Tsunami risk levels mapping in Puger Sub-District, Jember Regency

Puger sub-district is categorized as a tsunami-prone area because of its location in the South Coast, directly facing the Indian Ocean, which is the meeting point for two active tectonic plates. The active plate zone is prone to causing earthquakes that raise tsunamis. This article will describe the tsunami hazard and vulnerability level in Puger sub-district using the Geographic Information System (GIS) application. The method in this study uses a weighted overlay method. The weighting method is carried out to determine the level of tsunami hazard and vulnerability by following the weighting criteria in previous studies. Physical vulnerability criteria include land elevation, slope, beach type, land use, coastline distance, and rivers. The tsunami hazard level is determined based on the tsunami run-up map from previous studies. Based on the results of the risk mapping, it was found that there were five risk categories in Puger sub-district, namely the very low level (13.90 Ha), low level (271.99 Ha), medium level (7133.25 Ha), high level (644.22 Ha), and very high level (23.29 Ha).

Comparisons of Numerical Models on Formation of Sediment Deposition Induced by Tsunami Run-Up

Tsunami sediments provide direct evidence of tsunami arrival histories for tsunami risk assessments. Therefore, it is important to understand the formation process of tsunami sediment for tsunami risk assessment. Numerical simulations can be used to better understand the formation process. However, as the formation of tsunami sediments is affected by various conditions, such as the tsunami hydraulic conditions, topographic conditions, and sediment conditions, many problems remain in such simulations when attempting to accurately reproduce the tsunami sediment formation process. To solve these problems, various numerical models and methods have been proposed, but there have been few comparative studies among such models. In this study, inter-model comparisons of tsunami sediment transport models were performed to improve the reproducibility of tsunami sediment features in models. To verify the reproducibility of the simulations, the simulation results were compared with the results of sediment transport hydraulic experiments using a tsunami run-up to land. Two types of experiments were conducted: a sloping plane with and without coverage by silica sand (fixed and movable beds, respectively). The simulation results confirm that there are conditions and parameters affecting not only the amount of sediment transport, but also the distribution. In particular, the treatment of the sediment coverage ratio in a calculation grid, roughness coefficient, and bedload transport rate formula on the fixed bed within the sediment transport model are considered important.

Megatsunamis Induced by Volcanic Landslides in the Canary Islands: Age of the Tsunami Deposits and Source Landslides

Evidence for frequent, large landslides on the flanks of the volcanic edifices forming the Canary Islands include outstanding landslide scars and their correlative submarine and subaerial rock and debris avalanche deposits. These landslides involved volumes ranging from tens to hundreds of km3. The sudden entry of large volumes of rock masses in the sea may have triggered tsunamis capable of affecting the source and neighboring islands, with the resulting huge waves dragging coastal and seabed materials and fauna and redepositing them inland. Here, we present new geological evidence and geochronological data of at least five megatsunamis in Tenerife, Lanzarote, and Gran Canaria, triggered by island flank megalandslides, and occasionally explosive eruptions, during the last 1 million years. The exceptional preservation of the megatsunami deposits and the large area they cover, particularly in Tenerife, provide fundamental data on the number of tsunami events and run-ups, and allow proposals on the sources and age of the tsunamis. Tsunami run-up heights up to 290 m above coeval sea level, some of the highest known on Earth in recent geological times, were estimated based on sedimentological, geomorphological, paleontological, and geochronological data. The research results made it possible to estimate the recurrence of tsunamis in the archipelago during the last hundreds of thousands of years, and to establish relationships between tsunami deposits and the probable triggering island flank landslides.

Probabilistic near-field tsunami source and tsunami run-up distribution inferred from tsunami run-up records in northern Chile

Understanding a tsunami source and its impact is vital to assess a tsunami hazard. Thanks to the efforts of the tsunami survey teams, high-quality tsunami run-up data exists for contemporary events. Still, it has not been widely used to infer a tsunami source and its impact mainly due to the computational burden of the tsunami forward model. In this study, we propose a TRRF-INV (Tsunami Run-up Response Function-based INVersion) model that can provide probabilistic estimates of a near-field tsunami source and tsunami run-up distribution from a small number of run-up records. We tested the TRRF-INV model with synthetic tsunami scenarios in northern Chile and applied it to the 2014 Iquique, Chile, tsunami event as a case study. The results demonstrated that the TRRF-INV model can provide a reasonable tsunami source estimate to first order and estimate tsunami run-up distribution well. Moreover, the case study results agree well with the United States Geological Survey report and the global Centroid Moment Tensor solution. We also analyzed the performance of the TRRF-INV model depending on the number and the uncertainty of run-up records. We believe that the TRRF-INV model has the potential for supporting accurate hazard assessment by (1) providing new insights from tsunami run-up records into the tsunami source and its impact, (2) using the TRRF-INV model as a tool to support existing tsunami inversion models, and (3) estimating a tsunami source and its impact for ancient events where no data other than estimated run-up from sediment deposit data exists.

Rapid prediction of alongshore run-up distribution from near-field tsunamis

Rapid prediction of the spatial distribution of the run-up from near- field tsunamis is critically important for tsunami hazard characterization. Even though significant advances have been made over the last decade, physics- based numerical models are still computationally intensive. Here, we present a response surface methodology (RSM)-based model called the tsunami run-up response function (TRRF). Derived from a discrete set of tsunami simulations, TRRF can produce a rapid prediction of a near-field tsunami run-up distribution that takes into account the influence of variable local topographic and bathymetric characteristics in a given region. This new method reduces the number of simulations required to build an RSM model by separately modeling the leading order contribution and the residual part of the tsunami run-up distribution. Using the northern region of Puerto Rico as a case study, we investigated the performance (accuracy, computational time) of the TRRF. The results reveal that the TRRF achieves reliable prediction while reducing the prediction time by six orders of magnitude (computational time: < 1 second per earthquake).

Assessing local impacts of the 1700 CE Cascadia earthquake and tsunami using tree-ring growth histories: a case study in South Beach, Oregon, USA

We present an investigation of the disturbance history of an old-growth Douglas-fir (Pseudotsuga menziesii) stand in South Beach, Oregon, for possible growth changes due to tsunami inundation caused by the 1700 CE Cascadia Subduction Zone (CSZ) earthquake. A high-resolution model of the 1700 tsunami run-up heights at South Beach, assuming an “L”-sized earthquake, is also presented to better estimate the inundation levels several kilometers inland at the old-growth site. This tsunami model indicates the South Beach fir stand would have been subjected to local inundation depths from 0 to 10 m. Growth chronologies collected from the Douglas-fir stand shows that trees experienced a significant growth reductions in the year 1700 relative to nearby Douglas-fir stands, consistent with the tsunami inundation estimates. The ±1–3-year timing of the South Beach disturbances are also consistent with disturbances previously observed at a Washington state coastal forest ∼220 km to the north. Moreover, the 1700 South Beach growth reductions were not the largest over the >321-year tree chronology at this location, with other disturbances likely caused by climate drivers (e.g., drought or windstorms). Our study represents a first step in using tree growth history to ground truth tsunami inundation models by providing site-specific physical evidence.

Shoreline Changes along Northern Ibaraki Coast after the Great East Japan Earthquake of 2011

In this study, we analyze the influence of the Great East Japan Earthquake, which occurred on 11 March 2011, on the shoreline of the northern Ibaraki Coast. After the earthquake, the area experienced subsidence of approximately 0.4 m. Shoreline changes at eight sandy beaches along the coast are estimated using various satellite images, including the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer), ALOS AVNIR-2 (Advanced Land Observing Satellite, Advanced Visible and Near-infrared Radiometer type 2), and Sentinel-2 (a multispectral sensor). Before the earthquake (for the period March 2001–January 2011), even though fluctuations in the shoreline position were observed, shorelines were quite stable, with the averaged change rates in the range of ±1.5 m/year. The shoreline suddenly retreated due to the earthquake by 20–40 m. Generally, the amount of retreat shows a strong correlation with the amount of land subsidence caused by the earthquake, and a moderate correlation with tsunami run-up height. The ground started to uplift gradually after the sudden subsidence, and shoreline positions advanced accordingly. The recovery speed of the beaches varied from +2.6 m/year to +6.6 m/year, depending on the beach conditions.