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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.
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Abstract Accelerating mountain glacier recession in a warming climate threatens the sustainability of mountain water resources. The extent to which groundwater will provide resilience to these water resources is unknown, in part due to a lack of data and poorly understood interactions between groundwater and surface water. Here we address this knowledge gap by linking climate, glaciers, surface water, and groundwater into an integrated model of the Shullcas Watershed, Peru, in the tropical Andes, the region experiencing the most rapid mountain‐glacier retreat on Earth. For a range of climate scenarios, our model projects that glaciers will disappear by 2100. The loss of glacial meltwater will be buffered by relatively consistent groundwater discharge, which only receives minor recharge (~2%) from glacier melt. However, increasing temperature and associated evapotranspiration, alongside potential decreases in precipitation, will decrease groundwater recharge and streamflow, particularly for the RCP 8.5 emission scenario. , Plain Language Summary Mountain regions play an important role in water supply, because meltwater from snow and ice feeds rivers during dry periods. Groundwater (water stored in the pore spaces of soils and rock), which flows into rivers, is also an important store of water in mountain areas and may help to protect water resources against the negative impacts of shrinking mountain glaciers. We used extensive field measurements and computer modeling of the Shullcas Watershed in the Peruvian Andes to determine the current and future role of groundwater in the face of climate change. Our model projects that glaciers in our study area will disappear by 2100. The loss of glacier meltwater is buffered in the short term (~30 years) by consistent groundwater flow to rivers. However, in the long term (>60 years), precipitation is expected to decrease and rising temperatures lead to increased evaporation and water use by plants. These factors reduce groundwater recharge and storage, causing dry season streamflow to drop. , Key Points Groundwater accounts for a large fraction of streamflow and only receives minor (~2%) recharge from glaciers in the study catchment in Peru As meltwater decreases, groundwater provides consistent discharge in the near term (~30 years), becoming a larger fraction of streamflow In the long term (>60 years), groundwater storage and discharge decrease in response to higher evapotranspiration and lower precipitation
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Abstract. Climate models predict amplified warming at high elevations in low latitudes, making tropical glacierized regions some of the most vulnerable hydrological systems in the world. Observations reveal decreasing streamflow due to retreating glaciers in the Andes, which hold 99 % of all tropical glaciers. However, the timescales over which meltwater contributes to streamflow and the pathways it takes – surface and subsurface – remain uncertain, hindering our ability to predict how shrinking glaciers will impact water resources. Two major contributors to this uncertainty are the sparsity of hydrologic measurements in tropical glacierized watersheds and the complication of hydrograph separation where there is year-round glacier melt. We address these challenges using a multi-method approach that employs repeat hydrochemical mixing model analysis, hydroclimatic time series analysis, and integrated watershed modeling. Each of these approaches interrogates distinct timescale relationships among meltwater, groundwater, and stream discharge. Our results challenge the commonly held conceptual model that glaciers buffer discharge variability. Instead, in a subhumid watershed on Volcán Chimborazo, Ecuador, glacier melt drives nearly all the variability in discharge (Pearson correlation coefficient of 0.89 in simulations), with glaciers contributing a broad range of 20 %–60 % or wider of discharge, mostly (86 %) through surface runoff on hourly timescales, but also through infiltration that increases annual groundwater contributions by nearly 20 %. We further found that rainfall may enhance glacier melt contributions to discharge at timescales that complement glacier melt production, possibly explaining why minimum discharge occurred at the study site during warm but dry El Niño conditions, which typically heighten melt in the Andes. Our findings caution against extrapolations from isolated measurements: stream discharge and glacier melt contributions in tropical glacierized systems can change substantially at hourly to interannual timescales, due to climatic variability and surface to subsurface flow processes.
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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.
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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
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Evaluating the historical contribution of the volume loss of ice to stream flow based on reconstructed volume changes through the Little Ice Age (LIA) can be directly related to the understanding of glacier-hydrology in the current epoch of rapid glacier loss that has disquieting implications for a water resource in the Cordillera Blanca in the Peruvian Andes. However, the accurate prediction of the future glacial meltwater availability for the developing regional Andean society needs more extensive quantitative estimation from long-term glacial meltwater of reconstructed glacial volume. Modeling the LIA paleoglaciers through the mid-19th century (with the most extensive recent period of mountain glacier expansion having occurred around 1850 AD) in different catchments of the Cordillera Blanca allows us to reconstruct glacier volume and its change from likely combinations of climatic control variables and time. We computed the rate and magnitude of centennial-scale glacier volume changes for glacier surfaces between the LIA and the modern era, as defined by 2011 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2) and 2008 Light Detection and Range (LiDAR) data. The model simulation showed good agreement with the observed geomorphic data and the volume and surface area (V-S) scaling remained within the 25% error range in the reconstructed simulation. Also, we employed a recently demonstrated approach (Baraër, M. et al.) to calculate meltwater contribution to glacierized catchment runoff. The results revealed multiple peaks of both mean annual and dry season discharge that have never been shown in previous research on the same mountain range.
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The rapidly melting glaciers of Peru are posing new risks to regional dry season water supplies, and this is evident in the Cordillera Blanca, the mountain range with the world's largest concentration of tropical glaciers. Permanent ice loss is causing reductions to dry season streamflow, which is coupled with shifting demands and control over water access and entitlements in the region. A full evaluation of hydrologic inputs is required to inform future water management in the relative absence of glaciers. Over the last decade, new studies have shown groundwater to be a significant component of the regional water budget during the dry season, and it cannot be ignored when accounting for water quality and quantity downstream of the Cordillera Blanca's alpine catchments. Distinctive common features of the Cordillera Blanca's proglacial catchments are sediment‐filled valleys that were once under proglacial lake conditions. The combination of lake sediments with other alpine depositional features results in storage and interseasonal release of groundwater that comprises up to 80% of the valley's streamflow during the driest months of the year. We summarize the emerging understanding of hydrogeologic processes in proglacial headwater systems of the region's principal river, the Rio Santa, and make suggestions for future research that will more clearly characterize the spatial distribution of stored groundwater within the mountain range. As glaciers continue to recede, differences in aquifer thickness and groundwater residence time between alpine catchments in the region will increasingly control dry season water availability at the local and basin scale. This article is categorized under: Science of Water > Hydrological Processes Science of Water > Water and Environmental Change Engineering Water > Planning Water
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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.
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This paper presents the extension of the monolayer snow model of a semi-distributed hydrological model (HYDROTEL) to a multilayer model that considers snow to be a combination of ice and air, while accounting for freezing rain. For two stations in Yukon and one station in northern Quebec, Canada, the multilayer model achieves high performances during calibration periods yet similar to the those of the monolayer model, with KGEs of up to 0.9. However, it increases the KGE values by up to 0.2 during the validation periods. The multilayer model provides more accurate estimations of maximum SWE and total spring snowmelt dates. This is due to its increased sensitivity to thermal atmospheric conditions. Although the multilayer model improves the estimation of snow heights overall, it exhibits excessive snow densities during spring snowmelt. Future research should aim to refine the representation of snow densities to enhance the accuracy of the multilayer model. Nevertheless, this model has the potential to improve the simulation of spring snowmelt, addressing a common limitation of the monolayer model.
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In Nordic watersheds, estimation of the dynamics of snow water equivalent (SWE) represents a major step toward a satisfactory modeling of the annual hydrograph. For a multilayer, physically-based snow model like MASiN (Modèle Autonome de Simulation de la Neige), the number of modeled snow layers can affect the accuracy of the simulated SWE. The objective of this study was to identify the maximum number of snow layers (MNSL) that would define the trade-off between snowpack stratification and SWE modeling accuracy. Results indicated that decreasing the MNSL reduced the SWE modeling accuracy since the thermal energy balance and the mass balance were less accurately resolved by the model. Nevertheless, from a performance standpoint, SWE modeling can be accurate enough with a MNSL of two (2), with a substantial performance drop for a MNSL value of around nine (9). Additionally, the linear correlation between the values of the calibrated parameters and the MNSL indicated that reducing the latter in MASiN increased the fresh snow density and the settlement coefficient, while the maximum radiation coefficient decreased. In this case, MASiN favored the melting process, and thus the homogenization of snow layers occurred from the top layers of the snowpack in the modeling algorithm.
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Abstract The increased frequency of mild rain‐on‐snow (R.O.S.) events in cold regions associated with climate change is projected to affect snowpack structure and hydrological behaviour. The ice layers that form in a cold snowpack when R.O.S. events occur have been shown to influence flowthrough processes and liquid water retention, with consequences for winter floods, groundwater recharge, and water resources management. This study explores interconnections between meteorological conditions, ice layer formation, and lateral flows during R.O.S. events throughout the 2018–2019 winter in meridional Quebec, Canada. Automated hydro‐meteorological measurements, such as water availability for runoff, snow water equivalent, and snowpit observations, are used to compute water and energy balances, making it possible to characterize a snowpack's internal conditions and flowthrough regimes. For compatibility assessment, water and energy balances‐based flowthrough scenarios are then compared to different hydro‐meteorological variables', such as water table or streamlet water levels. The results show an association between highly variable meteorological conditions, frequent R.O.S. events, and ice layer formation. Lateral flows were mainly observed during the early stage of the ablation period. The hydrologically significant lateral flows observed in the study are associated with winter conditions that are predicted to become more frequent in a changing climate, stressing the need for further evaluation of their potential impact at the watershed scale.
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Abstract. Accurate knowledge of snow depth distributions in forested regions is crucial for applications in hydrology and ecology. In such a context, understanding and assessing the effect of vegetation and topographic conditions on snow depth variability is required. In this study, the spatial distribution of snow depth in two agro-forested sites and one coniferous site in eastern Canada was analyzed for topographic and vegetation effects on snow accumulation. Spatially distributed snow depths were derived by unmanned aerial vehicle light detection and ranging (UAV lidar) surveys conducted in 2019 and 2020. Distinct patterns of snow accumulation and erosion in open areas (fields) versus adjacent forested areas were observed in lidar-derived snow depth maps at all sites. Omnidirectional semi-variogram analysis of snow depths showed the existence of a scale break distance of less than 10 m in the forested area at all three sites, whereas open areas showed comparatively larger scale break distances (i.e., 11–14 m). The effect of vegetation and topographic variables on the spatial variability in snow depths at each site was investigated with random forest models. Results show that the underlying topography and the wind redistribution of snow along forest edges govern the snow depth variability at agro-forested sites, while forest structure variability dominates snow depth variability in the coniferous environment. These results highlight the importance of including and better representing these processes in physically based models for accurate estimates of snowpack dynamics.
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Abstract. This article presents a comprehensive hydrometeorological dataset collected over the past two decades throughout the Cordillera Blanca, Peru. The data-recording sites, located in the upper portion of the Rio Santa valley, also known as the Callejon de Huaylas, span an elevation range of 3738–4750 m a.s.l. As many historical hydrological stations measuring daily discharge across the region became defunct after their installation in the 1950s, there was a need for new stations to be installed and an opportunity to increase the temporal resolution of the streamflow observations. Through inter-institutional collaboration, the hydrometeorological network described in this paper was deployed with the goal of evaluating how progressive glacier mass loss was impacting stream hydrology, and understanding better the local manifestation of climate change over diurnal to seasonal and interannual time scales. The four automatic weather stations supply detailed meteorological observations and are situated in a variety of mountain landscapes, with one on a high-mountain pass, another next to a glacial lake, and two in glacially carved valleys. Four additional temperature and relative humidity loggers complement the weather stations within the Llanganuco valley by providing these data across an elevation gradient. The six streamflow gauges are located in tributaries to the Rio Santa and collect high-temporal-resolution runoff data. The datasets presented here are available freely from https://doi.org/10.4211/hs.35a670e6c5824ff89b3b74fe45ca90e0 (Mateo et al., 2021). Combined, the hydrological and meteorological data collected throughout the Cordillera Blanca enable detailed research of atmospheric and hydrological processes in tropical high-mountain terrain.