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, 600 100 noujasphy@gmail.com 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 ~100-150 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 0.5 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 -168900 173600 2300 N 0.4 Km North of VN1 VN3 -240900 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 = 0.004 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 = -53300 m3/year, Gross drift = 92828 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 2014. 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 = 0.004 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 = 0.004 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), 2006. U.S Army Coastal Engineering Research Centre, Washington, D.C. (6 volumes). DHI, 2014. 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. 54-61. Rao, R. V., Ramana Murthy, M.V., Manjunath Bhat, Reddy, N.T., 2009. Littoral sediment transport and shoreline changes along Ennore on the southeast coast of India: Field observations and numerical modeling, Geomorphology, 112, 158-166 Shamji, V.R., Hameed, T.S.S., Kurian, N.P., Thomas, K.V., 2010. Application of numerical modelling for morphological changes in a high-energy beach during the south-west monsoon. Curr. Science 98 (5), 691-695 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