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Publication Abstract

Investigating the Water Quality of Lower Pearl River Estuary

Dash, P., Silwal, S., Moorhead, R. J., Sackreiter, J., Ochs, C., & Pinckney, J. (2015). Investigating the Water Quality of Lower Pearl River Estuary. Coastal and Estuarine Research Federation (CERF) Meeting. Portland, OR.

Harmful Algal Blooms (HABs), harmful microorganisms, and toxic metals represent three main water quality deteriorating agents in water bodies. The objectives of this research were to take a systems level approach to investigate the water quality of Lower Pearl River Estuary (LPRE) located in the Pearl River State Wildlife Management Area near Slidell, Louisiana and to develop algorithms for mapping some of the water quality indicators using high resolution data from an Unmanned Aerial System (UAS). Two field campaigns were undertaken (one in December, 2014 and another in March 2015) and at least three more field campaigns are planned before December, 2015 to the LPRE for collecting water samples, to measure the physical parameters including temperature, salinity, dissolved oxygen and pH and to measure remote sensing reflectance, fluorescence, and backscattering at approximately thirty discrete sites in the estuary. The water samples are being collected for high performance liquid chromatography (HPLC) photopigments, colored dissolved organic matter (CDOM), suspended particulate matter (SPM), cyanobacterial pigment phycocyanin (PC), phycotoxins, nutrients, absorption, bacterial counts, toxic metals, and microscopy analyses. Preliminary analyses of the data obtained thus far demonstrated that the organic SPM surpassed the inorganic counterpart in March 2015, which indicates that the biotic component had a bigger share in the water quality deterioration in this system. Relative abundances of major algal groups will be obtained employing ChemTax on the HPLC-derived photo-pigment data, which will be compared with the detailed community structure obtained using an imaging microcope, FlowCAM, and the toxin producing species quantified using qPCR. The phytoplankton, SPM, and CDOM concentrations will be used in tandem with reflectance measurements by the UAS for developing the capability for rapidly quantifying these water quality indicators using UAS data.