Remote sensing of Water Quality (WQ) parameters, including Total Suspended Sediments (TSS) and Dissolved Organic Carbon (DOC), offers vital insights into aquatic ecosystem health. This study focuses on the TSS and DOC contribution of riverine catchment systems to their outflows and impact on the estuarine and coastal regions. We sampled in-situ measurements of absorption and backscattering co-efficient of particulate and dissolved matter for Hawkesbury, Hunter, and Clarence catchments in 2022, along coastline NSW in 2010, and then derived simulated reflectance using a radiative transfer model, Hydrolight. This spectral library with associated uncertainty was then used to train a Dense Deep Learning Network (DDLN) and applied to an atmospherically corrected decadal Landsat-8 dataset (2013-2023) for the three catchments utilising a cloud platform with Open Data Cube (ODC) libraries. Hunter was found to have the highest sediment and carbon concentration of 266.94(TSS)/69.06(DOC) mgL-1km-2yr-1 than Clarence (235.85/62.41mgL-1km-2 yr-1) and Hawkesbury (195.72/58.82 mgL-1km-2 yr-1) at the river mouths. Significant variations in yearly TSS and DOC estimates were observed in all three catchments, with maximum plume extents of 32.27km2 for Hunter, 15.89km2 for Clarence, and 11.76km2 for Hawkesbury. DDLN was effective in non-linear mapping of reflectance and WQ, providing rapid TSS and DOC estimates.