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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]

This case study presented herein compares the GIS-based landslide susceptibility mapping methods such as conditional probability (CP), logistic regression (LR), artificial neural networks (ANNs) and support vector machine (SVM) applied in Koyulhisar (Sivas, Turkey). Digital elevation model was first constructed using GIS software. Landslide-related factors such as geology, faults, drainage system, topographical elevation, slope angle, slope aspect, topographic wetness index, stream power index, normalized difference vegetation index, distance from settlements and roads were used in the landslide susceptibility analyses. In the last stage of the analyses, landslide susceptibility maps were produced from ANN, CP, LR, SVM models, and they were then compared by means of their validations. However, area under curve values obtained from all four methodologies showed that the map obtained from ANN model looks like more accurate than the other models, accuracies of all models can be evaluated relatively similar. The results also showed that the CP is a simple method in landslide susceptibility mapping and highly compatible with GIS operating features. Susceptibility maps can be easily produced using CP, because input process, calculation and output processes are very simple in CP model when compared with the other methods considered in this study. [ABSTRACT FROM AUTHOR]