Refinement of the Charlotte Harbor National Estuary Programs Numeric Water Quality Targets for Lemon

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Refinement of the Charlotte Harbor National
Estuary Programs Numeric Water Quality Targets
for Lemon Bay, Charlotte Harbor and Estero Bay,
Florida
Catherine A. Corbett1 and Mike Wessel2 1Charlot
te Harbor National Estuary Program 2Janicki
Environmental Inc.
March 25, 2008
Photo by J. Boswell SCCF
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Why Numeric Targets?

• Rapid population increase and urbanization in
  watershed in recent past and trend is expected to
  continue
• Water quality in some areas of Charlotte Harbor
  is degrading
• Reason for concern for the long-term maintenance
  of essential fish habitat in region
• How do we stop the declining trends and protect
  the Charlotte Harbor watershed for future
  generations?
• Need scientifically defensible methods

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Resource Management Concerns

• Seasonal hypoxia in bottom waters of upper
  Charlotte Harbor
• Conditions started ca. 1950s (Turner et al.)
• In 1980s FDNR reported Caloosahatchee reached
  nutrient loading limits
• Seasonal chl a levels gt 60-80 µg/l in the tidal
  Peace since monitoring began in 1976 (FDEP)
• Seasonal chl a levels gt 20µg/l consistently
  observed in the tidal Peace and Myakka (FDEP)
• Conditions are considered indicative of eutrophic
  to hypereutrophic conditions in some estuarine
  water quality classification systems (e.g., NOAA)

From News-Press, 2006
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Water Quality Impairments (southern CH)

• TMDLs expected
• Dissolved Oxygen

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Water Quality Impairments (southern CH)

• TMDLs expected
• Dissolved Oxygen
• Nutrients (chl a TSI)
• 2008 for Caloosahatchee nutrients
• 2009 for Estero Bay

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Water Quality Impairments (CH/Lemon Bay)

• TMDLs expected
• Upper Lemon Bay
• Nutrients (chl a)
• Alligator Creek Rock Creek
• Dissolved Oxygen
• Expected 2008

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Water Quality Impairments (CH/Lemon Bay)

• TMDLs expected
• Upper Lemon Bay
• Nutrients (chl a)
• Alligator Creek Rock Creek
• Dissolved Oxygen
• Expected 2008

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Water Quality Trends (Upper Lemon Bay)

• TP, chl a ammonia increasing (TN, TKN, BOD
  decreasing)
• Light attenuation decreasing
• No trends in color
• Dec trend in TSS
• Inc trend in turbidity
• Salinity Cond inc

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Water Quality Trends (Upper Lemon Bay)

• TP, chl a ammonia increasing (TN, TKN, BOD
  decreasing)
• Light attenuation decreasing
• No trends in color
• Dec trend in TSS
• Inc trend in turbidity
• Salinity Cond inc

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Water Quality Trends (Upper Lemon Bay)

• TP, chl a ammonia increasing (TN, TKN, BOD
  decreasing)
• Light attenuation decreasing
• No trends in color
• Dec trend in TSS
• Inc trend in turbidity
• Salinity Cond inc

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Water Quality Trends (southern CH)

• Nutrients increasing through 2005
• Suspended matter increasing through 2005

Numeric Water Quality Targets serve as the basis
for restoration maintenance activities to stop
declining trends
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Methods for Water Quality Targets

• Historical Conditions - water quality conditions
  of Charlotte Harbor in pre-development or a
  specified time period
• Regulatory - adopt existing regulations (e.g.,
  DEPs Impaired Waters Rule)
• annual average chl a concentration of 11 ug/L
• DO shall not average less than 5.0 mg/L in a
  24-hour period and shall never be less than 4.0
• Turbidity lt 29 NTU above natural background
  conditions
• Transparency shall not be reduced by more than
  10 as compared to the natural background value
• Reference Site - compared to a pristine
  location
• Resource-Baseddetermine needs to meet a resource
  or recreational use/aesthetic value

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Local Examples

• Tampa Bay Resource Based Approach Restore to
  95 of 1950s seagrass coverageequals a recovery
  of 12,350 acres of seagrass
• Water clarity in Tampa Bay is related to
  phytoplankton chlorophyll a levels
• Target maintain existing conditions by reducing
  future nitrogen emissions to the Bay by _at_7 by
  2010 or 17 tons per year
• Reductions in nitrogen loadings since 1982
  resulted in increased seagrass coverage between
  1982-1996

• Indian River Lagoon Resource-based Approach
  Segmented Lagoon into 5 segments determined
  depth distribution of seagrass in eachJupiter
  Inlet had deepest beds
• Used median deep edges of Jupiter Inlet beds as
  target depth (1.3 meters)
• Compared water quality conditions in areas that
  had beds gt 1.3 m deep and used median values of
  these regions as targets for salinity, color,
  turbidity, DO, pH and PAR

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Light Attenuation inCharlotteHarbor

• Spatial and Temporal Variability
• Non-chlorophyll suspended matter contributes
  30-72 to total light attenuation
• Colored dissolved organic matter contributes
  13-66
• Chlorophyll a contributes 4-18
• Seawater contributes 3-6
• Max depths of seagrass beds inc with distance
  from rivers and inc salinitiesWater clarity inc
  w/ inc salinity

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12 Hydrologic Segments55 FDEP Seagrass
Transects
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Seagrass Depth Targets by Segment
1) Used 55 FDEP Seagrass Transects
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Seagrass Depth Targets by Segment
2) Added Bathymetry and WMDs Seagrass Maps
analysis gt95 coverage shallower than target
depth
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Seagrass Annual Light Requirements

• In Indian River Lagoon, H. wrightii and S.
  filiforme require between 23-37 (cited in
  Gallegos and Kenworthy, 1996)
• 20.5 PAR in Tampa Bay, 25-50 PAR in Sarasota
  Bay (cited in Dixon, L.K. 2000)
• 15-30 PAR in Charlotte Harbor (Dixon and
  Kirkpatrick 1999)
• Tomasko and Hall 1999 found average 23 PAR
  reaching T. testudinum beds but noted decline
  temperature and salinity stress factors
• For optical model to follow, we used a goal of
  25 subsurface irradiance reaching deep edge of
  seagrass beds (25 light that has already passed
  thru air-water interface)

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Goal 25 incident light at 2.2 m depth(using
PIS and SCB segments as examples)

• Solve for k at 2.2 m and 25 PAR using
  Lambert-Beers Law
• light at depth/100 e-kd
• where light at depth is seagrass light
  requirement, e is the base of the natural
  logarithm, k is the light attenuation coefficient
  (in m-1), and d equals our depth goal
• 0.25 e-k2.2
• ln(0.25) ln(e-k2.2)
• -1.4 -k2.2
• k 0.6

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Components of Light Attenuation in Water Column

• Kd KColor KNaSS Kchl a Kwater (Kirk
  1983)
• Kd 0.014color 0.062turbidity0.049Chl
  a0.30
• (McPherson and Miller 1994)
• This gives us our Intercepts
• Color 24.0 PtCo
• Turbidity 5.4 NTU
• Chl a 6.9 µg/L

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Seagrass Depth Targets with partial attenuation
intercepts
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Plane of Constant Attenuation
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Model Validation

• Based on model predictions, wq conditions do not
  meet the developed targets most of time
• Next step was to evaluate the optical model
  validity reliability to how well model
  predicted observed Kd data
• Resultsvariability between modeled observed
  data in few places the model may over-estimate
  the effects of chl a on light attenuation
• for most basins the model predicted Kd without
  significant bias

Therefore, the optical model is generally
appropriate
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Future Refinements

• Develop Exceedance Criteria
• Incorporate Quality of Light component to
  Quantity of Light
• Better understand components of color and
  non-algal suspended matter spatially and
  temporally
• Refine the non-algal suspended matter partial
  coefficient derived from McPherson and Miller
  1994
• component is generally responsible for over 50
  of light attenuation
• the components of non-algal suspended matter
  will differ by stratum and by season
• quantity of TSS and turbidity differ
  significantly between dry and wet seasons and TSS
  differs between strata
• Incorporate Seasonality--water clarity important
  in growing season
• Better understand role of salinity stress affects
  on light needs of seagrass species

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Current Work

• Before creation of Exceedance criteria
• Validate hydrologic segments
• CHAP staff will calculate the quantity of area,
  the season and locations of collected data that
  exceed the plane of constant attenuation for each
  individual segment
• Segments now composite water quality data
  collected in rivers with open bay
• Could be vastly different water chemistry (e.g.,
  Estero Bay)

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Current Work

• Regionally-Specific Optical Models
• CHAP staff are creating regionally specific
  partial attenuation coefficients
• Seasonal as well
• Determine if partial coefficients change
  significantly between segments
• Model works generally well for entire region but
  could segment-specific models significantly
  improve method?
• This step could incorporate regional concerns
  (e.g., regional/seasonal importance of individual
  light attenuation components)

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New

• As of 3/19/08, FDEP will be using these as
  targets for Caloosahatchee River nutrient TMDLs
• Using targets for San Carlos Bay segment (2.2
  meters for seagrass depth, 25 PAR and line of
  constant attenuation)

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Acknowledgements

• Peter Doering Bob Chamberlain
• Keith Kibbey Tony Pellicer
• Jennifer Nelson
• Mike Wessel Tony Janicki
• Jason Hale, Patrick Biber Ron Miller
• Katie Fuhr, Judy Ott Stephanie Erickson
• Dave Tomasko Ray Kurz
• Charles Kovach, Holly Greening and Seagrass
  Working Group
• Keith Kibbey, James Evans, Connie Jarvis, Patrick
  Casey, Kris Kaufman, Philip Stevens, Joanne
  Vernon others of Coastal Charlotte Harbor
  Monitoring Network
• Jaime Greenawalt Boswell and Kris Kaufman

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Questions?