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- W1578729569 abstract "Coastal sea of the southern Gulf of Finland is under heavy anthropogenic stress due to development of harbors and increase of ship traffic. During dredging operations, the increase of suspended particulate matter (SPM) concentration in seawater is inevitable. Water transparency decreases with an increased SPM concentration, which leads to worsening of underwater light conditions. Diminishing of light intensity that penetrates to the sea bottom has negative effect on the growth of benthic macroalgae, which is an indicator of water quality in the coastal zone. Monitoring of SPM transport and distribution along with the estimation of dredging impact on marine environment is crucial especially when sensitive and critical marine areas are close to dredging site. The monitoring system that combines satellite remote sensing and numerical modeling and is supported by measurements is presented. The modeling part consists of hydrodynamic model, particle transport model and benthic macroalgae growth model. A simple approach is followed in the formulation of the system and on the determination of required relationships that are based on the measurements. The monitoring system was applied to Pakri Bay during dredging in Paldiski North harbor, which lasted a one and half year. Comparison of SPM distributions from remote sensing images and numerical model results showed qualitatively similar patterns. Quantitative comparison allowed separating SPM concentrations due to dredging operations from background values of natural origin. Underwater light conditions were the most affected close to the harbor and in the coastal sea. Estimations of the changes of macroalgae biomass due to diminishing underwater light intensity showed minor effect, as the dredging was carried out mainly from late autumn until early spring when macroalgae growth is limited by water temperature." @default.
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- W1578729569 date "2006-05-01" @default.
- W1578729569 modified "2023-10-02" @default.
- W1578729569 title "Environmental monitoring of water quality in coastal sea area using remote sensing and modeling" @default.
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- W1578729569 doi "https://doi.org/10.1109/baltic.2006.7266166" @default.
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