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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Environmental Microbial & Food Safety Laboratory » Research » Publications at this Location » Publication #340244

Research Project: Design and Implementation of Monitoring and Modeling Methods to Evaluate Microbial Quality of Surface Water Sources Used for Irrigation

Location: Environmental Microbial & Food Safety Laboratory

Title: Optimizing the bio-optical algorithm for estimating chlorophyll-a and phycocyanin concentrations in inland waters in Korea

Author
item Pyo, Jongcheol - University Of Ulsan College Of Medicine
item Pachepsky, Yakov
item Baek, Sangsoo - University Of Ulsan College Of Medicine
item Kwon, Yongseong - University Of Ulsan College Of Medicine
item Kim, Minjeong - University Of Ulsan College Of Medicine
item Lee, Hyuk - National Institute Of Environmental Research
item Park, Sanghyin - National Institute Of Environmental Research
item Cha, Yoonkyung - University Of Seoul

Submitted to: International Journal of Remote Sensing
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/26/2017
Publication Date: 5/30/2017
Citation: Pyo, J., Pachepsky, Y.A., Baek, S., Kwon, Y., Kim, M., Lee, H., Park, S., Cha, Y. 2017. Optimizing the bio-optical algorithm for estimating chlorophyll-a and phycocyanin concentrations in inland waters in Korea. International Journal of Remote Sensing. 9(6):542.

Interpretive Summary: Bio-optical algorithms use the measured reflectance at several wavelengths to estimate concentrations of Chlorophyll a and Phycocyanin pigments to predict the total algae biomass and biomass of toxic cyanobacteria in water. These algorithms need to be calibrated to reflect the site-specifc properties of the atmosphere and water. The objective of this work to determine if the performance of bio-optical algorithms could be improved by using both measured pigment concentrations and the adsorption coefficients. Using data from a reservoir in South Korea, we showed that using the measured adsorption coefficient during calibration indeed substantially improved the performance of the algorithms. Results of this work will be of use for researchers, consultants, and monitoring agencies that use remote sensing data to estimate concentrations of algae-related pigments in aerial surveys to assess biological water quality.

Technical Abstract: Several bio-optical algorithms were developed to estimate the chlorophyll-a (Chl-a) and phycocyanin (PC) concentrations in inland waters. This study aimed at identifying the influence of the algorithm parameters and wavelength bands on output variables and searching optimal parameter values. The optimal parameters of seven bio-optical algorithms were applied to estimate the Chl-a and PC concentrations. The absorption coefficient measurements were coupled with pigment measurements. The elementary effect test was conducted to analyze the sensitivity of the bio-optical algorithm parameters. The parameters in the Y function and specific absorption coefficient were the most sensitive parameters. All parameters of the algorithms were calibrated from the data of the pigment contents in the water body. Parameters were optimized via single- and multi-objective optimization. The single-objective optimization aimed at optimizing the parameters focusing on the pigment concentration. It led to substantial errors in absorption coefficients. In contrast, the multi-objective optimization algorithm was used to search the optimal parameter sets with the optimization criterion that included both pigment concentrations and absorption coefficient values. The multi-objective optimization not only improved the algorithm performance with respect to the absorption coefficient estimates but also improved pigment concentration estimates. The optimized parameters of the absorption coefficient reflected the high-particulate content in waters of the Baekje reservoir by using an infrared backscattering wavelength and relatively high value of Y. Results indicate the value of measuring the site-specific absorption coefficients if site-specific optimization of bio-optical algorithm parameters was envisioned.