the dates of occurrence of winter maximum daily flows increased significantly during the last winter decade (ten days) after the 1970s for most rivers in southern Quebec. The copula method did not, however, reveal any significant change in the dependency between the timing and magnitude of winter maximum daily flows over time. Finally, canonical correlation analysis revealed that the magnitude of winter maximum daily flows is positively correlated with the Pacific Decadal Oscillation (PDO), while their dates of occurrence are correlated with the North Atlantic Oscillation (NAO).

We analyze the relationship between four climate variables (maximum and minimum extreme temperatures, rainfall and snowfall) measured in winter (December to March) at 17 stations from 1950 to 2000 in the three hydroclimate regions of southern Quebec, and six seasonal climate indices using canonical correlation analysis (CCA) and the copula method. This analysis yielded these major results: (1) extreme temperatures are not correlated with the amount of winter rain or snow in southern Quebec; (2) winter seasonal climate indices show better correlations with climate variables than do fall climate indices; (3) winter extreme temperatures are best correlated (positive correlation) with the Atlantic Multidecadal Oscillation (AMO) in the eastern region, but show a negative correlation with the Arctic Oscillation (AO) in the southwestern region; (4) the total amount of winter snow is best correlated (negative correlation) with the Pacific Decadal Oscillation (PDO) in the three hydroclimate regions; (5) the total amount of winter rain is best (negatively) correlated with PDO in the eastern region, but shows a positive correlation with AO in the southeast region. Finally, the copula method revealed very little change in the dependence between climate indices and climate variables in the three hydroclimate regions.

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.

We compared the spatiotemporal variability of temperatures and precipitation with that of the magnitude and timing of maximum daily spring flows in the geographically adjacent L’Assomption River (agricultural) and Matawin River (forested) watersheds during the period from 1932 to 2013. With regard to spatial variability, fall, winter, and spring temperatures as well as total precipitation are higher in the agricultural watershed than in the forested one. The magnitude of maximum daily spring flows is also higher in the first watershed as compared with the second, owing to substantial runoff, given that the amount of snow that gives rise to these flows is not significantly different in the two watersheds. These flows occur early in the season in the agricultural watershed because of the relatively high temperatures. With regard to temporal variability, minimum temperatures increased over time in both watersheds. Maximum temperatures in the fall only increased in the agricultural watershed. The amount of spring rain increased over time in both watersheds, whereas total precipitation increased significantly in the agricultural watershed only. However, the amount of snow decreased in the forested watershed. The magnitude of maximum daily spring flows increased over time in the forested watershed.

Algeria is periodically affected by severe and repeated flooding. Flood hazard studies require the estimation of extreme flood flows. To predict and estimate the characteristics of maximum flows, knowledge of their distribution law is essential. The L-moments method was used to determine homogeneous regions and the appropriate distribution for these regions. Three homogeneous regions were delineated. This technique produced a Pearson type III distribution for the coastal region and the Tell Atlas and a Pareto distribution for the steppe regions and high plateaus of Eastern and Western Algeria. To estimate maximum flow at ungauged sites for different return periods, the 'index-flood' method was used. An empirical formula was developed that uses the average annual maximum flow as a function of catchment area and the average slope of the main channel to estimate maximum flow at any point on the Oued. The coefficient of determination and the Nash criterion, for the three regions, are superiors to 88% and 83% respectively. The root mean squared error, for the three regions, is less than 12%. These values show the robustness of the developed models.