Chaubey et al., 2016 (In Press)

Paper/Book

Water quality estimation of river plumes in Southern Lake Michigan using Hyperion

Tan, J, K.A. Cherkauer, I. Chaubey, C.D. Troy, and R. Essig (2016)
Journal of Great Lakes Research  

Abstract

This study focuses on the calibration of an existing bio-geo-optical model for studying the spatial variability of water quality parameters including chlorophyll (CHL), non-algal particles (NAP), and colored dissolved organic matter (CDOM) in episodic river plumes. The geographic focus is the St. Joseph River plume in southern Lake Michigan. One set of EO-1 Hyperion imagery and one set of boat-based spectrometer measurements were successfully acquired to capture episodic plume events. Coincident water quality measurements were also collected during these plume events. In this study, a database of inherent optical properties (IOPs) measurements and spectral signatures was generated and used to calibrate the bio-geo-optical model. Field measured concentrations of NAP and CDOM at 67% of the sampled sites fall within one standard deviation of the retrieved means using the spectrometer measurements. The percentage of sites, 88%, is higher for the estimation of CHL concentrations. Despite the dynamic nature of the observed plume and the time lag during field sampling, 77% of the sampled sites show field measured CHL and NAP concentrations falling within one standard deviation of the Hyperion derived values. The spatial maps of water quality parameters generated from the Hyperion image provided a synoptic view of water quality conditions. Results show that concentrations of NAP, CHL, and CDOM were more than three times higher in conjunction with river outflow, and inside the river plumes, than in ambient water. It is concluded that the storm-initiated plume is a significant source of sediments, carbon and chlorophyll to Lake Michigan.

Citation

Tan, J, K.A. Cherkauer, I. Chaubey, C.D. Troy, and R. Essig (2016): Water quality estimation of river plumes in Southern Lake Michigan using Hyperion. Journal of Great Lakes Research. DOI: 10.1016/j.jglr.2016.02.009