American Journal of Fluid Dynamics
p-ISSN: 2168-4707 e-ISSN: 2168-4715
2018; 8(1): 30-39
doi:10.5923/j.ajfd.20180801.04

Ehsan Isaie Moghaddam 1, Habib Hakimzadeh 2, Mohammad Nabi Allahdadi 3, Ardalan Hamedi 4, Ali Nasrollahi 5
1Faculty of Civil Engineering, Sahand University of Technology, Tabriz, Iran,
2Faculty of Civil Engineering, Sahand University of Technology, Tabriz, Iran
3North Carolina State University, Department of Marine, Earth and Atmospheric Sciences, Raleigh North Carolina, USA
4Head of Civil and Marine Structure of Pishahangan Amayesh Consultant Engineering, Tehran, Iran
5Noandishan Fan va Tejarat Company, Tehran, Iran
Correspondence to: Mohammad Nabi Allahdadi , North Carolina State University, Department of Marine, Earth and Atmospheric Sciences, Raleigh North Carolina, USA.
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Copyright © 2018 by the authors and Scientific & Academic Publishing.
This work is licensed under the Creative Commons Attribution International License (CC BY).
http://creativecommons.org/licenses/by/4.0/

The spectral wave model Mike 21-SW coupled with the hydrodynamics model HD-FM was used to study nearshore wave and wave-induced currents at Ramin Port in the north of the Gulf of Oman with the main objective of prescribing solutions for sedimentation inside the port basins. Computational meshes with triangular elements were used in regional and local scales to determine nearshore wave characteristics and their induced coastal currents. Regional model covering the offshore area and vast areas in the east and west of Ramin Port was successfully evaluated using wave data measured by buoy located at outer tip of eastern Chabahar Bay. Simulation of coastal currents for three different monsoon and non-monsoon wave events that are dominant over the study area showed that coastal currents flow to the port minor basin and form cyclonic genres that contribute in carrying and depositing coastal sediments inside the port basins. Current patterns were in good agreement with historical sedimentation maps of the port basins demonstrating the validity of current and wave simulations.
Keywords: Ramin Port, Wave-induced currents, Sedimentation, Monsoon waves, Numerical modelling
Cite this paper: Ehsan Isaie Moghaddam , Habib Hakimzadeh , Mohammad Nabi Allahdadi , Ardalan Hamedi , Ali Nasrollahi , Wave-induced Currents in the Northern Gulf of Oman: A Numerical Study for Ramin Port along the Iranian Coast, American Journal of Fluid Dynamics, Vol. 8 No. 1, 2018, pp. 30-39. doi: 10.5923/j.ajfd.20180801.04.
= 0.15-0.35 mm, where
is the average diameter of sediment grains). This range of sediment size along with energetic monsoon waves that are predominant over the study area, result high values of Ω when applied in the context of criterion suggested by Masselink and Short [7]. According to this criterion, high values for Ω is an indication that beach is more likely dissipative. The hydrodynamic and coastal morphology along the Iranian coasts on the Gulf of Oman are substantially affected by wave climatology of the Indian Ocean. The spatiotemporal variability of wave regime over the northern Arabian Sea and the Gulf of Oman reveals that the wave parameters and wave-induced currents of the region vary based on a seasonal manner known as monsoons [8, 9]. Annual wind climate over the Gulf of Oman includes northeasterly monsoon winds during December-March, southwesterly monsoon winds during June-September, and local westerly Oman Sea winds during the transitional period between the two monsoons. The latter is associated with northwesterly Shamal winds that normally occur during winter and summer [10, 11]. In addition to the normal annual variations, the northern Arabian Sea and the Gulf of Oman is rarely impacted by tropical storms generated over the Indian Ocean during summer. These tropical storms can cause extreme waves and influence the Iranian coasts of Oman Sea [12]. The seasonal cycle of winds leads to a seasonal cycle of wave field over the study region [13]. The sea state over the Gulf of Oman exhibits multi-peaked wave spectra resulted from a combination of high energy southerly monsoon waves from the Indian Ocean and higher frequency wind waves from west to southwest that are mainly generated during the non-monsoon periods [14].![]() | Figure 2. Windroses for the study area based on observed and modeled data |
![]() | Figure 3. Long-term waveroses at location P1 offshore of Ramin Port based on a) Monitoring (1985-2006) and b) ISWM (1992-2002) hindcast wave data |
![]() | Figure 4. Variations of significant wave height, peak wave period and mean wave direction at the location P1 in 1994 |
![]() | (1) |
. This data is required for further simulation of wave-induced currents by Flow module of Mike 21. This model is a comprehensive system based on numerical solution of incompressible and Reynolds averaged shallow water equations by assuming Boussinesq approximation and hydrostatic pressure [19, 20]:Continuity equation:![]() | (2) |
![]() | (3) |
![]() | (4) |
is water depth, x and y are horizontal Cartesian axes,
and
are depth average horizontal velocity in x and y directions respectively, f is the Coriolis parameter, g is acceleration due to gravity which is 9.81 m2/s,
is water level with respect to still water datum,
is initial water density,
is time-dependent density,
is air pressure,
and
are wind stress components at water surface,
and
are bottom friction components, and
are wave radiation stress components. Model equations are solved for h,
and
on a mesh with triangular elements using a cell-centered finite element method.![]() | Figure 5. a) Computational mesh for the regional model, b) Computational mesh and bathymetry for local model comprising Ramin Port and the coastline around the port |
![]() | (5) |
is mean current speed at the bottom, fc is friction coefficient due to current, k is wave number with the spectral average of
, E(f,θ) is spectral energy at frequency f and direction θ, and d is water depth. For calculation of bed friction coefficient, Nikuradse roughness coefficient with value of 0.065 m was selected. The rate of energy dissipation due to wave breaking within the surfzone is considered using the relationship presented by Battjes and Janssen [21]:![]() | (6) |
![]() | (7) |
![]() | (8) |
is average frequency, Qb the portion of breaking waves in the spectrum, γ is the ratio between the wave height and water depth at the breaking point, and Hrms is the root mean square wave height in the spectrum. In the present study the default values of 1 and 0.85 were used for αBJ and γ respectively.For the purpose of the model verification, simulation results from the regional model were compared to the measured wave data at the location of Chabahar buoy (station P2 in Figure 1). Comparison results for wave height, mean zero-crossing period, and mean wave direction showed that the regional model was successful in reproducing the wave conditions at the location of the buoy (Figure 6). This is a demonstration that the approach used for wave transformation from deep water to the coastal area using a directionally decoupled model is appropriate. Detailed analysis of deep water wave information reveals the monsoon waves with characteristics presented in table 1 (events 1 and 2) have the most contributions in the annual waverose over the study area (Figure 3). In addition, storm events occurred occasionally over the Gulf of Oman during the pre and post monsoon can lead to changes in hydrodynamic pattern and beach morphology of Ramin Port (event 3 in table 1). Boundary conditions for the local model (at location P3) were extracted from the regional model and the coupled wave-flow model was run to determine the coastal flow pattern. Radiation stress field obtained from the local wave transformation model is the driving force of the flow model to simulate wave-induced flow in the nearshore area. Formulations by Smagorinsky and Manning were used to represent horizontal eddy viscosity and bed resistance. Default values were used for the constant for Smagorinsky (0.28 m2/s) formulation and Manning coefficient (0.025m1/3/s).![]() | Figure 6. Comparison between regional model results and measured waves at buoy location (P2) |
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![]() | Figure 7. Simulation results for a) nearshore waves and b) coastal currents for event 1 |
![]() | Figure 8. Simulation results for a) nearshore waves and b) coastal currents for event 2 |
![]() | Figure 9. Simulation results for a) nearshore waves and b) coastal currents for event 3 |