TY - Generic T1 - Towards a Decision Support Tool for Understanding the Effect of Forest Thinning on the Sierra Nevada Snowpack T2 - 87th Annual Western Snow Conference Y1 - 2019 A1 - Sebastian A. Krogh A1 - Adrian Harpold A1 - Patrick Broxton KW - forest thinning KW - Lake Tahoe KW - LiDAR KW - snow hydrology AB -

Snowmelt from the Sierra Nevada is a key water resource in the western US supporting economic development and ecological functions. Previous forest management practices have revealed that snowmelt volume depends on the complex interaction between changes to sublimation from canopy interception and net radiation at the snow surface. Despite decades of research, we lack insight into how to thin a forest to maximize snow accumulation and retention in complex topography. To better understand how different forest treatments might impact the snowpack, this study uses the Snow Physics and LiDAR Mapping (SnowPALM) model to simulate snowpack changes under a virtual forest thinning scenario over two mountainous watersheds at the west shore of Lake Tahoe, California. SnowPALM uses information about canopy density and height from lidar data to simulate tree-scale snow processes at 1-meter resolution. Questions addressed in this research are: what type of forest thinning are the most efficient to increase snow accumulation and melt volume, where do they have the largest impact, and what mechanism are driving these impacts? Simulations from this study will be used to produce a decision support tool for stakeholders, forest managers and policy makers at the west shore of Lake Tahoe.

JF - 87th Annual Western Snow Conference CY - Reno, NV UR - /files/PDFs/2019Krogh.pdf ER -