Rip currents are known as one of the most dangerous hazards on sandy beaches worldwide. Indian beaches are least explored to study the variability of rip currents in space and time. The present study is the first attempt made to understand its dynamics by utilizing indigenously developed GNSS (Global Navigation Satellite System) drifters and Rhodamine-B dye experiments. The Rama Krishna (RK) and Rushikonda Beaches of Visakhapatnam are chosen for this study, due to a recorded number of rip current-related drowning cases observed during the past decade. Few experiments were conducted during pre- and post-monsoon seasons of 2018. Drifters work on the Lagrangian principle, where they measure the current velocities along their paths driven by the surface currents. Error analysis of drifter measurements showed that they are capable of resolving surf zone motions very accurately. Strong rip currents were observed in few locations in the study area, where at times current velocities reached ${\sim}$1 ms$^{-1}$. Also, Rhodamine-B dye was released into the rip current prone zones along with the drifters and observed that the dye patches also followed the drifters. From these experiments, it has been observed that the rip currents are relatively strong during the post-monsoon season, which could be due to the change in the beach morphology. Similar experiments with more number of drifters would help in understanding rip current dynamics and would help in reducing rip current drowning in the beaches.

$\bf{Highlights}$

$\bullet$ GNSS based drifters have been designed, developed and field-tested to measure rip currents in the surf zone.

$\bullet$ Post-Processing Kinematic (PPK) resulted in position estimates with centimeter level accuracy.

$\bullet$ The drifters are capable to resolve the surf zone motions more accurately in the order of greater than 0.02 ms$^{-1}$.

$\bullet$ Several drifter deployments and Rhodamine-B dye experiments were carried out at RK and Rushikonda Beaches to measure the dangerous rip currents and coastal currents.

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.