Rapidly portraying landside runout and debris-flow inundation using simple, empirical methods

Landslide runout and debris-flow inundation are crucial, yet often neglected, threats that can impact areas far beyond initial landslide sources. Understanding where mobile landslides initiate and how far they travel is essential to hazard and risk reduction worldwide, as mitigation strategies vary with landslide mobility. Moreover, debris flows can grow volumetrically as they travel, resulting in larger, faster flows with greater inundation. However, most landslide susceptibility maps focus on steep slopes and fail to address runout and inundation onto flatter ground, which typically encompasses more inhabitants and infrastructure. Given the widespread importance of runout and inundation, it is vital to have simple-to-use methods that rapidly map the effects of these mobile processes over large regions, especially in locations with limited geotechnical data.

We present an empirical approach for mapping areas susceptible to landslides and debris flows from their initiation to deposition. Using the publicly available USGS software package, Grfin Tools, we delineate landslide source areas, landslide runout, and debris-flow inundation zones within a DEM. Grfin is an acronym of Growth + flow + inundation and this computationally fast software uses simple, well-tested, and fully documented empirical models. Potential landslide runout is determined using angles of reach. Potential debris-flow inundation from volumetric growth is delineated using volume-area scaling relations based on worldwide observations, combined with a novel use of spatially integrated growth factors. These models require minimal input parameters and place an emphasis on regional geomorphic and topographic controls rather than specific material properties.

Using Grfin Tools, we illustrate our approach by mapping a spectrum of mass-movement mobility zones on three island states of the Federated States of Micronesia where landslide runout and debris-flow inundation onto flatter ground have resulted in fatalities. Future mobile events pose a deadly threat, yet previous landslide information is incomplete. To estimate the empirical model parameters needed to portray multiple mass-movement zones, we use satellite-derived landslide inventories combined with topographic thresholds obtained from 10-m resolution DEMs. Based on field observations of debris-flow deposits from 138 stream locations, our debris-flow inundation model incorporating spatially integrated growth has a prediction success of greater than 85%. Our methods using Grfin Tools can rapidly create preliminary regional assessments, provide multiple scenario assessments, or act as a screening tool to identify critical areas for further detailed studies across a wide variety of landscapes.