1. Longshore sediment transport estimation using a oneline numerical model along Vengurla coast, South Maharashtra
V. Noujas, R.S. Kankara and K. Rasheed
ICMAM Project Directorate, MoES, Chennai,
Abstract
The physical processes associated with sediment transport around the breaker zone are highly complex. Sediment transport can occur alongshore or cross-shore depends upon incident wave direction. Longshore sediment transport is primarily associated with wave- induced longshore currents. Accurate knowledge of longshore sediment transport in the littoral zone is essential for managing and developing any coastal zone. Numerical models provide a useful tool to understand and investigate various processes responsible for sediment transport in holistic manner. A one dimensional LITPACK model has been implemented along Vengurla coast to identify the critical input parameters and data requirement to estimate the longshore sediment transport. Several experiment were carried out and found that cross-shore profile, wave climate, coastline orientation and sediment characteristics were very important for sediment transport estimation. Accordingly data have been collected for set up model for one year. The model results were analyses for monthly/seasonal basis. It is observed that depth of closure was 8 m and maximum sediment transport occurs ~ m from coastline which falls at a depth of 3 to 5 m during May to July months. Coastline angle changes by 10 net sediment transport rate changes around 80 m3/day. Nearshore steepness of southern sector is 1:50 and northern sector is 1:67 and hence sediment transport rate is higher in southern sector of the study region. The model result shall be further used for shoreline and morphological evolution model studies along this sector.
1. Introduction
The physical processes associated with sediment transport around the breaker zone are highly complex. The wave induced spatially varying currents and highly irregular flows make this environment extremely dynamic. Waves breaking near the coast mobilize the sediments around the breaker point and the currents generated by the waves transport the sediments along and across the coast. A thorough knowledge of sediment transport in the littoral zone is essential for implementing any structure on the coast (CEM, 2006). Estimation of Sediment transport along the world has been carried out by various researchers using different approximation. The measured beach profiles in regular intervals were used by some researchers. Mathematical/Emperical methods using measured wave data are adopted by some other researchers and organizations. Nearshore measured wave data is not available for most of the locations and hence the hind-cast wave parameters from the regional spectral model were also used for sediment drift estimation. Third generation numerical models were used for sediment transport estimation by various researchers (Rao et al., 2009; Shamji et al., 2010; Noujas et al., 2014).
The present study computed the longshore sediment transport rate using well established numerical model. The sediment transport estimated using Hr interval of one year wave data. The sensitive analysis were also carried out to find out the exact contribution of parameters such as coastline orientation, bathymetry, wave height, wave direction, wave period, grain diameter and bed roughness for sediment transport.
4.2 Model run for extreme wave events
Fig. 9 Net drift along different locations during extreme events
Fig. 4 Comparison of simulated SWAN Tz with measured data
Table 2. Sediment transport rates for different coastline angle
Location
Net Drift (m3)
Gross drift (m3)
Coastline angle
Remarks VC
2298
42760
2480 N
1.8 Km south from northern boundary
VS1
2132
42540
1 Km south of VC
VS2
2045
42920
1 Km south of VS1
VS3
283300
2730 N
1 Km south of VS2
VN1
-38180
54830
2430 N
0.6 Km North of VC
VN2
173600
2300 N
0.4 Km North of VN1
VN3
240900
2200 N
0.2 Km North of VN2
Fig. 5 Comparison of simulated SWAN wave direction with measured data 1 5 9
2. Study region
4.3 Model run for one year
Correlation co-efficient Hs is of 0.97 and that of Tz and wave direction are 0.51
4. Results & Discussion
Hrms = 1.2 m, Dm = 2390
Tz = 5.8 s, Duration = 83 days, d50 = 0.2 mm,
Bed roughness = m
Net drift (m3)
Fig. 6 sediment drift variation for coastline angle change
4.1 Sensitive Analysis
Table 3. Annual sediment drift along Vengurla coast
Month
Net drift (m3/month
Accumulated drift (m3 )
January
-2839
February
-677
-3516
March
-1420
-4936
April
674
-4262
May
2384
-1878
June
8450
6572
July
-44944
-38372
August
-18052
-56424
September
-5132
-61556
October
5196
-56360
November
1944
-54416
December
1116
-53300
Net sediment drift = m3/year, Gross drift = m3/year
Maximum sediment transport obtained during the month of July and towards south
The sediment transport is southward during January to March with negligible magnitude
Maximum northerly transport obtained during the month of June and October
When coastline angle is changes 1 approximately 77 m3/day change in sediment transport occurs 2 6 10
3. Methodology
Sediment transport along the coast under study has been computed with LITDRIFT module of LITPACK software developed by Danish Hydraulic Institute (DHI, 2014). LITDRIFT provides a detailed deterministic description of the cross-shore distribution of the longshore sediment transport and calculates the net/gross littoral transport for a section of coastline over a specific design period. The major input for LITDRIFT model is bathymetry, which is given as cross-shore profile and it is collected during February 2015 using echo-sounder. The nearshore wave climate derived from WAVEWATCH-SWAN coupled model. The ECMWF wind has given the input for coupled model. The SWAN model is calibrated with nearshore wave data collected during the year In addition to these inputs, sediment characteristics are also given as an input for LITDRIFT model.
Hrms = 1.2 m
Coastline angle = 2480
Tz = 5.8 s, Duration = 83 days, d50 = 0.2 mm,
Bed roughness = m
Initial wave angle =239
Wave angle change
Net drift (m3)
Fig. 10 Net drift along cross-shore profile
Fig. 7 sediment drift variation for wave angle change
wave angle is changes 10 approximately 71 m3/day change in sediment transport occurs
5. Conclusions
Coastline angle and wave direction is more sensitive to sediment transport.
Sediment transport is increasing for increasing wave height and wave period and decreasing with bed roughness.
The depth of closure is about 8m along the study region.
The net sediment transport is towards south and magnitude of 0.53 x105 m3/yr and Gross sediment transport is 0.9 x 105 m3/yr.
The model results can further used for shoreline evolution modelling along this sector.
Table 1. Role of cross-shore profiles for sediment transport
Profile name
Net drift
(m3)/period*
Location description in Km#
Remarks
VN3
48136
0.6
Hrms = 1.2 m
Tz = 5.8 s
Wave direction = 2390
Coastline angle = 2480
d50 = 0.2 mm, Bed roughness = m
duration = 83 days
VN2
49421
0.8
VN1
48782
1.2 VC
48541
1.8
VS1
49904
2.8
VS2
49444
3.8
VS3
50273
4.8
* period = 83 days, # distance from northern boundary
Fig. 1 Bathymetry & cross-shore profile extracted locations 3 7 11
Fig. 3 Comparison of simulated SWAN Hs with measured data
Fig. 2 Cross-shore profiles along Vengurla
3.1 Model Inputs
Southern sector cross-shore profiles are much steeper than northern sector profiles hence sediment transport in southern sector is comparatively higher
6. References
Coastal Engineering Manual (CEM), U.S Army Coastal Engineering Research Centre, Washington, D.C. (6 volumes).
DHI, User manual and reference guide for LITPACK and MIKE 21. Danish Hydraulic Institute, Denmark.
Noujas, V., Thomas, K.V., Sheela Nair, L., Shahul Hameed, T.S., Badarees, K.O and Ajeesh, N.R (2014). Management of Shoreline Morphological Changes Consequent to Breakwater Construction. Indian Journal of Geo Marine Sciences, 43 (1), pp
Rao, R. V., Ramana Murthy, M.V., Manjunath Bhat, Reddy, N.T., Littoral sediment transport and shoreline changes along Ennore on the southeast coast of India: Field observations and numerical modeling, Geomorphology, 112,
Shamji, V.R., Hameed, T.S.S., Kurian, N.P., Thomas, K.V., Application of numerical modelling for morphological changes in a high-energy beach during the south-west monsoon. Curr. Science 98 (5),
Net drift (m3 )
Acknowledgements
Authors are thankful to Project Director ICMAM for encouragement and support for this work. Authors are also thank to Mr. G. Udhaba Dora, Project Scientist, ICMAM PD for providing SWAN modelled nearshore wave climate, and Mr. Anoop, Research Scholar, NIO for supporting field data collection and processing bathymetric data. Authors are greatly acknowledged the project staffs, who have participated in field data collection.
Fig. 8 Role of various parameters for sediment transport
Wave direction is more sensitive for sediment transport. Followed by wave height and then wave period.
Comparatively grain diameter and bed roughness is less contributing sediment transport. 4 8 12