Photogrammetrically derived estimates of end-of-winter snow depth variability in complex terrain

Abstract:

Seasonal snow is a key cryospheric variable because of its influence on energy and water budgets, public safety, and regional economies. Quantitative information on the spatial distribution of snow depth and snow water equivalence (SWE) is central to numerous applications in cryospheric research. However, in complex terrain, strong orographic gradients and wind redistribution produce complicated accumulation patterns that are difficult to capture using traditional in situ and satellite-based approaches, and are challenging to model with acceptable levels of uncertainty. Here we apply a repeat airborne photogrammetric approach and employ a Structure from Motion (SfM) processing method to generate digital surface models (DSMs) of snow-free and end-of-winter snow covered surfaces. Surface elevation differencing of these datasets produces a continuous and accurate snow depth map into which we assimilate in situ SWE measurements to produce detailed estimates of SWE over complex terrain in the maritime-continental transition zone of the eastern Chugach Mountains.