Comparison of slope instability screening tools following a large storm event and application to forest management and policy

The objective of this study was to assess and compare the ability of two slope instability screening tools developed by the Washington State Department of Natural Resources (WDNR) to assess landslide risks associated with forestry activities. HAZONE is based on a semi-quantitative method that incorporates the landslide frequency rate and landslide area rate for delivery of mapped landforms. SLPSTAB is a GIS-based model of inherent landform characteristics that utilizes slope geometry derived from DEMs and climatic data. Utilization of slope instability screening tools by geologists, land managers, and regulatory agencies can reduce the frequency and magnitude of landslides. Aquatic habitats are negatively impacted by elevated rates and magnitudes of landslides associated with forest management practices due to high sediment loads and alteration of stream channels and morphology. In 2007 a large storm with heavy rainfall impacted southwestern Washington State trigging over 2500 landslides. This storm event and accompanying landslides provides an opportunity to assess the slope stability screening tools developed by WDNR. Landslide density (up to 6.5 landslides per km2) from the storm was highest in the areas designated by the screening tools as high hazard areas, and both of the screening tools were equal in their ability to predict landslide locations. Landslides that initiated in low hazard areas may have resulted from a variety of site-specific factors that deviated from assumed model values, from the inadequate identification of potentially unstable landforms due to low resolution DEMs, or from the inadequate implementation of the state Forest Practices Rules. We suggest that slope instability screening tools can be better utilized by forest management planners and regulators to meet policy goals regarding minimizing landslide rates and impacts to sensitive aquatic species.

► Landslide density was highest in the screening tools' highest hazard categories.
► Screening tools were equal in their ability to predict landslide locations.
► Screening tools can be better utilized in forest management to meet policy goals.