SEISMIC LANDSLIDE HAZARD ANALYSIS: CASE STUDY THE 2009 WEST SUMATRA EARTHQUAKE - RESFIANDHI (NIM: 22413009) , RULY
The earthquake with magnitude of 7,6 shook the West Sumatra and surroundings area on 30 September 2009, at 5:16 pm, with epicenter location at 0,84Ã‚Â°S dan 99,65Ã‚Â°E and depth of 71 km. The earthquake induced landslides with widespread distribution and scale. The researches about earthquake induced landslides has been done, but conventional and non-intact. The estimation of seismic landslide hazard analysis based on the integration of seismic shaking parameters, geotechnical, geologic, and geomorphologic in spatial data, including landslide inventories with deterministic approach. NewmarkÃ‚Â’s displacement method models a landslide as a rigid friction block that resting on an inclined plane at an angle. The block has a known critical acceleration required to overcome shear resistance and initiate sliding, and subjected to a base acceleration representing the earthquake shaking. These data sets include (1) a comprehensive landslide inventories use remote sensing technology, (2) 1:250000 scale geologic maps of the region geological maps scale, (3) data on geologic engineering properties, (4) 30-m digital elevation models (DEM), and (5) data of shear wave velocity of upper 30 m of materials. The research steps: (1) compute the static safety factor by combining use compiled the geologic engineering unit and slope model from DEM, (2) compute the critical acceleration which represents seismic landslide susceptibility, by combining the static safety factor with slope model. (3) estimate Arias intensity as model of shaking intensity limitation from the another research using an empirical equations by combining the Vs30 data, before that, estimate of Vs30 value from another an empirical equation, with data of earthquake sources (location, geometry, and mechanism), (4) estimate Newmark displacements using an empirical equation from another research to combine the critical acceleration with Arias intensity models, and (5) construct a curve to estimate probability of slope failure as a function of Newmark displacement, by comparing the landslide inventories with sequential intervals of Newmark displacement, with the result that plot the proportion of failed slopes in each interval as a function of displacement. Result obtained Newmark displacement model range from 0 to 227,4 cm for all site conditions and from 0 to 257,5 cm for rock site condition. For the calculation of probability of slope failure, Newmark displacement result not correlate well. Probability of slope failure occured on small displacement (0 to 1 cm) with maximum proportion of cells 40,15% for each site conditions, either all site or rock site. This can be explained by the input data to the model with the resulting constrained. The used of digital elevation model of resolution 30 m which is less good, quantity and assignment of geotechnical data obtained, and the use of empirical equations to get the model Arias intensity resulting limitation of models with poor quality. The shear strengt data used in the model reflect peak strength values, added with assessment unit weight in order to producing model statically stable by limiting the value of FS ≥ 1. Assessment of the variability of the data shear strength and unit weight of the resulting landslide proportion (29.2%) of the regions displayed FS ≤ 1 are not included in the analysis that contributes reduction in the number of probability of slope failure. The fact that the landslide occured during rainfall, making assumptions on the value assessment section layer saturated and representative assessment on a regional scale region provide uncertainty of the model. Arias intensity models, obtained by the input value of the constrained empirical equation Vs30 other research studies, so it would provide uncertainty. With the resulting of Arias intensityÃ‚Â’s value small, with a wide range of critical acceleration values, so resulting Newmark displacement will be dominated by a small value (less than 1 cm). With the increase in the quantity and quality of data expected to be useful in a more comprehensive analysis resulting in a measurement model that approaches the performance on the field. Then, taking into account the limitations and simplification, this analysis can be applied as an alternative method for determining the category of regional hazard prediction earthquake induced landslide in the future.