The development of methodologies to monitor our planet is important if we are to understand the effects of climate change. The objective of this thesis is to develop satellite-based retrieval methodologies for water constituents in optically complex coastal waters, the NW Baltic Sea and Dublin Bay. It utilises the Sentinel-3 Ocean and Land Colour Instrument (OLCI) satellite sensor. These water constituents are: TSM, Chl-a, CDOM, and Secchi depth. There are three studies in this work. 1) The Baltic Sea study validated the Level-2 water products from the Case-2 Regional CoastColour (C2RCC) processor. These water products were regionally adapted using Inherent Optical Properties (IOPs). Additionally, the standard Level-2 OLCI Case-2 Neural Network (NN) products were validated, including the “CHL NN”, “TSM NN”, and “ADG443 NN” products. The effects of the EUMETSAT System Vicarious Calibration (SVC) on the water products was validated for the first time in the region. SVC reduced the performance of the products. Their application resulted in RMSD increases of 36% for the “conc tsm” product and 118% for the “conc chl” product in one processing chain. 2) The next study developed a novel C2RCC regionally adapted parameter estimation methodology. Instead of using IOPs to regionally parameterise the processor, a subset of the validation data was used. This methodology was developed as IOPs are not available for most water bodies, including Dublin Bay. 3) In the Dublin Bay study, the Level-2 water products were validated in the region for the first time. The novel parameter estimation methodology was used to regionally adapt these products in place of IOPs. Furthermore, the effects of the EUMETSAT SVC gains on the water products was validated in the region. To conclude, being able to retrieve satellite-derived water products in coastal waters is important. This thesis’s findings will aid in meeting requirements of EU directives, namely the WFD, MSFD, and BWD.