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The hindcast related deep-water wave-rose is presented in Fig. 7. Notably, the wave climate is seen to be fairly mild in this region with the predominant direction of waves from SSE Monsoon direction. The morphological and hydrodynamic modeling of the aforementioned inlet was performed, using MIKE Zero software package. For offshore wave climate, Hindcast results from the Iranian Seas Wave Modeling (ISWM) project were incorporated in the present study. In short, wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF), lasting for over an eleven years period along Iranian coastal waters, were used to drive the Mike21 SW spectral wave generation and propagation model with the modeling, calibration and verification methodology, as described by Golshani et. al. (2007) for the Caspian Sea region. In order to correlate the significant waveheight and mean wave period, To2, a regression analysis was performed for ISWM wave data leading to the following equation for wind- generated waves:

Figure 7 The hindcast related deep-water wave-rose is presented in Fig. 7. Notably, the wave climate is seen to be fairly mild in this region with the predominant direction of waves from SSE Monsoon direction. The morphological and hydrodynamic modeling of the aforementioned inlet was performed, using MIKE Zero software package. For offshore wave climate, Hindcast results from the Iranian Seas Wave Modeling (ISWM) project were incorporated in the present study. In short, wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF), lasting for over an eleven years period along Iranian coastal waters, were used to drive the Mike21 SW spectral wave generation and propagation model with the modeling, calibration and verification methodology, as described by Golshani et. al. (2007) for the Caspian Sea region. In order to correlate the significant waveheight and mean wave period, To2, a regression analysis was performed for ISWM wave data leading to the following equation for wind- generated waves:

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Tang inlet, located on the south-eastern shores of Iran on the northern shoreline of the Gulf of the Oman, provides a channel between the fairly narrow Tang bay and the Gulf of Oman (Fig. 1). Figure 1. Location of Tang inlet.
Tang inlet, located on the south-eastern shores of Iran on the northern shoreline of the Gulf of the Oman, provides a channel between the fairly narrow Tang bay and the Gulf of Oman (Fig. 1). Figure 1. Location of Tang inlet.
Table 1: Shoreline erosion/accretion areas outside of bay from 1966 to 2009.
Table 1: Shoreline erosion/accretion areas outside of bay from 1966 to 2009.
Figure 3. Sedimentation pattern inside the bay, from 1993 to 2000 based hydrographical charts.
Figure 3. Sedimentation pattern inside the bay, from 1993 to 2000 based hydrographical charts.
Figure 5. Sedimentation pattern inside the bay, from 2000 to 2009 based hydrographical charts. Figure 5. Sedimentation pattern inside the bay, from 2000 to 2009 based hydrographical charts
Figure 5. Sedimentation pattern inside the bay, from 2000 to 2009 based hydrographical charts. Figure 5. Sedimentation pattern inside the bay, from 2000 to 2009 based hydrographical charts
The eastern channel, according to Fig. 6c, has eroded by more than 250,000 m? or 30,000 m*/yr, in part aiding the growth of the eastern accretion pattern and the rest being carried away by the outside littoral currents, either to the east or in front of the rock formation away toward the west.
The eastern channel, according to Fig. 6c, has eroded by more than 250,000 m? or 30,000 m*/yr, in part aiding the growth of the eastern accretion pattern and the rest being carried away by the outside littoral currents, either to the east or in front of the rock formation away toward the west.
Wave-breaking was also incorporated, also for estimating wave-driven currents related to sediment transport characterization of the site. For this purpose, the formula of Battjes and Janssen (1978) was employed by taking the default parameter values as recommended in the user manual of the model. As for the model solution method, a Pade type approximation was incorporated. The bed roughness representing bottom friction was considered as a calibration parameter. The model was run for all contributing wave-directions, extending from east to west, in seven intervals of 22.5 degrees. The simulation result from the dominant SE direction is presented in Fig. 8. Evidently, various proposed new fishery port layouts are overlaid on the simulation result so that wave characteristics next to breakwaters for each layout could be determined and further used for site selection and preliminary design purposes.
Wave-breaking was also incorporated, also for estimating wave-driven currents related to sediment transport characterization of the site. For this purpose, the formula of Battjes and Janssen (1978) was employed by taking the default parameter values as recommended in the user manual of the model. As for the model solution method, a Pade type approximation was incorporated. The bed roughness representing bottom friction was considered as a calibration parameter. The model was run for all contributing wave-directions, extending from east to west, in seven intervals of 22.5 degrees. The simulation result from the dominant SE direction is presented in Fig. 8. Evidently, various proposed new fishery port layouts are overlaid on the simulation result so that wave characteristics next to breakwaters for each layout could be determined and further used for site selection and preliminary design purposes.
Figure 9. PMS wave transformation modeling result for SE wave direction around the natural reef for both cases of including and excluding port layout. modeling. For calculation of wave motion outside the boundary layer, the semi-empirical Doering and Bowen (1995) approach was incorporated which is valid for all depths and both breaking and non- breaking types of waves. Moreover, the effect of streaming was taken into account by including convective terms in the solution method. The bed concentration was determined by a deterministic approach in all of the simulations. As per other parameters, the default values recommended by LITPACK model were employed. Sediment roses obtained for five sample points are presented in Fig. 10, indicating most dominant transport direction being from South-Easterly sector.
Figure 9. PMS wave transformation modeling result for SE wave direction around the natural reef for both cases of including and excluding port layout. modeling. For calculation of wave motion outside the boundary layer, the semi-empirical Doering and Bowen (1995) approach was incorporated which is valid for all depths and both breaking and non- breaking types of waves. Moreover, the effect of streaming was taken into account by including convective terms in the solution method. The bed concentration was determined by a deterministic approach in all of the simulations. As per other parameters, the default values recommended by LITPACK model were employed. Sediment roses obtained for five sample points are presented in Fig. 10, indicating most dominant transport direction being from South-Easterly sector.
Fig. 10. Sediment-rose plot for five points along the coast.
Fig. 10. Sediment-rose plot for five points along the coast.
Figure 11. Accumulated net annual littoral drift plot for two sample cross-sections.
Figure 11. Accumulated net annual littoral drift plot for two sample cross-sections.
Figure 12. Coastline evolution in Tang region over the time-span of 40 years. Furthermore, the shoreline evolution was modeled using the one-line morphological module of LITPACK known as LITLINE. The effect of current and sedimentation from the bay were included as a source term in the model in complimentary model runs. Annual sediment yield potential from Tang watershed is estimated to be between 44000 and 74000 m*/yr, the maximum of which was incorporated in the one-line model rather conservatively. The height of active beach was considered to be 3 m. Moreover, the presence of the natural breakwater was simulated. For solution parameters, the recommended default values of LITLINE were chosen. The coastline evolution for a time span of forty years, considered as fishery port’s lifetime, was modeled and is presented in Fig. 12. Apart from sedimentation around the eastern ebb-tidal channel bar no distinct change in coastline is observed, which attest observations from satellite images concerning dynamic equilibrium of the beach on the one hand, and an explanation for the westward delta breaching of the channel on the other.
Figure 12. Coastline evolution in Tang region over the time-span of 40 years. Furthermore, the shoreline evolution was modeled using the one-line morphological module of LITPACK known as LITLINE. The effect of current and sedimentation from the bay were included as a source term in the model in complimentary model runs. Annual sediment yield potential from Tang watershed is estimated to be between 44000 and 74000 m*/yr, the maximum of which was incorporated in the one-line model rather conservatively. The height of active beach was considered to be 3 m. Moreover, the presence of the natural breakwater was simulated. For solution parameters, the recommended default values of LITLINE were chosen. The coastline evolution for a time span of forty years, considered as fishery port’s lifetime, was modeled and is presented in Fig. 12. Apart from sedimentation around the eastern ebb-tidal channel bar no distinct change in coastline is observed, which attest observations from satellite images concerning dynamic equilibrium of the beach on the one hand, and an explanation for the westward delta breaching of the channel on the other.
Figure 13. Numerical modeling domain for tidal simulation (left) and one month tidal measurements at boundary of the domain (right). monitoring of the eroded area as presented in Fig. 6c. As for the ebb half-cycle, numerical modeling results show two regions for the occurrence of maximum current velocity, one located at inlet throat and the other at the opening of the eastern channel that agrees well with observations as explained in site monitoring section. Moreover, it is observed that the value for maximum velocity exceeds 1 m/s which is required to prevent the closure of the inlet system (Escoffier 1940).
Figure 13. Numerical modeling domain for tidal simulation (left) and one month tidal measurements at boundary of the domain (right). monitoring of the eroded area as presented in Fig. 6c. As for the ebb half-cycle, numerical modeling results show two regions for the occurrence of maximum current velocity, one located at inlet throat and the other at the opening of the eastern channel that agrees well with observations as explained in site monitoring section. Moreover, it is observed that the value for maximum velocity exceeds 1 m/s which is required to prevent the closure of the inlet system (Escoffier 1940).
Figure 14, A sample numerical modeling current field result for both flood (right) and ebb (left) periods.
Figure 14, A sample numerical modeling current field result for both flood (right) and ebb (left) periods.
Figure 15. Transport capacity rates for flood (right) and ebb (left) cases. CONCLUSIONS
Figure 15. Transport capacity rates for flood (right) and ebb (left) cases. CONCLUSIONS
Related topics:
Inlet dynamics
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