STUDY OF TSUNAMI INUNDATION ON THE PANDEGLANG COASTAL AREA DUE TO THE 2018 ANAK KRAKATAU SUBAERIAL LANDSLIDE
The Tsunami Occurred in the Sunda Strait on September 22, 2018, Caused by the Anak Krakatau Volcanic Landslide. This event resulted in a significant loss of life, especially in the Pandeglang Regency. Therefore, it is necessary to conduct a tsunami reconstruction to analyze the tsunami risk, whic...
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Format: | Theses |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/79493 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | The Tsunami Occurred in the Sunda Strait on September 22, 2018, Caused by the
Anak Krakatau Volcanic Landslide. This event resulted in a significant loss of life,
especially in the Pandeglang Regency. Therefore, it is necessary to conduct a
tsunami reconstruction to analyze the tsunami risk, which can be used as a basis
for tsunami hazard mitigation efforts. This tsunami reconstruction is carried out
using numerical simulation models using the COMCOT software (Cornell Multigrid
Coupled Tsunami Model). The numerical model uses BATNAS data with a
resolution of 180.22 m, and for topographic data, it utilizes DEMNAS data with a
resolution of 8.33 m. Spatial variation data for the Manning coefficient is sourced
from RBI (Indonesian Earth Shape) data, converted into Manning coefficients using
the Manning coefficient table from Wang et al (2011). The simulation includes 7
tsunami model scenarios with varying landslide parameters and 2 inundation
model scenarios with different Manning values. The parameters used for tsunami
model scenarios are landslide volume, landslide angle, and landslide duration.
Different Manning values are considered for inundation model scenarios. The
model results are validated using field survey data, including inundation height and
water level elevation data collected at 4 BIG station locations. Among the 7 tsunami
model scenarios, LS07 with a volume of 0.326 km3, a landslide angle of 8.20, and a
landslide duration of 420 seconds is identified as the best scenario with a model
accuracy of 97.228%. The simulation results match the detected tsunami arrival
time at the BIG water level elevation stations. This study also investigates the model
sensitivity to parameters such as landslide mass length, Manning coefficient values,
landslide start-to-end distance, and landslide angle. A shorter landslide mass
length of 300 m results in higher tsunami heights, with a maximum average tsunami
height difference of 0.18 m at each station. A Manning value of 0.013 produces
higher tsunami heights compared to a Manning value of 0.026, with a maximum
average tsunami height difference of 0.20 m at each station. A longer landslide
distance of 485 m results in higher tsunami heights, with a maximum average
tsunami height difference of 0.19 m at each station. There is no significant
difference observed for a landslide angle difference of 2.30. At the 30-minute mark
of the tsunami simulation, the tsunami wave pattern in the Sunda Strait becomes
complex, with waves propagating in various directions due to interactions with
bathymetry, coastlines, and other islands. This complexity increases over time due
to further wave reflections within the strait. The area with the highest tsunami wave
is Tanjung Lesung, reaching approximately 7 m in height, while Carita and Labuan
experience tsunami wave heights of 5 m to 6 m. Panimbang has a tsunami wave
height of around 2 m. Among the 2 inundation model scenarios, I01 with spatially
varying Manning values is identified as the best model with a model accuracy of
95.39%. From the tsunami risk analysis, it is found that Tanjung Lesung is the most
extensively affected area by the tsunami disaster, with a total affected area of 3.225
km2, and the highest risk area (level) of 0.494 km2. For Carita, Labuan, and
Panimbang, the risk area level 1 covers an area of 0.176 km2, 0.093 km2, and 0.017
km2, respectively. The total submerged area for Carita, Labuan, and Panimbang is
1.969 km2, 2.154 km2, and 1.448 km2, respectively.
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