Spatio-Temporal Assessment of Chlorophyll-A Dynamics in Lake Beyşehir Using Remote Sensing

Monitoring chlorophyll-a dynamics in inland water bodies is critical for assessing ecosystem health, detecting eutrophication, and informing sustainable water resource management. This study examines the spatiotemporal dynamics of chlorophyll-a concentrations in Lake Bey & scedil;ehir, T & uuml;rkiye, with a specific focus on August 2021-a period marked by a documented algal bloom event. By integrating Sentinel-2 derived Normalized Difference Chlorophyll Index (NDCI) indices, Principal Component Analysis (PCA), and profile-based transect evaluations, the research offers a novel remote sensing-based framework for detecting early signs of eutrophication and identifying spatial hotspots in large inland freshwater systems. Utilizing four high-resolution Sentinel-2 MSI satellite images, the Case 2 Regional Coast Color (C2RCC) neural network algorithm was applied in conjunction with PCA to reveal dominant chlorophyll-a distribution patterns. Average chlorophyll-a levels increased from 3.19 mg/m(3) (4 August) to 5.33 mg/m(3) (29 August), with peak concentrations reaching up to 43.7 mg/m(3). Red-dominated high-concentration zones expanded from 29 to 56% of lake surface area. However, when assessing historical monthly NDCI data from 2017 to 2024, the results did not support a statistically significant long-term positive trend (R-2 = 0.82, p < 0.005). PCA composites and spatial transects highlight persistent variability hotspots in shallow and anthropogenically influenced shoreline areas. Overall, the results underscore the utility of satellite remote sensing for long-term lake monitoring and suggest that increasing chlorophyll-a levels may be influenced by climatic and land-use changes, reinforcing the need for continuous observation and adaptive environmental management strategies.