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This review presents a summary of the influences of floods on river ecology, both instream and on the adjacent floodplain, mostly in a Canadian context. It emphasizes that ecological impacts and benefits can be highly dependent on flood-generation processes and their magnitude and timing. In Canada, floods can occur under open-water or ice-influenced river conditions. The ecological impacts of floods generated from ice jamming are particularly relevant in Canadian ecosystems due to the potentially higher water levels produced and suspended sediment concentrations that can be detrimental to instream aquatic habitat, but beneficial to floodplains. Large floods provide a major source of physical disturbance. Moderate floods with shorter return periods can be beneficial to aquatic habitats by providing woody debris that contributes to habitat complexity and diversity, by flushing fine sediments and by providing important food sources from terrestrial origins. Floods also influence water-quality variables such...

Abstract Few records of spring paleoclimate are available for boreal Canada, as biological proxies recording the beginning of the warm season are uncommon. Given the spring warming observed during the last decades, and its impact on snowmelt and hydrological processes, searching for spring climate proxies is receiving increasing attention. Tree‐ring anatomical features and intra‐annual widths were used to reconstruct the regional March to May mean air temperature from 1770 to 2016 in eastern boreal Canada. Nested principal component regressions calibrated on 116 years of gridded temperature data were developed from one Fraxinus nigra and 10 Pinus banksiana sites. The reconstruction indicated three distinct phases in spring temperature variability since 1770. Ample phases of multi‐decadal warm and cold springs persisted until the end of the Little Ice Age (1850–1870 CE) and were gradually replaced since the 1940s by decadal to interannual variability associated with an increase in the frequency and magnitude of warm springs. Significant correlations with other paleotemperature records, gridded snow cover extent and runoff support that historical high flooding were associated with late, cold springs with heavy snow cover. Most of the high magnitude spring floods reconstructed for the nearby Harricana River also coincided with the lowest reconstructed spring temperature per decade. However, the last 40 years of observed and reconstructed mean spring temperature showed a reduction in the number of extreme cold springs contrasting with the last few decades of extreme flooding in the eastern Canadian boreal region. This result indicates that warmer late spring mean temperatures on average may contribute, among other factors, to advance the spring break‐up and to likely shift the contribution of snow to rain in spring flooding processes.

Flood events and their associated damages have escalated significantly in the last few decades. To add to the gruesome situation, many reports and studies warn that flood risk would aggravate significantly in future periods due to significant alterations in the climate patterns and socio-economic dynamics. Floodplain mapping is looked upon as a viable option to tackle this global issue as it provides both quantitative and qualitative information on flood dynamics. Moreover, with the increasing availability of global data and enhancement in computational simulations, it has become easier to simlate flooding patterns at large scales. This study deter-mines the usability of publicly available datasets in capturing flood hazards over Canada. Run-off data set from the North American Regional Reanalysis (NARR), along with a few other rele-vant inputs are fed to CaMa-Flood, a robust global hydrodynamic model to generate flooding patterns for 1 in 100 and 1 in 200-yr return period events over Canada . The simulated maps are compared and validated with the existing maps of a few flood-prone regions in Canada, thereby establishing their performance over both regional and country-scale. Later, the simulated flood-plain maps are used in conjunction with property related information at 34 cities (within the top 100 populous cities in Canada) to determine the degree of exposure due to flooding in 1991, 2001, and 2011. The results indicate that around 80 percent of inundated spots belong to high and very-high hazard classes in a 200-yr event, which is roughly 4 percent more than simulated for 100-yr event. NARR derived floodplain maps perform very well while compared over the six flood-prone regions. While analyzing the exposure of properties to flooding, we notice an in-crease in the number during the last three decades, with the maximum rise observed in Toronto, followed by Montreal, and Edmonton. To disseminate the extensive flood-related information, a web-based public tool, Flood Map Viewer (http://www.floodmapviewer.com/) is developed. The development of the tool was motivated by the commitment of the Canadian government to provide $63 M over the next three years for the completion of flood maps for higher-risk areas. The study reaches out to demonstrate how publicly available datasets can be utilized with a lesser degree of uncertainty in representing flooding patterns over large regions. The flood re-lated information derived from the study can be used along with vulnerability for quantifying flood risk, which will help in developing appropriate pathways for resilience building for long-term sustainable benefits.

Abstract In spring 2011, an unprecedented flood hit the complex eastern United States (U.S.)–Canada transboundary Lake Champlain–Richelieu River (LCRR) Basin, destructing properties and inducing negative impacts on agriculture and fish habitats. The damages, covered by the Governments of Canada and the U.S., were estimated to C$90M. This natural disaster motivated the study of mitigation measures to prevent such disasters from reoccurring. When evaluating flood risks, long‐term evolving climate change should be taken into account to adopt mitigation measures that will remain relevant in the future. To assess the impacts of climate change on flood risks of the LCRR basin, three bias‐corrected multi‐resolution ensembles of climate projections for two greenhouse gas concentration scenarios were used to force a state‐of‐the‐art, high‐resolution, distributed hydrological model. The analysis of the hydrological simulations indicates that the 20‐year return period flood (corresponding to a medium flood) should decrease between 8% and 35% for the end of the 21st Century (2070–2099) time horizon and for the high‐emission scenario representative concentration pathway (RCP) 8.5. The reduction in flood risks is explained by a decrease in snow accumulation and an increase in evapotranspiration expected with the future warming of the region. Nevertheless, due to the large climate inter‐annual variability, short‐term flood probabilities should remain similar to those experienced in the recent past.

Abstract. The potential impact of future climate change on runoff generation processes in two southern British Columbia catchments was explored using the Canadian Centre for Climate Modelling Analysis General Circulation Model (CGCMa1) to estimate future changes in precipitation, temperature and cloud cover while the U.B.C. Watershed Model was used to simulate discharges and quantify the separate runoff components, i.e. rainfall, snowmelt, glacier melt and groundwater. Changes, not only in precipitation and temperature but also in the spatial distribution of precipitation with elevation, cloud cover, glacier extension, altitude distribution of vegetation, vegetation biomass production and plant physiology were considered. The future climate of the catchments would be wetter and warmer than the present. In the maritime rain-fed catchment of the Upper Campbell, runoff from rainfall is the most significant source of flow for present and future climatic conditions in the autumn and winter whereas runoff from groundwater generates the flow in spring and summer, especially for the future climate scenario. The total runoff, under the future climatic conditions, would increase in the autumn and winter and decrease in spring and summer. In contrast, in the interior snow-covered Illecillewaet catchment, groundwater is the most significant runoff generation mechanism in the autumn and winter although, at present, significant flow is generated from snowmelt in spring and from glacier runoff in summer. In the future scenario, the contribution to flow from snowmelt would increase in winter and diminish in spring while the runoff from the glacier would remain unchanged; groundwater would then become the most significant source of runoff, which would peak earlier in the season. Keywords: climatic change, hydrological simulation, rainfall, snowmelt, runoff processes

The causes of peak flows in two climatically different mountainous-forested basins of British Columbia have been identified. The U.B.C. watershed model was used to identify the causes of peak flows, since this model separately calculates the runoff components, i.e. rainfall, snowmelt and glacier runoff. The results showed that the flood flows in the maritime basin of Upper Campbell are mainly generated by rainfall during the fall months and winter rain-on-snow events. Rainfall runoff constitutes the largest percentage of peak flow for all types of events. On the other hand, the flood flows in the inland basin of Illecillewaet are mainly produced by spring rain and snowmelt events, snowmelt events alone and summer events when runoff from the glacier melt contributes to peak discharge. However, snowmelt runoff is the dominant component of peak flows. Based on these findings, flood frequency analysis showed that considering the flow component frequency distributions marginally improves the probability distribution flows in the two examined watersheds.

In the context of global warming, the Clausius–Clapeyron (CC) relationship has been widely used as an indicator of the evolution of the precipitation regime, including daily and sub-daily extremes. This study aims to verify the existence of links between precipitation extremes and 2 m air temperature for the Ottawa River Basin (ORB, Canada) over the period 1981–2010, applying an exponential relationship between the 99th percentile of precipitation and temperature characteristics. Three simulations of the Canadian Regional Climate Model version 5 (CRCM5), at three different resolutions (0.44°, 0.22°, and 0.11°), one simulation using the recent CRCM version 6 (CRCM6) at “convection-permitting” resolution (2.5 km), and two reanalysis products (ERA5 and ERA5-Land) were used to investigate the CC scaling hypothesis that precipitation increases at the same rate as the atmospheric moisture-holding capacity (i.e., 6.8%/°C). In general, daily precipitation follows a lower rate of change than the CC scaling with median values between 2 and 4%/°C for the ORB and with a level of statistical significance of 5%, while hourly precipitation increases faster with temperature, between 4 and 7%/°C. In the latter case, rates of change greater than the CC scaling were even up to 10.2%/°C for the simulation at 0.11°. A hook shape is observed in summer for CRCM5 simulations, near the 20–25 °C temperature threshold, where the 99th percentile of precipitation decreases with temperature, especially at higher resolution with the CRCM6 data. Beyond the threshold of 20 °C, it appears that the atmospheric moisture-holding capacity is not the only determining factor for generating precipitation extremes. Other factors need to be considered, such as the moisture availability at the time of the precipitation event, and the presence of dynamical mechanisms that increase, for example, upward vertical motion. As mentioned in previous studies, the applicability of the CC scaling should not be generalised in the study of precipitation extremes. The time and spatial scales and season are also dependent factors that must be taken into account. In fact, the evolution of precipitation extremes and temperature relationships should be identified and evaluated with very high spatial resolution simulations, knowing that local temperature and regional physiographic features play a major role in the occurrence and intensity of precipitation extremes. As precipitation extremes have important effects on the occurrence of floods with potential deleterious damages, further research needs to explore the sensitivity of projections to resolution with various air temperature and humidity thresholds, especially at the sub-daily scale, as these precipitation types seem to increase faster with temperature than with daily-scale values. This will help to develop decision-making and adaptation strategies based on improved physical knowledge or approaches and not on a single assumption based on CC scaling.

A four-dimensional variational data assimilation (4DVAR) scheme has recently been implemented in the medium-range weather forecast system of the Meteorological Service of Canada (MSC). The new scheme is now composed of several additional and improved features as compared with the three-dimensional variational data assimilation (3DVAR): the first guess at the appropriate time from the full-resolution model trajectory is used to calculate the misfit to the observations; the tangent linear of the forecast model and its adjoint are employed to propagate the analysis increment and the gradient of the cost function over the 6-h assimilation window; a comprehensive set of simplified physical parameterizations is used during the final minimization process; and the number of frequently reported data, in particular satellite data, has substantially increased. The impact of these 4DVAR components on the forecast skill is reported in this article. This is achieved by comparing data assimilation configurations that range in complexity from the former 3DVAR with the implemented 4DVAR over a 1-month period. It is shown that the implementation of the tangent-linear model and its adjoint as well as the increased number of observations are the two features of the new 4DVAR that contribute the most to the forecast improvement. All the other components provide marginal though positive impact. 4DVAR does not improve the medium-range forecast of tropical storms in general and tends to amplify the existing, too early extratropical transition often observed in the MSC global forecast system with 3DVAR. It is shown that this recurrent problem is, however, more sensitive to the forecast model than the data assimilation scheme employed in this system. Finally, the impact of using a shorter cutoff time for the reception of observations, as the one used in the operational context for the 0000 and 1200 UTC forecasts, is more detrimental with 4DVAR. This result indicates that 4DVAR is more sensitive to observations at the end of the assimilation window than 3DVAR.

The Canadian Sea Ice and Snow Evolution (CanSISE) Network is a climate research network focused on developing and applying state-of-the-art observational data to advance dynamical prediction, projections, and understanding of seasonal snow cover and sea ice in Canada and the circumpolar Arctic. This study presents an assessment from the CanSISE Network of the ability of the second-generation Canadian Earth System Model (CanESM2) and the Canadian Seasonal to Interannual Prediction System (CanSIPS) to simulate and predict snow and sea ice from seasonal to multi-decadal timescales, with a focus on the Canadian sector. To account for observational uncertainty, model structural uncertainty, and internal climate variability, the analysis uses multi-source observations, multiple Earth system models (ESMs) in Phase5 of the Coupled Model Intercomparison Project (CMIP5), and large initial-condition ensembles of CanESM2 and other models. It is found that the ability of the CanESM2 simulation to capture snow-related climate parameters, such as cold-region surface temperature and precipitation, lies within the range of currently available international models. Accounting for the considerable disagreement among satellite-era observational datasets on the distribution of snow water equivalent, CanESM2 has too much springtime snow mass over Canada, reflecting a broader northern hemispheric positive bias. Biases in seasonal snow cover extent are generally less pronounced. CanESM2 also exhibits retreat of springtime snow generally greater than observational estimates, after accounting for observational uncertainty and internal variability. Sea ice is biased low in the Canadian Arctic, which makes it difficult to assess the realism of long-term sea ice trends there. The strengths and weaknesses of the modelling system need to be understood as a practical tradeoff: the Canadian models are relatively inexpensive computationally because of their moderate resolution, thus enabling their use in operational seasonal prediction and for generating large ensembles of multidecadal simulations. Improvements in climate-prediction systems like CanSIPS rely not just on simulation quality but also on using novel observational constraints and the ready transfer of research to an operational setting. Improvements in seasonal forecasting practice arising from recent research include accurate initialization of snow and frozen soil, accounting for observational uncertainty in forecast verification, and sea ice thickness initialization using statistical predictors available in real time.

Climate variability influences the availability of water resources throughout Canada, and projected climate change is anticipated to affect future water availability. This is the first paper of a three-part analysis of water availability indicators in Canada (Parts II and III, this issue). The concept of water availability has been described in different ways in the literature. In Part I, the various approaches for estimating water availability are reviewed and compared, with a focus on Canadian studies. Global examples are used when necessary. The approaches to estimate water availability are organized into three categories: (1) climate-based indicators, (2) hydrology-based indicators and (3) water demand/supply-based indicators. Climate-based indicators use variables such as precipitation, and potential or actual evapotranspiration to calculate water budgets. Widely used meteorological drought indices that calculate moisture surpluses and deficits are also examined. Hydrology-based indicators focus on v...

This study quantified the contributions of overland and tile flow to total runoff (sum of overland and tile flow) and nutrient losses in a Vertisolic soil in the Red River valley (Manitoba, Canada), a region with a cold climate where tile drainage is rapidly expanding. Most annual runoff occurred as overland flow (72–89%), during spring snowmelt and large spring and summer storms. Tile drains did not flow in early spring due to frozen ground. Although tiles flowed in late spring and summer (33–100% of event flow), this represented a small volume of annual runoff (10–25%), which is in stark contrast with what has been observed in other tile‐drained landscapes. Median daily flow‐weighted mean concentrations of soluble reactive P (SRP) and total P (TP) were significantly greater in overland flow than in tile flow ( p < 0.001), but the reverse pattern was observed for NO 3 –N ( p < 0.001). Overland flow was the primary export pathway for both P and NO 3 –N, accounting for >95% of annual SRP and TP and 50 to 60% of annual NO 3 –N losses. Data suggest that tile drains do not exacerbate P export from Vertisols in the Red River valley because they are decoupled from the surface by soil‐ice during snowmelt, which is the primary time for P loss. However, NO 3 –N loading to downstream water bodies may be exacerbated by tiles, particularly during spring and summer storms after fertilizer application. Core Ideas Overland flow was the primary pathway for runoff and nutrient loss at field edge. Most runoff and nutrient loss occurred during spring snowmelt and rain events. Tile drains are unlikely to exacerbate P losses from Vertisolic soils. Tile drains may enhance N loading in this region.

Seasonal forecasting of spring floods in snow-covered basins is challenging due to the ambiguity in the driving processes, uncertain estimations of antecedent catchment conditions and the choice of predictor variables. In this study we attempt to improve the prediction of spring flow peaks in southern Quebec, Canada, by studying the preconditioning mechanisms of runoff generation and their impact on inter-annual variations in the timing and magnitude of spring peak flow. Historical observations and simulated data from a hydrological and snowmelt model were used to study the antecedent conditions that control flood characteristics in twelve snow-dominated catchments. Maximum snow accumulation (peak SWE), snowmelt and rainfall volume, snowmelt and rainfall intensity, and soil moisture were estimated during the pre-flood period. Stepwise multivariate linear regression analysis was used to identify the most relevant predictors and assess their relative contribution to the interannual variability of flood characteristics. Results show that interannual variations in spring peak flow are controlled differently between basins. Overall, interannual variations in peak flow were mainly governed, in order of importance, by snowmelt intensity, rainfall intensity, snowmelt volume, rainfall volume, peak SWE, and soil moisture. Variations in the timing of peak flow were controlled in most basins by rainfall volume and rainfall and snowmelt intensity. In the northernmost, snow-dominated basins, pre-flood rainfall amount and intensity mostly controlled peak flow variability, whereas in the southern, rainier basins snowpack conditions and melt dynamics controlled this variability. Snowpack interannual variations were found to be less important than variations in rainfall in forested basins, where snowmelt is more gradual. Conversely, peak flow was more sensitive to snowpack conditions in agricultural basins where snowmelt occurs faster. These results highlight the impact of land cover and use on spring flood generation mechanism, and the limited predictability potential of spring floods using simple methods and antecedent hydrological factors.

Abstract. Glacier mass balance models are needed at sites with scarce long-term observations to reconstruct past glacier mass balance and assess its sensitivity to future climate change. In this study, North American Regional Reanalysis (NARR) data were used to force a physically based, distributed glacier mass balance model of Saskatchewan Glacier for the historical period 1979–2016 and assess its sensitivity to climate change. A 2-year record (2014–2016) from an on-glacier automatic weather station (AWS) and historical precipitation records from nearby permanent weather stations were used to downscale air temperature, relative humidity, wind speed, incoming solar radiation and precipitation from the NARR to the station sites. The model was run with fixed (1979, 2010) and time-varying (dynamic) geometry using a multitemporal digital elevation model dataset. The model showed a good performance against recent (2012–2016) direct glaciological mass balance observations as well as with cumulative geodetic mass balance estimates. The simulated mass balance was not very sensitive to the NARR spatial interpolation method, as long as station data were used for bias correction. The simulated mass balance was however sensitive to the biases in NARR precipitation and air temperature, as well as to the prescribed precipitation lapse rate and ice aerodynamic roughness lengths, showing the importance of constraining these two parameters with ancillary data. The glacier-wide simulated energy balance regime showed a large contribution (57 %) of turbulent (sensible and latent) heat fluxes to melting in summer, higher than typical mid-latitude glaciers in continental climates, which reflects the local humid “icefield weather” of the Columbia Icefield. The static mass balance sensitivity to climate was assessed for prescribed changes in regional mean air temperature between 0 and 7 ∘C and precipitation between −20 % and +20 %, which comprise the spread of ensemble Representative Concentration Pathway (RCP) climate scenarios for the mid (2041–2070) and late (2071–2100) 21st century. The climate sensitivity experiments showed that future changes in precipitation would have a small impact on glacier mass balance, while the temperature sensitivity increases with warming, from −0.65 to −0.93 m w.e. a−1 ∘C−1. The mass balance response to warming was driven by a positive albedo feedback (44 %), followed by direct atmospheric warming impacts (24 %), a positive air humidity feedback (22 %) and a positive precipitation phase feedback (10 %). Our study underlines the key role of albedo and air humidity in modulating the response of winter-accumulation type mountain glaciers and upland icefield-outlet glacier settings to climate.

This study evaluates predictive uncertainties in the snow hydrology of the Fraser River Basin(FRB) of British Columbia(BC), Canada, using the Variable Infiltration Capacity(VIC) model forced with several high-resolution gridded climate datasets. These datasets include the Canadian Precipitation Analysis and the thin-plate smoothing splines(ANUSPLIN), North American Regional Reanalysis(NARR), University of Washington(UW) and Pacific Climate Impacts Consortium(PCIC) gridded products. Uncertainties are evaluated at different stages of the VIC implementation, starting with the driving datasets, optimization of model parameters, and model calibration during cool and warm phases of the Pacific Decadal Oscillation(PDO). The inter-comparison of the forcing datasets (precipitation and air temperature) and their VIC simulations (snow water equivalent – SWE – and runoff) reveals widespread differences over the FRB, especially in mountainous regions. The ANUSPLIN precipitation shows a considerable dry bias in the Rocky Mountains, whereas the NARR winter air temperature is 2°C warmer than the other datasets over most of the FRB. In the VIC simulations, the elevation-dependent changes in the maximum SWE(maxSWE) are more prominent at higher elevations of the Rocky Mountains, where the PCIC-VIC simulation accumulates too much SWE and ANUSPLIN-VIC yields an underestimation. Additionally, at each elevation range, the day of maxSWE varies from 10to 20days between the VIC simulations. The snow melting season begins early in the NARR-VIC simulation, whereas the PCIC-VIC simulation delays the melting, indicating seasonal uncertainty in SWE simulations. When compared with the observed runoff for the Fraser River main stem at Hope, BC, the ANUSPLIN-VIC simulation shows considerable underestimation of runoff throughout the water year owing to reduced precipitation in the ANUSPLIN forcing dataset. The NARR-VIC simulation yields more winter and spring runoff and earlier decline of flows in summer due to a nearly 15-day earlier onset of the FRB springtime snowmelt. Analysis of the parametric uncertainty in the VIC calibration process shows that the choice of the initial parameter range plays a crucial role in defining the model hydrological response for the FRB. Furthermore, the VIC calibration process is biased toward cool and warm phases of the PDO and the choice of proper calibration and validation time periods is important for the experimental setup. Overall the VIC hydrological response is prominently influenced by the uncertainties involved in the forcing datasets rather than those in its parameter optimization and experimental setups.

Une coulee de slush (bouillie de neige fondante) est un ecoulement rapide constitue d’un melange de neige fondante, d’eau, de boue et de debris de toutes sortes. Les sept sites analyses demontrent que les coulees de slush peuvent survenir dans des contextes topographiques fort differents qui presentent toutefois des similitudes au niveau du mode d’enneigement et des conditions hydro-meteorologiques. Les coulees de slush etudiees demarrent dans des ruisseaux d’ordre 1 ou 2, etroits et peu profonds, de pente tres variable (de 1° a plus de 30°), qui sont combles par des bouchons de neige dense soufflee par le vent ou transportee par les avalanches. Parce qu’ils s’opposent a la libre circulation des eaux de fusion lors des periodes de fonte acceleree, ces bouchons de neige favorisent la saturation du manteau neigeux jusqu’a la rupture sous l’effet combine de la pression hydrostatique et de la gravite. Les onze coulees analysees, qui se sont produites entre 1936 et 2013, permettent de definir deux scenarios hydro-meteorologiques propices a leur declenchement : 1) des redoux de longue duree caracterises par des temperatures qui restent positives pendant plusieurs jours consecutifs sans apport de precipitations liquides; 2) des redoux relativement courts (moins de 48 heures) couples a des precipitations liquides abondantes. Largement meconnues au Quebec, les coulees de slush pourraient etre plus frequentes a l’avenir en reponse au rechauffement climatique en cours.

Although numerous studies have looked at the long-term trend of the temporal variability of winter temperature and precipitation in southern Quebec, no study has focused on the shifts in series means and the dependence between these two types of climate variables associated with this long-term trend. To fill these gaps, we used the Lombard method to detect the shifts in mean values and the copula method to detect any change in dependence between extreme (maximum and minimum) temperatures and precipitation (snow and rain) over the periods 1950–2000 (17 stations) and 1950–2010 (7 stations). During these two periods, the shifts in mean values of temperature and precipitation were recorded at less than half of the stations. The only significant change observed at the provincial scale is a decrease in the amount of snowfall, which occurred in many cases during the 1970s. This decrease affected stations on the north shore (continental temperate climate) more strongly than stations on the south shore (maritime temperate climate) of the St Lawrence River. However, this decrease in the amount of snowfall had no impact on the dependence over time between temperature and precipitation as snow.

ABSTRACTStatistical relationships between weather conditions and the release of snow avalanches in the low-elevation coastal valleys of the northern Gaspe Peninsula are still poorly validated. As s...

The objective of this study is to analyze the temporal variability in water levels of Lake Mégantic (27.4 km2) during the period 1920–2020 in relation to anthropogenic and natural factors on the one hand, and its impact on the intensity and frequency of heavy flooding (recurring floods ≥ 10 years) of the Chaudière River of which it is the source, on the other hand. The application of four different Mann–Kendall tests showed a significant decrease in lake water levels during this period. The Lombard test revealed two breaks in the average daily maximum and average water levels, but only one break in the average daily minimum water levels. The first shift, which was smoothed, occurred between 1957 and 1963. It was caused by the demolition in 1956 of the first dam built in 1893 and the significant storage of water in the dams built upstream of the lake between 1956 and 1975. The second shift, which was rather abrupt, occurred between 1990 and 1993. It was caused by the voluntary and controlled lowering of the lake’s water levels in 1993 to increase the surface area of the beaches for recreational purposes. However, despite this influence of anthropogenic factors on this drop in water levels, they are negatively correlated with the global warming climate index. It is therefore a covariation, due to anthropogenic factors whose impacts are exerted at different spatial scales, without a physical causal link. However, the winter daily minimum water levels, whose temporal variability has not been influenced by anthropogenic activities, are positively correlated with the NAO and AO indices, but negatively with PDO. Finally, since the transformation of Lake Mégantic into a reservoir following the construction of the Mégantic dam in 1893 and 1973 to control heavy flooding in the Chaudière River, all recurrent floods ≥ 10 years have completely disappeared in the section of this river located downstream of Lake Mégantic. However, the disappearance of these floods and the drop in water levels of Lake Mégantic have not significantly impacted the stationarity in the flow series of the Chaudière River since 1920.

Abstract The Chaudière River in Quebec, Canada, is well known for its frequent ice jam flooding events. As part of a larger watershed research program, an extensive field campaign has been carried out during the 2018–2019 and 2019–2020 winter seasons to quantify the spatiotemporal characteristics of the break-up processes along the Chaudière River. The results showed that mid-winter ice jams have formed in the Intermediate Chaudière and persisted until spring break-up. Spring break-ups were initiated in the Upper Chaudière, and then, almost simultaneously, in the Intermediate and Lower Chaudière reaches. The break-up in the Intermediate Chaudière usually lasts longer than the rest of the river since the slope is much milder, and the occurrence of mid-winter ice jams has been seen to delay the ice clearing. A reach-by-reach characterization of the cumulative degree day of thawing and discharge thresholds for the onset of break-up has been identified. During the field campaign, 51 ice jams were documented together with their location, length, date of formation, and the morphological feature triggering jam formation. Break-up patterns, hydrometeorological thresholds of ice mobilization, and ice jam sites identified in this study can serve as a basis for the implementation of an early warning system.