scholarly journals Tsunami Hazard Mitigation at Palabuhanratu, Indonesia

2012 ◽  
Vol 7 (1) ◽  
pp. 19-25 ◽  
Author(s):  
Yuichiro Tanioka ◽  
◽  
Hamzah Latief ◽  
Haris Sunendar ◽  
Aditya Riadi Gusman ◽  
...  
Keyword(s):  
Local Government ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Height Distribution ◽  
Tsunami Height ◽  
Plate Interface ◽  
Tsunami Disaster ◽  
Inundation Area ◽  
Evacuation Routes ◽  
Andaman Earthquake

Several large earthquakes have recently occurred along the Sumatra-Java subduction zone, the 2004 great Sumatra-Andaman earthquake, the 2005 great Nias earthquake, the 2006 West Java tsunami earthquake, the 2007 great Bengkulu earthquake, and the 2010Mentawai tsunami earthquakes. Serious tsunami disasters were caused by the great underthrust earthquakes which ruptured the plate interface near the trench such as the 2004 Sumatra-Andaman, 2006West Java, 2010Mentawai earthquakes. At Palabuhanratu, maximum tsunami height distribution and inundation areas were computed from expected fault models located near the Java trench. The results shows that the most populated areas of Palabuhanratu would be severely damaged by the expected tsunami caused by the fault model of Mw 8.5. After discussing tsunami disaster mitigation measures with the local government, the result of tsunami inundation area in this study were used to decide tsunami evacuation areas and evacuation routes. The local government also installed tsunami evacuation sign boards near the coast.

Tsunami Disaster Mitigation by Integrating Comprehensive Countermeasures in Padang City, Indonesia

2012 ◽  
Vol 7 (1) ◽  
pp. 48-64 ◽  
Author(s):  
Fumihiko Imamura ◽  
◽  
Abdul Muhari ◽  
Erick Mas ◽  
Mulyo Harris Pradono ◽  
...  
Keyword(s):  
Disaster Mitigation ◽  
Frame Structure ◽  
Earthquake Scenario ◽  
Tsunami Disaster ◽  
Inundation Area ◽  
Residential Population ◽  
Vertical Evacuation ◽  
Evacuation Routes ◽  
Tremor Analysis ◽  
The Impact

This paper describes the results of a comprehensive analysis for tsunami disaster mitigation in Padang City, Indonesia. Assessment consists of several steps, starting from the construction of tsunami hazard maps based on the most probable earthquake scenario in the future. Results are then analyzed to determine the impact on residential population along potential evacuation routes. Next, from the standpoint of hazards, we move to the analysis of human’s vulnerability during evacuation. The term “vulnerability” is associated with available evacuation time. Here, we conducted a static evacuation model using the GIS platform and a dynamic approach using multiagent paradigm. Results of evacuationmodeling suggest that some residents may not have enough time to leave the tsunami inundation area before the first wave comes. We therefore propose using relatively high buildings as vertical evacuation sites. One of potential candidates that survived from a devastated earthquake with 7.6 Mw in 2009 is selected to be further analyzed its antiseismic deficiencies based on design ground motion obtained from micro-tremor analysis and synthesized recorded wave in Padang. As a result, even though the building underwent some damage, the frame structure was able to withstand the shaking and keep the building from collapsing.

scholarly journals Disaster Mitigation Study in School Prone to Earthquake and Tsunami Disaster (Case Study Of SMAN 4 Pariaman)

2020 ◽  
Vol 2 (1) ◽  
pp. 47-55
Author(s):  
Suci Maharani ◽  
Erianjoni Erianjoni
Keyword(s):  
Data Processing ◽  
Quantitative Research ◽  
Disaster Mitigation ◽  
Tsunami Disaster ◽  
A Value ◽  
Earthquake Resistant ◽  
Evacuation Routes ◽  
Evacuation Route ◽  
And Training

SMAN 4 Pariaman is located in an area prone to disasters, especially the earthquake and tsunami. SMAN 4 Pariaman is located on the coast of the West Coast of Sumatra, which belongs to the tsunami red zone in Pariaman City. Based on this, all school residents must be prepared to face the disasters that will occur, especially the earthquake and tsunami. This type of research is a combination of research (Mixed Methods). This research is a step of research by combining two pre-existing forms of research namely qualitative research and quantitative research. The results of the study found 5 main priorities, namely 1) Optimization of meeting the basic needs of disaster management with a value of (5,000), 2) Application of evacuation routes and zones of vulnerability to our position or presence (4,556), 3) Socialization through facilities and infrastructure prepared by parties BPBD with grades (4,412), 4) Make maps to the evacuation sites of schools with grades (4,200), 5) Facilitate evacuation route signs such as posters with grades (3,587). The results of the FGD and data processing by data processing with Bayes method obtained 5 main priorities, namely 1) Schools must incorporate knowledge about disasters into the curriculum or subjects with values ​​(5,100), 2) Improvement of earthquake resistant facilities (4,467), 3) Schools must enter disaster mitigation activities into extracurricular values ​​(3,933), 4) Making maps of tsunami evacuation routes to TES with values ​​(3,923), 5) Conduct TRC education and training with a value of 3,857.

scholarly journals Self-similar stochastic slip distributions on a non-planar fault for tsunami scenarios for megathrust earthquakes

2020 ◽  
Author(s):  
Masaru Nakano ◽  
Shane Murphy ◽  
Ryoichiro Agata ◽  
Yasuhiko Igarashi ◽  
Masato Okada ◽  
...  
Keyword(s):  
Arrival Time ◽  
Near Field ◽  
Early Warning Systems ◽  
Disaster Mitigation ◽  
Slip Distribution ◽  
Height Distribution ◽  
Tsunami Height ◽  
Arrival Times ◽  
Megathrust Earthquakes ◽  
Scenario Earthquakes

Abstract Megathrust earthquakes that occur repeatedly along the plate interface of subduction zones can cause severe damage due to strong ground motion and the destructive tsunamis they can generate. We developed a set of scenario earthquakes to evaluate tsunami hazards and tsunami early warning systems for such devastating earthquakes. Although it is known that the slip distribution on a fault strongly affects the tsunami height distribution in near-field coastal areas, the slip distribution of future earthquakes cannot be exactly predicted. One way to resolve this difficulty is to create a set of scenario earthquakes in which a set of heterogeneous slip distributions on the source fault is stochastically generated based on a given slip probability density function (SPDF). The slip distributions generated in this manner differ from event to event, but their average over a large ensemble of models converges to a predefined SPDF resembling the long-term average of ruptures on the target fault zone. We created a set of SPDF-based scenario earthquakes for an expected future M w 8.2 Tonankai earthquake in the eastern half of the Nankai trough, off southwest Japan, and computed the ensuing tsunamis. We found that the estimated peak coastal amplitudes among the ensemble of tsunamis along the near-field coast differed by factors of 3 to 9 and the earliest and latest arrivals at each observation site differed by 400 to 700 s. The variations in both peak tsunami amplitude and arrival time at each site were well approximated by a Gaussian distribution. For cases in which the slip distribution is unknown, the average and standard deviation of these scenario datasets can provide first approximations of forecast tsunami height and arrival time and their uncertainties, respectively. At most coastal observation sites, tsunamis modelled similarly but using a uniform slip distribution underpredicted tsunami amplitudes but gave earlier arrival times than those modeled with a heterogeneous slip distribution. Use of these earlier arrival times may be useful for providing conservative early warnings of tsunami arrivals. Therefore, tsunami computations for both heterogeneous and uniform slip distributions are important for tsunami disaster mitigation.

scholarly journals Numerical and Statistical Analyses of Tsunami Heights with the L-Moments Method

2019 ◽  
Vol 9 (24) ◽  
pp. 5517
Author(s):  
Cheol Kang ◽  
Koo-Yong Park ◽  
Yong-Sik Cho
Keyword(s):  
Normal Distribution ◽  
Generalized Pareto Distribution ◽  
Height Distribution ◽  
Prevention Measures ◽  
Tsunami Height ◽  
Tsunami Disaster ◽  
L Moments ◽  
Log Normal ◽  
Log Normal Distribution ◽  
Best Fit

As devastating and unpredictable tsunamis generated by underwater earthquakes are occurring more frequently, the need for tsunami disaster prevention measures is rapidly increasing. In this study, tsunami heights were estimated, and the best-fit distribution was examined through a combination of numerical analyses and statistical methods. A numerical model was employed to estimate the tsunami heights, and the parameters were estimated using the method of L-moments applied to the estimated tsunami heights. The best-fit distribution was determined by applying the estimated parameters to the L-moment ratio diagram. The study areas were the Imwon Port and the Sadong Port located in the eastern part of the Korean Peninsula. The tsunami height distribution was represented by a log-normal distribution for the Imwon Port, whereas the distribution was represented by a generalized Pareto distribution for the Sadong Port. The study indicates that the distribution most commonly suggested by previous studies, i.e., the log-normal distribution, is not always accurate. Therefore, when performing statistical analysis on tsunami heights, the assumption of a log-normal distribution should be considered carefully.

scholarly journals Self-similar stochastic slip distributions on a non-planar fault for tsunami scenarios for megathrust earthquakes

2020 ◽  
Author(s):  
Masaru Nakano ◽  
Shane Murphy ◽  
Ryoichiro Agata ◽  
Yasuhiko Igarashi ◽  
Masato Okada ◽  
...  
Keyword(s):  
Arrival Time ◽  
Near Field ◽  
Early Warning Systems ◽  
Disaster Mitigation ◽  
Slip Distribution ◽  
Height Distribution ◽  
Tsunami Height ◽  
Arrival Times ◽  
Megathrust Earthquakes ◽  
Scenario Earthquakes

Abstract Megathrust earthquakes that occur repeatedly along the plate interface of subduction zones can cause severe damage due to strong ground motion and the destructive tsunamis they can generate. We developed a set of scenario earthquakes to evaluate tsunami hazards and tsunami early warning systems for such devastating earthquakes. Although it is known that the slip distribution on a fault strongly affects the tsunami height distribution in near-field coastal areas, the slip distribution of future earthquakes cannot be exactly predicted. One way to resolve this difficulty is to create a set of scenario earthquakes in which a set of heterogeneous slip distributions on the source fault is stochastically generated based on a given slip probability density function (SPDF). The slip distributions generated in this manner differ from event to event, but their average over a large ensemble of models converges to a predefined SPDF resembling the long-term average of ruptures on the target fault zone. We created a set of SPDF-based scenario earthquakes for an expected future Mw 8.2 Tonankai earthquake in the eastern half of the Nankai trough, off southwest Japan, and computed the ensuing tsunamis. We found that the estimated peak coastal amplitudes among the ensemble of tsunamis along the near-field coast differed by factors of 3 to 9 and the earliest and latest arrivals at each observation site differed by 400 to 700 s. The variations in both peak tsunami amplitude and arrival time at each site were well approximated by a Gaussian distribution. For cases in which the slip distribution is unknown, the average and standard deviation of these scenario datasets can provide first approximations of forecast tsunami height and arrival time and their uncertainties, respectively. At most coastal observation sites, tsunamis modelled similarly but using a uniform slip distribution underpredicted tsunami amplitudes but gave earlier arrival times than those modeled with a heterogeneous slip distribution. Use of these earlier arrival times may be useful for providing conservative early warnings of tsunami arrivals. Therefore, tsunami computations for both heterogeneous and uniform slip distributions are important for tsunami disaster mitigation.

Special Issue on Disaster and Big Data Part 3

2018 ◽  
Vol 13 (2) ◽  
pp. 233-233
Author(s):  
Shunichi Koshimura
Keyword(s):  
Big Data ◽  
Natural Disasters ◽  
New Technologies ◽  
Social Systems ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Editorial Committee ◽  
Tsunami Disaster ◽  
New Findings ◽  
Working Together

The 2011 Great East Japan Earthquake and Tsunami Disaster left behind many lessons to learn, and there have since been many new findings and insights that have led to suggestions made and implemented in disaster observation, sensing, simulation, and damage determination. The challenges for mitigating the damage from future catastrophic natural disasters, such as the Tokyo Metropolitan Earthquake or the Nankai Trough Earthquake and Tsunami, are in how we share our visions of the possible impacts, how we prepare to mitigate the losses and damages, and how we enhance society’s disaster resilience. The huge amount of information obtained, called “disaster big data,” is related to the dynamic movement, as IoT, of a large number people, vehicles, and goods from inside and outside the affected areas. This has dramatically facilitated our understanding of how our society has responded to unprecedented catastrophes. The key question is how to utilize big data in establishing social systems that respond promptly, sensibly, and effectively to natural disasters, and in withstanding adversity with resilience. Researchers with various types of expertise are working together under a collaborative project called JST CREST “Establishing the advanced disaster reduction management system by fusion of real-time disaster simulation and big data assimilation.” The project aims to identify possible earthquake and tsunami disaster scenarios that occur and progress in a chained or compound manner and to create new technologies to lead responses and disaster mitigation measures to help society to recover from disasters. As we have published two previous special issues entitled “Disaster and Big Data” since 2016, this issue is our third. Included are 14 papers that aim to share the recent progress of the project as the sequel to Part 2, published in March 2017. As one of the guest editors of this issue, I would like to express our deep gratitude for the insightful comments and suggestions made by the reviewers and the members of the editorial committee. I do hope that this work will be utilized in disaster management efforts to mitigate the damage and losses in future catastrophic disasters.

scholarly journals PEMANFAATAN ANALISIS SPASIAL UNTUK PEMETAAN RISIKO BENCANA ALAM TSUNAMI MENGGUNAKAN PENGOLAHAN DATA SPASIAL SISTEM INFORMASI GEOGRAFIS

2020 ◽  
Vol 7 (2) ◽  
pp. 210
Author(s):  
Deny Budiyanto ◽  
Trisya Septiana ◽  
Mona Arif Muda
Keyword(s):  
Information Systems ◽  
Disaster Mitigation ◽  
Risk Level ◽  
Dense Population ◽  
Tsunami Disaster ◽  
Tsunami Risk ◽  
The Indian Ocean ◽  
Property Losses ◽  
Evacuation Routes ◽  
Made In

<p><em>Lampung Province, which is located in the southernmost region of the island of Sumatra, is also a disaster-prone region, such as the tsunami and eruption of Mount Anak Krakatau that occurred in 2018 which resulted in casualties and property losses, because Lampung Province is an area with a dense population. One of the disasters that threatened the Lampung province was the Tsunami. The threat occurs because Lampung Province is located in an area bordering the Sunda Strait, and the Indian Ocean so there is a potential for disaster in this region. The purpose of this study is to carry out a part of disaster mitigation namely disaster risk analysis using Geographic Information Systems (GIS). The mapping of tsunami risk level was made in the form of tsunami disaster-prone zones and evacuation routes, and this mapping has been carried out in the coastal area of South Lampung, Lampung Province.</em></p><p><strong><em>Keywords</em></strong><em> : Information Systems, GIS, Sumatra, South Lampung</em><strong><em> </em></strong></p><p><em>Provinsi Lampung yang terletak diwilayah paling selatan pulau Sumatera juga  merupakan daerah yang rentan bencana, seperti kejadian tsunami dan erupsi gunung anak Krakatau yang terjadi pada 2018 yang mengakibatkan korban jiwa dan kerugian harta benda, Karena Provinsi Lampung adalah wilayah dengan jumlah penduduk yang padat. Salah satu bencana yang mengancam provinsi lampung adalah Tsunami. Ancaman terjadi karena Provinsi Lampung terletak di wilayah yang berbatasan dengan Selat Sunda, dan Samudra Hindia sehingga ada potensi bencana di wilayah ini. Tujuan dari penelitian ini adalah melakukan bagian mitigasi bencana yaitu analisis resiko bencana dengan menggunakan Sistem Informasi Geografis (SIG). Pemetaan tingkat resiko tsunami ini dibuat dalam bentuk zona-zona rawan bencana tsunami serta jalur evakuasi, dan pemetaan ini telah dilakukan pada daerah pesisir Lampung Selatan, Provinsi Lampung.</em></p><p><strong><em>Kata kunci</em></strong><em> : Sistem Informasi, SIG, Sumatera, Lampung Selatan</em></p>

scholarly journals Mapping of Tsunami disaster evacuation pathways based on Tsunami altitude scenario using Network Analyst Method (case study: Palu City, Central Sulawesi)

2020 ◽  
Vol 4 (1) ◽  
pp. 304-311
Author(s):  
I Made Edy Kusuma Putra ◽  
Hanna Prillysca Chernovita
Keyword(s):  
Travel Time ◽  
Regional Analysis ◽  
Disaster Mitigation ◽  
Tsunami Disaster ◽  
Cost Distance ◽  
Network Analyst ◽  
Evacuation Routes ◽  
Evacuation Route ◽  
Central Sulawesi

Central Sulawesi's Palu city is one of the regions in Indonesia that is vulnerable to tsunami disasters. A tsunami disaster is a disaster that can cause many victims of both casualties and materials. One of the disaster mitigation to reduce the victim's fall is by evacuating the community to a safer place, to evacuate the population required evacuation routes that can direct people to evacuation sites. The purpose of this research is to make a tsunami runoff using cost distance and to make tsunami evacuation and use a Network analyst on Arcgis 10.4 software. The most affected regional analysis is the Northern Palu sub-district with a total area of 8.643528 km2, and there are 93 evacuation routes with 92 evacuation points. The longest evacuation route is 4,297 M with a travel time of 27.6 minutes with running and the shortest evacuation route of 96 m with a travel time of 0.6 minutes by running.

scholarly journals Damage in Ports due to the 2011 off the Pacific Coast of Tohoku Earthquake Tsunami

2013 ◽  
Vol 8 (4) ◽  
pp. 594-604 ◽  
Author(s):  
Takashi Tomita ◽  
◽  
Taro Arikawa ◽  
Tadashi Asai ◽  
Keyword(s):  
Pacific Coast ◽  
Tohoku Earthquake ◽  
Disaster Mitigation ◽  
Mitigation Measures ◽  
Worst Case ◽  
Tsunami Disaster ◽  
Cargo Handling ◽  
Port Facilities ◽  
The Pacific ◽  
Industrial Operations

The tsunami following the 2011 off the Pacific Coast of Tohoku Earthquake devastated ports in the Tohoku and Kanto regions of Japan. Even Iwate Prefecture in Tohoku, which had experienced many tsunami disasters and prepared tsunami disaster mitigation measures, incurred great devastation because the tsunami was both higher than any historically recorded tsunamis and than any estimated tsunamis for disaster management. The tsunami-induced inundation destroyed many of wooden houses widely found in the area. Many ships and boats at sea were displaced by the tsunami, with some vessels colliding with others and port facilities such as cargo handling equipment and quay walls being damaged. Much debris was generated and disrupted rescue and restoration activities in the disaster aftermath. Port devastation caused stagnation in logistics and industrial operations, negatively impacting on residents’ lives and industrial activities in the disaster aftermath. There was a positive lesson that breakwaters and seawalls damaged by the tsunami reduced tsunami impacts behind them. Ports should be robust and resilient against possible tsunami hazards, considering measures for worst-case earthquake and tsunami scenarios.

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