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Cartographie et suivi du contenu en eau de la neige à l’aide de mesures géoradar dronoporté récurrentes

Translated title of the thesis: Capturing the spatiotemporal variability of snowpack hydrological characteristics using a UAV based GPR
  • Eole Valence

Student thesis: Master's thesisMaster in Engineering: Construction Engineering

Abstract

Seasonal snow cover plays an important role in northern and alpine hydrology. By modifying the flow path and velocity, the internal properties of the snowpack dictate the distribution of melt water among water courses and groundwater. This phenomenon is even more remarkable during rain-on-snow events: by modifying the flow velocity of the water, the snowpack modifies the quantity of water discharging at the outlet of a system, increasing risk of flooding and ice jams. Recent observations and modelling predict more rain-on-snow events in many cold regions around the world for the future years. This could lead to an increase in the intensity and amount of ice jams and winter floods. A better understanding of processes and internal parameters influencing snowpack release of water is needed to predict the hydrological consequences of rain-on-snow increase. Based on winter 2020-2021 observations at the Sainte-Marthe experimental watershed, this study aims to develop a multi-method approach to measure the internal properties of the snowpack. Sainte-Marthe experimental watershed automatic weather station allows the identification of 2020-2021 winter ablation period, as well as identification of rain-on-snow events and validation of snow properties measurements. In addition, the snow depth over the studied area was determined on a weekly basis with drone-based photogrammetry. During the ablation period, maps of snow liquid water content were created with the combination between snow depth data and drone-based ground-penetrating radar (GPR) survey. The snowpack internal properties evolution between drones’ measurement was monitored with time domain reflectometry (TDR), and finally, the snowpack properties evolution was validated during manual measurements each week. The winter of 2020-2021 demonstrated the value and potential of this multi-method approach. The snowpack hydrological properties evolution was evaluated with drone-based GPR measurement over the 2020-2021 ablation period. In addition, the combination between GPR observation and TDR measurement has shown to be adapted to monitor the snowpack moisture winterlong.
Date14 Feb 2022
Original languageFrench
Awarding Institution
  • École de technologie supérieure
SupervisorMichel Baraër (Supervisor)

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