Using fixed GPR for Monitoring Flows of Liquid Water through Snowpacks ans Assessing LWC Measurement Capabilities

Using fixed GPR for Monitoring Flows of Liquid Water through Snowpacks and Assessing LWC Measurement Capabilities

Mathis Goujon, Michel Baraër2, and Lisa Michaud3

• 1 ÉTS, University of Quebec, HC3, Montreal, Canada (mathis.goujon.1@ens.etsmtl.ca)
• 2 ÉTS, University of Quebec, HC3, Montreal, Canada (michel.baraer@etsmtl.ca)
• 3 ÉTS, University of Quebec, HC3, Montreal, Canada

The snow liquid water content (LWC) is of great significance across various scientific disciplines, including meteorology, hydrology, and climate modeling. Precise LWC assessment plays a pivotal role in processes like weather prediction, water resource management, avalanche risk evaluation, and understanding the effects of climate change. Nevertheless, measuring LWC within snowpacks presents a formidable challenge due to the intricate physical properties of snow and its spatial variability. Several methodologies have been developed to tackle this challenge, each with its own advantages and limitations. These challenges arise from the rapidly changing physical characteristics of snow and its uneven distribution.

Unmanned Aerial Vehicle (UAV)-mounted high-frequency Ground Penetrating Radars (GPR) have emerged as a unique technique capable of capturing the spatial variability of LWC within snowpacks in a repetitive and non-destructive manner. However, this technique faces high uncertainties due to factors like the use of empirical equations to convert electromagnetic wave characteristics into LWC, challenges in interpreting radargrams, and the absence of robust reference methods.

This study is dedicated to enhancing the utility of UAV-mounted GPR for large-scale LWC measurements within snowpacks. It involves collecting real-time data from a portable 1500 MHz GPR positioned in a fixed location while the snowpack undergoes dynamic changes. Coupled with Time Domain Reflectometry (TDR) probes, the objective is to validate the presence of ice and infiltration during thaw and precipitation events and evaluate changes in the electromagnetic signal properties received by the GPR over time. This integration provides valuable insights into internal runoff dynamics during thaw periods. Automated GPR and TDR measurements are complemented by weekly snow pit characterizations, including LWC measurements using an A2 Photonics WISe sensor, a Snow Fork probe, and a calorimeter.

Fieldwork was conducted at the Sainte-Marthe experimental watershed in Quebec, Canada, during the winter of 2023. Initially, the effectiveness of the A2 Photonics WISe sensor, Snow Fork probe, and calorimeter in quantifying LWC under field conditions was critically assessed. Subsequently, the GPR trace time series was compared to LWC measurements, hydrometeorological variables, and TDR responses. The time series of traces was analyzed to extract Two-Way Travel times (TWT) for reflectors of interest, phase change events, and frequency-dependent attenuation factors at 2.5-minute intervals over a period of 5 weeks.

The results clearly demonstrate the 1500 MHz GPR's capability to detect and track the flow of liquid water through the snowpack. Among other findings, the time series reveals the role of an internal ice layer in partitioning snowpack hydrological responses above and below its surface. LWC evolution over time was calculated using different sets of equations from the literature and compared to reference methods.

Overall, this research underscores that fixed high-frequency GPR is a valuable tool for tracking water flows within snowpacks, with numerous potential applications in snow hydrology and hydrometeorology. The study also identifies optimal equation sets for calculating LWC from radargrams, both in fixed and mobile modes.