Identifying coastal stretches that are likely to erode under high wave conditions is essential to the coastal management community in addressing beach erosion-related issues. The manuscript presents a case study to predict erosion of a selected beach located on the eastern Indian coast during the 2018 southwest (SW) monsoon season. The pre-monsoon beach topography surveyed using DGPS is used as the initial topographic condition in the morphological model. The model simulates subsequent beach erosion during the SW monsoon season, which is forced by forecast waves. Beach erosion advisories that classify the beach as eroding, accreting and no change are disseminated with a lead period of 10 days. During the SW monsoon period, we have monitored the beach using the dumpy level, and the beach topography during the postmonsoon is generated using DGPS surveyed profiles and are used for model validation. The beach area under erosion observed from the model result is homologous with the in-situ observations. The model shows cross-shore sediment transport to dominate during the SW monsoon, particularly in the central and northern sectors of RK beach. The model estimated shoreline position agrees with the DGPS observations, where the central sector has undergone maximum erosion. The comparison shows the model’s ability to simulate beach morphodynamics like landward shifting of the berm crest under a high wave setup and oscillating water levels due to tides. The study highlights the importance of numerical modelling systems that decipher the beach response to the high monsoon waves.

$\bf{Highlights}$

$\bullet$ Beach erosion forecast system for RK Beach, India.

$\bullet$ Forecast system is developed using a combination of WAVEWATCHIII and Xbeach.

$\bullet$ Beach erosion advisories during monsoon period.

Extraction of shorelines using satellite imagery is an effective method because customary digitization is a longand hectic process. This study focuses on extracting and detecting shoreline changes from Landsat-8 imageries ofthe Visakhapatnam–Kakinada coast along the east coast of India using an object-based approach. An object-based approach for the automatic detection of coastline from Landsat imagery using the Feature Extraction Workflow by Maximum Likelihood is implemented by the maximum classification method (MLC). The resulting vector polyline is smoothened for every 100 m using ArcGIS software. Delineation of multi-temporal satellite images was performed by visual interpretation from 2014 to 2019 to detect the shoreline changes. Different available techniques and methods are employed to observe shoreline changes. In addition to this, the shoreline information simulated by satellite remote sensing is in fair agreement with RTK GPS observations. The observed and remote sensing shoreline changes help to identify the areas of accretion and eroding zones overthe long term. During this study, erosion and deposition changes were observed along RK beach, Rushikonda beach, Uppada beach, and Kakinada beach. The spatial variation rates were calculated using the statistical methods of the Digital Shoreline Analysis System (DSAS) during specific periods. The maximum observed shoreline accretion and erosion rates at Kakinada are 5.3 and –4.35 m/year indicates slight accretion. The maximum observed accretion and erosion rates at Uppada beach are 3.8 and –6.78 m/year, respectively indicatingerosion. Similarly, at RK Beach the maximum observed shoreline accretion and erosion rates are 3.68 and –3.68 m/year, respectively indicating the beach is in a stable state. At Rushikonda beach, the maximum observed shoreline accretion and erosion rates are 2.24 and –3.04 m/year, respectively indicating erosion.