A Slope Stability Hazard Ranking Algorithm for Frozen Soil Terrains, 20-R8096
Gary R. Walter
Stuart A. Stothoff
D. Marius Necsoiu
Goodluck I. Ofoegbu
Inclusive Dates: 08/01/10 – 12/01/10
Background — The objective of this research was to develop and demonstrate an algorithm for ranking the risk of slope failures and thermokarst development in areas underlain by permafrost (ground that is continually frozen for at least two years) due to permafrost thawing. The algorithm is incorporated into a geographical information system (GIS) application that uses remote sensing data analysis, land classification mapping and geological risk assessment to identify areas susceptible to the risks of frozen soil thawing caused by climate change.
Approach — The algorithm integrates a numerical ground thawing and freezing dynamics (GTFD) model for calculating the thickness of the active layer and depth of permafrost with simple slope stability, mass wasting and thermokarst development models. The algorithm is informed by soil, vegetation and slope classification maps derived from optical and multi-polarization synthetic aperture radar imagery and existing soil and land classification maps. The algorithm is applicable to both current and future climate conditions, and can be validated by ground movement measurements derived from interferometric synthetic aperture radar (InSAR) and multispectral data displacement analysis (MDDA) methodologies.
Accomplishments — The algorithm was demonstrated using data from the Kobuk Valley in north-central Alaska developed during another internal research project, an on-going NASA-funded grant to study the Great Kobuk Sand Dunes, and soil/vegetation classification maps provided by the National Park Service. Soil thawing probability and slope failure risk maps were developed for the study area and used to illustrate the capabilities of the slope failure algorithm to assess risk to infrastructure such a pipelines.