UAV-BASED LIDAR HIGH-RESOLUTION SNOW DEPTH MAPPING IN THE SWISS ALPS: COMPARING FLAT AND STEEP FORESTS

An upgraded version of a numerical solver is introduced to better capture the three-dimensional interactions between surface water and groundwater. Built using open-source software, it adds new features to handle the complexity of real environments, including the representation of subsurface geology and the simulation of diverse dynamic processes, such as solute transport and heat transfer, in both domains. A test case and a full description of the novel features are provided in this paper.

Snow microstructure controls snowpack properties, but most land surface models overlook this factor. To support future satellite missions, we created a new land surface model based on the Crocus scheme that simulates snow microstructure. Key improvements include better snow albedo representation, enhanced Arctic snow modeling, and improved forest module to capture Canada's diverse snow conditions. Results demonstrate improved simulations of snow density and melt across large regions of Canada.

How forests influence accumulation and melt of snow on the ground is of long-standing interest, but uncertainty remains in how best to model forest snow processes. We developed the Flexible Snow Model version 2 to quantify these uncertainties. In a first model demonstration, how unloading of intercepted snow from the forest canopy is represented is responsible for the largest uncertainty. Global mapping of forest distribution is also likely to be a large source of uncertainty in existing models.

The increasing impact of climate change and human activities on greenhouse gas emissions highlights the need for effective monitoring, especially from the soil. Our design introduces a low-cost solution for measuring soil gas flux that is adaptable to various environments. Additionally, we propose a novel method for ensuring data quality before deploying these systems in the field.

In this study, we present a dataset for the Dischma catchment in eastern Switzerland, which represents a typical high-alpine watershed in the European Alps. Accurate monitoring and reliable forecasting of snow and water resources in such basins are crucial for a wide range of applications. Our dataset is valuable for improving physics-based snow, land surface, and hydrological models, with potential applications in similar high-alpine catchments.