scholarly journals Assessment Of Tsunami Hazard In Sabah – Level Of Threat, Constraints And Future Work

2020 ◽  
Vol 70 (1) ◽  
pp. 1-15
Author(s):  
Felix Tongkul ◽  
◽  
Rodeano Roslee ◽  
Ahmad Khairut Termizi Mohd Daud

The coastal areas of Sabah are exposed to far-field earthquake-induced tsunamis that could be generated along the trenches of Manila, Negros, Sulu, Cotabato, Sangihe and North Sulawesi. Tsunami simulation models from these trenches indicated that tsunami waves can reach the coast of Sabah between 40 and 120 minutes with tsunami wave heights reaching up to 3 m near the coast. The level of tsunami threat is high in southeast Sabah due to its narrow continental shelf and proximity to tsunami source in the North Sulawesi Trench. The level of tsunami threat is moderate in north and east Sabah due to their proximity to tsunami source in the Sulu Trench. The level of tsunami threat is low in west Sabah due to its distant location to tsunami source from the Manila Trench. While tsunamis cannot be prevented, its impact on human life and property can be reduced through proper assessment of its threat using tsunami simulation models. Unfortunately, constraints remain in producing a reliable tsunami inundation models due to the lack of high-resolution topography and bathymetry data in Sabah and surrounding seas. It would be helpful if such data can be acquired by the relevant government agencies, at least first, in high threat-level areas, such as Tawau and Semporna districts. In order to properly plan mitigation measures tsunami risk mapping should be intensified in high threat-level areas. The locations of settlements (including water villages), population concentrations, types of buildings and houses, road system, drainage system, harbours, jetties and vegetations (including mangroves) need to be mapped in great detail. Based on the detailed tsunami risk map, targeted vulnerable communities could be given continuous and intensive education and awareness on basic tsunami science and tsunami hazard preparedness.

2015 ◽  
Vol 2 (3) ◽  
Author(s):  
Tatsuo Ohmachi ◽  
Shusaku Inoue ◽  
Tetsuji Imai

The 2003 Tokachi-oki earthquake (MJ 8.0) occurred off the southeastern coast of Tokachi, Japan, and generated a large tsunami which arrived at Tokachi Harbor at 04:56 with a wave height of 4.3 m. Japan Marine Science and Technology Center (JAMSTEC) recovered records of water pressure and sea-bed acceleration at the bottom of the tsunami source region. These records are first introduced with some findings from Fourier analysis and band-pass filter analysis. Water pressure disturbance lasted for over 30 minutes and the duration was longer than those of accelerations. Predominant periods of the pressure looked like those excited by Rayleigh waves. Next, numerical simulation was conducted using the dynamic tsunami simulation technique able to represent generation and propagation of Rayleigh wave and tsunami, with a satisfactory result showing validity and usefulness of this technique. Keywords: Earthquake, Rayleigh wave, tsunami, near-field


2021 ◽  
Author(s):  
Jeffrey Katan ◽  
Liliana Perez

Abstract. Wildfires are a complex phenomenon emerging from interactions between air, heat, and vegetation, and while they are an important component of many ecosystems’ dynamics, they pose great danger to those ecosystems, and human life and property. Wildfire simulation models are an important research tool that help further our understanding of fire behaviour and can allow experimentation without recourse to live fires. Current fire simulation models fit into two general categories: empirical models and physical models. We present a new modelling approach that uses agent-based modelling to combine the complexity found in physical models with the ease of computation of empirical models. Our model represents the fire front as a set of moving agents that respond to, and interact with, vegetation, wind, and terrain. We calibrate the model using two simulated fires and one real fire, and validate the model against another real fire and the interim behaviour of the real calibration fire. Our model successfully replicates these fires, with a Figure of Merit on par with simulations by the Prometheus simulation model. Our model is a stepping-stone in using agent-based modelling for fire behaviour simulation, as we demonstrate the ability of agent-based modelling to replicate fire behaviour through emergence alone.


Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 161
Author(s):  
Tawatchai Tingsanchali ◽  
Thanasit Promping

Estimating flood hazard, vulnerability, and flood risk at the household level in the past did not fully consider all relevant parameters. The main objective of this study is to improve this drawback by developing a new comprehensive and systematic methodology considering all relevant parameters and their weighting factors. This new methodology is applied to a case study of flood inundation in a municipal area of Nan City in the Upper Nan River Basin in Thailand. Field and questionnaire surveys were carried out to collect pertinent data for input into the new methodology for estimating flood hazard, vulnerability, and risk. Designed floods for various return periods were predicted using flood simulation models for assessing flood risk. The flood risk maps constructed for the return periods of 10–500 years show a substantial increase in flood risk with the return periods. The results are consistent with past flood damages, which were significant near and along the riverbanks where ground elevation is low, population density is high, and the number of household properties are high. In conclusion, this new comprehensive methodology yielded realistic results and can be used further to assess the effectiveness of various proposed flood mitigation measures.


2020 ◽  
Vol 15 (2) ◽  
pp. 12-27
Author(s):  
RIzki Kurnia Tohir ◽  
Fadlan Pramatana

Lampung Province has the threat of Forest and Land Fires (FLF) based on incident reports. There is a lack of data on how the threat level of the forest and land fires, so this research is important to do. This study aims to analyze the track record and potential for FLF incidents, to analyze the characteristics and level of the FLF threat. Threat mapping is done by weighting and scoring 11 variables. These variables are divided into natural factors and human factors. The results showed that the equation that gives a weighting of 90% to natural factors. The characteristics of FLF show that natural factors are sensitive factor for the occurrence of FLF in Lampung Province. Mapping of threats shows that the area of ​​low threat class is 244,811.96 ha (8%), medium threat class is 1207,716.15 ha (40%) and high threat class is 1,591,767.42 ha (52%). Three districts had the highest level of threat class, namely Way Kanan, Central Lampung, and East Lampung Districts. The results of the validation of field conditions are indicated by the results of this threat mapping, so that the results of this study can be used as material for consideration by policy makers.


2021 ◽  
Vol 331 ◽  
pp. 04006
Author(s):  
Leli Honesti ◽  
Meli Muchlian

A tsunami hazard is an adverse event that causes damage to properties and loss of life. The problem in assessing a tsunami risk zone for a small area is significant, as available tsunami inundation zone data does not give detailed information for tsunami inundation and run-up in every nested grid. Hence, this study aims to establish a tsunami risk map in the Pasir Jambak sub-district, Padang, Indonesia. The map was carried out in every nested grid point of the area and on a large scale (1:5,000). The TUNAMI N3 program was used for the simulation of the tsunami inundation. A tsunami assessment was made through simulations in nine scenarios of fault parameter data for Sipora block earthquakes. The result of the study provides a tsunami inundation map. Furthermore, this tsunami inundation map can be used for communities, local authorities, government, and others for many studies, and decision-makers can come up with mitigation plans for a small study area.


2019 ◽  
Author(s):  
Andrea Cerase ◽  
Massimo Crescimbene ◽  
Federica La Longa ◽  
Alessandro Amato

Abstract. According to a deep-rooted conviction, the occurrence of a tsunami in the Mediterranean Sea would be very rare. However, in addition to the catastrophic event of Messina and Reggio Calabria (1908) and the saved danger for the tsunami occurred on Cycladic sea in 1956, 44 events are reported in the Mediterranean Sea between 1951 and 2003, and other smaller tsunamis occurred off Morocco, Aegean and Ionian seashores between 2017 and 2018. Such events, that are just a little part of the over 200 historically events reported for the Mediterranean (Maramai, Brizuela & Graziani, 2014) should remind geoscientists, civil protection officers, media and citizens that 1) tsunami hazard in the Mediterranean is not negligible, and 2) tsunamis come in all shapes and colours, and even a small event can result in serious damages and loss of lives and properties. Recently, a project funded by the European Commission (TSUMAPS-NEAM, Basili et al., 2018) has estimated the tsunami hazard due to seismic sources in the NEAM region (one of the four ICG coordinated by the UNESCO IOC) finding that a significant hazard is present in most coasts of the area, particularly in those of Greece and Italy. In such a scenario, where low probability and high uncertainty match with poor knowledge and familiarity with tsunami hazard, risk mitigation strategies and risk communicators should avoid undue assumptions about public’s supposed attitudes and preparedness, as these may results in serious consequences for the exposed population, geoscientists, and civil protection officers. Hence, scientists must carefully shape their messages and rely on well-researched principled practices rather than on good intuitions (Bostrom, & Löfstedt, 2003). For these reasons, the Centro Allerta Tsunami of the Istituto Nazionale di Geofisica e Vulcanologia (hereinafter CAT-INGV) promoted a survey to investigate tsunami’s risk perception in two pilot regions of Southern Italy, Calabria and Apulia, providing a stratified sample of 1021 interviewees representing about 3.2mln people living in 183 coastal municipalities of two regions subjected (along with Sicily) to relatively high probability to be hit by a tsunami. Results show that people’s perception and understanding of tsunami are affected by media accounts of large tsunamis of 2004 (Sumatra) and 2011 (Tohoku, North East Japan): television emerged as the most relevant source of knowledge for almost 90 % of the sample, and the influence of media also results in the way tsunami risk is characterized. Risk perception appears to be low: for almost half of the sample the occurrence of a tsunami in the Mediterranean sea is considered quite unlikely. Furthermore, the survey’s results show that the word tsunami occupies a different semantic space with respect to the Italian traditional headword maremoto, with differences among sample strata. In other words, the same physical phenomenon would be understood in two different ways by younger, educated people and elders with low education level. Also belonging to different coastal areas appears to have a significant influence on the way tsunami hazard is conceived, having a stronger effect on risk characterization, for instance the interviewees of Tyrrhenian Calabria are more likely to associate tsunami risk to volcanoes with respect to other considered coastlines. The results of this study provide a relevant account of the issues at a stake, also entailing important implication both for risk communication and mitigation policies.


2012 ◽  
Vol 12 (1) ◽  
pp. 151-163 ◽  
Author(s):  
A. Grezio ◽  
P. Gasparini ◽  
W. Marzocchi ◽  
A. Patera ◽  
S. Tinti

Abstract. We present a first detailed tsunami risk assessment for the city of Messina where one of the most destructive tsunami inundations of the last centuries occurred in 1908. In the tsunami hazard evaluation, probabilities are calculated through a new general modular Bayesian tool for Probability Tsunami Hazard Assessment. The estimation of losses of persons and buildings takes into account data collected directly or supplied by: (i) the Italian National Institute of Statistics that provides information on the population, on buildings and on many relevant social aspects; (ii) the Italian National Territory Agency that provides updated economic values of the buildings on the basis of their typology (residential, commercial, industrial) and location (streets); and (iii) the Train and Port Authorities. For human beings, a factor of time exposition is introduced and calculated in terms of hours per day in different places (private and public) and in terms of seasons, considering that some factors like the number of tourists can vary by one order of magnitude from January to August. Since the tsunami risk is a function of the run-up levels along the coast, a variable tsunami risk zone is defined as the area along the Messina coast where tsunami inundations may occur.


Landslides ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. 2301-2315 ◽  
Author(s):  
Finn Løvholt ◽  
Sylfest Glimsdal ◽  
Carl B. Harbitz

Abstract Landslides are the second most frequent tsunami source worldwide. However, their complex and diverse nature of origin combined with their infrequent event records make prognostic modelling challenging. In this paper, we present a probabilistic framework for analysing uncertainties emerging from the landslide source process. This probabilistic framework employs event trees and is used to conduct tsunami uncertainty analysis as well as probabilistic tsunami hazard analysis (PTHA). An example study is presented for the Lyngen fjord in Norway. This application uses a mix of empirical landslide data combined with expert judgement to come up with probability maps for tsunami inundation. Based on this study, it is concluded that the present landslide tsunami hazard analysis is largely driven by epistemic uncertainties. These epistemic uncertainties can be incorporated in the probabilistic framework. Conducting a literature analysis, we further show examples of how landslide and tsunami data can be used to better constrain landslide uncertainties, combined with statistical and numerical analysis methods. We discuss how these methods, combined with the probabilistic framework, can be used to improve landslide tsunami hazard analysis in the future.


2021 ◽  
Vol 13 (9) ◽  
pp. 1819
Author(s):  
Tianjun Qi ◽  
Yan Zhao ◽  
Xingmin Meng ◽  
Guan Chen ◽  
Tom Dijkstra

Groups of landslides induced by heavy rainfall are widely distributed on a global basis and they usually result in major losses of human life and economic damage. However, compared with landslides induced by earthquakes, inventories of landslides induced by heavy rainfall are much less common. In this study we used high-precision remote sensing images before and after continuous heavy rainfall in southern Tianshui, China, from 20 June to 25 July 2013, to produce an inventory of 14,397 shallow landslides. Based on the results of landslide inventory, we utilized machine learning and the geographic information system (GIS) to map landslide susceptibility in this area and evaluated the relative weight of various factors affecting landslide development. First, 18 variables related to geomorphic conditions, slope material, geological conditions, and human activities were selected through collinearity analysis; second, 21 selected machine learning models were trained and optimized in the Python environment to evaluate the susceptibility of landslides. The results showed that the ExtraTrees model was the most effective for landslide susceptibility assessment, with an accuracy of 0.91. This predictive ability means that our landslide susceptibility results can be used in the implementation of landslide prevention and mitigation measures in the region. Analysis of the importance of the factors showed that the contribution of slope aspect (SA) was significantly higher than that of the other factors, followed by planar curvature (PLC), distance to river (DR), distance to fault (DTF), normalized difference vehicle index (NDVI), distance to road (DTR), and other factors. We conclude that factors related to geomorphic conditions are principally responsible for controlling landslide susceptibility in the study area.


2020 ◽  
Author(s):  
Steven J. Gibbons ◽  
Manuel J. Castro Díaz ◽  
Sylfest Glimsdal ◽  
Carl Bonnevie Harbitz ◽  
Maria Concetta Lorenzino ◽  
...  

<p>Probabilistic Tsunami Hazard Analysis (PTHA) is an approach to quantifying the likelihood of exceeding a specified metric of tsunami inundation at a given location within a given time interval. It provides scientific guidance for decision making regarding coastal engineering and evacuation planning. PTHA requires a discretization of many potential tsunami source scenarios and an evaluation of the probability of each scenario. The classical approach of PTHA has been the quantification of the tsunami hazard offshore, while estimates of the inundation at a given coastal site have been limited to a few scenarios. PTHA, with an adequate discretization of source scenarios, combined with high-resolution inundation modelling, has been out of reach with existing models and computing capabilities with tens to hundreds of thousands of moderately intensive numerical simulations being required. In recent years, more efficient GPU-based High Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have made a regional and local long-term hazard assessment feasible. PTHA is one of the so-called Pilot Demonstrators of the EC-funded ChEESE project (Center of Excellence for Exascale Computing in the Solid Earth) where a workflow has been developed with three main stages: source specification and discretization, efficient numerical inundation simulation for each scenario using the HySEA numerical tsunami propagation model, and hazard aggregation. HySEA calculates tsunami offshore propagation and inundation using a system of telescopic topo-bathymetric grids. In this presentation, we illustrate the workflows of the PTHA as implemented for HPC applications, including preliminary simulations carried out on intermediate scale GPU clusters. Finally, we delineate how planned upscaling to exascale applications can significantly increase the accuracy of local tsunami hazard analysis.</p><p>This work is partially funded by the European Union’s Horizon 2020 Research and Innovation Program under grant agreement No 823844 (ChEESE Center of Excellence, www.cheese-coe.eu).</p>


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