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Abstract This study compares the impacts of climate, agriculture and wetlands on the spatio-temporal variability of seasonal daily minimum flows during the period 1930–2019 in 17 watersheds of southern Quebec (Canada). In terms of spatial variability, correlation analysis revealed that seasonal daily minimum flows were mainly negatively correlated with the agricultural surface area in watersheds in spring, summer and fall. In winter, these flows were positively correlated with the wetland surface area and March temperatures but negatively correlated with snowfall. During all four seasons, spatial variability was characterized by higher daily minimum flow values on the north shore (smaller agricultural surface area and larger wetland surface area) than those on the south shore. As for temporal variability, the application of six tests of the long-term trend analysis showed that most agricultural watersheds are characterized by a significant increase in flows during the four seasons due to the reduction in agricultural area, thus favoring water infiltration, and increased rainfall in summer and fall. On the other hand, the reduction in the snowfall resulted in a reduction in summer daily minimum flows observed in several less agricultural watersheds.
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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 (<5%)). An analysis of the long-term trend of these flows showed that the DMEF of south-shore rivers have increased significantly since the 1960s, during the fall (October to December), due to an increase in rainfall and a reduction in cultivated land, which increased the infiltration in the region. Although there was little difference between the two shores in the spring (April to June), we observed a decrease in minimum extreme flows in half (50%) of the south-shore rivers located north of 47° N.
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Abstract This study explores the potential impacts of climate change on soil erosion in an agricultural catchment in eastern Canada. The Modified Universal Soil Loss Equation (MUSLE) was used to calculate the sediment yields from the Acadie River Catchment for the historical 1996–2019 period. The runoff variables of the MUSLE were obtained from a physically based hydrological model previously built and validated for the catchment. Then, the hydrological model was perturbed using climate change projections and used to assess the climate sensitivity of the sediment yield. Two runoff types representing possible modes of soil erosion were considered. While type A represents a baseline case in which soil erosion occurs due to surface runoff only, type B is more realistic since it assumed that tile drains also contribute to sediment export, but with a varying efficiency throughout the year. The calibration and validation of the tile efficiency factors against measurements in 2009–2015 for type B suggest that tile drains export the sediments with an efficiency of 20% and 50% in freezing and non-freezing conditions, respectively. Results indicate that tile drains account for 39% of the total annual sediment yield in the present climate. The timing of highest soil erosion shifts from spring to winter in response to warming and wetting, which can be explained by increasing winter runoff caused by shifting snowmelt timing towards winter, a greater number of mid-winter melt events as well as increasing rainfall fractions. The large uncertainties in precipitation projections cascade down to the erosion uncertainties in the more realistic type B, with annual sediment yield increasing or decreasing according to the precipitation uncertainty in a given climate change scenario. This study demonstrates the benefit of conservation and no-till pratices, which could reduce the annual sediment yields by 20% and 60%, respectively, under any given climate change scenario.
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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.