States can adopt numeric water quality criteria into their water quality standards to protect the designated uses of their coastal waters from eutrophication impacts. The first objective of this study was to provide an approach for developing numeric water quality criteria for coastal waters based on archived SeaWiFS ocean color satellite data. The second objective was to develop an approach for transferring water quality criteria assessments to newer ocean color satellites, such as MODIS and MERIS. Measures of SeaWiFS, MODIS, and MERIS chlorophyll-a (Chl RS -a , mgm −3 ) were resolved across Florida’s coastal waters between 1998 and 2009. Annual geometric means of SeaWiFS Chl RS -a were evaluated to determine a quantitative reference baseline from the 90th percentile of the annual geometric means. A method for transferring to multiple ocean color sensors was implemented with SeaWiFS as the reference instrument. The Chl RS -a annual geometric means for each coastal segment from MODIS and MERIS were regressed against SeaWiFS to provide a similar response among all three satellites. Standardization factors for each coastal segment were calculated based on the differences between 90th percentile from SeaWiFS to MODIS and SeaWiFS to MERIS. This transfer approach was allowed for future assessments, typically with <7% difference in the calculated criteria.
To enable the production of the best chlorophyll products from SeaWiFS data NOAA (Coastwatch and NOS) evaluated the various atmospheric correction algorithms by comparing the satellite derived water reflectance derived for each algorithm with in situ data. Gordon and Wang (1994) introduced a method to correct for Rayleigh and aerosol scattering in the atmosphere so that water reflectance may be derived from the radiance measured at the top of the atmosphere. However, since the correction assumed near infrared scattering to be negligible in coastal waters an invalid assumption, the method over estimates the atmospheric contribution and consequently under estimates water reflectance for the lower wavelength bands on extrapolation. Several improved methods to estimate near infrared correction exist: Siegel et al. (2000); Ruddick et al. (2000); Stumpf et al. (2002) and Stumpf et al. (2003), where an absorbing aerosol correction is also applied along with an additional 1.01% calibration adjustment for the 412 nm band. The evaluation show that the near infrared correction developed by Stumpf et al. (2003) result in an overall minimum error for U.S. waters. As of July 2004, NASA (SEADAS) has selected this as the default method for the atmospheric correction used to produce chlorophyll products.
Harmful algal blooms (HABs) have impacts on coastal economies, public health, and various endangered species. HABs are caused by a variety of organisms, most commonly dinoflagellates, diatoms, and cyanobacteria. In the late 1970's, optical remote sensing was found to have a potential for detecting the presence of blooms of <i>Karenia brevis</i> on the US Florida coast. Due to the nearly annual frequency of these blooms and the ability to note them with ocean color imagery, K. brevis blooms have strongly influenced the field of HAB remote sensing. However, with the variability between phytoplankton blooms, heir environment and their relatively narrow range of pigment types, particularly between toxic and non-toxic dinoflagellates and diatoms, techniques beyond optical detection are required for detecting and monitoring HABs. While satellite chlorophyll has some value, ecological or environmental characteristics are required to use chlorophyll. For example, identification of new blooms can be an effective means of identifying HABs that are quie intense, also blooms occurring after specific rainfall or wind events can be indicated as HABs. Several HAB species do not bloom in the traditional sense, in that they do not dominate the biomass. In these cases, remote sensing of SST or chlorophyll can be coupled with linkages to seasonal succession, changes in circulation or currents, and wind-induced transport--including upwelling and downwelling, to indicate the potential for a HAB to occur. An effective monitoring and forecasting system for HABs will require the coupling of remote sensing with an environmental and ecological understanding of the organism.
Conference Committee Involvement (1)
Remote Sensing of the Coastal Oceanic Environment
31 July 2005 | San Diego, California, United States