Low-cost spectroradiometer systems for improved spatial and temporal water quality monitoring

Session: Smart Lakes: Real-Time Monitoring, Networking, and Analytics Across the Great Lakes (2)

Robert Shuchman, Michigan Technological University, [email protected]
Mike Sayers, Michigan Tech. Research Inst., [email protected]
Reid Sawtell, Michigan Tech Research Inst., [email protected]
Karl Bosse, Michigan Tech Research Inst., [email protected]
Steve Ruberg, NOAA - GLERL, [email protected]
John Lekki, NASA Glenn Research Center, [email protected]

Abstract

Spectroradiometric measurements of surface water can provide valuable information about the bio-geochemical composition including phytoplankton abundance, water clarity, and presence of harmful algae.  While satellite remote sensing has shown great utility to provide global water quality information, limitations exist for optically complex inland waters. Field-deployed spectroradiometers can resolve small-scale spatial features including cyanobacteria blooms that orbiting platforms may not. Historically, in-situ radiometric devices are expensive and require significant user expertise, often prohibiting measurements at the scales needed to fully characterize the water quality phenomena of interest. MTRI has developed new low-cost high-fidelity radiometric instruments that can better monitor water quality in challenging environments. The first package, designed for deployment on fixed structures, measures reflectance at sub-minute time-scales which has been used to resolve the size and biomass of cyanobacteria surface mats undergoing advection from water currents. The second instrument is a handheld radiometer system using an off-the-shelf camera and 3D-printed optical housing. A controlling application for smart devices has been created to guide non-experts through the measurement process to ensure quality data. The low-cost nature of this solution allows for the potential distribution of radiometers to citizen scientists and water managers toward the formation of a distributed sensor network.