Coupling iSnobal and ASO: Towards an Integrated Water Supply Toolbox for Water Resource Managers

Abstract:

Since 2013, airborne lidar surveys have been performed throughout the melt season at near-weekly intervals over the 1,400 km2 Tuolumne River Basin in California's Sierra Nevada Mountains, with the goal of deriving high-resolution measurements of snow depth and reflectance for the NASA Airborne Snow Observatory (ASO). Since the beginning of the campaign, a distributed, physically-based snow model (iSnobal) has been used to estimate the spatial snow density distribution critical for providing accurate SWE products to water managers downstream. An important feature of iSnobal is the ability to stop and then restart using an initialization image constructed from the results of the prior time step. This work examines the effect of assimilating the ASO lidar-derived snow depths to guide the modeled density distribution, since precipitation has been found to be the most difficult parameter to distribute over large mountain basins. Results indicate that the initial model update for each winter is the most significant, with subsequent updates in the absence of severe spring storms having increasingly smaller impacts on the total modeled basin water storage. However, the unprecedented temporal resolution of the ASO lidar surveys provide new insight into the springtime evolution of a large basin snowpack and immensely improve melt timing predictions, which are becoming more and more vital for reservoir management in a changing climate.