Inventory-Based Landslide Susceptibility Mapping in Colorado Springs, USA

Landslides in Colorado, USA cause millions of dollars of damage, destroy homes and infrastructure, and cause loss of life. Within the state, the town of Colorado Springs and surrounding El Paso County has been identified as an area that needs ongoing attention due to the severity of landslide risk. Most of the highest risk areas are either already mapped as landslide deposits or are located on top of the Pierre Shale, a unit that is highly susceptible to landslides. Previous landslide hazard maps and predictive models tended to be coarse, with almost all the steep areas overlying the Pierre Shale classified as high hazard. Consequently, there is a need for models that are able to provide more granularity in dividing hazard levels. This study uses a landslide database of 561 events in the area to improve on previous predictive methods, and also expands the list of potential influencing factors. Using binary logistic regression methods, the most significant parameters were curvature, elevation, slope, topographic wetness index, and geology, producing models with an area under curve (AUC) ranging from 0.91-0.95. The models that generated the best maps were ones using slope and geology or using slope and elevation, parameters that are easy to generate by GIS using Digital Elevation Models and geologic maps. The first modelrelies on parameters used in previous research, but our pixel-based map provides more detail to distinguish various hazard levels. The second model uses a parameter that has not been included in previous studies and can serve as a verification. The strong correlation to slope, elevation, and geology is expected to be prevalent in other locations where weak sedimentary units are tilted upwards along linear fault-block mountain fronts, as is the case in Colorado Springs.

Keywords: Landslide, Prediction, Susceptibility, Hazard, Inventory, Slope.