Landslide susceptibility analysis using sinmap in Fraser's Hill, Malaysia
Shallow landslide is normally occurred between 1 to 2 meter depth and it also normally occurs in highly and completely weathered rocks (Grades IV to VI) or known as residual soil. It can be very active and widespread in occurrence especially during rainy seasons where the soil moisture is saturated...
Saved in:
| Main Author: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
2012
|
| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/33338/1/FPAS%202012%2010R.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Shallow landslide is normally occurred between 1 to 2 meter depth and it also normally occurs in highly and completely weathered rocks (Grades IV to VI) or known as residual soil. It can be very active and widespread in occurrence especially during rainy seasons where the soil moisture
is saturated or nearly saturated. Due to spatial variability in rainfall and runoff, soil depths, land
use and topographic characteristics, it is often difficult to predict and thus control the landslides occurrences at the catchment level. In this study an attempt has been made to evaluate the applicability of a slope stability model (SINMAP) to simulate shallow landslide in tropical
environment. The study was carried out in Fraser Hill Catchment, a popular hill resort area in Peninsular Malaysia. Model input parameters include soil bulk density, friction angle, cohesion and hydraulic conductivity were gathered through in situ and laboratory analysis. Landslides locations were recorded using GPS as well as image interpretation of SPOT 5 satellite imagery to
establish landslide source areas inventory. The historical landslide inventory was used to ass the model output performance. To evaluate the accuracy of the landslide susceptibility map produced by the model, two approaches were taken which are Success Rate (SR) and Modified
Success Rate (MSR). Comparison between simulated model output and the historical landslide inventoried map were done through overlay analysis. The results indicated that 68% of the actual landslide inventoried fall within the unstable area predicted by the model. The model also
indicated 70.5% of the catchment area is naturally unstable that most of the upper and middle part of the catchment is susceptible to shallow landslide, particularly areas where slopes are steep and lack of vegetation. When simulated using a 70 mm/hr of precipitation and estimated soil
depth at 2.64 m, 89% of the catchment area is in saturated zone when the event occurred. Prior to that, 87% of the landslide inventory fall into that saturated zone and this indicate that hydrologic factors might triggered the landslide incidence in Fraser Hill. DEM spatial resolution effect on the landslide susceptibility map was assessed by aggregating the DEM into 20, 30, 40, 60 and 80 m resolution sizes. Result shows that using coarser DEM resolution, the accuracy of prediction decreased gradually. However, at 20 and 30 m DEM resolution the result doesn’t significantly
change. Perfect DEM might not be available but choosing the right resolution for specific project is more important. Sensitivity analysis was done to evaluate model input parameters which are soil bulk density, friction angle, cohesion and ratio of transmissivity over recharge (T/R). Results from sensitivity analysis shows that the most significant parameter that gave the highest impact
on total predicted susceptible landslide area is soil cohesion. By manipulating the mean soil cohesion value at ±0.5 Std. Dev (SD), ±1.0 SD and ± 2.0 SD, the changes in predicted unstable zone varies from 0.3% (+2.0SD) to 89.0% km2 (-2.0SD). Friction angle, bulk density and T/R
input come second, third and fourth respectively. The simulated result was considered to be reasonably accurate taking into the consideration of constraint in the accuracy of the DEM constructed from 1: 50,000 topographic map. These findings may suggest that the model can be used as a decision support tool in many environmental impact analysis projects on catchment wide basis in this country. |
|---|