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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.

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.

Hydrological responses in cold regions are often complex and variable (both spatially and temporally) due to the complex and multiple interactions between the hydrological processes at play. Thus, there is a need to better understand and represent cold region hydrological processes within hydrological models. In this study, a physicallybased hydrological model has been developed using the Cold Regions Hydrological Model (CRHM) platform for the L’Acadie River Catchment in southern Quebec (Canada). Almost 70 % of the catchment is occupied by agricultural fields, being representative of the intensive farming landscape of the southern St-Lawrence lowlands, while the rest is mostly forested. The physical processes including blowing snow, snow interception in canopies, sublimation and snowmelt were simulated over 35 years using the CRHM platform. Hydrologic response units (HRUs), the smallest simulation spatial unit within the catchment, were derived based on the combination of land use/cover and vegetation types. Over the simulation period, considerable spatial variability was detected between agricultural and forested sites. Snow accumulation and associated snow water equivalent (SWE) were found to be higher in forested sites than agricultural sites, which can be explained by blowing snow transport from agricultural sites to the forested sites where aerodynamic roughness is greater. Higher rates of blowing snow sublimation were detected over the agricultural sites compared to snow intercepted in the forest canopies. This can be explained by the fact that there is a great amount of blowing snow over the agricultural sites, and thus available suspended snow for sublimation, while over the forested sites the snow is more firmly retained by the canopies and thus there is less blowing snow and consequently less blowing snow sublimation. In addition, although snow cover duration shows variation over the simulation period, the snow generally lasts longer in forested fields than in agricultural fields. Our findings indicating more snow in forested fields than agricultural (open) fields are contrary to the usual notion that there is less snow accumulation on forest ground due to the high rates of canopy sublimation. However, this is true for the landscapes dominated by forests, while our study area is dominated by agricultural fields, so snow erosion of agricultural fields and snow deposition in forested fields seem to compensate canopy losses. Taken together, it is shown that land use exerts a critical control on snow distributions in this type of landscape, and perhaps on possible implications for future snow hydrology of the catchment.

Snowmelt dominated regions are receiving increasing attention due to their noticeably rapid response to ongoing climate change, which raises concerns about the altered hydrological risks under climate change scenarios. This study aims to assess the climate change impacts on hydrology over two contrasted catchments in southern Québec: Acadie River and Montmorency River catchments. These river catchments represent two predominant landscapes of the St. Lawrence River watershed; an intensive farming landscape in the south shore lowlands and the forested landscape on the Canadian Shield on the north shore, respectively. In this study, a physically based hydrological model has been developed using the Cold Regions Hydrological Model (CRHM) for both of the catchments. The hydrological model outputs showed that we were able to simulate snow surveys and discharge measurements with a reasonable accuracy for both catchments. The acceptable performance of the model along with the strong physical basis of structure suggested that this model could be used for climate change sensitivity simulations. Based on the climate scenarios reviewed, a temperature increase up to 8°C and an increase in total precipitation up to 20% were analysed for both of the catchments. Both catchments were found to be sensitive to climate change, however the degree of sensitivity was found to be catchment specific. Snow processes in the Acadie River catchment were simulated to be more sensitive to warming than in the Montmorency River catchment. In case of 2°C warming, reduction in peak SWE was not be able to be compensated even by increased precipitation scenario. Given that, the Acadie River has already a mixed flow regime, even if 2°C warming is combined with an increase in precipitation, pluvial regime kept becoming more dominant, resulting in higher peaks of rain events. On the other hand, even 3°C of warming did not modify the flow regime of the Montmorency River. While there is shift towards earlier peak spring flows in both catchments, the shift was found to be more pronounced in the Acadie River. An earlier occurrence of snowmelt floods and an overall increase in winter streamflow during winter have been simulated for both catchments, which calls for renewed assessments of existing water supply and flood risk management strategies.

Abstract This study confronts the new concept of ‘surface storage’ with the old concept of ‘sponge effect’ to explain the spatio-temporal variability of the annual daily maximum flows measured in 17 watersheds of southern Quebec during the period 1930–2019. The new concept takes into account the hydrological impacts of wetlands and other topographic components of the landscape (lakes, depressions, ditches, etc.) while that of the sponge effect only takes into account the hydrological impacts of wetlands. With regard to spatial variability, the area of wetlands and other water bodies is the variable best correlated negatively with the magnitude but positively with the duration of flows. As for the temporal variability, the application of the long-term trend tests revealed a significant increase in the magnitude and, to a lesser extent, the duration of the flows occurring in the watersheds of the north shore characterized by a greater area of wetlands and other water bodies (>5%). This increase is explained by the fact that the storage capacity of these land types, which remains unchanged over time, does not make it possible to store the surplus runoff water brought by the increase in rainfall during the snowmelt season.