Chlorophyll-a unveiled: unlocking reservoir insights through remote sensing in a subtropical reservoir.

Autor: Mpakairi KS; Department of Earth Sciences, Institute of Water Studies, University of the Western Cape, Bellville, 7535, South Africa. kudzishaun@gmail.com.; School of Wildlife Conservation, African Leadership University, Kigali, Rwanda. kudzishaun@gmail.com., Muthivhi FF; Department of Geography and Environmental Sciences, University of Venda, Thohoyandou, 0950, South Africa., Dondofema F; Department of Geography and Environmental Sciences, University of Venda, Thohoyandou, 0950, South Africa., Munyai LF; Aquatic Systems Research Group, School of Biology and Environmental Sciences, University of Mpumalanga, Nelspruit, 1200, South Africa., Dalu T; Aquatic Systems Research Group, School of Biology and Environmental Sciences, University of Mpumalanga, Nelspruit, 1200, South Africa.; South African Institute for Aquatic Biodiversity, Makhanda, 6140, South Africa.; Stellenbosch Institute for Advanced Study, Wallenberg Research Centre at Stellenbosch University, Stellenbosch, 7600, South Africa.
Jazyk: angličtina
Zdroj: Environmental monitoring and assessment [Environ Monit Assess] 2024 Mar 27; Vol. 196 (4), pp. 401. Date of Electronic Publication: 2024 Mar 27.
DOI: 10.1007/s10661-024-12554-w
Abstrakt: Effective water resources management and monitoring are essential amid increasing challenges posed by population growth, industrialization, urbanization, and climate change. Earth observation techniques offer promising opportunities to enhance water resources management and support informed decision-making. This study utilizes Landsat-8 OLI and Sentinel-2 MSI satellite data to estimate chlorophyl-a (chl-a) concentrations in the Nandoni reservoir, Thohoyandou, South Africa. The study estimated chl-a concentrations using random forest models with spectral bands only, spectral indices only (blue difference absorption (BDA), fluorescence line height in the violet region (FLH_violet), and normalized difference chlorophyll index (NDCI)), and combined spectral bands and spectral indices. The results showed that the models using spectral bands from both Landsat-8 OLI and Sentinel-2 MSI performed comparably. The model using Sentinel-2 MSI had a higher accuracy of estimating chl-a when spectral bands alone were used. Sentinel-2 MSI's additional red-edge spectral bands provided a notable advantage in capturing subtle variations in chl-a concentrations. Lastly, the -chl-a concentration was higher at the edges of the Nandoni reservoir and closer to the reservoir wall. The findings of this study are crucial for improving the management of water reservoirs, enabling proactive decision-making, and supporting sustainable water resource management practices. Ultimately, this research contributes to the broader understanding of the application of earth observation techniques for water resources management, providing valuable information for policymakers and water authorities.
(© 2024. The Author(s).)
Databáze: MEDLINE
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