Paper No. 4
Presentation Time: 9:00 AM-6:00 PM
APPLICATIONS OF MODIS DATA TO ESTIMATE WATER QUALITY PARAMETERS IN THE OPTICALLY COMPLEX WATERS OF THE WESTERN BASIN OF LAKE ERIE
MODIS sensor aboard Aqua Satellite has been successfully applied to monitor water quality of open marine waters where optical property is primarily governed by a single in-water constituent: phytoplankton. In this study application of Satellite to monitor water quality of large turbid inland water bodies is assessed. This study focuses on Lake Erie, which is biologically the most active among the Great Lakes of North America. For almost two decades, the western basin of Lake Erie has been affected with recurring toxic algal blooms dominated by cyanobacteria which are detrimental to human health and the lake’s biodiversity. Early detection of harmful algal blooms in Lake Erie requires a more efficient and accurate monitoring tool. Remote Sensing can become an efficient tool because its high spatial and temporal coverage allowing for accurate and timely detection of recurring cyanobacteria blooms. Multiple color producing agents (CPAs) including phytoplankton, colored dissolved organic matter (CDOM), and suspended sediment influence the optical properties of the Western Basin of Lake Erie (WBLE). This makes WBLE optically complex, and the task of independently retrieving estimates of the CPAs becomes challenging. In this study the performance of MODIS in WBLE is assessed by applying VIS/NiR bio-optical algorithms to determine chlorophyll- a (a proxy for phytoplankton density), total suspended matter and CDOM independently. In situ data, including biogeochemical properties of the lake, were collected and processed from 18 stations within WBLE on five cruises concurrent with MODIS overpass. CPA concentrations are estimated from MODIS data by applying bio-optical algorithms and correlating the results with in-situ measurements. Two specific bio-optical models are used to estimate chlorophyll-a values; blue/green (555 nm/488 nm) and NIR/red (748/678 nm) and these produced R2 values of 0.78 and 0.48, respectively. A blue/green model (531/667) is used to estimate CDOM values, producing an R2 value of 0.40. For total suspended sediment (TSM), the best correlation with MODIS data was found at 748 nm, producing an R2 value of 0.62. The resulting algorithms are applied to the MODIS images in the ENVI 4.8 environment to show the spatial and temporal variability for each constituent.