نشریه مهندسی دریا (Sep 2017)
TIDAL EFFECTS ON LONG-TERM MORPHOLOGY BEHAVIOUR IN LARGE TIDAL BASINS
Abstract
Tidal basins are described by major features such as tidal flat, tidal channel, intertidal area, and tidal prism, which have been formulated by some empirical relations based on field observations. Although empirical relations explain some morphological patterns, those are not applicable to all conditions. Due to the lack of observations for different areas and under different geophysical conditions the empirical relations are of limited validity and are not comprehensive. With respect to recent advances in development of numerical models, long-term morphological process-based models are now able to simulate the morphological behaviour of the tidal basins. In this study, we obtain adequate observations of morphological evaluation of tidal basins by establishing a numerical lab to guarantee the reality modeling in various conditions with specific shape of bathymetry.This study aims to evaluate the effects of morphological parameters on tidal basin equilibrium by setting up a numerical lab for the case of Musa Tidal Basin (MTB). Different simulations using a range of major parameters (cohesive material amounts, available sediment volume, sediment size and composition) are also carried out for the MTB case. In order to assess the morphology pattern which is affected by parameter values and to reduce the computational cost of long-term models, efficient scenarios are designed optimize the number of runs. In total, 65 simulations with different combinations of parameter values are carried out. Then the responses are analyzed by statistical approaches to define comprehensive effects of those parameters on the simulated morphological equilibrium. Using the achieved patterns, a method is developed to model the evolution of the MTB in 3000 years. The method is a combination of realistic and deterministic approaches. This methodology improves the long-term results in different conditions, which is confirmed by the comparison of the output and measured data.
