TERRAIN CONTROLS ON ICESAT-2 SNOW DEPTH ESTIMATES OVER ALPINE WATERSHEDS IN THE WESTERN UNITED STATES

Seasonal snow is a critical water resource around the world, yet there are few methods to monitor the watershed-scale snow changes that are important for water management and hazard mitigation in our changing climate. Snow distribution is controlled by numerous factors including wind-snow interactions, terrain, and orographic precipitation patterns. This creates a dynamic snowpack where snow depths can vary by orders of magnitude over ranges of 10s to 100s of meters. Airborne lidar has been an invaluable tool for large-scale snow depth mapping efforts, but it is expensive and logistically-challenging. Preliminary exploration of NASA’s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) lidar datasets suggests it may be useful for snow mapping in remote regions, providing repeat observations throughout the snow accumulation and melt seasons that can improve estimates of snowpack evolution. However, ICESat-2 derived snow depths need to be tested and refined for use in complex alpine watersheds, where the rugged and often densely vegetated terrain presents many challenges for snow mapping. Dense vegetation results in sparse ground returns and mountainous terrain can have dramatic elevation and aspect changes within an ICESat-2 spatial-averaging window, and preliminary snow depth mapping with ICESat-2 shows that the accuracy of snow depth estimation is slope dependent. Here we describe the effects of watershed terrain features, including slope, elevation, and aspect, on ICESat-2 snow depth uncertainty using data for multiple alpine watersheds in southern Idaho. We find that slope errors are reduced when ICESat-2 averaging segments are shortened and are able to resolve orographic effects on snow depth across a watershed. We plan to develop this work into a general method to produce snow depth maps from ICESat-2 elevations in any watershed where a high-resolution snow-free digital elevation model is available.