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Monitoring of Chlorophyll-a Levels in Lakes

Author

Listed:
  • Mirjana Horvat

    (Faculty of Civil Engineering Subotica, University of Novi Sad, Kozaracka 2a, 24000 Subotica, Serbia)

  • Zoltan Horvat

    (Faculty of Civil Engineering Subotica, University of Novi Sad, Kozaracka 2a, 24000 Subotica, Serbia)

  • Emese Kutassy

    (Faculty of Water Sciences, Ludovika University of Public Service, Bajcsy-Zsilinsky utca 12–24, 6500 Baja, Hungary)

Abstract

This study aimed to examine the possibility of introducing a more sustainable system for Chlorophyll-a monitoring in Lakes Palic and Ludas. The approach was based on identifying relationships between Chlorophyll-a concentrations and environmental indices to establish equations for predicting future estimates of Chlorophyll-a concentrations. Consequently, we employed remote sensing techniques, utilizing Sentinel-2 LC1 products and the SNAP software for data processing, to extract and manipulate satellite images for this purpose. The atmospheric corrections were performed using the C2RCC algorithm. The obtained images were used to extract water, resulting in normalized reflectance values that were then used to calculate a set of environmental indices. Evaluating the correlation between Chlorophyll-a concentrations and calculated indices helped select the indices for the models. Lastly, we assessed the developed models through statistical tests and via standard verification procedures. The results varied from good and reliable to unreliable, depending on the specific location. It was noted that this method of forecasting Chlorophyll-a concentrations is not suitable for lakes under significant influence of artificial factors. Further refining of the modeling procedure could make the models more dependable.

Suggested Citation

  • Mirjana Horvat & Zoltan Horvat & Emese Kutassy, 2025. "Monitoring of Chlorophyll-a Levels in Lakes," Sustainability, MDPI, vol. 17(16), pages 1-23, August.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:16:p:7256-:d:1722149
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    References listed on IDEAS

    as
    1. Yong Yan & Ying Wang & Cheng Yu & Zhimin Zhang, 2023. "Multispectral Remote Sensing for Estimating Water Quality Parameters: A Comparative Study of Inversion Methods Using Unmanned Aerial Vehicles (UAVs)," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    2. Congju Fu & Baoyin He & Yadong Zhou & Hui Liu & Fan Yang & Jinwen Song & Huiping Cai & Xiaoqin Yang, 2022. "Remote Sensing Monitoring of Changes in Lake Aquatic Vegetation before and after the Removal of the Fence Based on Sentinel-2: A Case Study in Lake Futou, Hubei Province," Sustainability, MDPI, vol. 14(19), pages 1-15, September.
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