Abstract
Turbidity, an optical measure of water clarity influenced by suspended sediments and organic matter, is a critical indicator of freshwater quality. Satellite remote sensing offers a practical means of monitoring turbidity over space and time by capturing water-leaving reflectance across spectral bands. This study explores the spatiotemporal retrieval of turbidity in the Upper Lake, Bhopal, an important urban freshwater body and Ramsar site in India, using Landsat-8 Operational Land Imager (OLI) Surface Reflectance (SR) data from 2013 to 2022. Field-based in-situ turbidity data collected during the pre-monsoon and post-monsoon seasons of 2022 were used to calibrate and validate several empirical models based on different band combinations. The best empirical models used the band ratio of the blue and red bands (Band-2 and Band-4), yielding a high agreement with field data (R² = 0.89) with a validation RMSE of 4.04 NTU. Temporal turbidity trends revealed a seasonal pattern, with higher turbidity observed in the post-monsoon season due to catchment runoff and anthropogenic activities. This study confirmed that Landsat-8 OLI SR, supported by field measurements, is a reliable tool for long-term turbidity monitoring in inland lakes.