Numerical simulation of the impacts of reflected tsunami waves on Pulo Raya Island during the 2004 Indian Ocean tsunami

2016 ◽  
Vol 20 (6) ◽  
pp. 489-499 ◽  
Author(s):  
Teuku Muhammad Rasyif ◽  
Syamsidik ◽  
Musa Al’ala ◽  
Mirza Fahmi
Keyword(s):  
Numerical Simulation ◽  
Indian Ocean ◽  
Indian Ocean Tsunami ◽  
2004 Indian Ocean Tsunami ◽  
Tsunami Waves

Numerical Simulation of the December 26, 2004: Indian Ocean Tsunami

2008 ◽  
pp. 59-68 ◽  
Author(s):  
J. Asavanant ◽  
M. Ioualalen ◽  
N. Kaewbanjak ◽  
S. T. Grilli ◽  
P. Watts ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Indian Ocean ◽  
Indian Ocean Tsunami ◽  
2004 Indian Ocean Tsunami

Numerical Simulations of Impacts of the 2004 Indian Ocean Tsunami on Coastal Morphological Changes Around the Ulee Lheue Bay of Aceh, Indonesia

2017 ◽  
Vol 11 (01) ◽  
pp. 1740005 ◽  
Author(s):  
Syamsidik ◽  
Tursina ◽  
Asrita Meutia ◽  
Musa Al’ala ◽  
Mirza Fahmi ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Morphological Changes ◽  
Indian Ocean Tsunami ◽  
Small Island ◽  
Wave Forces ◽  
2004 Indian Ocean Tsunami ◽  
Tsunami Waves ◽  
Near Shore ◽  
The Indian Ocean ◽  
Sea Area

Wave forces during the 2004 Indian Ocean tsunami have caused morphological deformations of some coastal areas in Aceh, Indonesia. The sediment transport process during the tsunami wave propagation around near shore areas is a challenging numerical problem. To observe the coastal morphological changes after the Indian Ocean tsunami, this study numerically simulates the coastline changes, sedimentation and erosion areas, and seabed profiles changes around the Ulee Lheue Bay of Aceh, which was severely damaged by the tsunami. Two-dimensional horizontal areas were simulated by Cornell Multi-grid Coupled Tsunami (COMCOT) and Delft3D. Data of the nearshore area were collected from previous measurements acquired by the Indonesian Navy. According to the results, sediment in the sea area was deposited approximately 2.5[Formula: see text]km from the initial coastline, at the northern part of one small island occupying the Ulee Lheue Bay. This island reduced the energy of the tsunami waves during the backwash process, dumping a significant amount of eroded sediment near the coastline area.

Medieval forewarning of the 2004 Indian Ocean tsunami in Thailand

Nature ◽  
2008 ◽  
Vol 455 (7217) ◽  
pp. 1228-1231 ◽  
Author(s):  
Kruawun Jankaew ◽  
Brian F. Atwater ◽  
Yuki Sawai ◽  
Montri Choowong ◽  
Thasinee Charoentitirat ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Tsunami ◽  
2004 Indian Ocean Tsunami

A snapshot of the 2004 Indian Ocean tsunami: societal impacts and consequences

2006 ◽  
Vol 15 (1) ◽  
pp. 163-177 ◽  
Author(s):  
Havidan Rodriguez ◽  
Tricia Wachtendorf ◽  
James Kendra ◽  
Joseph Trainor
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Tsunami ◽  
2004 Indian Ocean Tsunami ◽  
Societal Impacts

scholarly journals Developing tsunami fragility curves based on the satellite remote sensing and the numerical modeling of the 2004 Indian Ocean tsunami in Thailand

2011 ◽  
Vol 11 (1) ◽  
pp. 173-189 ◽  
Author(s):  
A. Suppasri ◽  
S. Koshimura ◽  
F. Imamura
Keyword(s):  
Indian Ocean ◽  
Building Materials ◽  
Fragility Curves ◽  
Distribution Functions ◽  
Least Square ◽  
Indian Ocean Tsunami ◽  
2004 Indian Ocean Tsunami ◽  
Inundation Depth ◽  
High Resolution Satellite Images ◽  
Tsunami Fragility

Abstract. The 2004 Indian Ocean tsunami damaged and destroyed numerous buildings and houses in Thailand. Estimation of tsunami impact to buildings from this event and evaluation of the potential risks are important but still in progress. The tsunami fragility curve is a function used to estimate the structural fragility against tsunami hazards. This study was undertaken to develop fragility curves using visual inspection of high-resolution satellite images (IKONOS) taken before and after tsunami events to classify whether the buildings were destroyed or not based on the remaining roof. Then, a tsunami inundation model is created to reconstruct the tsunami features such as inundation depth, current velocity, and hydrodynamic force of the event. It is assumed that the fragility curves are expressed as normal or lognormal distribution functions and the estimation of the median and log-standard deviation is performed using least square fitting. From the results, the developed fragility curves for different types of building materials (mixed type, reinforced concrete and wood) show consistent performance in damage probability and when compared to the existing curves for other locations.

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