Chlorophyll-a (Chl-a) and Total Suspended Matter (TSM) are key health indicators of the coastal ocean and seas. The former is linked to primary productivity, while the latter is associated with water quality; both are influenced by change in climate. Recent studies have highlighted a declining trend in Chl-a levels along the Mediterranean coastal region. River discharge plays an important role in regulating the coastal Chl-a concentration levels. The present research primarily focuses on understanding the significance of Tiber River −driven spatial dynamics of Chl-a and TSM along the central Tyrrhenian Sea coasts. The research also focuses on evaluating the applicability of Sentinel-2 and identifying a suitable method for estimating Chl-a and TSM from Sentinel-2. Neural networks and dark spectrum fitting techniques were applied using multiple algorithms to estimate the dynamic distribution of Chl-a and TSM driven by the Tiber River in the study area. Multiple statistical analyses were performed, and statistically significant relationships were observed. The Case-2 Regional Coast Colour Neural Network (C2RCC-Net) outperformed all other algorithms, with an R2 value of 0.903 for Chl-a and an R2 value of 0.966 for TSM. Furthermore, the present research also identified a positive pixel to pixel spatial correlation between Chl-a and TSM in all four seasons, highlighting the positive impact of Tiber River on maintaining Chl-a levels along the coasts of Tyrrhenian Sea. This stands in contrast with the negative trend seen in the Mediterranean scale.
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