Journal ArticleA new approach to mapping landslide hazards: a probabilistic integration of empirical and physically based models in the North Cascades of Washington, USAStrauch, Ronda; Istanbulluoglu, Erkan; Riedel, JonAbstract. We developed a new approach for mapping landslide hazards by combiningprobabilities of landslide impacts derived from a data-driven statisticalapproach and a physically based model of shallow landsliding. Ourstatistical approach integrates the influence of seven site attributes (SAs) onobserved landslides using a frequency ratio (FR) method. Influential attributesand resulting susceptibility maps depend on the observations of landslidesconsidered: all types of landslides, debris avalanches only, or source areasof debris avalanches. These observational datasets reflect the detection ofdifferent landslide processes or components, which relate to differentlandslide-inducing factors. For each landslide dataset, a stability index (SI) is calculated as a multiplicative result of the frequency ratios for all attributes and is mapped across our study domain in the North Cascades National Park Complex (NOCA), Washington, USA. A continuous function is developed to relate local SI values to landslide probability based on a ratio of landslide and non-landslide grid cells. The empirical model probability derived from the debris avalanche source area dataset is combined probabilistically with a previously developed physically based probabilistic model. A two-dimensional binning method employs empirical andphysically based probabilities as indices and calculates a joint probabilityof landsliding at the intersections of probability bins. A ratio of thejoint probability and the physically based model bin probability is used asa weight to adjust the original physically based probability at each gridcell given empirical evidence. The resulting integrated probability oflandslide initiation hazard includes mechanisms not captured by the infinite-slope stability model alone. Improvements in distinguishing potentiallyunstable areas with the proposed integrated model are statisticallyquantified. We provide multiple landslide hazard maps that land managers canuse for planning and decision-making, as well as for educating the publicabout hazards from landslides in this remote high-relief terrain.2019-01-0110185372Natural Hazards and Earth System Sciences19112477 to 24951684-9981https://doi.org/10.5194/nhess-19-2477-20191663859National Science Foundation