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Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager

February 1, 2018

In this study, we demonstrated that the Landsat-8 Operational Land Imager (OLI) sensor is a powerful tool that can provide periodic and system-wide information on the condition of drinking water reservoirs. The OLI is a multispectral radiometer (30 m spatial resolution) that allows ecosystem observations at spatial and temporal scales that allow the environmental community and water managers another means to monitor changes in water quality not feasible with field-based monitoring. Using the provisional Land Surface Reflectance product and field-collected chlorophyll-a (chl-a) concentrations from drinking water monitoring programs in North Carolina and Rhode Island, we compared five established approaches for estimating chl-aconcentrations using spectral data. We found that using the three band reflectance approach with a combination of OLI spectral bands 1, 3, and 5 produced the most promising results for accurately estimating chl-a concentrations in lakes (R2 value of 0.66; root mean square error value of 8.9 µg l−1). Using this model, we forecast the spatial and temporal variability of chl-a for Jordan Lake, a recreational and drinking water source in piedmont North Carolina and several small ponds that supply drinking water in southeastern Rhode Island.

Publication Year 2018
Title Monitoring algal blooms in drinking water reservoirs using the Landsat-8 Operational Land Imager
DOI 10.1080/01431161.2018.1430912
Authors Darryl Keith, Jennifer Rover, Jason Green, Brian Zalewsky, Mike Charpentier, Glen Hursby, Joseph Bishop
Publication Type Article
Publication Subtype Journal Article
Series Title International Journal of Remote Sensing
Index ID 70197955
Record Source USGS Publications Warehouse
USGS Organization Earth Resources Observation and Science (EROS) Center