A Model-based Approach to Quantify the Impacts of Forest thinning on a Maritime Snowpack

Abstract:

As climate warms, decreasing snow accumulation and increasing mid-winter ablation events threaten water availability. Resource managers in the maritime Mountain West (USA) need to consider adaptive strategies that increase water availability and promote healthy ecosystems. Forest thinning is one the few means available to manage the snowpack and increase water availability. While studies have documented that reducing forest density can increase snow accumulation and retention, we lack knowledge of effective thinning strategies at a basin wide scale. In this work we attempt to address this issue by adapting a spatially distributed percent canopy cover term to a physically based model SnowModel. This term allows us to scale the snowpack water and energy fluxes that are altered by the forest canopy. The model is calibrated to a series of paired open and forested snow course sites in the McKenzie River Basin (MRB), Oregon, USA. Each of these sites vary in span the seasonal snow zone elevations from 1100 m to 1450 m., canopy cover and mean winter temperatures. This calibrated model is then applied to the entire MRB using landcover from the National Land Cover Data set (NLCD), gridded percent canopy cover from the NLCD, and forced with a 3hr GridMet product. Basin-wide forest thinning was sequentially simulated with three different intensities by assigning a maximum of (60%, 40%, and 20%) canopy cover to the gridded canopy cover product. With this process, we investigate site-specific and basin-wide change in snowpack water and energy fluxes. Preliminary results show that the magnitude and timing of melt vary with changes in percent canopy cover. Additionally, aspect, elevation, and forest temperature play a crucial role in determining where thinning treatments can be effective. This work is part of the Willamette INFEWS project, where we investigate the coupled response of forest thinning to snow, streamflow, and wildfire. We hope that this work will inform climate adaptation policies and improve systems understanding of water and forest resource.