RegionGrow3D: A Deterministic Analysis for Characterizing Discrete Three‐Dimensional Landslide Source Areas on a Regional Scale

Abstract Regional‐scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics‐based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three‐dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad‐scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit‐equilibrium (LE)‐based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back‐calculated from inventoried landslides using 3D LE‐based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Authors

Institutions

Publication Details

Journal
Journal of Geophysical Research Earth Surface
Published
2024-08-31
DOI
https://doi.org/10.1029/2024jf007815
Citations
7
Primary Topic
Landslides and related hazards
Type
article
Field-Weighted Citation Impact
4.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

RegionGrow3D: A Deterministic Analysis for Characterizing Discrete Three‐Dimensional Landslide Source Areas on a Regional Scale

Michael J. Olsen, Adam M. Booth, Ben Leshchinsky, Benjamin B. Mirus et al.
7 citations
Journal of Geophysical Research Earth Surface
Landslides and related hazards
4.97
article

RegionGrow3D: A Deterministic Analysis for Characterizing Discrete Three‐Dimensional Landslide Source Areas on a Regional Scale

Michael J. Olsen, Adam M. Booth, Ben Leshchinsky, Benjamin B. Mirus, Nicolas Mathews
article en
7 citations

Abstract

Abstract Regional‐scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics‐based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three‐dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad‐scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km 2 ) using 3D, limit‐equilibrium (LE)‐based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back‐calculated from inventoried landslides using 3D LE‐based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Journal of Geophysical Research Earth SurfaceVol. 129(9)
Portland State University (US), United States Geological Survey (US), Oregon State University (US), Geologic Hazards Science Center
National Science Foundation, U.S. Department of Transportation, U.S. Department of Agriculture, Oregon Department of Transportation, Division of Civil, Mechanical and Manufacturing Innovation
Life below water
Openalex Percentile: Top 6%
Landslides and related hazards
4.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.