A spatiotemporal monitoring model of TSM and TDS in arid region lakes utilizing Sentinel-2 imagery

The assessment of lake water quality is crucial for protecting and managing natural resources. Total suspended matter (TSM) and total dissolved solids (TDS) are significant parameters in evaluating lake water quality, and their concentration levels provide useful information about the health of the ecosystem. However, measuring TSM and TDS concentrations in remote arid areas can be challenging, necessitating the development of a simple, efficient, and cost-effective monitoring system. In this study, the aim was to retrieve TDS and TSM concentrations in the arid region using an empirical and physics-based method simultaneously. Measured data and remote sensing images for Chah-Nimeh Reservoirs (CNRs), Iran, were used to establish the TSM and TDS concentration model. Twenty-seven Sentinel-2 multispectral instrument (MSI) data acquired from 2018 to 2021 were employed to determine the spatiotemporal distribution of TDS and TSM concentrations. The results indicate that Sentinel-2 MSI data is a productive tool for retrieving TSM concentration using the Case-2 Regional/Coastal Color (C2RCC) processor, with a high level of performance in the dry ecosystem of CNRs (R2 = 0.92). Furthermore, the Bayesian regularization artificial neural network (BRANN) algorithm was used to evaluate TDS concentration, and the results demonstrated that the BRANN algorithm outperforms other models, with a high level of performance (R2 = 0.89). It is noteworthy that evaluating TDS concentration is generally more challenging than TSM. The study provides a valuable model for monitoring TSM and TDS concentrations in remote arid areas using Sentinel-2 MSI data. The proposed approach can facilitate effective spatiotemporal monitoring of TSM and TDS concentrations and aid in the evaluation of lake water quality, specifically in regions where in-situ measurements are not feasible. The findings have significant implications for the management and conservation of natural resources in arid and remote regions.