Using Hypothetical Tsunami Scenarios to Analyze Tsunami Inundation Characteristics in the Coastal City of Ulsan, South Korea

2020 ◽  
Vol 95 (sp1) ◽  
pp. 1140
Author(s):  
Dong-Seag Kim ◽  
Yeong-Han Jeong ◽  
Hwa-Young Lee ◽  
Dong-Hwan Kim ◽  
Sung-Jin Hong
Keyword(s):  
South Korea ◽  
Tsunami Inundation ◽  
Coastal City ◽  
Tsunami Scenarios

scholarly journals Probabilistic tsunami inundation assessment of Kuroshio Town,Kochi Prefecture, Japan considering the Nankai-Tonankai megathrust rupture scenarios

2020 ◽  
Author(s):  
Katsuichiro Goda ◽  
Tomohiro Yasuda ◽  
Nobuhito Mori ◽  
Ario Muhammad ◽  
Raffaele De Risi ◽  
...  
Keyword(s):  
Tsunami Hazard ◽  
Grid Data ◽  
Seismic Region ◽  
Tsunami Inundation ◽  
Coastal Defense ◽  
Tsunami Risk ◽  
Hazard Assessments ◽  
Tsunami Scenarios ◽  
Management Council ◽  
Kochi Prefecture

Abstract. The Nankai-Tonankai megathrust earthquake and tsunami pose significant risks to coastal communities in western and central Japan. Historically, this seismic region hosted many major earthquakes, and the current national tsunami hazard assessments in Japan consider megathrust events having moment magnitudes between 9.0 and 9.1. In responding to the lack of rigorous uncertainty analysis, this study presents an extensive tsunami hazard assessment for the Nankai-Tonankai Trough events, focusing upon the southwestern Pacific region of Japan. A set of 1,000 kinematic earthquake rupture models is generated via stochastic source modelling approaches, and Monte Carlo tsunami simulations are carried out by considering high-resolution grid data of 10-m and coastal defense structures. Significant advantages of the stochastic tsunami simulation methods include the enhanced capabilities to quantify the uncertainty associated with tsunami hazard assessments and to effectively visualize the results in an integrated manner. The results from the stochastic tsunami simulations can inform regional and local tsunami risk reduction actions in light of inevitable uncertainty associated with such probabilistic tsunami hazard assessments, and complement conventional deterministic tsunami scenarios and their hazard predictions, such as those developed by the Central Disaster Management Council of the Japanese Cabinet Office.

scholarly journals Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Fumiyasu Makinoshima ◽  
Yusuke Oishi ◽  
Takashi Yamazaki ◽  
Takashi Furumura ◽  
Fumihiko Imamura
Keyword(s):  
Neural Networks ◽  
Convolutional Neural Networks ◽  
Observation Data ◽  
Time Data ◽  
Tsunami Inundation ◽  
2011 Tohoku Tsunami ◽  
Actual Observation ◽  
Tsunami Forecasting ◽  
Average Maximum ◽  
Tsunami Scenarios

AbstractRapid and accurate hazard forecasting is important for prompt evacuations and reducing casualties during natural disasters. In the decade since the 2011 Tohoku tsunami, various tsunami forecasting methods using real-time data have been proposed. However, rapid and accurate tsunami inundation forecasting in coastal areas remains challenging. Here, we propose a tsunami forecasting approach using convolutional neural networks (CNNs) for early warning. Numerical tsunami forecasting experiments for Tohoku demonstrated excellent performance with average maximum tsunami amplitude and tsunami arrival time forecasting errors of ~0.4 m and ~48 s, respectively, for 1,000 unknown synthetic tsunami scenarios. Our forecasting approach required only 0.004 s on average using a single CPU node. Moreover, the CNN trained on only synthetic tsunami scenarios provided reasonable inundation forecasts using actual observation data from the 2011 event, even with noisy inputs. These results verify the feasibility of AI-enabled tsunami forecasting for providing rapid and accurate early warnings.

Development and Utilization of Real-Time Tsunami Inundation Forecast System Using S-net Data

2019 ◽  
Vol 14 (2) ◽  
pp. 212-224 ◽  
Author(s):  
Shin Aoi ◽  
Wataru Suzuki ◽  
Naotaka Yamamoto Chikasada ◽  
Takayuki Miyoshi ◽  
Taro Arikawa ◽  
...  
Keyword(s):  
Disaster Response ◽  
Pressure Data ◽  
Forecast System ◽  
Tsunami Forecast ◽  
Index Method ◽  
Tsunami Inundation ◽  
Target Region ◽  
Multi Index ◽  
Tsunami Disaster ◽  
Tsunami Scenarios

It is important to advance preparation for a tsunami disaster, one of the great concerns in Japan. Forecasting tsunami inundation is one such solution, which contributes to perceiving the danger of the tsunami, as the inundation is directly linked with the damage. Therefore, we developed a new real-time tsunami forecast system, aimed at rapidly and accurately forecasting tsunami inundation on land, based on offshore tsunami data observed by the seafloor observation network along the Japan Trench, S-net. The developed system takes a database approach. A database called a tsunami scenario bank was constructed by assuming all the possible tsunami sources affecting the target region and simulating offshore pressure data, coastal tsunami heights, and tsunami inundation. The forecast system searches for suitable tsunami scenarios whose offshore pressure data explain the observed data, based on the multi-index method. The multi-index method can evaluate the resemblance of offshore pressure data by using three indices, which are sensitive to different aspects of the pressure change distribution. When tsunami scenarios meet the criteria of the multi-index method, the system provides forecast information generated from coastal tsunami heights and tsunami inundation of the selected scenarios. A prototype system was constructed for the Pacific coastal region of Chiba prefecture as a target region and has been updated through a test operation. We also investigated the comprehensible visualization and effective disaster response using tsunami forecast information. Through workshops and tabletop exercises with local government officers using the forecast system, timelines and local disaster management plans for tsunamis were tested and revised. This led to the establishment of a standard operating procedure for tsunami disaster response through the use of tsunami observation and forecast information.

scholarly journals Physical Modeling and Numerical Analysis of Tsunami Inundation in a Coastal City

2019 ◽  
Vol 5 ◽  
Author(s):  
Adi Prasetyo ◽  
Tomohiro Yasuda ◽  
Takuya Miyashita ◽  
Nobuhito Mori
Keyword(s):  
Numerical Analysis ◽  
Physical Modeling ◽  
Tsunami Inundation ◽  
Coastal City

scholarly journals TSUNAMI INUNDATION EXPERIMENT USING COASTAL CITY MODEL

2016 ◽  
Vol 72 (2) ◽  
pp. I_385-I_390 ◽  
Author(s):  
Tomohiro YASUDA ◽  
Taiki MIYAUE ◽  
Adi PRASETYO ◽  
Masato KAMO ◽  
Nobuhito MORI ◽  
...  
Keyword(s):  
Tsunami Inundation ◽  
Coastal City ◽  
City Model

scholarly journals Uncertainty quantification of tsunami inundation in Kuroshio, Kochi Prefecture, Japan, using the Nankai–Tonankai megathrust rupture scenarios

2020 ◽  
Vol 20 (11) ◽  
pp. 3039-3056
Author(s):  
Katsuichiro Goda ◽  
Tomohiro Yasuda ◽  
Nobuhito Mori ◽  
Ario Muhammad ◽  
Raffaele De Risi ◽  
...  
Keyword(s):  
Tsunami Hazard ◽  
Grid Data ◽  
Seismic Region ◽  
Tsunami Inundation ◽  
Megathrust Earthquakes ◽  
Tsunami Risk ◽  
Hazard Assessments ◽  
Tsunami Scenarios ◽  
Management Council ◽  
Kochi Prefecture

Abstract. Nankai–Tonankai megathrust earthquakes and tsunamis pose significant risks to coastal communities in western and central Japan. Historically, this seismic region hosted many major earthquakes, and the current national tsunami hazard assessments in Japan consider megathrust events as those having moment magnitudes between 9.0 and 9.1. In responding to the lack of rigorous uncertainty analysis, this study presents an extensive tsunami hazard assessment for the Nankai–Tonankai Trough events, focusing on the southwestern Pacific region of Japan. A set of 1000 kinematic earthquake rupture models is generated via stochastic source modelling approaches, and Monte Carlo tsunami simulations are carried out by considering high-resolution grid data of 10 m and coastal defence structures. Significant advantages of the stochastic tsunami simulation methods include the enhanced capabilities to quantify the uncertainty associated with tsunami hazard assessments and to effectively visualize the results in an integrated manner. The results from the stochastic tsunami simulations can inform regional and local tsunami risk reduction actions in light of inevitable uncertainty associated with such tsunami hazard assessments and complement conventional deterministic tsunami scenarios and their hazard predictions, such as those developed by the Central Disaster Management Council of the Japanese Cabinet Office.

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