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. 2012 Jan 17;46(2):916-22.
doi: 10.1021/es2014105. Epub 2012 Jan 5.

An approach to developing numeric water quality criteria for coastal waters using the SeaWiFS Satellite Data Record

Blake A Schaeffer  1 , James D Hagy, Robyn N Conmy, John C Lehrter, Richard P Stumpf
Affiliations
Free PMC article

An approach to developing numeric water quality criteria for coastal waters using the SeaWiFS Satellite Data Record

Blake A Schaeffer et al. Environ Sci Technol. .
Free PMC article

Abstract

Human activities on land increase nutrient loads to coastal waters, which can increase phytoplankton production and biomass and associated ecological impacts. Numeric nutrient water quality standards are needed to protect coastal waters from eutrophication impacts. The Environmental Protection Agency determined that numeric nutrient criteria were necessary to protect designated uses of Florida's waters. The objective of this study was to evaluate a reference condition approach for developing numeric water quality criteria for coastal waters, using data from Florida. Florida's coastal waters have not been monitored comprehensively via field sampling to support numeric criteria development. However, satellite remote sensing had the potential to provide adequate data. Spatial and temporal measures of SeaWiFS OC4 chlorophyll-a (Chl(RS)-a, mg m(-3)) were resolved across Florida's coastal waters between 1997 and 2010 and compared with in situ measurements. Statistical distributions of Chl(RS)-a were evaluated to determine a quantitative reference baseline. A binomial approach was implemented to consider how new data could be assessed against the criteria. The proposed satellite remote sensing approach to derive numeric criteria may be generally applicable to other coastal waters.

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Figures

Figure 1
Figure 1
Station data and coastal segments used in satellite remote sensing analysis of ChlRS-a and KdRSPAR. Coastal segments were delineations proposed in this approach to develop numeric chlorophyll criteria for the (A) Florida Panhandle, (B) West Florida Shelf, and (C) Atlantic Coast. Open circles indicate the station data used to compare Chl-a to satellite remote sensing observations of ChlRS-a. Filled triangles indicate station data used to compare KdPAR to satellite remote sensing observations of KdRSPAR. Numbers are coastal segment numbers ranging from 1 through 76.
Figure 2
Figure 2
SeaWiFS observations of ChlRS-a compared to in situ Chl-a from stations within coastal segments (A) and for all the stations (B). Gray dashed line is 1:1 fit and black line is regression slope. Plots are presented in log space, but regression coefficients have been converted to linear space to represent a linear regression formula of y = slope*x + intercept.
Figure 3
Figure 3
Corrected ChlRS-a boxplots for all coastal segments between 1997 and 2009 with the minimum and maximum (black dots), the 10th and 90th (whiskers), the 25th and 75th (boxes) percentiles.
Figure 4
Figure 4
(A) Trailing 3-year cumulative distribution functions for ChlRS-a in segment 22 (outside Tampa Bay) for 1998 through 2009. The estimate of the 90th percentile of medians and upper quartiles (75th percentile), which are 2.37 and 3.10, respectively, could be used as criteria values. (B) Computed criteria values for all 76 coastal water segments. Insufficient data prevent computations for segments 35 and 72.
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