Wind- and gravity-induced redistribution of snow leads to a high variability in snow depth across a slope, which is one of the major drivers to be taken into account for the assessment of avalanche danger. However, data on snow depth distribution in avalanche release zones at high spatial and temporal resolution are rarely available. We applied a newly developed monitoring system using low cost lidar and optical data that measured the snow depth distribution once per hour over the winter season 2023/24 at the release zone of the Wildi avalanche in Davos, Switzerland. The dataset consists of more than 3’000 epochs, each including an RGB image and lidar scans. In this contribution we present our experiences after one winter season of measurements, focusing on the station stability. By investigating apparent position changes of stable targets in the scan area we can quantify the stability of our measurement system. Additionally, we take first steps towards basic snow depth distribution modeling, by correlating the measured snow depths to terrain parameters. With the topographic position index (TPI) we test the common assumption that the mean snow depth is lower at ridges and hilltops, and higher at gullies and valleys than the mean overall snow depth. Up-to-date information on the snow depth variability in avalanche release zones is valuable for the refinement of avalanche simulation approaches, as well as for practitioners who decide on avalanche safety measures.