Scholarly record

SPATIO-TEMPORAL ANALYSIS OF LAKE WATER QUALITY PARAMETERS USING SENTINEL-2 IMAGERY

Andreea Florina Stoleriu, Iuliana Gabriela Breaban, Alexandra Petronela Stoleriu

Abstract

Lake water quality is an important sign of ecosystem health, biodiversity, and sustainable management of freshwater resources. As human activities, climate change, and eutrophication increase, the need for efficient and consistent monitoring methods grows. Traditional field sampling provides accurate local data but is limited by how often and where samples are collected, as well as by high costs. Satellite remote sensing is a practical way to monitor inland water bodies, enabling repeated, large-scale assessments of water quality. In this study, we use Sentinel-2 images to track changes in lake water quality over time. This study evaluates the potential of Sentinel-2 data for monitoring and mapping water quality in Tansa Lake, located within the Bahlui catchment (Romania). This study aims to demonstrate how multispectral imagery can be used to track changes in important water quality parameters. Sentinel-2 images from 2024 were collected during three different seasons, focusing on chlorophyll-a, turbidity, and total suspended matter (TSM). The methodological workflow included resampling, subsampling, reprojection (Stereo 70), atmospheric correction, and the use of spectral bands in the visible, near-infrared (NIR), and short-wave infrared (SWIR) regions, which are sensitive to these parameters. In situ measurements were used to verify the accuracy of the satellite data, achieving R2 values of 0.95-0.98. The results show clear differences in water quality across the lake, with decreasing values from the tail of the lake towards the dam. The analysis also highlights areas with higher turbidity (0.63 - 39.62 NTU, 0.36 - 39.87 NTU, and 0.77 - 34.86 NTU) or chlorophyll levels (0.12 - 28.95 mg/m3, 0.22 - 27.10 mg/m3 and 0.67 - 19.84 mg/m3) due to excess nutrients close to the maximum allowed limit or exceeding it. Using Sentinel-2 images from different periods, it can be seen that changes over the lake are not always captured by traditional monitoring. In conclusion, the findings demonstrate that Sentinel-2 multispectral imagery provides an effective and accessible method for monitoring lake water quality over time. The integration of remote sensing data and statistical analysis allows the detection of changes occurring in lake environments. By incorporating remote sensing into operational monitoring frameworks, sustainable water management strategies can be developed at both regional and global scales.

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