TSS (Total Suspended Solid) In Tri An Reservoir Assessment From Satellite Images Using GEE (Google Earth Engine) Cloud Platform

Abstract

Tri An Reservoir plays a key role in providing and regulating water for Vietnam’s southern provinces. It is presently threatened by surface water contamination causing from household activities, industrial areas, and fish farming. Thus, systematic monitoring and evaluation of water quality in the reservoir are essential for gauging pollution extents and developing robust strategies to manage surface water quality. Remote sensing imagery facilitates holistic data acquisition over the full extent of the lake, yielding ongoing analytical datasets and enabling precise detection of temporal variations in surface water quality. This study assessed Total Suspended Solids (TSS) levels in Tri An Reservoir, Dong Nai Province, from 2020 to 2023, identifying an optimal model for predicting TSS concentrations based on remote sensing variables and diverse statistical indicators via linear regression within the Google Earth Engine (GEE) platform. The resulting multivariate regression model, with a coefficient of determination R2 = 0.751 and root mean square error RMSE = 0.139, shows good agreement between predicted and observed TSS values. The findings of this research powerfully underscore the exceptional potential of remote sensing data to provide a thorough and exhaustive depiction of spatial trends in surface water quality across rivers, streams, lakes, and ponds. In addition, they support the retrieval of historical water quality concentrations, helping to overcome limitations caused by sparse or missing in situ monitoring data for future water environment assessments.