Semi-automated regional scale debris-flow and debris-flood susceptibility mapping based on digital elevation model metrics and Flow-R software

Abstract

Regional scale debris-flow or debris-flood susceptibility mapping based on terrain analysis is limited by a high degree of effort and the availability of surface evidence for past events, which may be obfuscated by development or obscured by repeat erosion or debris inundation. This paper presents a semi-automated methodology for debris-flow and debris-flood susceptibility mapping at regional scale based on a combination of digital elevation model (DEM) metrics to identify potential source zones, and flow propagation simulations using the Flow-R code. The DEM metrics allow identification and preliminary, process-based classification of streams prone to debris flow and debris flood, respectively. Flow-R simulations are based on a combination of spreading and runout algorithms considering DEM topography and empirical runout parameters. The methodology was first tested in a region of the Canadian Rocky Mountains, where detailed debris-flood hazard assessments had been previously undertaken based on both field mapping and numerical modeling. It was then applied over two regions, with 22,000 km2 and 55,000 km2 areas, respectively, in central British Columbia, Canada. One important advantage of the presented methodology is the limited amount of data required to generate a preliminary susceptibility map over a large region. Once incorporated in a risk assessment framework, this map can be used to prioritize more detailed assessments. The methodology was also applied at a higher level of detail to an approximately 30 km long roadway corridor in Southwestern British Columbia. At the assessment level of this project, the methodology allowed generation of a susceptibility map which considered the cumulative contribution of several potential source zones within each debris-flow and debris-flood watershed. This map allowed risk-based prioritization and supported debris-flow risk reduction decision making.