Snowmelt sensing using arrays of passive wireless microwave sensors

Context :

Snow is made up of air, ice crystals, and sometimes liquid water from melting or precipitation. The liquid water content in wet snow varies over time and space and is important for predicting snowmelt infiltration and wet-snow avalanches. Measuring water content is challenging and typically involves manual, destructive methods that are time-consuming and not highly accurate. Liquid water in snow also affects the dielectric permittivity, allowing for remote measurements via radar or GNSS, although these methods have their shortcomings. Members of the team have developed a unique system composed of numerous passive Radiofrequency Identification (RFID) sensors to monitor snow mass and temperature. Yet, its main challenge remains the measurement of liquid water content ; we have identified several indicators qualitatively and want to confirm them quantitatively.

Objectives :

The aim of this thesis is to confirm and quantify the ability to measure liquid water content using passive RFID sensors through experimental work. Their influence parameters will be measured in a cold chamber laboratory and compared with ground truth measurements. You will use this data to calibrate the new RFID measurement method, estimate the relevance of each indicator, create a first model for calculating liquid water content, and finally apply this model to existing field data. You would also support the implementation of a winter-long field campaign to monitor the snowpack.

We would like to start the project before the coming winter, before January ideally. We offer free accommodation in a shared flat for the duration of the project. Please contact Mathieu Le Breton (mathieu.le-breton slf.ch) and Eric Larose (Eric.larose univ-grenoble-alpes.fr) for further information. To apply, please send your CV, a current transcript of records and a short motivation letter by email.