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Estimation and Assessment of Total Phosphorus and Trophic State Index Estimated from Landsat 8 Dataset on 2018 at Daecheong Reservoir
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Objectives : Remote sensing of water quality parameters (WQPs) has been widely applied along with the emerging importance of obtaining the spatial pattern of water quality at inland reservoir. This study retrieved the Total Phosphorus (TP) via remote sensing imagery at Daecheong reservoir and used it for acquiring the spatial distribution of Trophic State Index (TSI).Methods : First, stepwise regression for TP was established using the ground-based TP measurement and reflectance of Landsat 8 collocated in space and time. With the developed regression model, we estimated the spatial distribution of TSI and evaluated the severity of eutrophication at Daecheong reservoir.Results and Discussion : The result confirmed that predicted TP yielded reasonable statistics compared against measured TP with R<sup>2</sup> of 0.956 and p-value of 0.022. Seasonal variation of TP was highly influenced by the precipitation. Similarly, precipitation also influenced to the spatial pattern of TSI. Before the rainfall event (e.g., August 22 2018) at Daecheong reservoir, TSI metric indicated the oligotrographic stage. However, TSI of Daecheong reservoir after the rainfall (e.g., October 25 2018) indicated the mesotrophic and eutrophic stage.Conclusions : These results confirmed that the retrieval of WQP from remote sensing imagery can serve as a robustness tool to monitor the water quality over the large scale area.
Korean Society of Environmental Engineering
Title: Estimation and Assessment of Total Phosphorus and Trophic State Index Estimated from Landsat 8 Dataset on 2018 at Daecheong Reservoir
Description:
Objectives : Remote sensing of water quality parameters (WQPs) has been widely applied along with the emerging importance of obtaining the spatial pattern of water quality at inland reservoir.
This study retrieved the Total Phosphorus (TP) via remote sensing imagery at Daecheong reservoir and used it for acquiring the spatial distribution of Trophic State Index (TSI).
Methods : First, stepwise regression for TP was established using the ground-based TP measurement and reflectance of Landsat 8 collocated in space and time.
With the developed regression model, we estimated the spatial distribution of TSI and evaluated the severity of eutrophication at Daecheong reservoir.
Results and Discussion : The result confirmed that predicted TP yielded reasonable statistics compared against measured TP with R<sup>2</sup> of 0.
956 and p-value of 0.
022.
Seasonal variation of TP was highly influenced by the precipitation.
Similarly, precipitation also influenced to the spatial pattern of TSI.
Before the rainfall event (e.
g.
, August 22 2018) at Daecheong reservoir, TSI metric indicated the oligotrographic stage.
However, TSI of Daecheong reservoir after the rainfall (e.
g.
, October 25 2018) indicated the mesotrophic and eutrophic stage.
Conclusions : These results confirmed that the retrieval of WQP from remote sensing imagery can serve as a robustness tool to monitor the water quality over the large scale area.
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