Recent tsunami events have inflicted devastating damage to coastal communities. Existing design standards provide a certain level of evaluation of tsunami effects such that critical infrastructure can be designed to resist tsunamis. Tsunami momentum flux, used to design structures is a function of water level height and velocity of tsunami bores. Understanding tsunamis and developing mitigation measures is essential. So far, some mitigation measures have been suggested, and to improve them, further investigations are required. The design of tsunami inundation effects mitigation canals is one of the suggested solutions which has received limited attention. The first objective of this study was to investigate the effects of a rectangular canal on the hydrodynamics of turbulent bores before and after the canal by conducting a series of physical experiments. A dam-break wave was used to simulate the tsunami-like turbulent waves passing over a smooth and horizontal surface, in the presence and/or absence of a canal. Three canal water depths were used to model shallow, moderate, and deep conditions, and three canal widths were also selected to model narrow to wide conditions while the dam break waves were generated from three different impoundment depths in a reservoir located upstream of the canal. The dam-break wave propagation over a horizontal, dry, and smooth bed revealed four regimes describing the variations of bore height with time. The time to reach the maximum bore height and the quasi steady-state regime were correlated with each impoundment depth and an empirical formulation was proposed to estimate the onset of the quasi steady-state flow. The maximum bore heights measured before and after the mitigation canal location were approximately 40 % and 50 % respectively, higher compared with those recorded in the corresponding tests without the presence of a canal. The second objective of this study was to experimentally investigate the effects of canal depth on the time history of bore height and its velocity. The experimental results were used for calibration and validation of a developed numerical model. The rapid release of an upstream impoundment water depth was employed to generate a bore analogous to a tsunami-induced inundation. The time histories of wave heights and velocity were measured upstream and downstream of the canal. The recorded time-series of the water surface levels and velocities were compared with the simulation results and good agreement was found between experimental and numerical water surface profiles using a Root Mean Square Error (RMSE) and the Relative Error. Three turbulence models:, namely the standard k-ε, the Realizable k-ε, and the RNG k-ε were tested, and it was found that all turbulence models perform well but the standard k-ε model provided satisfactory accuracy. The velocity contour plots for shallow, medium, and deep mitigation canals showed the formation and evolution of jets of different characteristics. The energy dissipation and air bubble entrainment of the tsunami bore, as it plunged into a canal, increased as the canal depth increased, and the jet flow of the maximum bore velocity decreased with increased canal depth. It was found that the eye of the vortex in the canal moved steadily in the downstream direction. Generally, the bore fully plunged almost nearly into the middle of the canal and started to divide into two small vortices. The third objective of this study dealt with a sequence of numerical experiments conducted to investigate the impact of mitigation canals on the hydrodynamics of a tsunami-like turbulent bore moving across a flat bed. The effects of mitigation canal depth and its orientation on the reduction of maximum specific momentum and energy of turbulent bores crossing over it were investigated numerically. Variations in the ratio between the downstream and upstream maximum specific momentum and mean flow energy decreased as the canal depth increased, and the time history of the mean flow energy over a canal with a rectangular endwise profile revealed that the canal depth affects the jet stream of the maximum mean flow energy. As the canal depth increased, the period of time needed to dissipate the area of the jet stream with the maximum turbulent kinetic energy, vorticity, and energy dissipation rate decreased. Both the angled and perpendicular to flow direction canals caused the maximum specific momentum and energy of the turbulent bore to decrease downstream of the canal. The specific momentum and energy achieved their highest values for a canal orientation of 45º. The greatest reductions in maximum specific momentum for turbulent bores over canals with different depths and orientations were achieved for 𝜃 = 30°.

Tsunamis are characterized as shallow water waves, with long periods and wavelengths. They occur by a sudden water volume displacement. Earthquake is one of the main reasons of a tsunami development. Historical data for an observation period of 3500 years starting from 1500 B.C. indicates that approximately 100 tsunamis occurred in the seas neighboring Turkey. Historical earthquake and tsunami data were collected and used to develop two artificial neural network models to forecast tsunami characteristics for future occurrences and to estimate the tsunami return period. Artificial Neural Network (ANN) is a system simulating the human brain learning and thinking behavior by experiencing measured or observed data. A set of artificial neural network is used to estimate the future earthquakes that may create a tsunami and their magnitudes. A second set is designed for the estimation of tsunami inundation with relation with the tsunami intensity, the earthquake depth and the earthquake magnitude that are predicted by the first set of neural networks. In the case study, Marmara and Aegean regions are taken into consideration for the estimation process. Return periods including the last occurred earthquake in the Turkish seas, which was the izmit (Kocaeli) Earthquake in 1999, were utilized together with the average earthquake depths calculated for Marmara and Aegean regions for the prediction of the earthquake magnitude that may create a tsunami in the stated regions for various return periods of 1-100 years starting from the year of 2004. The obtained earthquake magnitudes were used together with tsunami intensities and earthquake depth to forecast tsunami wave height at the coast. It is concluded that, Neural Networks predictions were a satisfactory first step to implement earthquake parameters such as depth and magnitude, for the average tsunami height on the shore calculations.