Acquisition of satellite imagery for surface water quality monitoring has been widely used in coastal and ocean waters, and large lakes. Recent advances in the deployment of novel higher resolution satellites and the development of innovative and more accessible data, computing, and geospatial analysis tools provide an opportunity to test, deploy and operationalize new water quality monitoring approaches for smaller lakes. We propose the implementation, evaluation and operationalization of using remote sensing data from multispectral satellite imagery from two satellite constellations, Landsat-8 and Sentinel-2, to capture four water quality indicators: temperature, chlorophyll-a, turbidity, and phycocyanin in lakes of WA state using peer-reviewed
methods. Parameterization of satellite data will be achieved using existing field monitoring data complemented with measurements obtained via targeted field sampling efforts. Time series analysis will help evaluate whether remotely sensed data captured actual changes in field water quality conditions. We will examine these relationships to develop regional scale models for various water quality parameters (such as cyanotoxin concentrations) and lakes with varying trophic levels. Results of this work will inform strategies to mitigate water quality issues and develop climate-change resilient plans for lake management and will be of interest to managers of drinking water source protection areas and experts in charge of monitoring HABs for public
health practice, among other applications. The work also has significant student training and workforce development potential as it will broaden the participation of underrepresented minorities in research and help train a climate-ready engineering and science workforce via intra and inter-institutional partnerships.