An assessment of water quality monitoring tools in an estuarine system

• Showcase the use of ocean colour to derive water quality variables.
• Evaluate uncertainties and regression model performance.
• Demonstrate possible use of OLI Landsat 8 imagery.
• Intercompare water quality information derived from three independent platforms.

Ocean colour remote sensing (OCRS) has proved to be a powerful tool in monitoring biogeophysical and optical water quality variables. The different capabilities of OCRS in terms of spatial extent and temporal or revisit cycle dictate some of scientific questions we can resolve in a qualitative or quantitative manner. Typically, near-water surface platform measurements of (RRS) have minimal uncertainties, high spectral and temporal resolution but tend to have limited spatial coverage in contrast to measurements from satellite platforms. To this end, we completed correlation tests among salinity, turbidity and above-water RRS from the Wadden Sea time series station Spiekeroog to determine the extent of their respective associations. Strong correlations were then utilized to establish empirical predictive regression models to infer salinity and turbidity from above-water RRS. These regression models were determined to have reasonable average uncertainties of less than 29%. As satellites generally provide wider spatial coverage, we assessed the feasibility of applying these near-water OCRS regression models to the high spatial resolution (30 m) Operational Land Imager Landsat-8 imagery. Unbiased percent differences between above-water and satellite derived RRS at (443, 483, 561, and 655) nm centred wavebands were less than 22%. At high water level, basin tidal channels and creeks could be identified from Landsat-8 RGB composite imagery. This case study demonstrated potential applications of high spatial resolution (30 m) Landsat-8 imagery in both qualitative and quantitative observations of water quality variables as well as features in an optically complex estuarine systems. The observations of water quality variables from three platforms submerged, near water surface and satellite is also shown to provide comparable measurements giving some form of an accuracy and precision test. The study findings here highlight the need to take advantage and improve high spatial resolution OCRS approaches and predictive regression models for such optically complex estuarine waters for realistic multidisciplinary efforts to continuously observe water constituents.