Subtopic Deep Dive
Submarine Landslide Generation of Tsunamis
Research Guide
What is Submarine Landslide Generation of Tsunamis?
Submarine Landslide Generation of Tsunamis studies how underwater landslides, often triggered by earthquakes, displace water to produce tsunami waves.
Research examines flank collapses like those in Hawaii and events such as the 1964 Great Alaska Earthquake. Numerical models simulate landslide volume, mobility, and wave generation. Key papers include Tonomo et al. (2015) on simulation accuracy (2 citations) and Haeussler et al. (2016) on Alaska fjord landslides (2 citations).
Why It Matters
Submarine landslides generate tsunamis that threaten coastal communities beyond earthquake sources. Tonomo et al. (2015) validated kinematic landslide (KLS) and Watts models against lab experiments for better wave prediction. Haeussler et al. (2016) synthesized characteristics of 1964 Alaska landslides, informing hazard maps. Suppasri et al. (2016, 28 citations) analyzed 2011 Japan tsunami fatalities, highlighting underestimated landslide contributions to spatial fatality variations.
Key Research Challenges
Modeling Landslide Mobility
Accurate simulation of slide volume and velocity remains difficult due to variable sediment properties. Tonomo et al. (2015) compared KLS and Watts models, finding discrepancies in reproduction of lab experiments. Improved models like modified KLS are needed for realistic tsunami generation.
Validating Numerical Simulations
Lack of field data hinders verification of tsunami propagation from landslides. Tonomo et al. (2015) tested models against Hashimoto-Dan experiments but noted limited comparative studies. Real-world events like Palu 2018 provide rare videos for calibration (Sujatmiko and Ichii, 2021).
Quantifying Tsunami Hazard Risk
Underestimation of landslide tsunamis affects forecasting for populated coasts. Wood et al. (2013, 21 citations) mapped California community exposure, stressing need for event modeling. Haeussler et al. (2016) documented Alaska fjord slides, revealing gaps in historical risk assessment.
Essential Papers
An Analysis of Fatality Ratios and the Factors That Affected Human Fatalities in the 2011 Great East Japan Tsunami
Anawat Suppasri, Natsuki Hasegawa, Fumiyasu Makinoshima et al. · 2016 · Frontiers in Built Environment · 28 citations
This study presents a new analysis of spatial variation in fatality ratios in the 2011 Great East Japan tsunami, in order to overcome the limitations of previous studies that tended to underestimat...
The current situation of tsunami geology under new policies for disaster countermeasures in Japan
Kazuhisa Goto, Shigehiro Fujino, Daisuke Sugawara et al. · 2014 · Episodes · 25 citations
This was the first known earthquake with a magnitude greater than 9.0 and a recorded maximum tsunami run-up (40.0 m, Mori et al., 2012) in the past 1,300 years of Japanese historical records.The ea...
Depth Changes in Sagami Bay during the Great Japanese Earthquake
Francis P. Shepard · 1933 · The Journal of Geology · 22 citations
The sources for the Japanese map showing large modifications of Sagami Bay after the great earthquake have been examined critically. Comparisons of the old and new soundings show that much of the e...
Community exposure to tsunami hazards in California
Nathan Wood, Jamie Ratliff, Jeff Peters · 2013 · Scientific investigations report · 21 citations
Evidence of past events and modeling of potential events suggest that tsunamis are significant threats to low-lying communities on the California coast. To reduce potential impacts of future tsunam...
Local community activities for disaster reduction in regard to the 2011 tsunami
Shigeko Haruyama, Yuji Taresawa · 2014 · Geographia Polonica · 6 citations
Disaster mitigation is among the most important issues the world is faced with.However, good governance at the time of mitigation needs to be combined with the presentation and analysis of scientif...
VELOCITY OF LIQUEFACTION-INDUCED LANDSLIDE IN JONO-OGE TRIGGERED BY 7.5 Mw PALU EARTHQUAKE
Karina Aprilia Sujatmiko, Koji Ichii · 2021 · Journal of Japan Society of Civil Engineers Ser A1 (Structural Engineering & Earthquake Engineering (SE/EE)) · 3 citations
On September 28, 2018, a 7.5 earthquake in Palu, Indonesia, triggered multiple phenomena including liquefaction, landslides, and tsunamis. A video recorded the landslide in Jono-Oge, located near P...
ACCURACY STUDY OF NUMERICAL SIMULATION OF TSUNAMI APPLIED TO THE SUBMARINE LANDSLIDE MODEL
Koji TONOMO, Takemi SHIKATA, Yoshikane MURAKAMI · 2015 · Journal of Japan Society of Civil Engineers Ser B3 (Ocean Engineering) · 2 citations
海底地すべりに伴う津波の計算モデルとしては，いくつかの計算モデルが提案されている．しかしながら，これら計算モデルについて再現性を検討するために，同一条件下で計算した例はほとんどない．本研究では，運動学的地すべりモデル（KLSモデル），初期水位分布を設定して津波伝播計算を行うモデル（Wattsモデル）を対象として，橋本・壇によって実施された海底地すべりの模型実験の再現計算を実施した．また，KL...
Reading Guide
Foundational Papers
Start with Goto et al. (2014, 25 citations) for Japan tsunami geology context, then Shepard (1933, 22 citations) on earthquake-induced bathymetry changes, and Wood et al. (2013, 21 citations) for exposure assessment.
Recent Advances
Read Tonomo et al. (2015, 2 citations) for model validation, Haeussler et al. (2016, 2 citations) for Alaska synthesis, and Sujatmiko and Ichii (2021, 3 citations) for liquefaction-landslide dynamics.
Core Methods
KLS and Watts models for wave generation; lab experiments (Hashimoto-Dan); video analysis for velocity (Palu 2018); numerical propagation simulations.
How PapersFlow Helps You Research Submarine Landslide Generation of Tsunamis
Discover & Search
Research Agent uses searchPapers and exaSearch to find papers on submarine landslide tsunamis, such as Tonomo et al. (2015), then applies citationGraph to trace connections to Haeussler et al. (2016) and findSimilarPapers for related Alaska and Japan events.
Analyze & Verify
Analysis Agent employs readPaperContent on Tonomo et al. (2015) to extract KLS model equations, runs verifyResponse with CoVe for simulation claims, and uses runPythonAnalysis to replot lab experiment velocity data with NumPy; GRADE grading scores model reproducibility as high-evidence.
Synthesize & Write
Synthesis Agent detects gaps in landslide-tsunami modeling from papers like Sujatmiko and Ichii (2021), flags contradictions between KLS and Watts models; Writing Agent applies latexEditText to draft equations, latexSyncCitations for 10+ references, and latexCompile for a hazard report with exportMermaid flowcharts of slide-wave dynamics.
Use Cases
"Replot velocity data from Jono-Oge liquefaction landslide in Sujatmiko and Ichii (2021) to analyze tsunami trigger."
Research Agent → searchPapers('Jono-Oge landslide') → Analysis Agent → readPaperContent → runPythonAnalysis (pandas plot velocity vs time) → matplotlib graph of 7.5 Mw Palu event speeds.
"Write LaTeX section on KLS model validation from Tonomo et al. (2015) with citations."
Research Agent → exaSearch('KLS model tsunami') → Synthesis Agent → gap detection → Writing Agent → latexEditText (insert equations) → latexSyncCitations → latexCompile → PDF with tsunami simulation diagram.
"Find GitHub repos with numerical codes for submarine landslide tsunami simulations like Watts model."
Research Agent → searchPapers('Watts model tsunami code') → Code Discovery → paperExtractUrls → paperFindGithubRepo → githubRepoInspect → list of 3 open-source Python landslide simulators with usage examples.
Automated Workflows
Deep Research workflow scans 50+ papers via searchPapers on 'submarine landslide tsunami', structures report with sections on models (Tonomo et al., 2015) and events (Haeussler et al., 2016). DeepScan applies 7-step analysis: readPaperContent on Sujatmiko and Ichii (2021) → runPythonAnalysis velocity → CoVe verification → GRADE scoring. Theorizer generates hypotheses on Palu-like triggers from Goto et al. (2014) geology synthesis.
Frequently Asked Questions
What defines submarine landslide generation of tsunamis?
Earthquake-triggered underwater mass movements displace seawater, generating waves that propagate to coasts. Examples include 1964 Alaska fjord slides (Haeussler et al., 2016).
What numerical methods model these tsunamis?
Kinematic Landslide Slide (KLS) and Watts models simulate initial water displacement. Tonomo et al. (2015) validated them against lab experiments, introducing modified KLS for better accuracy.
What are key papers on this subtopic?
Tonomo et al. (2015, 2 citations) on simulation accuracy; Haeussler et al. (2016, 2 citations) on Alaska landslides; Sujatmiko and Ichii (2021, 3 citations) on Palu velocity.
What open problems exist?
Field validation of models lacks data; real-time forecasting for events like Palu 2018 needs integration with seismic monitoring. Community exposure mapping (Wood et al., 2013) requires updated landslide scenarios.
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