Monitoring dynamic changes in water quality parameters of dam reservoirs using remote sensing

Articles in Press

Document Type : Research Paper

Authors

1 Associated Professor, Dep. of Water Engineering, Faculty of Water and Soil, Gorgan University of Agricultural Sciences and Natural Resources, Golestan.

2 Water Engineerin Department, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.

Abstract

Continuous monitoring of water quality in dam reservoirs, especially under the influence of climate change and anthropogenic pressures, is vital for sustainable water resource management. This study utilized Landsat 8 satellite imagery to model and map two key water quality parameters chlorophyll-a and turbidity in the Choke Canyon Reservoir, Texas, USA. A multivariate nonlinear regression model was developed based on in-situ data collected from 19 points across the reservoir surface. The results showed that the developed models performed well at the reference time, with R² and RMSE values of 0.96 and 0.09 for chlorophyll-a, and 0.84 and 0.10 for turbidity, respectively. To address temporal changes and environmental variability, a Spectral Correction Parameter (SCP) was introduced, which improved model accuracy for future time predictions. The RMSE for chlorophyll-a estimation decreased from 0.15 to 0.09, and for turbidity from 0.14 to 0.05 after applying SCP. Spatial analysis revealed that higher chlorophyll-a concentrations were mainly found in the western, shallow, and nearshore areas of the reservoir, while higher turbidity levels were concentrated in the central and deeper zones. These spatial patterns were closely related to environmental factors such as water depth, inflow currents, and reservoir topography. Overall, the integration of remote sensing data, statistical modeling, and spectral correction techniques proved effective for low-cost, large-scale monitoring of water quality in reservoirs.

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Iranian Journal of Soil and Water Research

Articles in Press, Accepted Manuscript
Available Online from 01 October 2025

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