Estimation of Underwater Visibility by Integrating Remote Sensing and Numerical Modeling

Abstract

In maritime accidents leading to missing persons, acquiring accurate underwater environment information is crucial for effective search and rescue (SAR) operations. Current remote sensing techniques have limitations in providing comprehensive data beneath the sea surface. This study proposes a novel technology that enhances underwater visibility estimation by incorporating numerical modeling with high-resolution satellite data. First, turbidity was calculated utilizing the 560 nm surface reflectance data from Sentinel-2. The accuracy of turbidity values was assessed by comparison with in-situ turbidity data. To delineate detailed vertical mixing patterns influencing underwater visibility distribution, a comprehensive vertical profile database for water temperature and salinity was established using the Regional Ocean Modeling System (ROMS) model. Indices of vertical mixing, as a critical factor influencing underwater visibility, was achieved through quantitative analysis of seawater temperature and salinity data. The detailed underwater visibility distance is calculated by incorporating turbidity and vertical mixing effects. Subsequently, the underwater visibility will be validated through in-situ experimental measurements of both vertical and horizontal visibility along the coast using a Secchi disk. The outcomes of this study are anticipated to significantly contribute to enhancing the efficiency of rapid search and rescue operations for missing persons at sea. ？ 2024 IEEE.