A LANDSLIDE INVENTORY AND GEOSTATISTICAL ANALYSIS FOR GRAND TETON NATIONAL PARK, WYOMING

Mass movements are a widespread and frequently destructive occurrence in places that experience high topographic relief, recent deglaciation, active seismicity, and/or intense precipitation such as northwest Wyoming's Teton Range. Because roads, trails, and other infrastructure or populated spaces often co-occur within these landscapes, landslide inventory maps serve as a foundational dataset for modeling landslide susceptibility and assessing the hazards and risks posed by future events. In this study, we use a 0.5-meter LiDAR dataset, aerial imagery, and detailed field observations to produce a novel landslide inventory map encompassing Grand Teton National Park, the John D. Rockefeller, Jr. Memorial Parkway, and the National Elk Refuge. The current inventory includes ~750 independent mass movements throughout the study region. The diversity of mass movement types and topographic and geologic settings enables us to prospect for patterns in the dataset. Toward this end, we apply three geostatistical methods. First, descriptive statistics identify broad patterns in the frequency and distribution of landslides in the park. For instance, the frequency and type of movements is spatially heterogeneous throughout the park, with debris flows, rockfall, and earth flows comprising the majority of observed mass movements, but are clustered in unique settings. Second, we use logistic regression tests to explore which different topographic domains, geologic substrates, and bedding orientations predict the presence and absence of landslides. Finally, multinominal logistic regression ascertains the degree to which these same factors control mass movement type. Since the Teton Range has wide variations in topography, structure, and lithology, our statistical findings serve to advance our understanding of where and how mass movements occur in other landslide-prone regions. We also aim to share our findings with the public and management community through a StoryMap web portal, hopefully instigating further research into the triggers, history, and risk mitigation of mass movements in the region.