Direct Insertion of NASA Airborne Snow Observatory‐Derived Snow Depth Time Series Into the iSnobal Energy Balance Snow Model Water Resources Research

Accurately simulating the spatiotemporal distribution of mountain snow water equivalent improves estimates of available meltwater and bene fits the water resource management community. In this paper we present the first integration of lidar-derived distributed snow depth data into a physics-based snow model using direct insertion. Over four winter seasons (2013 –2016) the National Aeronautics and Space Administration/Jet Propulsion Laboratory (NASA/JPL) Airborne Snow Observatory (ASO) performed near-weekly lidar surveys throughout the snowmelt season to measure snow depth at high resolution overthe Tuolumne River Basin above Hetch Hetchy Reservoir in the Sierra Nevada Mountains of California. The modeling component of the ASO program implements the iSnobal model to estimate snow density for