Investigation of near-shore processes along North Goa beaches: A study based on field observations and numerical modelling

Abstract

The dynamic coastal environment comprising of near-shore zone and beach continuously undergoes substantial morphological changes due to man-made and natural processes. These processes are always mutually dependent and therefore understanding their physical mechanisms is complicated. In this study, an attempt has been made to understand the physical interactions between the waves, tides and currents in the near-shore regions of four major tourist beaches of Goa using field measurements and numerical modelling. The state-of-the-art instruments were deployed at 6 m water depth, for a fortnight at each beach for two seasons in 2018. In-situ depth data were collected along the 8 km stretch covering Baga to Sinquerim using a mechanised boat equipped with an Echo sounder and a differential global positioning system. A coupled Delft3D model was set up with the model domain created using in-situ bathymetry soundings, beach profiles’ elevation and naval hydrographic chart data. Model simulations were performed for two seasons (Jan–Feb) for calibration and (Oct–Nov) for validation by forcing the FLOW and WAVE models with time-varying water levels obtained from the TOPEX/POSEIDON global tide model, wave parameters from European Centre for Medium-range Weather Forecasting data and the measured wind data. The model results were validated by comparing the significant wave height, current speed and water level with the in-situ data. From these experiments, it has been observed that near-shore parameters change significantly with the season and are mutually interactive. Especially, the near-shore currents are varying according to the wave heights and water level variations (due to tides). The Delft3D model is capable of addressing the near-shore processes with a good level of accuracy. However, fine-tuning the model parameters with more seasonal data would help in addressing several coastal processes for any future datasets and therefore could be utilised for investigating and forecasting near-shore processes