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This paper presents the first example of how to systematically identify the submarine landslide source of a tsunami using an innovative hybrid approach. This ground-breaking method is developed to resolve the puzzle around the source mechanism of the mysterious tsunami observed on 6th February 2023 in the Eastern Mediterranean Sea. The tsunami followed the two inland Mw 7.8 and Mw 7.5 Türkiye–Syria earthquakes, which occurred consequently with a 9 h interval on this day. The first earthquake (Mw 7.8) had an epicentral distance of 90 km from the nearest coast, which is closer than the second one (Mw 7.5) to the coast and yet its crustal deformation was almost entirely limited to inland. Therefore, the co-seismic surface displacement generated by the earthquake was ruled out as the source of the tsunami, confirmed by numerical modelling. Here, we hypothesized that the tsunami was most likely generated by a submarine landslide triggered by the earthquake. Analysis of tide gauge observations revealed that the waves arrived from 27 min to 48 min after the first earthquake (Mw 7.8) at different coastal locations, implying that the potential submarine landslide was triggered by the first earthquake (Mw 7.8). Backward tsunami travel time mapping using tide gauge observations guided us to constrain the area of the potential landslide. We approximated the dimensions of the landslide using spectral analysis of the tsunami observations. Consequently, an iterative trial-and-error approach was employed to confirm the landslide source of the tsunami by defining various informed alternative landslide scenarios and applying numerical modeling. Modelling showed that a submarine landslide can reproduce the tsunami observations reasonably well. It is located on a steep slope of the seafloor approximately 50 km from Arsuz. The submarine landslide is estimated to have caused a seafloor deformation measuring approximately 16 km in length and 4.0 km in width. [ABSTRACT FROM AUTHOR]

Landslides are one of the devastating geohazards that cause extensive socio-economic and environmental damages on local, regional, and global scales. Previous studies based on digital media sources have attracted attention to the high fatal landslide rate in Turkey, at a continental or global scale; however, the preparation of a comprehensive and long-term database for Turkey has been neglected until today. To examine this data gap, we present a new database of fatal landslide events resulting in fatalities from 1929 to 2019, which has been compiled using Turkish national and local printed and digital media reports, academic papers, disaster, and city annual reports. The fatal database of Turkey (FATALDOT) shows that, in total, 1343 people were killed in 389 fatal landslide events. The spatiotemporal distribution of the fatal landslides highlighted increasing trends with reference to two distinct hotspot zones throughout the Eastern Black Sea and Marmara Region, mostly around Istanbul megacity. Our results show that there has been a significant uniformity between the number of fatalities and fatal landslides triggered by anthropogenic and natural factors over the past decade, indicating an increasing dominance of human activities in fatality rates. Our findings also, for the first time, remarked the potential signatures of the economic crisis and political steadiness on fatal landslide trends. Nevertheless, we conclude that the increasing rate of anthropogenic disturbances in urban and mountainous areas, together with regional variances in topography and climatic setting, is essential in governing the pattern of fatal landslides. [ABSTRACT FROM AUTHOR]

This paper focuses on the evaluation of temporal and spatial propagations of impulse waves using 3D numerical simulation-based models for a potential landslide area in the Tersun Dam reservoir, Northeast Turkey. The topographical model was created using Stereo Lithography files, and a drift-flux model was used to simulate the landslides. The wave generation was simulated using the Reynolds-averaged Navier–Stokes equations. The Drift-Flux approach was selected, and a renormalization group-based k-ε turbulence model was used to create a fluid–solid coupled model. The results show that a 16.5-m impulse wave is created as a result of sliding material hitting the water at a velocity of 16.4 m/s. The wave will reach the opposite shore in 27.4 s, and the run-up height will reach up to 48.8 m. As the wave, with an average velocity of 11.6 m/s in the reservoir, propagates toward the dam body, its height will decrease, and a 3.7-m-high wave will hit the dam in 155 s. A validation analysis performed using empirical equations and laboratory model tests indicates small differences in the results. The main reason for these differences is that the evaluation of wave properties is independent of the type of mass movement in empirical methods. A proper stability analysis is required to have a better estimation of the volume and the velocity of the sliding mass. [ABSTRACT FROM AUTHOR]

Of the natural hazards in Turkey, landslides are the second most devastating in terms of socio-economic losses, with the majority of landslides occurring in the Eastern Black Sea Region. The aim of this study is to use a statistical approach to carry out a landslide susceptibility assessment in one area at great risk from landslides: the Sera River Basin located in the Eastern Black Sea Region. This paper applies a multivariate statistical approach in the form of a logistics regression model to explore the probability distribution of future landslides in the region. The model attempts to find the best fitting function to describe the relationship between the dependent variable, here the presence or absence of landslides in a region and a set of independent parameters contributing to the occurrence of landslides. The dependent variable (0 for the absence of landslides and 1 for the presence of landslides) was generated using landslide data retrieved from an existing database and expert opinion. The database has information on a few landslides in the region, but is not extensive or complete, and thus unlike those normally used for research. Slope, angle, relief, the natural drainage network (including distance to rivers and the watershed index) and lithology were used as independent parameters in this study. The effect of each parameter was assessed using the corresponding coefficient in the logistic regression function. The results showed that the natural drainage network plays a significant role in determining landslide occurrence and distribution. Landslide susceptibility was evaluated using a predicted map of probability. Zones with high and medium susceptibility to landslides make up 38.8 % of the study area and are located mostly south of the Sera River Basin and along streams. [ABSTRACT FROM AUTHOR]

This paper describes the cut slope stability problems of southern engineered slopes along 57 km long Mersin-Tarsus Motorway. While the northern slopes were slipping during and following construction, the stability problems occurred at southern slopes after heavy rains in December 2001. The most recent slope stability problem took place on chainage at the km 10+800 embankment on 9 April 2009. About 3.62 × 10 m soil materials have currently slipped at 60 different location. After the occurrence of slides, different remedial methods (reshaping slopes, soil improvements, etc.) have been applied to stabilize the slipped slopes. The slope stability studies were carried out using back analysis to determine the slope failure mechanisms and to estimate effective shear strength parameters. Pore water pressures increase following intense rainfall events and cause reduced resistance to shear strength at the engineered slopes. In addition, the affects of the static and dynamic parameters to analyse the state of the slope after excavation were investigated and possible remedies to improve the state (toe rockfill and retaining wall) were assessed for motorway slopes through determining the slope stability with water parameter and seismic loading, separately and together. The results of the stability analysis have exhibited that a good drainage system and retaining wall prevents the motorway slope slides. [ABSTRACT FROM AUTHOR]

Based on morphobathymetric and seismic reflection data, we studied a large landslide body from the eastern Sea of Marmara (NW Turkey), along the main strand of the North Anatolian Fault, one of the most seismically active geological structures on Earth. Due to its location and dimensions, the sliding body may cause tsunamis in case of failure possibly induced by an earthquake. This could affect heavily the coasts of the Sea of Marmara and the densely populated Istanbul Metropolitan area, with its exposed cultural heritage assets. After a geological and geometrical description of the landslide, thanks to high-resolution marine geophysical data, we simulated numerically possible effects of its massive mobilization along a basal displacement surface. Results, within significant uncertainties linked to dimensions and kinematics of the sliding mass, suggest generation of tsunamis exceeding 15–20 m along a broad coastal sector of the eastern Sea of Marmara. Although creeping processes or partial collapse of the landslide body could lower the associated tsunami risk, its detection stresses the need for collecting more marine geological/geophysical data in the region to better constrain hazards and feasibility of specific emergency plans. [ABSTRACT FROM AUTHOR]

Landslides occur when masses of rock, earth, and other debris move down a slope. The slope of an area is directly responsible for the magnitude of the landslide. Being able to identify regional locations more likely to be impacted by landslides is essential if interventions to prevent loss of life and liberty are to be implemented. To further this objective, studies have been carried out using deep learning methods to assess the likelihood of landslides in a localized area. This study seeks to illuminate the reliability in using the deep learning method to effectively detect landslide zones for the purpose of enacting proactive interventions. Pre-trained models of Resnet-50, VGG-19, Inception-V3, and Xception, all of which are established deep learning approaches, were used to automatically detect regional landslides and then compare results. In addition, Grad-CAM, Grad-CAM + + , and Score-CAM visualization techniques were considered depending on the deep learning methods used to accurately predict the location of landslides. The present research focuses on the landslides that took place in the Gündoğdu area of Rize, a city on the Black Sea cost of Turkey, from August 26 to 27, 2010, where unfortunately a significant number of individuals lost their lives. As a large number of landslide scene images are needed in order to facilitate a learning model's deep learning, images from the area were obtained by aircraft and then organized as a dataset. Non-landslide scenes were added as a separate class in the training dataset to estimate the landslide regions more accurately. In total, 80% of the data will be used for training the model, while 20% will be used for testing the model that is built out of it. The experimental results were evaluated with the receiver operating curves and f1-score applicable to landslide detection characteristics. Obtained results show that both Resnet-50 and VGG-19 had a success rate of over 90%. Results also effectively demonstrate how the best visualization techniques for localizations are Grad-CAM and Score-CAM. [ABSTRACT FROM AUTHOR]

A number of new winter sports facilities were constructed in the city of Erzurum for 2011 FISU—Universiade Winter Games, some of which constituted the first examples in Turkey. One of those is the ski-jumping complex, which hosts 5 runways along with a cluster of structures in various sizes and annexes, complementing the runways. On the northern slope of Kiremitlik Hill, where the complex is situated, a landslide occurred on 15th July of 2014, leading into complete collapse of the runways and major damage to the entire facility. This study presents a technical summary and forensic analysis of the formation of this natural hazard to illuminate the causes that cumulatively led to this engineering failure that created a massive material loss. In this work, we investigate the issue from geological, geophysical and geotechnical perspectives to illuminate the true causes of this engineering failure. We also hope that this technical evaluation provides an example for engineers as well as public administrators not to overlook the critical ground conditions and well-established design principles of civil engineering. [ABSTRACT FROM AUTHOR]

Uzungöl settlement and Lake Uzungöl are located in the south of Çaykara, Trabzon, Eastern Black Sea region, and are an important tourist destination in Turkey, with natural beauty and rich flora. However, the settlement and the lake were formed by a historical landslide that covered the front of the Haldizen stream. Residential buildings, tourist facilities, transportation routes, and agricultural activities are located on ground that consists of the material that accumulated from the landslide. In this study, a geophysical investigation using integrated shallow seismic methods was carried out in Uzungöl settlement to provide detailed scientific imaging data on the structure of the subsurface, the physical properties of the soil and rock, the bedrock topography, and the vertical and lateral variation in the landslide deposits. For this purpose, seismic refraction and active and passive multichannel surface wave data were collected from 16 profiles in four separate zones designated according to the agricultural activity and geomorphology of the area. In addition, an electrical resistivity tomography survey of a profile was carried out to determine the reason for low-velocity anomalies such as cavities or man-made voids appearing in P-wave velocity–depth sections and underground water content. After applying basic processes including trace killing/editing, random noise filtering of the data, and amplitude balancing to all seismic data, 2D P-wave velocity–depth sections obtained by tomographic inversion, 1D S-wave velocity–depth profiles, and 2D S-wave velocity–depth sections were generated via analysis of MASW and ReMi data. P- and S-wave velocity–depth sections generally demonstrate three main lithological units in the area: the soil (Vp = 300–600 m/s, Vs = 195–350 m/s and H = 0–2.5 m), the landslide material (Vp = 600–2400 m/s, Vs = 350–680 m/s and H = 2.5–15 m), and the bedrock (Vp > 2400 m/s, Vs > 680 m/s and H ≥ 15 m). In particular, the landslide material exhibits variable thickness from profile to profile and represents the complexity of the subsurface. However, we observed that the deposit thickness increases close to the lake. It was determined that the high seismic velocities of the landslide deposits are attributable to the densely packed deposits and the primarily dry or very poor underground water, according to electrical resistivity tomography results. Moreover, the top of the bedrock is characterized by soft rock, and the deeper part of the bedrock is harder and more compact. We believe that this information will be a useful contribution to geotechnical project development and risk mitigation in the Uzungöl area. [ABSTRACT FROM AUTHOR]

Owing to the increase in population, transportation has become one of the major research topics. Among existing transportation systems, railway is one of the most economic and fast systems, and therefore, there has been an increase in new railway constructions in recent years. In Turkey, the longest railway tunnels, the Bahce–Nurdag high-speed rail tunnels, are under construction in the southern part of the country. This twin tubes tunnels are approximately 10 km in length, and they are excavated using tunnel boring machines (TBM). The tunnel route locates in the East Anatolian Fault Zone and the portal region is composed of debris and old landslide deposits. For this reason, mitigating the potential landslide hazard is critical for the tunnel. Therefore, the present study investigates the TBM tunnelling–landslide relationship by employing 3D numerical analyses. The analyses show that the last 600 m of the tunnel has a potential landslide hazard and some additional measures should be considered along this part to ensure tunnel safety. The tunnel conditions are highly complex, and thus it is an interesting case for tunnel engineers. [ABSTRACT FROM AUTHOR]

This study was carried out for determining the type, and factors of mass movements occurred in Upper Eocene-Lower Miocene mudstone and sandstone alternation (with varying ratios) of the Elmalı Formation. Those sediments crop out in a vast area in SW Turkey. The main mass movement type is determined as an earthflow understanding of tilting trees, electric pole and bumpy topography. Locally, complex mass wasting including rotational landslide with various sizes, creep, earthflow and translational movement were also determined during the field study. They are threatening people's life and property. Slope inclination, bed attitudes, joint measurement, hydrogeological observations, in situ strength measurements, geophysical application and rock sampling were performed during the field analysis. In addition, petrographic investigations, XRF and XRD analyses were performed for determining the contents of sample. Basic physico-mechanical properties, including specific gravity, porosity, Atterberg limits of samples were determined in the laboratory. Tectonic history was responsible from sheared, overturned, faulted and fractured lithology. The chaotic mudstone behaves like soil mass on hard-durable sandstone beds. Mid to high inclined slope promote the earthflow. In addition, the surface and ground water increase unstable mass weight and act as a lubricant on durable sandstone, which promote earthflow. The toe of the slope eroded and removed by streams. Thus, the earthflow continues on slope. In addition, local disturbance due to human impact (road cut, settlements, garden opening) caused small-scale but more dangerous complex mass movement. [ABSTRACT FROM AUTHOR]

In this study, it was aimed at evaluating the slope stability conditions in a residential area exposed to two landslides in the past by using two- and three-dimensional limit equilibrium analyses. Two separate, but interdependent, landslides were observed in the investigated area. In 1992 and 1994, two landslides occurred in the region after heavy precipitation and caused damages on the houses and infrastructures. An extensive field work was performed to obtain input parameters for the analyses. In addition, an unmanned aerial vehicle was flown to obtain a three-dimensional view of the landslide area for better understanding of the past failures. The landslides occurred in a flysch-type material representing complex geological characteristics. Hoek–Brown failure criterion and Geological Strength Index were chosen for the strength and visual definition of the geological unit. Since the landslide triggering factor was precipitation, the analyses were focused on the water conditions causing the failure. Sensitivity and back-analyses were performed to obtain the conditions of failure. It was revealed that a high pore pressure ratio was needed to trigger the landslides. However, the second landslide was failed with a lower pore water pressure and the current topography was determined to be on the edge of failure with a slight increase in the pore pressure ratio. In other words, the study area was still found to be prone to possible landslides in the future. [ABSTRACT FROM AUTHOR]

Landslide database construction is one of the most crucial stages of the landslide susceptibility mapping studies. Although there are many techniques for preparing landslide database in the literature, representative data selection from huge data sets is a challenging, and, to some extent, a subjective task. Thus, in order to produce reliable landslide susceptibility maps, data-driven, objective and representative database construction is a very important stage for these maps. This study mainly focuses on a landslide database construction task. In this study, it was aimed at building a representative landslide database extraction approach by using Chebyshev theorem to evaluate landslide susceptibility in a landslide prone area in the Western Black Sea region of Turkey. The study area was divided into two different parts such as training (Basin 1) and testing areas (Basin 2). A total of nine parameters such as topographical elevation, slope, aspect, planar and profile curvatures, stream power index, distance to drainage, normalized difference vegetation index and topographical wetness index were used in the study. Next, frequency distributions of the considered parameters in both landslide and nonlandslide areas were extracted using different sampling strategies, and a total of nine different landslide databases were obtained. Of these, eight databases were gathered by the methodology proposed by this study based on different standard deviations and algebraic multiplication of raster parameter maps. To evaluate landslide susceptibility, Artificial Neural Network method was used in the study area considering the different landslide and nonlandslide data. Finally, to assess the performances of the so-produced landslide susceptibility maps based on nine data sets, Area Under Curve (AUC) approach was implemented both in Basin 1 and Basin 2. The best performances (the greatest AUC values) were gathered by the landslide susceptibility map produced by two standard deviation database extracted by the Chebyshev theorem, as 0.873 and 0.761, respectively. Results revealed that the methodology proposed by this study is a powerful and objective approach in landslide susceptibility mapping. [ABSTRACT FROM AUTHOR]

In the literature, different sampling strategies (such as landslide area, seed cell, scarp, point) have been applied to landslide susceptibility mapping studies. Landslide sampling strategy should reflect the pre-failure conditions of failures. Hence, researchers tried to develop sampling methods to provide pre-failure conditions. The main purpose of this study was to modify the seed cell sampling strategy for landslide susceptibility evaluations. Furthermore, landslide susceptibility maps were produced using two different sampling strategies (seed cell and landslide area), and compared in terms of their results. In accordance with these purposes, the eastern part of the Gallipoli Peninsula (Canakkale, Turkey) was selected as the study area in which to apply these two sampling strategies. For the seed cell sampling strategy, different random samplings were prepared by considering different buffer distances and different spatial resolutions. Sensitivity analyses were carried out using the landslide area (with depletion and accumulation zones) and samples and seed cells were acquired from different buffer zones with respect to different resolutions. The spatial performance of the landslide susceptibility maps of both sampling strategies were evaluated using area under the ROC curve (AUC) values. The resulting AUC results obtained from different random samplings and different spatial resolutions indicated that the appropriate buffer distance used to produce seed cells for the evaluation of landslide susceptibility maps in medium scale should be approximately 50 m. [ABSTRACT FROM AUTHOR]