Hydrological behaviour of an ice‐layered snowpack in a non‐mountainous environment - Paquotte, Andrea; Baraer, Michel (Hydrological Processes, 2022)
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.
Keywords: Baraer_Michel; Infolettre; Infolettre_Ete_2023

Meteorological control on snow depth evolution and snowpack energy exchanges in an agro-forested environment by a measurement-based approach: A case study in Sainte-Marthe, Eastern Canada - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (Agricultural and Forest Meteorology, 2024)
Keywords: Baraer_Michel; Kinnard_Christophe

An Accuracy Assessment of Snow Depth Measurements in Agro-Forested Environments by UAV Lidar - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (Remote Sensing, 2022)
This study assesses the performance of UAV lidar system in measuring high-resolution snow depths in agro-forested landscapes in southern Québec, Canada. We used manmade, mobile ground control points in summer and winter surveys to assess the absolute vertical accuracy of the point cloud. Relative accuracy was determined by a repeat flight over one survey block. Estimated absolute and relative errors were within the expected accuracy of the lidar (~5 and ~7 cm, respectively). The validation of lidar-derived snow depths with ground-based measurements showed a good agreement, however with higher uncertainties observed in forested areas compared with open areas. A strip alignment procedure was used to attempt the correction of misalignment between overlapping flight strips. However, the significant improvement of inter-strip relative accuracy brought by this technique was at the cost of the absolute accuracy of the entire point cloud. This phenomenon was further confirmed by the degraded performance of the strip-aligned snow depths compared with ground-based measurements. This study shows that boresight calibrated point clouds without strip alignment are deemed to be adequate to provide centimeter-level accurate snow depth maps with UAV lidar. Moreover, this study provides some of the earliest snow depth mapping results in agro-forested landscapes based on UAV lidar.
Keywords: Baraer_Michel; Kinnard_Christophe

Topographic and vegetation controls of the spatial distribution of snow depth in agro-forested environments by UAV lidar - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (The Cryosphere, 2023)
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.
Keywords: Baraer_Michel; Kinnard_Christophe

A new interpolation method to resolve under-sampling of UAV-lidar snow depth observations in coniferous forests - Dharmadasa, Vasana; Kinnard, Christophe; Baraër, Michel (Cold Regions Science and Technology, 2024)
Keywords: Baraer_Michel; Kinnard_Christophe

Proglacial icings as records of winter hydrological processes - Chesnokova, Anna; Baraër, Michel; Bouchard, Émilie (The Cryosphere, 2020)
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.
Keywords: Baraer_Michel

Editorial: Connecting Mountain Hydroclimate Through the American Cordilleras - Fernández, Alfonso; Mark, Bryan G.; Baraer, Michel (Frontiers in Earth Science, 2021)
Keywords: Baraer_Michel

Extension of a Monolayer Energy-Budget Degree-Day Model to a Multilayer One - Augas, Julien; Foulon, Etienne; Rousseau, Alain N.; Baraër, Michel (Water, 2024)
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.
Keywords: Baraer_Michel; Rousseau_Alain

What is the Trade-Off between Snowpack Stratification and Simulated Snow Water Equivalent in a Physically-Based Snow Model? - Augas, Julien; Abbasnezhadi, Kian; Rousseau, Alain N.; Baraer, Michel (Water, 2020)
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.
Keywords: Baraer_Michel; Rousseau_Alain

Drone-based ground-penetrating radar (GPR) application to snow hydrology - Valence, Eole; Baraer, Michel; Rosa, Eric; Barbecot, Florent; Monty, Chloe (The Cryosphere, 2022)
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.
Keywords: Baraer_Michel; Infolettre; Infolettre_Octobre_2022; Site_internet_RIISQ

Using ground-based thermal imagery to estimate debris thickness over glacial ice: fieldwork considerations to improve the effectiveness - Aubry-Wake, Caroline; Lamontagne-Hallé, Pierrick; Baraër, Michel; McKenzie, Jeffrey M.; Pomeroy, John W. (Journal of Glaciology, 2023)
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.
Keywords: Baraer_Michel

Role of Mountain Glaciers in the Hydrological Dynamics of Headwater Basins in the Wet Andes - Lizama, Elizabet; Valenzuela, Marcelo Somos; Rivera, Diego; Lillo, Mario; Morales, Bastian; Baraër, Michel; Fernandez, Alfonso (2024)
Keywords: Baraer_Michel

Trace Metal Stream Contamination in a Post Peak Water Context: Lessons from the Cordillera Blanca, Peru - Guittard, Alexandre; Baraer, Michel; McKenzie, Jeffrey M.; Mark, Bryan G.; Rapre, Alejo C.; Bury, Jeffrey; Carey, Mark; Young, Kenneth R. (ACS Earth and Space Chemistry, 2020)
Keywords: Baraer_Michel

High-temporal-resolution hydrometeorological data collected in the tropical Cordillera Blanca, Peru (2004–2020) - Mateo, Emilio I.; Mark, Bryan G.; Hellström, Robert Å.; Baraer, Michel; McKenzie, Jeffrey M.; Condom, Thomas; Rapre, Alejo Cochachín; Gonzales, Gilber; Gómez, Joe Quijano; Encarnación, Rolando Cesai Crúz (Earth System Science Data, 2022)
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.
Keywords: Baraer_Michel