Connections Between Forest Disturbance and Snowpack in a Pacific Northwest Watershed

The Cascade Mountains of the western United States are characterized by large conifer forests and a snow-melt dominated hydrologic cycle. Current analyses and those of projected climate change impacts show rising temperatures in the region. These increasing trends are accompanied by decreased storage of water in the snowpack, a shorter snow cover season and forests that are more susceptible to broad-scale disturbances. In this model-based study we examined how changes in forest composition affect the distribution and timing of SWE and snowmelt in the McKenzie River Basin, Oregon in predicted climates. We used the physically based SnowModel for estimations of SWE and snowmelt at 100m resolution. Descriptive vegetation layers for the model were altered to reflect hypothetic local, meso, and broad scale disturbances in the basin. The model was then rerun with the perturbed vegetation for the time period of 2000-2009. For future climate scenarios, temperature and precipitation inputs for 2000-2009 were perturbed based upon downscaled Intergovernmental Panel on Climate Change (IPCC) model predictions. These predictions are based on a composite of nineteen IPCC climate models downscaled to the Pacific Northwest region for scenarios A1B and B1 for the period for 2010-2039, 2030-2050, and 2080-2099. These perturbations were computed using the change from present-day climate to a projected future climate (delta value). The delta value was applied to daily temperature and precipitation data using a prescribed monthly value and the model was rerun using these perturbed values.