Improved cross-shore sediment transport relationships and models

A modified nonlinear cross-shore sediment transport relationship is developed based on equilibrium beach profile concepts and dimensional scaling relationships. This nonlinear relationship provides a reasonable explanation for the significantly different time scales of beach evolution evident in various laboratory experiments. To predict a beach profile response under wave action, a finite difference method is applied to solve the sediment transport and continuity equations numerically. The proposed nonlinear model called "CROSS" is calibrated and compared with the commonly employed linear transport relationship using laboratory data. A total of seven large scale wave tank experiments from three different facilities are examined. The results demonstrate that the nonlinear transport model provides overall better predictions than the linear transport equations. The CROSS model and the three other commonly used models are applied to predict beach erosion at Ocean City, Maryland, during the November 11, 1991, and January 4, 1992, storms. Seven survey lines are available for comparison with the numerical simulations. Two versions (2.0 and 3.0) of SBEACH are applied. Among the four models, the CCCL model is the only one overpredicting average dune erosion and the other three models have different degrees of underprediction with SBEACH version 2.0 underpredicting most. Overall, CROSS, EDUNE and SBEACH version 3.0 present reasonable predictions for both dune erosion and the entire profiles. The sensitivity of CROSS to the transport coefficient, active water depth, storm surge levels and the storm wave heights are studied for the storm erosion at Ocean City. It appears that CROSS is very insensitive to the transport coefficient. The subaqueous part of a profile is quite sensitive to the wave height and the subaerial part is less affected. The CROSS model provides better predictions with the ratio of active water depth to incoming wave height of 1 than with the ratio of 1.28, and the 20% increased storm surge yields a better simulation.