Evaluating Slope Stability in Forest Uplands with Deterministic and Probabilistic Models

Abstract

Research Article| January 01, 1998 Evaluating Slope Stability in Forest Uplands with Deterministic and Probabilistic Models THOMAS E. KOLER THOMAS E. KOLER Intermountain Natural Resource Consultants, 5258 Matson Road, Viola, ID 83872 Search for other works by this author on: GSW Google Scholar Environmental & Engineering Geoscience (1998) IV (2): 185–194. https://doi.org/10.2113/gseegeosci.IV.2.185 Article history first online: 09 Mar 2017 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Tools Icon Tools Get Permissions Search Site Citation THOMAS E. KOLER; Evaluating Slope Stability in Forest Uplands with Deterministic and Probabilistic Models. Environmental & Engineering Geoscience 1998;; IV (2): 185–194. doi: https://doi.org/10.2113/gseegeosci.IV.2.185 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyEnvironmental & Engineering Geoscience Search Advanced Search Abstract Deterministic Level I Stability Analysis (DLISA) and probabilistic Level I Stability Analysis (LISA) models provide information for a slope stability analysis. These computer codes have been developed, tested, and validated by U. S. Department of Agriculture Forest Service researchers. The purpose of this research was to provide engineers and scientists a personal computer program for evaluating potential slope instability within planning areas in forested uplands. Physical soil values within the infinite slope equation are evaluated within DLISA for possible frequency distributions. LISA, the probabilistic computer program, adds a stochastic simulation by the Monte Carlo method of these frequency distributions. The result from these analyses is a probability of slope failure. Potential shallow landslides, such as debris flows, have been evaluated since 1987 and can be predicted with DLISA and LISA. This content is PDF only. Please click on the PDF icon to access. First Page Preview Close Modal You do not have access to this content, please speak to your institutional administrator if you feel you should have access.