scholarly journals On the characteristics of landslide tsunamis

2015 ◽  
Vol 373 (2053) ◽  
pp. 20140376 ◽  
Author(s):  
F. Løvholt ◽  
G. Pedersen ◽  
C. B. Harbitz ◽  
S. Glimsdal ◽  
J. Kim
Keyword(s):  
Laboratory Experiments ◽  
Tsunami Generation ◽  
Long Run ◽  
Subaerial Landslide ◽  
Modelling Techniques ◽  
Landslide Deformation ◽  
Landslide Tsunami ◽  
Weak Influence ◽  
Positive Interference ◽  
Landslide Tsunamis

This review presents modelling techniques and processes that govern landslide tsunami generation, with emphasis on tsunamis induced by fully submerged landslides. The analysis focuses on a set of representative examples in simplified geometries demonstrating the main kinematic landslide parameters influencing initial tsunami amplitudes and wavelengths. Scaling relations from laboratory experiments for subaerial landslide tsunamis are also briefly reviewed. It is found that the landslide acceleration determines the initial tsunami elevation for translational landslides, while the landslide velocity is more important for impulsive events such as rapid slumps and subaerial landslides. Retrogressive effects stretch the tsunami, and in certain cases produce enlarged amplitudes due to positive interference. In an example involving a deformable landslide, it is found that the landslide deformation has only a weak influence on tsunamigenesis. However, more research is needed to determine how landslide flow processes that involve strong deformation and long run-out determine tsunami generation.

scholarly journals Modeling the Slump-Type Landslide Tsunamis Part II: Numerical Simulation of Tsunamis with Bingham Landslide Model

2020 ◽  
Vol 10 (19) ◽  
pp. 6872
Author(s):  
Thi-Hong-Nhi Vuong ◽  
Tso-Ren Wu ◽  
Chun-Yu Wang ◽  
Chia-Ren Chu
Keyword(s):  
Rheological Properties ◽  
Froude Number ◽  
Laboratory Experiments ◽  
Laboratory Data ◽  
Navier Stokes ◽  
Tsunami Generation ◽  
Bingham Number ◽  
Bingham Material ◽  
Landslide Tsunami ◽  
Moving Speed

This paper incorporates the Bingham rheology model with the Navier–Stokes solver to simulate the tsunamis excited by a slump-type landslide. The slump is modeled as the Bingham material, in which the rheological properties changing from the un-yield phase to yield phase is taken into account. The volume of fluid method is used to track the interfaces between three materials: air, water, and slump. The developed model is validated by the laboratory data of the benchmark landslide tsunami problem. A series of rheological properties analyses is performed to identify the parameter sensitivity to the tsunami generation. The results show that the yield stress plays a more important role than the yield viscosity in terms of the slump kinematics and tsunami generation. Moreover, the scale effect is investigated under the criterion of Froude number similarity and Bingham number similarity. With the same Froude number and Bingham number, the result from the laboratory scale can be applied to the field scale. If the slump material collected in the field is used in the laboratory experiments, only the result of the maximum wave height can be used, and significant errors in slump shape and moving speed are expected.

scholarly journals Dengue Outbreak Prediction Based on Artificial Neural Networking Model Using Climatic Parameters

2020 ◽  
Author(s):  
Biplab Ghosh ◽  
Monika Soni
Keyword(s):  
Dengue Fever ◽  
Meteorological Parameters ◽  
Ann Model ◽  
Data Set ◽  
Long Run ◽  
Modelling Techniques ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
And Control ◽  
The Relationship

Abstract Background: Dengue fever is a vector-borne tropical disease radically amplified by 30 times in occurrence between 1960 and 2010. The upsurge is considered to be because of urbanization, population growth and climate change. Therefore, Meteorological parameters (temperature, precipitation and relative humidity) have impact on the occurrence and outbreaks of dengue fever. There are not many studies that enumerate the relationship between the dengue cases in a particular locality and the meteorological parameters. This study explores the relationship between the dengue cases and the meteorological parameters. In prevalent localities, it is essential to alleviate the outbreaks using modelling techniques for better disease control.Methods: An artificial neural network (ANN) model was developed for predicting the number of dengue cases by knowing the meteorological parameters. The model was trained with 7 years of dengue fever data of Kamrup and Lakhimpur district of Assam, India. The practicality of the model was corroborated using independent data set with satisfactory outcomes. Findings: It was apparent from the sensitivity analysis that precipitation is more sensitive to the number of dengue cases than other meteorological parameters. Conclusion: This model would assist dengue fever alleviation and control in the long run.

Validation and inter-comparison of models for landslide tsunami generation

2022 ◽  
pp. 101943
Author(s):  
James T. Kirby ◽  
Stephan T. Grilli ◽  
Juan Horrillo ◽  
Philip L.-F. Liu ◽  
Dmitry Nicolsky ◽  
...  
Keyword(s):  
Tsunami Generation ◽  
Landslide Tsunami

Macroeconomic Determinants Of Non-Fuel Primary Commodity Price Movements

2011 ◽  
Vol 24 (1) ◽  
Author(s):  
Raymond Swaray
Keyword(s):  
Commodity Prices ◽  
Commodity Price ◽  
Real Effective Exchange Rate ◽  
Crude Oil Price ◽  
Long Run ◽  
Effective Exchange ◽  
Modelling Techniques ◽  
Macroeconomic Determinants ◽  
Effective Exchange Rate ◽  
The Relationship

<p class="MsoNormal" style="text-align: justify; margin: 0in 0.5in 0pt; tab-stops: .5in 1.0in 1.5in 2.0in 2.5in 3.0in 3.5in 4.0in 4.5in 5.0in 5.5in 6.0in;"><span style="mso-ansi-language: EN-GB;" lang="EN-GB"><span style="font-size: x-small;"><span style="font-family: Times New Roman;">This paper uses cointegration and error correction modelling techniques to examine the relationship between non-fuel commodity prices and world macroeconomic and monetary variables. The results show that fluctuations in industrial production of OECD countries, real effective exchange rate of the U.S. dollar and oil prices have significant short- and long- run impact on non-fuel commodity prices. In addition, there is evidence of highly significant positive correlation between the index of non-fuel commodity prices and crude oil price. This implies non-fuel commodity-dependent developing countries that are net importers of oil can derive little benefit from upward movements in commodity prices.</span></span></span></p>

Faster Than Real Time tsunami simulations – challenges and solutions towards High Performance Exascale Computing

2020 ◽  
Author(s):  
Jorge Macias ◽  
Manuel J. Castro ◽  
Marc de la Asunción ◽  
José Manuel González-Vida ◽  
Carlos Sánchez-Linares ◽  
...  
Keyword(s):  
Real Time ◽  
High Performance ◽  
Simulation Models ◽  
Early Warning Systems ◽  
Tsunami Generation ◽  
Tsunami Propagation ◽  
Tsunami Early Warning ◽  
Horizon 2020 ◽  
Landslide Tsunami ◽  
Tsunami Early Warning Systems

&lt;p&gt;Tsunami simulation in the framework of Tsunami Early Warning Systems (TEWS) is a quite recent achievement, but still limited regarding the size of the problem and restricted to tsunami wave propagation. Faster Than Real Time (FTRT) tsunami simulations require greatly improved and highly efficient computational methods to achieve extremely fast and effective calculations. HPC facilities have the role to bring this efficiency to a maximum possible and drastically reducing computational times. Putting these two ingredients together is the aim of Pilot Demonstrator 2 (PD2) in ChEESE project. This PD will comprise both earthquake and landslide sources. Earthquake tsunami generation is to an extent simpler than landslide tsunami generation, as landslide generated tsunamis depend on the landslide dynamics which necessitate coupling dynamic landslide simulation models to the tsunami propagation. In both cases, FTRT simulations in several contexts and configurations will be the final aim of this pilot.&lt;/p&gt;&lt;p&gt;Among the objectives of our work in ChEESE project are achieving unprecedented FTRT tsunami computations with existing models and investigate the scalability limits of such models; increasing the size of the problems by increasing spatial resolution and/or producing longer simulations while still computing FTRT, dealing with problems and resolutions never done before; developing a TEWS including inundation for a particular target coastal zone, or numerous scenarios allowing PTHA (PD7) and PTF (PD8), an aim unattainable at present or including more physics in shallow water models for taking into account dispersive effects.&lt;/p&gt;&lt;p&gt;Up to now, the two European tsunami flagship codes selected by ChESEE project (Tsunami-HySEA and Landslide-HySEA) have been audit and efficiency further improved. The improved code versions have been tested in three European 0-Tier HPC facilities: BSC (Spain), CINECA (Italy) and Piz Daint (Switzerland) using up to 32 NVIDIA Graphic Cards (P100 and V100) for scaling purposes. Computing times have been drastically reduced and a PTF study composed by around 10,000 scenarios (4 nested grids, 12 M cells, 8 hours simulations) have been computed in 6 days of wall-clock computations in the 64 GPUs available for us at the BSC.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&amp;#160;&lt;/strong&gt;&lt;strong&gt;Acknowledgements&lt;/strong&gt;. This research has been partially supported by the Spanish Government Research project &lt;strong&gt;MEGAFLOW&lt;/strong&gt; (RTI2018-096064-B-C21), Universidad de M&amp;#225;laga, Campus de Excelencia Internacional Andaluc&amp;#237;a Tech and ChEESE project (EU Horizon 2020, grant agreement N&amp;#186; 823844), https://cheese-coe.eu/&lt;/p&gt;

scholarly journals Landslide tsunamis in lakes

2015 ◽  
Vol 772 ◽  
pp. 784-804 ◽  
Author(s):  
Louis-Alexandre Couston ◽  
Chiang C. Mei ◽  
Mohammad-Reza Alam
Keyword(s):  
Near Field ◽  
Finite Size ◽  
Wave Runup ◽  
Multiple Reflections ◽  
Time Period ◽  
Near Shore ◽  
Lakes And Reservoirs ◽  
Landslide Tsunami ◽  
Tsunami Energy ◽  
Landslide Tsunamis

Landslides plunging into lakes and reservoirs can result in extreme wave runup at the shores. This phenomenon has claimed lives and caused damage to near-shore properties. Landslide tsunamis in lakes are different from typical earthquake tsunamis in the open ocean in that (i) the affected areas are usually within the near field of the source, (ii) the highest runup occurs within the time period of the geophysical event, and (iii) the enclosed geometry of a lake does not let the tsunami energy escape. To address the problem of transient landslide tsunami runup and to predict the resulting inundation, we utilize a nonlinear model equation in the Lagrangian frame of reference. The motivation for using such a scheme lies in the fact that the runup on an inclined boundary is directly and readily computed in the Lagrangian framework without the need to resort to approximations. In this work, we investigate the inundation patterns due to landslide tsunamis in a lake. We show by numerical computations that Airy’s approximation of an irrotational theory using Lagrangian coordinates can legitimately predict runup of large amplitude. We also demonstrate that in a lake of finite size the highest runup may be magnified by constructive interference between edge waves that are trapped along the shore and multiple reflections of outgoing waves from opposite shores, and may occur somewhat after the first inundation.

scholarly journals Landslide tsunami case studies using a Boussinesq model and a fully nonlinear tsunami generation model

2003 ◽  
Vol 3 (5) ◽  
pp. 391-402 ◽  
Author(s):  
P. Watts ◽  
S. T. Grilli ◽  
J. T. Kirby ◽  
G. J. Fryer ◽  
D. R. Tappin
Keyword(s):  
Case Studies ◽  
Papua New Guinea ◽  
New Guinea ◽  
Marine Geology ◽  
Tsunami Generation ◽  
Tsunami Propagation ◽  
Propagation Models ◽  
Fully Nonlinear ◽  
Successful Case ◽  
Landslide Tsunami

Abstract. Case studies of landslide tsunamis require integration of marine geology data and interpretations into numerical simulations of tsunami attack. Many landslide tsunami generation and propagation models have been proposed in recent time, further motivated by the 1998 Papua New Guinea event. However, few of these models have proven capable of integrating the best available marine geology data and interpretations into successful case studies that reproduce all available tsunami observations and records. We show that nonlinear and dispersive tsunami propagation models may be necessary for many landslide tsunami case studies. GEOWAVE is a comprehensive tsunami simulation model formed in part by combining the Tsunami Open and Progressive Initial Conditions System (TOPICS) with the fully non-linear Boussinesq water wave model FUNWAVE. TOPICS uses curve fits of numerical results from a fully nonlinear potential flow model to provide approximate landslide tsunami sources for tsunami propagation models, based on marine geology data and interpretations. In this work, we validate GEOWAVE with successful case studies of the 1946 Unimak, Alaska, the 1994 Skagway, Alaska, and the 1998 Papua New Guinea events. GEOWAVE simulates accurate runup and inundation at the same time, with no additional user interference or effort, using a slot technique. Wave breaking, if it occurs during shoaling or runup, is also accounted for with a dissipative breaking model acting on the wave front. The success of our case studies depends on the combination of accurate tsunami sources and an advanced tsunami propagation and inundation model.

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