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Abstract Fluvial biogeomorphology has proven to be efficient in understanding the evolution of rivers in terms of vegetation succession and channel adjustment. The role of floods as the primary disturbance regime factor has been widely studied, and our knowledge of their effects on vegetation and channel adjustment has grown significantly in the last two decades. However, cold rivers experiencing ice dynamics (e.g., ice jams and mechanical breakups) as an additional disturbance regime have not yet been studied within a biogeomorphological scope. This study investigated the long‐term effects of ice dynamics on channel adjustments and vegetation trajectories in two rivers with different geomorphological behaviours, one laterally confined (Matapédia River) and one mobile (Petite‐Cascapédia River), in Quebec, Canada. Using dendrochronological analysis, historical data and aerial photographs from 1963 to 2016, this study reconstructed ice jam chronologies, characterized flood regimes and analysed vegetation and channel changes through a photointerpretation approach. The main findings of this study indicate that geomorphological impacts of mechanical ice breakups are not significant at the decadal and reach scales and that they might not be the primary factors of long‐term geomorphological control. However, results have shown that vegetation was more sensitive to ice dynamics. Reaches presenting frequent ice jams depicted high regression rates and turnovers even during years with very low floods, suggesting that ice dynamics significantly increase shear stress on plant patches. This study also highlights the high resiliency of both rivers to ice jam disturbances, with vegetation communities and channel forms recovering within a decade. With the uncertainties following the reach/corridor and decadal scales, future research should focus on long‐term monitoring and refined spatial scales to better understand the mechanisms behind the complex interactions among ice dynamics, vegetation and hydrogeomorphological processes in cold rivers.

Abstract Global warming is causing glaciers in the Caucasus Mountains and around the world to lose mass at an accelerated pace. As a result of this rapid retreat, significant parts of the glacierized surface area can be covered with debris deposits, often making them indistinguishable from the surrounding land surface by optical remote-sensing systems. Here, we present the DebCovG-carto toolbox to delineate debris-covered and debris-free glacier surfaces from non-glacierized regions. The algorithm uses synthetic aperture radar-derived coherence images and the normalized difference snow index applied to optical satellite data. Validating the remotely-sensed boundaries of Ushba and Chalaati glaciers using field GPS data demonstrates that the use of pairs of Sentinel-1 images (2019) from identical ascending and descending orbits can substantially improve debris-covered glacier surface detection. The DebCovG-carto toolbox leverages multiple orbits to automate the mapping of debris-covered glacier surfaces. This new automatic method offers the possibility of quickly correcting glacier mapping errors caused by the presence of debris and makes automatic mapping of glacierized surfaces considerably faster than the use of other subjective methods.

Abstract The highly fissile lithology of the rockwalls and the diversity of mass‐wasting processes provide a specific character to the active talus slopes of the northern Gaspé Peninsula since deglaciation. At a regional scale, the geology of the rockwalls, the patterns and modalities of deglaciation and the evolution towards a cold temperate morphoclimatic regime in a maritime context still influence the geomorphological dynamics of scree slopes today. At a local scale, the south–north orientation of the main coastal valleys influences insolation and exposure to prevailing winds, which in turn influence the snow cover regime and the occurrence of freeze–thaw cycles. The statistical analyses carried out from the mapping of 43 talus slopes and their geometric variables allowed the identification of significant environmental factors for the characterization of the dominant geomorphic processes: snow avalanches, frost‐coasted clast flows, debris flows and rockfalls. Slope aspect appears to be a key parameter in the nature of the processes acting on the talus slopes. East‐ and north‐facing talus slopes are generally covered by a significant snowpack in winter and the dominant processes are snow avalanches and debris flows. West‐ and south‐facing talus slopes face prevailing winds and insolation and are subject to frost‐coated clast flows, the main driver for forest regression, and rockfalls. However, the evolution of scree slopes in forested environments remains extremely complex due to the multiscale components that affect their evolution in the short, medium and long term.

Droughts are increasingly recognized as a significant global challenge, with severe impacts observed in Canada's Prairie provinces. While less frequent in Eastern Canada, prolonged precipitation deficits, particularly during summer, can lead to severe drought conditions. This study investigates the causes and consequences of droughts in New Brunswick (NB) by employing two drought indices: the Palmer Drought Severity Index (PDSI) and Standardized Evapotranspiration Deficit Index (SEDI)– at ten weather stations across NB from 1971 to 2020. Additionally, the Canadian Gridded Temperature and Precipitation Anomalies (CANGRD) dataset (1979–2014) was utilized to examine spatial and temporal drought variability and its alignment with station-based observations. Statistical analyses, including the Mann–Kendall test and Sen's slope estimator, were applied to assess trends in drought indices on annual and seasonal timescales using both station and gridded data. The results identified the most drought-vulnerable regions in NB and revealed significant spatial and temporal variability in drought severity over the 1971–2020 period. Trend analyses further highlighted the intensification of extreme drought events during specific years. Coastal areas in southern NB were found to be particularly susceptible to severe drought conditions compared to inland regions, consistent with observed declines in both the frequency of rainy days and daily precipitation amounts in these areas. These findings underscore the need for targeted drought mitigation strategies particularly in NB’s coastal zones, to address the region’s increasing vulnerability to extreme drought events.

Seasonal snowpack deeply influences the distribution of meltwater among watercourses and groundwater. During rain-on-snow (ROS) events, the structure and properties of the different snow and ice layers dictate the quantity and timing of water flowing out of the snowpack, increasing the risk of flooding and ice jams. With ongoing climate change, a better understanding of the processes and internal properties influencing snowpack outflows is needed to predict the hydrological consequences of winter melting episodes and increases in the frequency of ROS events. This study develops a multi-method approach to monitor the key snowpack properties in a non-mountainous environment in a repeated and non-destructive way. Snowpack evolution during the winter of 2020–2021 was evaluated using a drone-based, ground-penetrating radar (GPR) coupled with photogrammetry surveys conducted at the Ste-Marthe experimental watershed in Quebec, Canada. Drone-based surveys were performed over a 200 m2 area with a flat and a sloped section. In addition, time domain reflectometry (TDR) measurements were used to follow water flow through the snowpack and identify drivers of the changes in snowpack conditions, as observed in the drone-based surveys. The experimental watershed is equipped with state-of-the-art automatic weather stations that, together with weekly snow pit measurements over the ablation period, served as a reference for the multi-method monitoring approach. Drone surveys conducted on a weekly basis were used to generate georeferenced snow depth, density, snow water equivalent and bulk liquid water content maps. Despite some limitations, the results show that the combination of drone-based GPR, photogrammetric surveys and TDR is very promising for assessing the spatiotemporal evolution of the key hydrological characteristics of the snowpack. For instance, the tested method allowed for measuring marked differences in snow pack behaviour between the first and second weeks of the ablation period. A ROS event that occurred during the first week did not generate significant changes in snow pack density, liquid water content and water equivalent, while another one that happened in the second week of ablation generated changes in all three variables. After the second week of ablation, differences in density, liquid water content (LWC) and snow water equivalent (SWE) between the flat and the sloped sections of the study area were detected by the drone-based GPR measurements. Comparison between different events was made possible by the contact-free nature of the drone-based measurements.

Abstract. The ongoing warming of cold regions is affecting hydrological processes, causing deep changes, such as a ubiquitous increase in river winter discharges. The drivers of this increase are not yet fully identified mainly due to the lack of observations and field measurements in cold and remote environments. In order to provide new insights into the sources generating winter runoff, the present study explores the possibility of extracting information from icings that form over the winter and are often still present early in the summer. Primary sources detection was performed using time-lapse camera images of icings found in both proglacial fields and upper alpine meadows in June 2016 in two subarctic glacierized catchments in the upper part of the Duke watershed in the St. Elias Mountains, Yukon. As images alone are not sufficient to entirely cover a large and hydrologically complex area, we explore the possibility of compensating for that limit by using four supplementary methods based on natural tracers: (a) stable water isotopes, (b) water ionic content, (c) dissolved organic carbon, and (d) cryogenic precipitates. The interpretation of the combined results shows a complex hydrological system where multiple sources contribute to icing growth over the studied winter. Glaciers of all sizes, directly or through the aquifer, represent the major parent water source for icing formation in the studied proglacial areas. Groundwater-fed hillslope tributaries, possibly connected to suprapermafrost layers, make up the other detectable sources in icing remnants. If similar results are confirmed in other cold regions, they would together support a multi-causal hypothesis for a general increase in winter discharge in glacierized catchments. More generally, this study shows the potential of using icing formations as a new, barely explored source of information on cold region winter hydrological processes that can contribute to overcoming the paucity of observations in these regions.

Abstract This study aims to isolate and quantify the role of shrinking glaciers in recent hydrological changes in eight watersheds in the southwestern Yukon (Canada) by using an original dual approach that consists of (i) watershed hydrological regime identification, followed by a trend analysis of discharge time series, and (ii) a model‐based peak water (PW) analysis using glacier cover change measurements. A distinction between hydrological regimes is a necessary add‐up to commonly used trend attribution methods as the lake runoff regime shares common characteristics with the glacier regime. Results show a link between shrinking glaciers and hydrological changes in the region, but the link is complex, and glacier retreat does not explain all the observed changes. Model outputs show that the two watersheds with a glacierized area exceeding 30% and one watershed with 2.9% glacierized area have not reached PW, whereas a 9.2% glacierized watershed and another watershed with 2.1% glacierized area have already passed it. These results suggest that glacierized area alone cannot explain short‐term changes related to watershed current position in terms of PW, and the rate of glacier retreat must be considered. By contrast, the actual rate of glacier retreat does not influence long‐term changes, such as the magnitude of PW and of the consequent drop in discharge. Once glaciers will have retreated to a point close to extinction, declines in summer discharge from 10% to 70% and proportional to the actual glacier cover are anticipated at watersheds that are currently more than 9% glacierized. , Plain Language Summary In this study, we aim to understand how shrinking glacier cover affects river discharges. In conditions of continuous retreat, glaciers produce an initial increase in runoff as they lose mass. The discharge then reaches a turning point, a plateau called peak water, and subsequently declines as the volume of glacial ice continues to decrease. When analyzing eight watersheds with different glacier covers in the southwestern Yukon, we found that two watersheds that are 30% covered by glaciers have not yet reached this plateau, and therefore, the discharge will continue to increase. Several watersheds with smaller glacierized portions have passed peak water, which means that the discharge will now continue to decrease. We were also able to estimate the magnitudes of these changes in discharge. We show that two watersheds with 30% glacierized area can still experience a 1.5‐ to 2‐fold increase in discharge and that watersheds currently more than 9% glacierized are predicted to show noticeable changes after peak water, with the possibility of discharge decreasing by a factor of 3 to 5 by the time glaciers have retreated to a point when their hydrological influence at the watershed scale becomes insignificant. , Key Points Noticeable acceleration of glacier retreat occurred in southwestern Yukon since 1999 with measured consequences for the regional hydrology Various hydrological changes have been detected at the study watersheds. Glacier retreat explains many but not all of those changes Long‐term hydrological changes are glacier cover dependent while decadal‐scale changes are driven by glacier retreat rate

Abstract Debris-covered glaciers are an important component of the mountain cryosphere and influence the hydrological contribution of glacierized basins to downstream rivers. This study examines the potential to make estimates of debris thickness, a critical variable to calculate the sub-debris melt, using ground-based thermal infrared radiometry (TIR) images. Over four days in August 2019, a ground-based, time-lapse TIR digital imaging radiometer recorded sequential thermal imagery of a debris-covered region of Peyto Glacier, Canadian Rockies, in conjunction with 44 manual excavations of debris thickness ranging from 10 to 110 cm, and concurrent meteorological observations. Inferring the correlation between measured debris thickness and TIR surface temperature as a base, the effectiveness of linear and exponential regression models for debris thickness estimation from surface temperature was explored. Optimal model performance ( R 2 of 0.7, RMSE of 10.3 cm) was obtained with a linear model applied to measurements taken on clear nights just before sunrise, but strong model performances were also obtained under complete cloud cover during daytime or nighttime with an exponential model. This work presents insights into the use of surface temperature and TIR observations to estimate debris thickness and gain knowledge of the state of debris-covered glacial ice and its potential hydrological contribution.

Snow is the dominant form of precipitation and the main cryospheric feature of the High Arctic (HA) covering its land, sea, lake and river ice surfaces for a large part of the year. The snow cover in the HA is involved in climate feedbacks that influence the global climate system, and greatly impacts the hydrology and the ecosystems of the coldest biomes of the Northern Hemisphere. The ongoing global warming trend and its polar amplification is threatening the long-term stability of the snow cover in the HA. This study presents an extensive review of the literature on observed and projected snow cover conditions in the High Arctic region. Several key snow cover metrics were reviewed, including snowfall, snow cover duration (SCD), snow cover extent (SCE), snow depth (SD), and snow water equivalent (SWE) since 1930 based on in situ, remote sensing and simulations results. Changes in snow metrics were reviewed and outlined from the continental to the local scale. The reviewed snow metrics displayed different sensitivities to past and projected changes in precipitation and air temperature. Despite the overall increase in snowfall, both observed from historical data and projected into the future, some snow cover metrics displayed consistent decreasing trends, with SCE and SCD showing the most widespread and steady decreases over the last century in the HA, particularly in the spring and summer seasons. However, snow depth and, in some regions SWE, have mostly increased; nevertheless, both SD and SWE are projected to decrease by 2030. By the end of the century, the extent of Arctic spring snow cover will be considerably less than today (10–35%). Model simulations project higher winter snowfall, higher or lower maximum snow depth depending on regions, and a shortened snow season by the end of the century. The spatial pattern of snow metrics trends for both historical and projected climates exhibit noticeable asymmetry among the different HA sectors, with the largest observed and anticipated changes occurring over the Canadian HA.

Abstract Having a realistic estimation of snow cover by conceptual hydrological models continues to challenge hydrologists. The calibration of the free model parameters is an unavoidable step and the uncertainties resulting from the use of this optimal set remains a source of concern, especially in forecasting applications and climate changes impact assessments. This study seeks to improve the calibration of the conceptual hydrological model GR4J coupled with the Cemaneige snow model, in order to obtain a more realistic simulation of the snow water equivalent (SWE) and to reduce the uncertainty of the free parameters. The performance of the two models was tested over twelve snow-dominated basins in southern Quebec, Canada. Four calibration strategies were adopted and compared. In the first two strategies, the parameters were calibrated against observed streamflow alone using a local and a global algorithm. In the third and fourth strategies the calibration of snow and hydrological parameters was performed against observed streamflow and snow water equivalent (SWE) measured at snow course transects, first separately, and then with a multiobjective approach. An ensemble of equifinal parameters was used to compare the capacity of the global and multiobjective algorithms to improve the parameters identifiability and to assess the impact of parameter equifinality on the temperature sensitivity of spring peak streamflow. The large number of equifinal parameters found during calibration underscores the importance of structural non-identifiability of the coupled GR4J-Cemaneige model. The inclusion of snow observations within a multiobjective calibration improved the simulation of SWE, the identifiability of the parameters and their correlation with basins characteristics. Parameter equifinality caused a small but non negligible uncertainty in the simulated response of spring peak flow to warming temperatures. Parameter equifinality should be considered in climate impact studies in snow-dominated basins where poorly constrained snow parameters can affect the temperature sensitivity of streamflow.

Reduced snow storage has been associated with lower river low flows in mountainous catchments, exacerbating summer hydrological droughts. However, the impacts of changing snow storage on summer low flows in low-elevation, snow-affected catchments has not yet been investigated. To address this knowledge gap, the dominant hydroclimate predictors of summer low flows were first identified through correlation analysis in 12 tributary catchments of the St. Lawrence River in the Canadian province of Quebec. The correlation results show that summer low flow is most sensitive to summer rainfall, while maximum snow water equivalent (SWE) is the dominant winter preconditioning factor of low flows, particularly at the end of summer. The multivariate sensitivity of summer low flow to hydroclimate predictors was then quantified by multilevel regression analysis, considering also the effect of catchment biophysical attributes. Accumulated rainfall since snow cover disappearance was found to be the prime control on summer low flow, as expected for the humid climate of Quebec. Maximum SWE had a secondary but significant positive influence on low flow, sometimes on the same order as the negative effect of evapotranspiration losses. As a whole, our results show that in these low elevation catchments, thicker winter snowpacks that last longer and melt slower in the spring are conducive to higher low flows in the following summer. More rugged and forested catchments with coarser soils were found to have higher summer low flows than flatter agricultural catchments with compacted clayed soils. This emphasizes the role of soils and geology on infiltration, aquifer recharge and related river baseflow in summer. Further climate warming and snowpack depletion could reduce future summer low flow, exacerbating hydrological droughts and impacting ecosystems integrity and ecological services.

Estimating snowmelt in semi-arid mountain ranges is an important but challenging task, due to the large spatial variability of the snow cover and scarcity of field observations. Adding solar radiation as snowmelt predictor within empirical snow models is often done to account for topographically induced variations in melt rates. This study examines the added value of including different treatments of solar radiation within empirical snowmelt models and benchmarks their performance against MODIS snow cover area (SCA) maps over the 2003-2016 period. Three spatially distributed, enhanced temperature index models that, respectively, include the potential clear-sky direct radiation, the incoming solar radiation and net solar radiation were compared with a classical temperature-index (TI) model to simulate snowmelt, SWE and SCA within the Rheraya basin in the Moroccan High Atlas Range. Enhanced models, particularly that which includes net solar radiation, were found to better explain the observed SCA variability compared to the TI model. However, differences in model performance in simulating basin wide SWE and SCA were small. This occurs because topographically induced variations in melt rates simulated by the enhanced models tend to average out, a situation favored by the rather uniform distribution of slope aspects in the basin. While the enhanced models simulated more heterogeneous snow cover conditions, aggregating the simulated SCA from the 100 m model resolution towards the MODIS resolution (500 m) suppresses key spatial variability related to solar radiation, which attenuates the differences between the TI and the radiative models. Our findings call for caution when using MODIS for calibration and validation of spatially distributed snow models.