Slope Assessment Systems: A Review and Evaluation of Current Techniques Used for Cut Slopes in the Mountainous Terrain of West Malaysia
In Malaysia, slope assessment systems (SAS) are widely used in assessing the instability of slopes or the probability of occurrence and likely severity of landslides. These SAS can be derived based on either one particular approach or combination of several approaches of landslide assessments and...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English English |
| Published: |
Electronic Journal of Geotechnical Engineering
2008
|
| Online Access: | http://psasir.upm.edu.my/id/eprint/7767/1/Ppr0855.pdf http://psasir.upm.edu.my/id/eprint/7767/ http://www.ejge.com/Index_ejge.htm |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universiti Putra Malaysia |
| Language: | English English |
| Summary: | In Malaysia, slope assessment systems (SAS) are widely used in assessing the instability of
slopes or the probability of occurrence and likely severity of landslides. These SAS can be
derived based on either one particular approach or combination of several approaches of
landslide assessments and prediction. This paper overviews five slope assessment systems
(SAS) developed in Malaysia for predicting landslide for large-scale assessments. They are
the Slope Maintenance System (SMS), Slope Priority Ranking System (SPRS), Slope
Information Management System (SIMS), the Slope Management and Risk Tracking System
(SMART), and the Landslide Hazard and Risk Assessment (LHRA). An attempt is made to
evaluate the accuracy of these SAS in predicting landslides based on slope inventory data
from 139 cut slopes in granitic formations, and 47 cut slopes in meta-sediment formations,
which are the two most common rock/soil formations found in West Malaysia. Based on this
study, it was found that none of the existing SAS is satisfactory for predicting landslides of
cut slopes in granitic formations, for various reasons such as the use of a hazard score
developed from another country, an insufficient data base, an oversimplified approach, and
the use of data base derived from different rock/soil formations. However for the case of cut
slopes in meta-sediment, the Slope Management and Risk Tracking System (SMART) was
found to be satisfactory with a 90% prediction accuracy. The current database of SMART is
largely based on meta-sediment formations from the Kundusang area of Sabah, East
Malaysia. |
|---|