Arctic coastal ecosystems are undergoing rapid change, including large increases in delivery of freshwater (and associated sediments, nutrients and organic matter) from land to sea. Although these changes are expected to have a broad range of impacts on coastal biogeochemistry and ecology, the dynamic nature of coastal ecosystems, where physicochemical conditions and biological processes are highly variable over space and time, makes it challenging to study ongoing and potential future changes in Arctic coastal waters. Remote sensing is increasingly being seen as a promising tool for the study of these dynamic processes, and in particular the potential for using remote sensing of water colour in order to estimate water quality parameters including suspended particulate matter (SPM), chlorophyll a (Chl a) and chromophoric dissolved organic matter (cDOM) holds a great deal of promise for exploring these parameters at higher spatial resolution and higher frequency than is possible with traditional field sampling.
My project aims to build on and complement ongoing work related to land-ocean interactions in Adventfjorden, a river-influenced fjord on Svalbard, by carrying out high frequency field sampling through the 2020 melt season, and by pairing field data with satellite and drone observations of water colour. By generating robust field data on key water quality parameters (SPM, Chl a, cDOM) and pairing these data with remote sensing observations, I will test and refine algorithms for prediction of water quality parameters from remote sensing in optically complex coastal waters on Svalbard, allowing for broader application of remote sensing approaches (including use of drones) to coastal research questions.