Investigating shallow water bottom feature using SAR data along Gulf of Khambhat, India

Abstract

The coastal bathymetry often forms complex and transient morphology, especially along the tide-dominated regions like the Gulf of Khambhat (GoK), west coast of India. The high tidal currents within the gulf relentlessly modify the morphology of the bathymetric features that prompts for a frequently updated bathymetric information. The SAR estimated bathymetry represent updated depth values based on the transient bathymetric features observed from the SAR images. The present study has used ALOS PALSAR-1/2 data to update the depth of shallow water bottom features of GoK. The method involves modeling the gradient in the backscatter coefficient (σ°) modulated by the slope of the bathymetric features with the satellite images. The slope corresponding to the bathymetric feature from hydrographic charts (initial guess bathymetry) and the simulated current velocity forms the input to the model. The bathymetry is updated by varying the slopes of the bathymetric features through iteration until the σ° converges. The method is applied to update the depth of various bathymetric features observed from the SAR images of 2008, 2010, 2014 and 2018. We validated the updated depth from 2018 satellite data using available in situ measurements. The comparison of in situ observation with the hydrographic chart has resulted in RMSE of 3.2 m, while the RMSE have improved to 1.5 m when compared with the SAR updated bathymetry. The temporal dynamics of the bathymetric features are studied using the pair of 2008–10 and 2010-14 SAR images. Analysis has comprehended the morphodynamics of bathymetric features like lateral migration of tidal bars, erosion along the tidal channel periphery, and deposition at the tidal spits. We updated the depth of rapidly changing bathymetric features using the 2018 SAR images. The study shows its potential in operational usage to update the complex nearshore bathymetry from the SAR image.