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Monitoring of lake water quality along trophic gradient using landsat data
Article 15: Volume 8, Number 4, Autumn 2011, Pages 817-822 (6) XML PDF (611 K)
Authors
N. Karakaya; F. Evrendilek; G. Aslan; K. Gungor; D. Karakas
Abstract
Effects of differential trophic states on remote sensing-based monitoring and quantification of surface water quality are an important but understudied context. Landsat ETM+ data-based multiple linear regression models were conducted to quantify dynamics of lake surface water quality along a oligotrophic-to-eutrophic gradient and to explore influence of the trophic state on the detection of water quality dynamics by the best multiple linear regression models. The best MLR models of dissolved oxygen, chlorophyll-a, Secchi depth, water temperature, and turbidity had R2adj values ranging 36.2% in water temperature to 93.1% in dissolved oxygen for eutrophic Lake Yenicaga and from 36.1% in Secchi depth to 99.7% in water temperature for oligotrophic Lake Abant. The difference in the trophic state between Lakes Abant and Yenicaga significantly affected the composition of the nine Landsat ETM+ spectral bands included in the multiple linear regression models as well as the predictive power of the multiple linear regression models. Remote sensing-based monitoring of lake water quality variables appears to be promising in terms of devising adaptive management decisions towards sustainability of water resources.
Keywords
Modeling; Remote sensing; Spatio-temporal dynamics; Surface water
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