Estimation of Chlorophyll-a, TSM and salinity in mangrove dominated tropical estuarine areas of Hooghly River, North East Coast of Bay of Bengal, India using sentinel-3 data

Abstract

This study aims to explore the variations in spatio-temporal characteristics of water quality factors of three estuaries in the western portion of the Indian Sundarbans. Reliable retrieval of near surface concentrations of parameters such as Chlorophyll-a, SST & TSM in various aquatic ecosystems with broad ranges of trophic needs has always remained a complex issue. In this study the application of C2RCC processor has been tested for its accuracy across different bio optical regimes in inland & coastal waters. Satellite images for the same period were also collected and analysed using the C2RCC processing sequence to retrieve values of factors like the depth of water, surface re ectance, water temperature, inherent optical properties (IOPs), chlorophyll-a, salinity and total suspended matter (TSM) using the SNAP software. During the 2017-2020 season, in situ sampling from speci c locations and laboratory water quality analysis were carried out. The OLCI retrieved results were then trained and corroborated by means of the in situ datasets. It was observed that the highest amount of TSM was recorded in Diamond Harbour during the pre-monsoon, in the year 2018 (301.40 mgL -1 in-situ value, and 308.54 mg L -1 estimated value). Similarly, chlorophyll-a had higher concentrations through the monsoon season (3.03 mg m -3 , in-situ, and 2.96 mg m -3 , estimated) in Fraserganj and Sagar south points. Very good tted correlation results for all seasons between Chl-a, r = 0.829 and TSM, r = 0.924 remained established throughout the comparisons of OLCI and in situ results. The high level of correlation highlights the importance of both primary as well as secondary information in understanding any dynamic system properly. Finally, the result shows that the water quality model outperforms conventional techniques and OLCI chl-a and TSM products. This paper empirically investigates a reliable remote sensing method for estimating coastal TSM and chl-a concentrations and supports the use of OLCI data in ocean colour remote sensing.