Tsunami hazard assessment for the central and southern pacific coast of Colombia

Escobar, Ronald Efrén Sánchez; Díaz, Luis Jesús Otero; Guerrero, Anlly Melissa; Galindo, Milton Gabriel Puentes; Mas, Erick; Koshimura, Shunichi; Adriano, Bruno; Urra, Luisa; Quintero, Paola

doi:10.1080/21664250.2020.1818362

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…Hence, we think that it is better to use a planar fault model and uniform slip to lessen the use of random parameters that could increase the uncertainty in the results. We also note that although probabilistic approaches are becoming more common, the deterministic method is still included in recent tsunami hazard studies (e.g., Wronna et al, 2015;Roshan et al, 2016;Gonzáles et al, 2017;Escobar et al, 2020;Rashidi et al, 2020Rashidi et al, , 2022El-Hussain et al, 2021).…”

Section: Slip Modelmentioning

confidence: 99%

Tsunami hazard in Lombok and Bali, Indonesia, due to the Flores back-arc thrust

Felix

Hubbard

Bradley

et al. 2022

Nat. Hazards Earth Syst. Sci.

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Abstract. The tsunami hazard posed by the Flores back-arc thrust, which runs along the northern coast of the islands of Bali and Lombok, Indonesia, is poorly studied compared to the Sunda Megathrust, situated ∼250 km to the south of the islands. However, the 2018 Lombok earthquake sequence demonstrated the seismic potential of the western Flores Thrust when a fault ramp beneath the island of Lombok ruptured in two Mw 6.9 earthquakes. Although the uplift in these events mostly occurred below land, the sequence still generated local tsunamis along the northern coast of Lombok. Historical records show that the Flores fault system in the Lombok and Bali region has generated at least six ≥Ms 6.5 tsunamigenic earthquakes since 1800 CE. Hence, it is important to assess the possible tsunami hazard represented by this fault system. Here, we focus on the submarine fault segment located between the islands of Lombok and Bali (below the Lombok Strait). We assess modeled tsunami patterns generated by fault slip in six earthquake scenarios (slip of 1–5 m, representing Mw 7.2–7.9+) using deterministic modeling, with a focus on impacts on the capital cities of Mataram, Lombok, and Denpasar, Bali, which lie on the coasts facing the strait. We use a geologically constrained earthquake model informed by the Lombok earthquake sequence, together with a high-resolution bathymetry dataset developed by combining direct measurements from the General Bathymetric Chart of the Oceans (GEBCO) with sounding measurements from the official nautical charts for Indonesia. Our results show that fault rupture in this region could trigger a tsunami reaching Mataram in <9 min and Denpasar in ∼ 23–27 min, with multiple waves. For an earthquake with 3–5 m of coseismic slip, Mataram and Denpasar experience maximum wave heights of ∼ 1.6–2.7 and ∼ 0.6–1.4 m, respectively. Furthermore, our earthquake models indicate that both cities would experience coseismic subsidence of 20–40 cm, exacerbating their exposure to both the tsunami and other coastal hazards. Overall, Mataram is more exposed than Denpasar to high tsunami waves arriving quickly from the fault source. To understand how a tsunami would affect Mataram, we model the associated inundation using the 5 m slip model and show that Mataram is inundated ∼ 55–140 m inland along the northern coast and ∼230 m along the southern coast, with maximum flow depths of ∼ 2–3 m. Our study highlights that the early tsunami arrival in Mataram, Lombok, gives little time for residents to evacuate. Raising their awareness about the potential for locally generated tsunamis and the need for evacuation plans is important to help them respond immediately after experiencing strong ground shaking.

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Section: Slip Modelmentioning

confidence: 99%

Tsunami hazard in Lombok and Bali, Indonesia, due to the Flores back-arc thrust

Felix

Hubbard

Bradley

et al. 2022

Nat. Hazards Earth Syst. Sci.

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“…Disaster risks can be measured by multiplying hazard/H by vulnerability/V and divided it by capacity/C (Amri et al, 2016). Threats or hazards become a disaster if a community is vulnerable or has lower capacity than the hazard level, or they even become a source of the disaster (Escobar et al, 2020;Ramirez-Andreotta et al, 2016). Hence, improving disaster preparedness behaviors as a part of the capacity will reduce the disaster risks.…”

Section: Introductionmentioning

confidence: 99%

Disaster preparedness behaviors in biology education: Knowledge of environmental disaster mitigation

et al. 2021

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Environmental disaster was important issue to be solved. Current situation disasters such as flood, earthquake, tsunami, volcanoes and others could be happened. This study aimed to obtain information about the relationship between knowledge of disaster and preparedness behaviors and disaster preparedness behaviors. This research was a Sequential Explanatory combination research consisting of 2 variables, namely knowledge about disaster mitigation as an independent variable (X) and disaster preparedness behaviors as a dependent variable (Y). This research was conducted in January-June 2019. The population in this study was all students of Grade XI MIPA in MAN in Bogor City in the academic year 2018/2019 with a total sample of 207 respondents. Research data were obtained using multiple choice test and observation sheet. Quantitative data analysis with descriptive statistical calculations, prerequisite tests using the Liliefors test and the Bartlett test. The data hypotheses testing used the Pearson Product Moment formula. Analysis of qualitative data carried out by reducing data, presenting data, and drawing conclusions. The results showed that there was a positive relationship between knowledge of disaster mitigation and disaster preparedness behaviors (t-value 3.56 > t-statistic 0.05, r=0.234 & r2=5.51%) with a low interpretation value. The conclusion of this research there were low relationship between knowledge of disaster and preparedness behaviors.

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