TCAA Water Quality Data Review and Information-Sharing Program
Growers Summary
University of Florida Water Institute & UF/IFAS Extension
Mark Clark, Wendy Graham, Kathleen McKee and Jeff Ullman
June 2012
The following is a less technical version of the main TCAA Water Quality Data Review. This less
technical summary was a recommendation during a draft review of the main document. We
hope it will be sufficient to answer questions initially posed by growers at the beginning of this
process, but if additional details for any of these questions are desired we encourage you to
reference the main TCAA Water Quality Data Review Document.
1.a. What assumptions, methods, and data were used to determine that the Lower St. Johns
River (LSJR) is impaired?
All waters under the jurisdiction of the State of Florida have a specified “designated use.” Each
designated use classification has associated water quality standards that are used as
benchmarks or thresholds to protect and maintain the designated use of the water body. The
designated use of the Lower St. Johns River is that of a “Class III” water which is intended to
support recreation, fishing and the protection of a healthy well balanced population of plants
and animals.
Routine water quality monitoring conducted by the SJRWMD and FDEP between 1991 and 2000
indicated that some water quality parameters in the river were not meeting the designated use
standards. This resulted in listing of the LSJR as potentially impaired. To verify if indeed the
river was impaired, additional water quality monitoring and studies were conducted and
findings collected between 1996 and 2003 indicated that nutrient levels and algal growth were
not meeting standards that would be expected to protect a healthy population of plants and
animals and therefore water quality was causing impairment of the designated use of the river.
Specific concerns related to 1) levels of algae in the water column (measured as chlorophyll-a)
that were either higher than acceptable thresholds or had increased more than 50% over
historical values for more than two consecutive years, 2) combined levels of chlorophyll-a and
concentrations of nitrogen and phosphorus in the water column that showed a high potential
for additional algal growth (known as the Trophic State Index or TSI), and 3) although not
specifically used in the verification process, low levels of dissolved oxygen in the marine portion
of the river.
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1.b. What assumptions methods, and data were used to determine nutrient loads to the
LSJR?
Point-source (e.g. wastewater treatment plant) nutrient loads to the LSJR basin (LSJRB) were
estimated using wastewater treatment plant effluent monitoring data (flow and nutrient
concentration) using interpolation between data points to fill in any monitoring gaps.
Agricultural and urban nonpoint-source nutrient loads to the LSJR basin were estimated using
the Pollution Load Screening Model (PLSM). The PLSM is a computer-driven spreadsheet model
that uses measured rainfall, land use, soils classifications, estimated seasonal runoff
coefficients, an estimated long-term rain ratio adjustment (accounts for changes in antecedent
moisture conditions associated with intra-annual patterns in rainfall and evapotranspiration),
and estimated water quality coefficients. The model predicts streamflow and stream nutrient
load at the outlet of drainage basins within the LSJRB on a seasonal basis.
The runoff coefficients used in the PLSM:
 vary seasonally,
 are land use and soil-drainage classification specific,
 were estimated based on data from studies conducted within the State of Florida
(including the LSJRB), and
 were evaluated using streamflow data from 5 sub-basins (called calibration
watersheds by SJRWMD) within the LSJRB from 1992 to 1995.
The long-term rain ratio adjustment was estimated using streamflow data from 4 of the 5
calibration watersheds measured from 1995 to 1999. Deep Creek data was not used to
estimate the long-term rain ratio due to poor performance of the acoustic flow meter at this
site.
The estimated water quality coefficients for Total Nitrogen (TN) and Total Phosphorus (TP):
 vary seasonally,
 are landuse specific and
 were estimated based on observations taken within 29 sub-basins in the LSJRB
from 1992 to 1995, and evaluated using data taken from 1995 to 1999.
It should be noted that PLSM estimates aggregated nutrient loads at the outlet of drainage
basins, based on the distribution of land uses within the basins, not at specific properties within
the basin.
1.b.i. What are the estimated relative load contributions for various land uses in the basin?
PLSM was used to estimate the 1995-1999 average TN and TP loads for nonpoint natural
sources (e.g. atmospheric deposition and natural forests), agricultural nonpoint sources (e.g.
row crops) and urban nonpoint sources (e.g. some residential and commercial land uses).
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These nonpoint-source TN and TP loads were added to measured point-source TN and TP loads
to estimate total TN and TP loads to the LSJR.
Figure 1 shows the relative TN load contributions and Figure 2 shows the relative TP load
contributions in the fresh tidal region of the LSJR that includes the Tri-County Agricultural Area
(TCAA).
Fresh Tidal Region Total N Loads
Other Nonpoint
0%
Urban Nonpoint
4%
Point Source
24%
Natural
Nonpoint
48%
Agricultural
Nonpoint
24%
Figure 1: Estimated TN Loads in the fresh tidal region (1995-1999) From Hendrickson et al.
(2002).
Nitrogen: Model predictions indicate that in the fresh tidal region of the river that receives
water from the TCAA, natural nonpoint sources (e.g., atmospheric deposition and natural
forests) are the major contributor to TN loads at 48%. However, the TN load from this natural
nonpoint source is largely in the form of refractory organic N, which breaks down slowly and
does not promote algal growth as readily as labile organic N. Agricultural nonpoint loads and
point-source loads are each estimated to contribute 24% of TN, with 71% of this TN estimated
to be in the forms of labile organic N and inorganic N, which are readily assimilated for algal
growth (Hendrickson et al, 2002). Because of the small fraction of urban area in this region,
urban nonpoint-source loads of TN are estimated to contribute only 4% (estimated to be in the
form of labile organic N).
Phosphorus: For TP, agricultural nonpoint-source loads are estimated to be the highest in the
fresh tidal region at 39%, with point-source loads estimated at 31%, natural nonpoint-source
loads estimated at 23%, and urban nonpoint-source loads estimated at 6%.
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Fresh Tidal Region Total P Loads
Point Source
31%
Other Nonpoint
1%
Urban Nonpoint
6%
Natural
Nonpoint
23%
Agricultural
Nonpoint
39%
Figure 2: Estimated TP Loads in the Fresh Tidal Region (1995-1999) From Hendrickson et al.
(2002).
1.b.ii. Is there information available to show how these loads have changed over time?
Annual modeled loads were estimated for 1995-1999. All of these estimates used the same
land use (i.e., the 1995 land use map for the LSJR basin, with agricultural land uses within the
TCAA updated using 2000 survey data) but different annual rainfall totals. No model
predictions have been made to date that vary land use over time to look at estimated changes
in load resulting from changes in land use.
However, measurements of TN and TP are made by the SJRWMD at the outlets of many subbasins in the LSJRB. Figures 3 and 4 show these data at the outlets of the five calibration
watersheds that were used to validate the runoff coefficients for the PLSM model. These data
indicate that the watersheds dominated by agricultural land uses (Deep Creek) have higher
mean TN and TP concentrations and higher peak concentrations than those dominated by
forested (N. Fork and S. Fork of Black Creek) or urban land uses (Ortega and Cedar). The
periodic peaks of TN and TP observed in agricultural watersheds (see full report for additional
data) indicate a potential to reduce total loads by developing management practices that
mitigate these events. Visually, there are no obvious changes over time in the TN and TP
measured at the outlets of these watersheds.
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30
Calibration Watersheds TN
North Fork Black Creek
Deep Creek
25
South Fork Black Creek
Ortega
Cedar
TN (mg/l)
20
15
10
5
0
07/11/89 04/06/92 01/01/95 09/27/97 06/23/00 03/20/03 12/14/05 09/09/08 06/06/11
Figure 3. Measured total nitrogen (TN) time series from approximately 11/1989 through
11/2011 for the stations of the five calibration watersheds in the LSJR basin (data obtained
from SJRWMD, 2011).
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4
Calibration Watersheds TP
North Fork Black Creek
3.5
Deep Creek
South Fork Black Creek
3
Ortega
TP (mg/L)
2.5
Cedar
2
1.5
1
0.5
0
07/11/89 04/06/92 01/01/95 09/27/97 06/23/00 03/20/03 12/14/05 09/09/08 06/06/11
Figure 4. Measured total phosphorus (TP) time series from approximately 11/1989 through
11/2011 for the stations of the five calibration watersheds in the LSJR basin (data obtained
from SJRWMD, 2011).
1.c. What assumptions, methods, and data were used to develop the TMDLs for the LSJR?
Chlorophyll a threshold: Previous research on the Lower St. Johns River concluded that

to maintain the diversity of plankton community,

to allow for the upward transfer of primary production to higher trophic levels while
maintaining zooplankton diversity and

to minimize the potential dominance of detrimental algal species and production of
algal toxins;
Chlorophyll-a concentrations should not exceed 40 µg/L (micrograms/Liter) more than 10% of
the time.
If levels rise above 40 µg/L for extended periods, research has shown there will be a shift in
algal species toward undesirable blue-green and toxic algal and a decline in zooplankton
communities, all of which would signal an imbalance in the aquatic plants and animals as well
as potential impacts to recreational activity due to algal blooms.
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Methods and Data: Using this understanding between chlorophyll-a concentration and the
biological health of the LSJR, relationships were developed for the amounts of nutrients that
could be added to the river and still maintain chlorophyll-a levels less than 40 µg/L for 90% of
the time.
The maximum level of nitrogen and phosphorus that could be added to the river and still
maintain this chlorophyll-a target and acceptable levels of dissolved oxygen is the Total
Maximum Daily Load (TMDL). TMDLs for water bodies are typically calculated on an annual
average basis.
To determine the TMDL in the LSJR, three models were used to:
1. Estimate nutrient loads coming from the entire LSRJ watershed (PSLM model),
2. Predict hydrodynamics of flow in the St Johns River (Environmental Fluid Dynamics Code
model – EFDC),
3. Simulate the transport and transformation of nutrients and processes affecting the
conversion of nutrients into algal growth and changes in dissolved oxygen levels in the
St Johns River (CE-QUAL-ICM version 2, Core of Engineers – Quality Integrated
Compartment Model).
Results of these models indicated that to maintain chlorophyll-a concentration and duration
within the target range, and to maintain dissolved oxygen levels in the marine portion of the
LSJR, the maximum loading of nitrogen and phosphorus in the freshwater portion of the river
would need to be less than 8,571,563 kg/yr and 500,325 kg/yr, respectively.
1.d. What assumptions, methods, and data were used to develop the load reduction
allocations for the LSJR BMAP and for the TCAA in particular?
Load reduction allocations were developed for individual land uses in the LSJRB based on
guidelines established by the Statewide Allocation Technical Advisory Committee (ATAC). This
committee and the guidelines they established were meant as a general rule for load
reductions in all BMAPs not just the LSJR. The ATAC recommended that agricultural and urban
nonpoint sources be required to implement BMPs to provide minimum levels of treatment as a
more “even-handed and balanced approach to attainment of water quality objectives” before
point sources are required to implement additional reductions (FDEP, 2001). The general ATAC
allocation process consists of a multistep approach whereby potential load reductions resulting
from implementation of BMPs are initially subtracted from the needed reductions in nutrient
loads and then if the required load reduction is not met then the remaining load reduction
required is distributed proportionally among land uses based on initial estimates of contributed
loads.
In the case of agricultural lands in the TCAA discharging to freshwater portions of the LSJR, the
initial starting load was estimated at 683,540 lbs/yr for TN and 183,601 lbs/yr for TP (Table 1).
The allowable loading from agricultural land uses – while still meeting protective water quality
targets in freshwater portions of the LSJR – was found to be 427,538 lbs/yr of TN and 156,143
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lbs/yr of TP. The difference between the initial load and the allowable load is 256,001 lbs/yr of
TN and 27,458 lbs/yr of TP, or a required reduction of 37.5% TN and 15% TP. Implementation
of agricultural BMPs on 100% of agricultural lands was estimated to result in a 36% (246,074
lbs/yr) reduction in TN and an 11% (20,196 lbs/yr) reduction in TP. This leaves 9,927 lbs/yr of
TN and 7,262 lbs/year of TP as remaining load reduction required from agriculture after BMPs
are implemented. This residual amount is expected to be treated using Regional Stormwater
Treatment systems (RSTs).
Table 1: Fresh tidal region agricultural load reduction summary
TN (lbs/year) TP (lbs/year)
Initial load from agricultural lands in the fresh tidal region
683,540
183,601
Allowable loading from agriculture to the river in the fresh tidal
427,538
156,143
region
Difference = What needs to be removed before going to river
Assumed reduction by implementing agricultural BMPs on 100%
of agricultural land in the fresh tidal region
Remaining load reduction to be achieved by other means (e.g.
regional stormwater systems)
256,001
(37.5%)
246,074
(36%)
9,927
27,458
(15%)
20,196
(11%)
7,262
1.d.i. Is the required load reduction aggregated by total land use in the basin, or is it a
required reduction per unit acre of a specific land use?
In the LSJR BMAP, nonpoint-source load reduction responsibilities are assigned for general land
use categories and thus required load reductions are not applied on a unit acre basis. One
hundred percent implementation of BMPs for nonpoint sources is expected for both
agricultural and urban areas in the LSJRB.
Agricultural producers in a BMAP area either must adopt BMPs to protect water quality or
monitor their water quality to demonstrate compliance with water quality standards.
Producers who implement applicable FDACS BMPs receive a “presumption of compliance” and
have fulfilled their responsibilities.
1.d.ii. Was the feasibility of reducing nutrient loads and effectiveness of implementing
agricultural and urban BMPs considered when allocating load reductions?
It was assumed that FDACS-adopted agricultural BMPs are economically feasible. It was
similarly assumed that urban nonpoint sources would reduce loads to the Maximum Extent
Possible (MEP) using BMPs. One hundred percent implementation of BMPs was required for
agriculture and urban nonpoint sources to cover their “fair share” of load reductions. The
remainder of the reduction required for agriculture was planned to be achieved by Regional
Stormwater Treatment systems (RSTs).
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The following BMP efficiencies were assumed in the LSJR BMAP calculations:

Urban stormwater: 30% Nitrogen Removal, 50% Phosphorus Removal

Agricultural stormwater: 36% Nitrogen Removal, 11% Phosphorus Removal
1.d.iii. What is the performance of the two existing RSTs?
The purpose of the Regional Stormwater Treatment systems (RSTs) is to treat the remaining
nitrogen and phosphorus load allocated to agricultural sources that cannot be met by
implementation of on-farm BMPs. Relative to target load reductions outlined in the Basin
Management Action Plan, which was 1,000 kg/yr of TN and 818 kg/yr of TP for the Deep Creek
West RST, the system has outperformed expectations. Nutrient load data available for 2009
through August 2010 showed an average 3,017 kg of TN and 1,321 kg of TP removed each year.
This is 302% and 162% higher nitrogen and phosphorus removal efficiencies than the BMAP
performance target. No load data was available for the Edgefield RST and therefore its load
reduction relative to performance targets could not be evaluated. Long-term efficacy of these
systems may change and will need to be monitored but based on performance data from the
Deep Creek RST, nitrogen and phosphorous removal rates are presently significantly greater
than target levels.
2. Were the assumptions, data, and models used to develop the TMDL and BMAP for the LSJR
consistent with best professional practices for development of other TMDLs? Did the process
make use of the best information available? If not, how could the assumptions, data, models,
and development process be improved?
Determination of the TMDL: Methods and assumptions used to determine that the LSJR was
impaired are similar to those being implemented throughout the State of Florida to determine
and verify if a water body is meeting water quality standards established for a particular
designated use. Determination of the TMDL for the LSJR was the first developed for a large river
system in Florida that combined both freshwater and marine mixing zones. Due to the
complexity of this interaction, an appropriately complex modeling effort was used to evaluate
the nutrient and biological response dynamics of the system in an effort to best determine the
TMDL that would be protective of Class III waters designated use. The modeling effort applied
was, and still is, one of the most sophisticated models available to predict the effects of
estuarine eutrophication, and its results were confirmed with a substantial suite of monitoring
data collected from the LSJR.
The threshold chlorophyll-a concentrations used to set the TMDL were based on research
findings from monitoring data and studies conducted in the LSJR, and are expected to be
protective of a well-balanced aquatic flora and fauna. The application of these site-specific
criteria – rather than thresholds based only on the Impaired Waters Rule (IWR) guidelines –
demonstrates the level of effort in this basin to use the best available site-specific information.
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Although this TMDL was one of the first to be developed (and therefore did not have many
documents to compare to at the time) the approach to verifying impairment and establishing
appropriate nutrient thresholds, established the precedent for TMDLs developed subsequently.
Recommendations: There was a considerable amount of high-quality monitoring and research
data available to support both chlorophyll-a threshold development and modeling efforts for
this TMDL. Continued monitoring to confirm nutrient dynamics and biological and dissolved
oxygen response (as predicted in TMDL effort using the EFDC and CE-QUAL-ICM models) is
recommended to build further confidence in model predictions of the system.
Estimation of the nonpoint-source loads: Use of the PLSM to estimate nonpoint-source loads is
generally consistent with best practices for TMDL and BMAP development, and has been used
to estimate watershed loadings at various locations in Florida. The strength of the PLSM model
is that it is an empirical model constrained by data taken within the LSJRB. The Hydrologic
Simulation Program – Fortran (HSPF), Surface Water Management Model (SWMM), and
Watershed Assessment Model (WAM) (Borah and Bera, 2004; Graham et al., 2009) are more
process-oriented models that have also been recognized by EPA and FDEP as useful for
estimating watershed loads for TMDL development. However these models require much more
data for calibration and validation than the PLSM, and are not guaranteed to be more accurate.
PLSM Recommendations: At the time the PLSM was first developed and applied to the LSJR
(during 1992-2000), it utilized the readily available data for land use, soil drainage, rainfall,
streamflow, and water quality to determine inputs and estimate runoff and water quality
coefficients. However, since the model was developed, land use has changed and additional
rainfall, streamflow, and water quality data have become available. Thus, for the next round of
TMDL/BMAP development for the LSJRB, the land use in PLSM should be updated, and the
runoff and load predictions should be validated with new rainfall, streamflow, and water quality
data to evaluate the predictive reliability of the model. If possible, additional field-scale runoff
and nutrient water quality data should be gathered to help refine land-use-specific runoff and
water quality coefficients. In addition, the sensitivity of PLSM streamflow volume and nutrient
load predictions to model structure and parameter uncertainty should be formally assessed.
Conducting these activities in collaboration with agricultural stakeholders should help build
confidence that the PLSM model developed for this application is as accurate as possible and
suitable for the purpose intended.
While there is some uncertainty in the loading estimates provided by the PLSM for the LSJRB,
available measured data and model estimates indicate that agricultural practices have
contributed to nutrient loads and decline in water quality in the LSJR. The exact efficacy of
agricultural BMPs has not been fully assessed and current efficacy estimates should be reevaluated over time as additional data are collected to determine the effectiveness of existing
and new BMPs.
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Recommendations for next round of TMDL/BMAP evaluation: During this review the
committee found a discrepancy between the considerable efforts made by agencies to facilitate
stakeholder awareness and elicit input during the LSJR TMDL/BMAP process; and the actual
awareness by agricultural stakeholders of the process, their understanding of the technical
details and their perception that their concerns were actually heard. Since the greatest
expectation for success in addressing nutrient loading is a partnership among all stakeholders,
resolving this discrepancy in future BMAP processes should be a high priority. Jordan et al.
(2011), NRC (2001,2008), and Pahl-Wostl (2009) provide interesting insights on strengths and
weaknesses of various methods for engaging the public in environmental decision making, and
provide strategies for bringing multi-stakeholder groups together to improve the capacity,
salience, legitimacy, and credibility of environmental governance and decision-making for
issues ranging from TMDL development to global climate change. During the next round of
TMDL/BMAP evaluation, as well as implementation of TMDL/BMAP programs in other
watersheds, new strategies for engaging agricultural stakeholders in the process should be
explored.
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