# MODEL-BASED ESTIMATES OF TOTAL

NITROGEN LOADING TO TAMPA BAY:

CURRENT CONDITIONS AND UPDATED

2010 CONDITIONS

Prepared for:



# Tampa Bay Estuary Program

Mail Station I-1/NEP

100 8 th 

# Avenue SE

St. Petersburg, FL 33701

Prepared by:

A. Janicki, R. Pribble, H. Zarbock,

S. Janicki, and M. Winowitch

1155 Eden Isle Drive NE

St. Petersburg, FL 33704

July 2001

# FOREWORD

This report was prepared by Janicki Environm ental, Inc. under the direction of Mr. Dick

Eckenrod and Ms. Holly Greening of the Tamp a Bay Estuary Program. This work was

performed under Contract No. T-98-06 for the Tampa Bay Estuary Program.

ii

# ACKNOWLEDGMENTS

Many individuals and groups contributed to th e completion of this report through review

and technical insight, and by providing data a nd other information vital to this analysis.

Special thanks are extended to the following groups and individuals for their assistance:

the SWFWMD/TBEP Joint Water Quality Subc ommittee; Mr. Bruce DeGrove, Florida

Phosphate Council; Mr. Richard Eckenrod, Ta mpa Bay Estuary Program; Ms. Holly

Greening, Tampa Bay Estuary Program; Ms. Sheri Lovely, Pinellas County Utilities; Mr.

Charles Kovach, Florida Department of Envi ronmental Protection, Tampa Office; and Ms.

Marsha Reese, Environmental Protec tion Commission of Hillsborough County.

iii

# TABLE OF CONTENTS

FOREWORD i i

ACKNOWLEDGMENTS iii

1 I NTRODUCTION 1

- 1

1

. 1 O b j e c t i v e s 1

- 2

2 ATMOSPHERIC DEPOSITION 2

- 1

2.1 Current Conditions Atmospheric De position Loading Estimates 2-1

2.1.1 Data Sources 2-1

2.1.2 Methods 2-1

2.2 2010 Conditions Atmospheric Depos ition Loading Estimates 2-2

2.2.1 Data Sources 2-2

2.2.2 Methods 2-3

3 DOMESTIC AND INDUSTRIAL POINT SOURCES 3-1

3.1 Current Conditions Point Source Loading Estimates 3-1

3.1.1 Data Sources 3-1

3.1.2 Methods 3-2

3.2 2010 Conditions Point Source Lo ading Estimates 3-3

3.2.1 Data Sources 3-4

3.2.2 Methods 3-4

4 SPRINGS AND GROUNDWATER 4

- 1

4.1 Current Conditions Springs and Gr oundwater Loading Estimates 4-1

4.1.1 Data Sources 4-1

4.1.2 Methods 4-1

4.2 2010 Conditions Springs and Groundwat er Loading Estimates 4-2

4.2.1 Data Sources and Methods 4-2

5 MATERIAL LOSSES 5

- 1

5.1 Current Conditions Material Losses Loading Estimates 5-1

5.1.1 Data Sources 5-1

5.1.2 Methods 5-1

5.2 2010 Conditions Material Losses Loading Estimates 5-1

5.2.1 Data Sources and Methods 5-1

6 NONPOINT SOURCES 6

- 1

6.1 Current Conditions Nonpoint Source s Loading Estimates 6-1

6.1.1 Data Sources 6-1

6.1.2 Methods 6-3

iv

### 6.2 2010 Conditions Nonpoint Sources Loading Estimates 6-6

6.2.1 Data Sources 6-6

6.2.2 Methods 6-11

7 RESULTS OF LOADING ANALYSIS 7

- 1

7.1 Current Conditions 7-1

7.2 2010 Conditions 7-7

8 CONCLUSIONS 8

- 1

9 LITERATURE CITED 9

- 1

APPENDIX 1 Individuals Contacted for Future C onditions Point Source Information and

Summary of Interviews

APPENDIX 2 Aggregated Florida Land Use and Cover Classification System Categories

APPENDIX 3 Land Use-Specific Seasonal Runoff Coefficients

APPENDIX 4 Land Use-Specific Runoff Water Quality Concentrations

APPENDIX 5 Existing and Projected Future Land Use Acreages

v

# 1. INTRODUCTION

One of the primary goals established in th e Tampa Bay National Estuary Program (TBNEP)

Comprehensive Conservation and Management Pl an (CCMP) (TBNEP, 1996) is to restore

seagrass extent in the bay to levels similar to those observed in the 1950s. Seagrass extent

and condition can be impacted by many factors, including water quality.

To attain the seagrass restoration goal, th e TBNEP developed the Nitrogen Management

Strategy. The Strategy seeks to prevent future impacts due to excessive nitrogen loadings to

Tampa Bay. To provide quantifiable goals for the Strategy, a paradigm that relates nitrogen

loading to water quality and re storable seagrass acreage was utilized, as shown in Figure 1-

1.

TN LOAD CHLORO PHYLL LI GHT

ATT E NU AT I O N

SEAG RA SS LI G H T

REQU I R E M EN T SEAG RA SS

COV E RA GE



### Figure 1-1. TBNEP Nitrogen Management Paradigm.

To quantify the relationships represented in th e paradigm, empirical relationships between

external total nitrogen (TN) loads and chlorophyll a concentrations, between chlorophyll a concentrations and light attenuation, and betw een light availability and restorable seagrass

area were developed and presented in Janicki and Wade (1996). These relationships were

developed for the Old Tampa Bay (OTB), H illsborough Bay (HB), and Middle Tampa Bay

(MTB) segments.

Using these relationships, predictions of the responses in chlorophyll a concentrations,

light attenuation, and the extent of seagrass restoration to changes in external TN loading

were derived.

The model predictions suggested that seagrass restoration goals could be met by meeting

chlorophyll a concentration and light attenuation targets for the four mainstem bay

segments. Two sets of chlorophyll a targets were considered, as follows:

• the chlorophyll a concentrations which would be expected to result in

restoration of 95% of the seagrass goals for the segments; and

1-1

### • the mean chlorophyll a concentrations observed during the 1992-94 period,

i.e., current conditions at the time.

The latter set was considered since all evide nce suggested that seagrass areal coverage had

been increasing since 1988. It was concluded that the more prudent targets would be the

lower of these two sets for each bay segmen t. Light attenuation targets were set based on

the segment-specific depths necessary to allow for attainment of 95% of the seagrass goals.

The estimated 1992-1994 mean annual TN loads represent those loads identified by the

TBNEP expected to result in light availability sufficient to meet the seagrass restoration

goals. The empirical model relating total n itrogen loads to seagrass restoration goals

(Janicki and Wade, 1996) suggested that light av ailability necessary fo r obtaining seagrass

restoration goals could be met by establishing a “hold the line” strategy fo r nitrogen loads.

This strategy would hold nitrogen loads to each segment of the bay to the average levels of

1992-1994. The Tampa Bay Nitrogen Managemen t Consortium adopted this strategy in

1996.

To implement this strategy, local government pa rtners agreed to pr eclude increases in

future nitrogen loadings to the bay. The ca. 2010 total nitrogen loading estimates

presented in Zarbock et al. (1996a) were developed to quantify expected TN loading

increases, and were used for the TBNEP Allocation Workshops.

1.1 Objectives

The Tampa Bay Estuary Program (TBEP) is curre ntly performing an update of the estimated

TN loadings for the ca. 2010 period. This update incorporates the best available

information as of 2000 for es timating ca. 2010 TN loads. The objective of this report is to

update the expected future nitrogen loading from external sources to each bay segment

for the year 2010. The annual average loading estim ates for 2010 are derived from

estimated future monthly loading estimates, us ing methods similar to those used previously

(Zarbock et al., 1996a). In additional, this update contains the modeled TN loading

estimates for current conditions.

Loading estimates were develope d for each of the seven segments of Tampa Bay (Figure 1-

2). The loading sources examined include:

• atmospheric deposition,

• domestic and industrial point sources,

• groundwater and springs,

• material losses from fertilizer handling facilities, and

• nonpoint sources.

1-2

### The following sections present descriptions of the data and methods used for the estimated

current and 2010 TN loadings from each lo ading source in the Tampa Bay watershed

(Figure 1-3). Then a summary of the estimat ed TN loadings by bay segment, and the

estimated loadings by bay segment and jurisdiction, for 2000 and 2010 is provided,

followed by the conclusions.

Jurisdictional loads were estim ated for Hillsborough, Pinellas, and Manatee counties, and

the cities of Tampa, St. Petersburg, Clearw ater, and Bradenton. Estimated loadings

originating in Polk, Pasco, and Sarasota coun ties were incorporated into the bay segment

TN loadings, but were not inco rporated into the jurisdictiona l loadings. Only land-based

sources of TN were accounted for in the jurisdictional load ings. Atmospheric deposition,

springs, and groundwater loadings were not apportioned to any county or municipality.

1-3

### Figure 1-2. Bay segments of Tampa Bay.

1-4

### Figure 1-3. Major basins of the Tampa Bay watershed.

1-5

# 2. ATMOSPHERIC DEPOSITION

2.1 Current Conditions Atmospheri c Deposition Loading Estimates

Atmospheric deposition is defined as the pollutant load delivered to the surface of

the bay from the fallout of airborne pollutants, including both rainfall (wet) and

airborne (dry) pollutants. Only nutrients delivered to the open water estuary were

accounted for as atmospheric input.

2.1.1 Data Sources

The methods used for estimation of the curre nt TN loading were the same as those

used previously, with the exception of the precipitation nitrogen concentration data

and the ratio of dry to wet nitrogen depositi on. Descriptions of the methods used in

both the previous current condition es timate (Zarbock et al., 1996a) and the

updated current conditions estimate are provided below.

The previous current loading estimate utilized the best available data for developing

the TN loading from atmospheric depositi on. Estimates of atmospheric deposition

loads were derived from the 1992-1994 NW S rainfall records and precipitation

concentration data from the NADP Vern a Wellfield site. The ratio of dry:wet

deposition was 2.04:1, as in the estimate of 1992-1994 loadings (Zarbock et al.,

1996b).

This updated loading estimate for current conditions differed from the previous

estimate by utilizing more s ite-specific information for precipitation concentration

and dry deposition. In Augu st 1996, the TBEP initiated monitoring as part of the

Tampa Bay Atmospheric Deposition Study (TBADS). This program includes

sampling elements for both wet and dry depos ition at an intensive monitoring site

located on the Gandy Bridge Causeway. The data available from TBADS that can

be used to estimate atmospheric depos ition to Tampa Bay include nitrogen

concentration data, wet and dry deposition ra tes, and an estimate of the ratio of

dry:wet deposition. These data, together with the 1992-1994 hydrologic load from

rainfall, were used to update the estim ate of current cond itions atmospheric

deposition TN loading.

2.1.2 Methods

Precipitation volume (rainfall depth times the open water area of the bay) and

pollutant concentration data were used to estimate pollutant loadings delivered

directly to the estuary via atmospheric deposition. Wet deposition loadings were

calculated on a monthly basis for each ba y segment by multiplying the precipitation

volume (expressed as volu me per unit time) by the pollutant concentration

(expressed as mg/L). The monthly mean pr ecipitation-weighted TN concentration in

2-1

### rainfall was derived from the TBADS da ta for the period August 1996 through

December 1998, and multiplied by the m onthly mean 1992-1994 hydrologic load

due to rainfall to derive the wet TN lo ading estimate for the current condition.

Pollutants are also delivered to the bay via dry deposition. Monitoring at the

TBADS site also provided data concerning atmospheric concentrations of nitrogen.

Utilizing these data, meteorological da ta, and a deposition model, dry fluxes of

nitrogen to the surface of the bay were estimated (Pribble et al., 2001). Seasonalspecific ratios of dry:wet deposition were then estimated. These ra tios were used to

estimate monthly atmospheric deposition from both wet and dry deposition.

2.2 2010 Conditions Atmospheric Deposition Loading Estimates

The same NWS precipitation data that were used for 1992-1994 atmospheric

deposition loading estimates were used fo r future condition loading estimates.

These data were used to develop average monthly rainfall, so that only the rainfall

chemistry concentrations and the dry:wet deposition ratio were different for this

future condition update.

2.2.1 Data Sources

The predicted change in nitrogen emi ssions used in the development of the

previous 2010 loading estimate was an increase of 10% between 1994 and 2010

(Zarbock et al., 1996a). The estimate utilized wet precipitation chemistry from the

NADP Verna Wellfield site, estimated rain fall volumes based on a rainfall surface

developed from data collected at 22 NWS s ites, and a ratio of dry:wet deposition of

2.04, as suggested by the FADS study (ES&E, 1987).

The updated 2010 TN loading estimate utilized more recent projections of a decline

in atmospheric nitrogen emissions. The de cline is based on changes in emissions

expected to occur from the Tampa Elec tric Company (TECO) Big Bend and F.J.

Gannon facilities. In 1997, these two fac ilities accounted for approximately 80% of

the stationary point source nitrogen emissions from Hillsborough and Pinellas

counties. As a result of a federal agreement, a reduction in NO

x 

### emissions from the

two facilities by approximately 90% will occur between 1997 and 2010 (TECO,

2000). These reductions cons titute a 46% reduction in NO

x 

### emissions from

Hillsborough and Pinellas counties compared to 1997 levels.

NO

x 

### emissions from mobile on-road sources are not expected to change

significantly by 2010 (FDEP, 2000). Proj ected increases in the numbers of

automobiles are expected to be offset by implementation of EPA emissions

standards taking effect in 2004, yielding no net change in NO

x 

### emissions from

mobile on-road sources.

2-2

### The monthly average precipitation-weighted TN concentrations for the 2010 period

were derived from the TBADS data fo r August 1996 through December 1998.

These data were used with the 1992-1994 ra infall data to derive an updated future

condition atmospheric loading estimate.

2.2.2 Methods

For the purposes of the updated 2010 atmos pheric deposition, the simplest method

of relating changes in atmospheric nitrogen concentration to changes in emissions

was used, as in the previ ous estimate. A reduction in atmospheric nitrogen

concentrations was considered to be linea rly related to a reduction in atmospheric

emissions. For these purposes, it was assumed that atmospheric emissions

remained unchanged in 2010 from the emi ssions for 1997 from sources other than

stationary point sources. The reduction in emissions resulting from the scheduled

modifications to the TECO facilities, and the projected no net change in on-road

mobile sources emissions, correspond to a reduction in atmospheric emissions of

46% by 2010. For this estimate, the 46% reduction in atmospheric emissions by

2010 corresponds to a 46% reduction in atmos pheric nitrogen concentrations from

the 1995-1998 period to 2010.

This relationship was used to provide the primary estimate of deposition, along with

the most site-specific data available for precipitation chemistry from the TBADS site,

and the dry:wet deposition ratio as derived from the TBADS site. These data were

also used in the estimation of the 1995- 1998 atmospheric deposition loadings to the

bay (Pribble et al., 2001). The updated 2010 estimate based on this method is

provided in the tabular presentation of pr edicted loadings later in this document.

The actual effects of the planned emission reductions with respect to changes in

deposition are unknown, however . To provide some boundaries to the predicted

2010 deposition, two additional methods we re used to provide alternative

estimates. The first met hod uses a previously deri ved relationship between

emission reductions and reductions in depos ition that estimated a 1 ton reduction in

deposition in response to a reduction in em issions of 400 tons (TBEP, 1999). The

second method assumed no changes in atmos pheric nitrogen concentrations from

1998 levels. A comparison of the results of these methods are shown in the results

section below.

2-3

# 3. DOMESTIC AND INDUSTRIAL POINT SOURCES

3.1 Current Conditions Point Source Loading Estimates

Existing domestic and industrial point sour ces were identified in Pribble et al.

(2001), and included direct surface discha rges and land application discharges

within the watershed with a permitted average daily flow (ADF) of 0.1 million

gallons per day (MGD) or greater. Throug h interviews with local government utility

planners and facility operators, projected flows and planned future facilities were

identified for this analysis.

3.1.1 Data Sources

Point sources were identified by reviewing FD EP point source disc harge locations in

relation to the Tampa Bay watershed. The locations of all point sources in Florida

were obtained from the PCS database prov ided by FDEP. These locations were

used to create a GIS coverage, and then mapped for FDEP Tampa office staff review.

The domestic point sources in the Tampa Bay watershed with ADF of 0.1 MGD or

greater were identified by FDEP Tampa office staff.

Sources used to estimate point source disc harges and concentrations data to Tampa

Bay for the current period, based on 1998 data, were as follows:

• MORs and DMRs obtained from th e EPCHC and the Tampa office of

the FDEP; and

• MOR and DMR data obtained direc tly from the domestic wastewater

treatment facilities for those data not obtained from the EPCHC and

FDEP.

The database was subjected to quality cont rol measures to ensure that the most

accurate flows and concentrations obtainabl e were used in the loading estimates.

The entries were scanned for incongruous data points. Obvious outliers (such as

flows of two or three orders of magnitude higher than the design capacity of the

facility) were removed from the record. Co mplete records existed for most domestic

wastewater treatment plants, with facilities reporting flow rate and TN

concentrations on a monthly basis. Attemp ts were made to locate sources of valid

data to replace missing or invalid valu es, often by contacting facility personnel

directly.

For those data gaps that could not be filled with actual recorded data, two methods

were used to complete th e record, depending upon the amount of data missing, as

follows.

3-1

### • If 1-3 months’ of data were missing consecutively, discharge and/or

pollutant concentrations were set to those of the last month’s for

which values existed.

• If more than 3 months’ of data we re missing consecutively, discharge

and/or pollutant concentrations were set to the monthly averages of

the 1995-1998 record.

In some cases, a form of nutrient other than total nitrogen was reported. For

example, if both total nitrogen and nitrate n itrogen were recorded for some months

at a facility, but only nitrate nitrogen wa s recorded for most months, the average

ratio of nitrate to total n itrogen was calculated for those months with both values.

The resulting ratio was applied to the other months, resulting in an estimate of total

nitrogen for those months. If only nitrate nitrogen data existed, then total nitrogen

concentration was set to the reported concentration of nitrate nitrogen.

If no data for a certain parameter were av ailable for a facility and it was known or

suspected that loadings of that chemical did occur, then other similar facilities were

examined. Typical or averaged data from these facilities were used to fill data gaps

if no other source of information was ava ilable. This method was chosen as an

alternative to showing missing data for loads from major point sources.

3.1.2 Methods

Current condition point source loading es timates were developed as monthly loads

for 1998. All facilities were assumed to discharge independently except the St.

Petersburg facilities. Effluen t from St. Petersburg’s four facilities enters a common

distribution system, and commingles prior to discharge as land application reuse.

Direct surface water discharges were cal culated by multiplying the flow (expressed

as volume per unit time, such as MGD, by the reported TN concentration (mg/L).

With appropriate conversion factors, this calculation yields a mass per unit time,

such as tons per year. All of the effluen t released via surface discharge was assumed

to reach the Tampa Bay system.

Land application of treated effluent is di scharged most commonly by either spray

irrigation or in percolati on ponds. The applied effluent either evaporates, is taken

up by vegetation, becomes surface runoff ( generally a very small component of the

total volume), or infiltrates to the water table. Therefore , pollutant loadings that

reach the bay generally do so via groundwat er. Land application loadings were

estimated using recorded effluent quality data from specific facilities, with

attenuation rates (Zarbock et al., 1996b) app lied to flows and nitrogen loads once

the effluent enters the environment.

3-2

### These attenuation rates are the same as those used previously for loading

estimations for the 1985-1994 period (Zarbock et al., 1994; 1996b), and account for

attenuation of pollutants in the environmen t prior to the efflu ent flow reaching the

receiving water of Tampa Bay. Polluta nt loading reductions applied to loads

discharged to land were as follows:

TN (spray irrigation) : 95% reduction for City of St. Petersburg

facilities,

: 90% reduction for all other facilities, and

TN (percolation pond) : 70% reduction.

These rates were the same as those us ed previously (Zarbock et al., 1994; 1996a;

1996b).

TN load reductions were based on literature values for nutrient behavior in the

subsurface environment and local WWTP m onitor well data. General assumptions

used to estimate land application loads include:

• Recorded monthly values for domes tic effluent for f acilities with land

application were used as the "influent" value.

• Initial concentration reductions result from above-ground and root

zone processes, followed by downward migration through the

unsaturated zone, to the water table.

• Some additional removal of TN may occur during waste stream

movement towards the receiving wate r (surface water), through the

surficial aquifer. However, this a dditional removal is thought to be

relatively small, so there was no acc ounting for varying distances of

effluent travel among individual sources.

• Removal rates for nitrogen in efflu ent are higher for spray irrigation

than for percolation ponds because of enhanced volatilization and

plant uptake that occurs with sp ray facilities. The City of St.

Petersburg plants operate to ma ximize the ammoni a proportion of

nitrogen in the effluent. This enha nces plant uptake and volatilization

of nitrogen, and supports the estim ated 95% removal rate calculated

using monitor well data (St. Petersburg, 1993).

3.2 2010 Conditions Point Source Loading Estimates

Future condition point source loads were obtained by revising existing conditions

loads base on projected changes in demand, treatment methods, or effluent disposal

method. Data sources and methods are described below.

3-3

### 3.2.1 Data Sources

Information on the quality and quantity of future discharges from domestic and

industrial point sources was obtained via telephone interviews and visits with

representatives of each of the governmental entities re sponsible for the specific

sources. A complete list of the persons contacted and a summary of the interviews

is presented in Appendix 1. For each in terview, the contacted party was supplied

with the information provided during the development of the previous future

condition estimates, and asked if there were any significant changes in these plans.

Through these interviews, it was determined which facilities are proposed to remain

in service or close, what changes in treatment levels or di scharge methods are

expected, and to what extent flows may be expected to rise or fall during the next

decade.

Any new information provided for future condition point source estimates was used

to develop updated 2010 loading estimates. For those facilities for which no

revisions of 2010 loadings were necessary, the estimated future loadings remained

the same as for the previ ous estimate. For those facilities that came online

following the 1992-1994 period, the 1998 estim ated loadings were used as a

baseline.

3.2.2 Methods

The methods used to estimate projected future loads were the same as those used to

estimate point source loads for the cu rrent period, using revised flows or

concentrations based on the interviews. Monthly flows were multiplied by the TN

concentrations to yield monthly load s, using the following assumptions:

• all loads from surface discharges reach the bay;

• 90% of the TN load from spray irrigation land application did not

reach the bay, but was attenua ted through process following

application (except for St. Petersburg facilities, which had 95% TN

attenuation because of the high l evel of volatile ammonia in the

effluent); and

• 70% of the TN loads from perc olation pond land application did not

reach the bay, but were attenua ted through processes following

application.

3-4

# 4. SPRINGS AND GROUNDWATER

4.1 Current Conditions Springs a nd Groundwater Loading Estimates

Springs are a significant source of nitrogen loading to the bay. Estimates of spring

loads were developed using existing measured data, and were developed

independently of groundwater loads. Gr oundwater provides a nother source of

nutrient loading to the bay. The surficial (water table), intermediate, and Floridan

aquifers all contribute loadings to the bay.

4.1.1 Data Sources

Recorded flows and water quality data were used to estimate freshwater inflow rates

and pollutant loadings from springs for the current condition. Previous loading

estimates have been developed for Sulphur Springs, Lithia Springs, and Crystal

Springs, which were identified as significan t discharges in the Tampa Bay watershed

(Zarbock et al., 1994; 1996b). Smaller spring s do exist in the watershed, but have

relatively small discharges and were not cons idered in this loading analysis or the

previous estimates. Lithia Springs and Sul phur Springs are not in gaged portions of

the Tampa Bay watershed, but are themselves gaged. Crystal Springs is located in a

gaged basin within the Hillsborough River watershed and its flow was accounted for

by the downstream gage, so that polluta nt loadings from Crystal Springs are

incorporated into the nonpoint source loading estimate, as done previously

(Zarbock et al., 1994; 1996b).

Estimates of wet and dry season groundwater inflow to Tampa Bay were completed

using the methods of Hutchinson (1983) a nd Brooks et al. (1993 ). Flow estimates

were calculated using a flow net analysis and Darcy's equation (Freeze and Cherry,

1979), a well-recognized analytical met hod for estimating groundwater flow. TN

concentration data for the surficial, inte rmediate, and Floridan aquifers were

obtained from the SWFWMD Ambien t Ground Water Monitoring Program

(AGWMP) (DeHaven, personal communicati ons). Only groundwater inflow that

entered the bay directly from the shor eline or bay bottom was considered.

Groundwater inflow to streams was accounted for in the nonpoint source empirical

model. Septic tank loadings to the bay in groundwater were not explicitly

accounted for in this analysis. Current condition groundwater loadings were set

equal to those of 1998, as previous ly derived (Pribble et al., 2001).

4.1.2 Methods

The methods used to calculate current pollutant loadings from springs and

groundwater follow those used in previous loading estim ates (Zarbock et al., 1996b;

Pribble et al., 2001). For both sources, average monthl y TN concentrations for

4-1

### 1998 were multiplied by monthly flows to yi eld monthly TN loadings. Springs and

groundwater loading estimates for the cu rrent period were set to those of 1998

(Pribble et al., 2001).

4.2 2010 Conditions Springs and Gr oundwater Loading Estimates

Loadings from springs and groundwater for future conditions were also estimated.

Loadings from Lithia Springs and Sulphur Springs were estim ated, as were the

combined loadings from the surficial, intermediate, and Floridan aquifers.

4.2.1 Data Sources and Methods

Future condition spring loadings were estimated using 1998 data from the USGS

and SWFWMD, as described for current conditions. No defensible means of

quantifying trends in spring flows or spring nutrient concentrations is available.

Therefore, the 1998 data were used to estimate future conditions spring loadings.

Similarly, groundwater loading estimates for 1998 were assumed to be

representative of future conditions.

4-2

# 5. MATERIAL LOSSES

5.1 Current Conditions Material Losses Loading Estimates

Fertilizer losses from loading docks at port facilities constitute a source of nutrient

loading classified as material losses. In particular, bulk phosphate fertilizer is

subject to product losses during its transfer from land carrier to storage facility, and

onto vessels for shipping. Product is lost both through spilled product washing into

the bay with stormwater runoff, and via fugitive dust. Material losses occur at

facilities at the Port of Tampa, in the Co astal Hillsborough Bay basin, and at Port

Manatee, in the Coastal Lower Tampa Bay basin.

5.1.1 Data Sources

Estimates of current total nitrogen loadin gs due to material losses were developed

from data provided by the facilities for 1998. For the 1995-1998 estimates, all

facilities provided spreadsheets containing loss estimates due to handling losses and

airborne (fugitive) losses on an annua l basis for the 1995-1998 period. These

estimates were requested and obtained thr ough the assistance of Mr. Craig Kovach,

CF Industries, and provided to the TBEP in electronic format.

5.1.2 Methods

The loss estimates for the 1995-1998 period we re much less than those from the

1992-1994 period (Zarbock et al., 1996). For the 1992-1994 estimates, facility

personnel provided rock and chemical masse s shipped. The shipped products were

then converted to losses using conversi on factors based on methods developed by

Morrison and Eckenrod (1994). These met hods suggested an overall loss rate of

approximately 0.02% of produc t shipped, so that the total masses of nitrogen and

phosphorus in the shipped product were multiplied by 0.0002 to derive the

pollutant loadings from the phosphate ha ndling facilities. The estimates for the

1995-1998 period, however, represent the best estimates by facility personnel of

actual losses. These estimates reflect bot h actual reductions in nutrient losses from

improved handling practices implemented by most facilities, and improved loss

estimation techniques for both ship lo ading losses and air borne losses.

5.2 2010 Conditions Material Losses Loading Estimates

5.2.1 Data Sources and Methods

Material losses for future conditions were estimated by changing existing condition

loadings by 1% per year from 1998 through 2010. This information was obtained

5-1

### from Mr. Craig Kovach, CF Industries, and Mr. Bruce DeGrove, Florida Phosphate

Council, as representative of i ndustry growth through 2010.

5-2

# 6. NONPOINT SOURCES

6.1 Current Conditions Nonpoint Sources Loading Estimates

Nonpoint sources include st ormwater runoff and baseflow as streamflow. All

nonpoint source loading estimates for exi sting conditions were model-based, and

used no measured water quality or flow data . This approach was used so that an

equitable comparison of existing conditi on to future condition loads (all modelbased) could be made.

6.1.1 Data Sources

Data used to estimate nonpoint source loads include rainfall, land use, soils,

subbasin boundaries, and land use-specific runoff coefficients and stormwater

quality concentrations. These data were all used to develop m odeled estimates of

TN loads to Tampa Bay.

Drainage Basin Boundaries

Drainage basin boundaries were incorporated into all geographically-based data

used for this project (e.g., land use data , precipitation data, drainage areas, point

source locations). The drainage area boundaries were based on a geographic

information system (GIS) coverage obtai ned from the Southwest Florida Water

Management District ( SWFWMD, 1992).

The Tampa Bay watershed includes a total of 425 subbasins covering approximately

2,276 sq. mi. (5,895 sq. km.), as delineate d by USGS (Foose, 1993). Internally

drained lands, which include 22 subbasins, encompass 125 sq. mi., or slightly more

than 5% of the watershed area. These areas may be expected to retain initial

rainfall volumes, and provide surface discha rge only after internal storage areas are

filled. For nonpoint source load modelin g, these noncontributing subbasins were

removed from the land area that generated stormwater runoff.

Rainfall Records

The precipitation data used for modeling surface water hydrology were obtained

from the NWS for the 1992-1994 period. Tot al monthly precipitation records for 22

long-term stations within or near the Tampa Bay watershed were obtained for the

period January 1992 through December 1994. The names and locations of these

stations are presented in Za rbock et al. (1994). Total monthly precipitation values

were estimated for each subbasin, month, and year of the existing period. Subbasin

estimates were interpolated from a precip itation response surface that was fit to the

entire watershed for each month and year of the existing peri od. The response

6-1

### surface was fit to account for regional patterns, but to give more emphasis to local

conditions.

Land Use/Land Cover Data

Land use/land cover GIS data for 1995 we re obtained from the SWFWMD and

incorporated into the surface water hydr ology model. These data represent an

update of the land use data from that used for the previous estimate (Zarbock et al.,

1996a), which were for 1990. The land use data were recorded following the

Florida Land Use Cover Cla ssification System (FLUCCS) level 3 developed by the

Florida Department of Transportati on Thematic Mapping Section (FDOT, 1985).

For the purpose of assigning land use-specific runoff and pollutant loading factors,

the FLUCCS land uses were aggregated into 21 classes, as presented in Appendix 2.

The aggregated land use classification sy stem was developed by examining the

source literature for the FLUCCS land uses , and combining hydrologically-similar

land uses based on stormwat er runoff coefficients and land use specific pollutant

loading factors. Land use-specific stormw ater runoff coefficients and pollutant

concentrations were determined from a r eview of field investigations from central

and south Florida, as described below.

Soils Data

The soils coverage includes discrete polygons of individual soil series (types) as

identified and delineated by the USDA Na tural Resources Conservation Service

(NRCS) in the Hillsborough, Pinellas, Mana tee, Polk, and Pasco county soil surveys.

The GIS coverage of these data was obtai ned from the SWFWMD. The discrete

soils polygons represented a soil series, and were aggregated by hydrologic soil

groups (A - D). The NRCS has assigned a hydrologic group identification to each

soil series to indicate runoff generating characteristics. "A" soils, in general,

generate the least, and "D" soils the most amount of runoff for a given rainfall. The

soils coverage was intersected with the la nd use coverage to provide the GIS layer

used to estimate runoff coefficients. Each unique combination of land use type, soil

series, and season has been assigned an associated runoff coefficient value.

L a n d U s e

- S p e c i f i c R u n o f f C o e f f i c i e n t s a n d S t o r m w a t e r Q u a l i t y C o n c e n t r a t i o n s

Land use-specific runoff coefficients we re obtained from published literature,

including references for the west-central and south Florida geographic area. A range

of runoff coefficient values for each la nd use was developed to account for seasonal

changes in rainfall/runoff relationships, and for local soils conditions, as described

in Zarbock et al. (1994) and used for th e previously modeled current and future

conditions (Zarbock et al., 1996a). These co efficients are presented in Appendix 3.

6-2

### An extensive list of regional water quality concentration data for nonpoint source

total nitrogen was compile d for this modeling effort, and is summarized in

Appendix 4 and further described in Zarbock et al. (1994) and Pribble et al. (2001).

The values are from a num ber of stormwater sampling programs and represent

averaged values from multiple sa mples from each program.

Because base flow is a component of wate r sampled in channels during periods of

runoff, base flow characteristics were assu med to be represented in these storm

samples. Therefore, base flows were not estimated separately.

6.1.2 Methods

All nonpoint source loads for existing c onditions were estimated using a modelbased approach, so that an equitable comp arison to modeled future loads could be

made. An empirical hydrologic model was developed to provide estimates of

nonpoint source surface water inflows (Z arbock et al., 1996a). Model construction

and methods for estimating nonpoint sour ce loads are summarized below.

Empirical data analyses indi cated that the preferred model for predicting runoff in

the Tampa Bay watershed was based on a lo g-linear relationship with rainfall and

land use categories as indepe ndent variables. Rainfall for two previous months was

included in the model in addition to rain fall for the present month. The land use

composition of each basin was include d through an adjustment factor ( a ). The

model used was:

FLOW = exp[ a + ( b 0 

### *RAIN 0 

### + b 1 

### *RAIN 1 

### + b 2 

### *RAIN 2 

### )] (Equation 1)

and,

a = ( c 1 

### * L 1 

### ) + ( c 2 

### * L 2 

### ) + ( c 3 

### * L 3 

### ) + ( c 4 

### * L 4 

### )

where

FLOW = nonpoint source flow (meters per month) for a given basin,

year, and month,

RAIN 0 

### = rainfall (meters per month) in the month,

RAIN 1 

### = rainfall (meters per month) in the month before the present

month,

RAIN 2 

### = rainfall (meters per month) two months before the present

month,

6-3

### L 1 

### = the fraction of the basin in the URBAN land use category,

L 2 

### = the fraction of the basin in the AGRICULTURAL land use

c a t e g o r y

,

L 3 

### = the fraction of the basin in the WETLANDS land use category,

L 4 

### = the fraction of the basin in the FORESTS land use category, and

c 1 

### , c 2 

### , c 3 

### , c 4 

### , b 0 

### , b 1 

### , and b 2 

### are parameters to be estimated.

The parameters associ ated with rainfall ( b 0 

### , b 1 

### , and b 2 

### ) act as weighting factors when

averaging rainfall over three months. The ir absolute magnitude also affects the

slope of the relationship between rainfa ll and runoff. The parameters associated

with land use categories ( c 1 

### , c 2 

### , c 3 

### , and c 4 

### ) define an aggregate adjustment factor (a)

that affects both the slope and the intercep t of the relationship between rainfall and

runoff.

The units of flow and rainfall listed above, meters per month (m/mo), were chosen

for computational purposes. For flow, m/mo represents the total flow from a land

area over the time period (month), expressed as a volume of water with an area

equal to the land area, and the depth in mete rs. Although the unit is listed as depth,

the volume is implicitly accounted for in the land area. For rainfall, m/mo

represents the depth of rainfall over th e land area during the time period (month).

A least squares regression with no inte rcept was used to estimate the seven

parameters in Equation (1) after taking th e natural logarithm of both sides of the

equation:

log(FLOW)

= ( c 1 

### *L 1 

### ) + ( c 2 

### *L 2 

### ) + ( c 3 

### *L 3 

### ) + ( c 4 

### *L 4 

### ) +

( b 0 

### *RAIN 0 

### + b 1 

### *RAIN 1 

### + b 2 

### *RAIN 2 

### ) (Equation 2)

Model development resulted in the defin ition of four separate rainfall/runoff

relationships, varying with season and basi n land use characteris tics. "More urban"

basins were defined as having greater th an 19% urban land use, and "less urban"

basins had less than 19% urba n land use. The selection of the 19% level was based

on an investigation of the distribution of urban land cover and the goodness of fit of

the rainfall/runoff relationships. Months we re classified into two categories based

on rainfall: dry season (November throug h June) or wet season (July through

October). The model was run for each co mbination of these categories, resulting in

four complete sets of parameter es timates for the following conditions:

6-4

### 19% urban, dry season

19% urban, wet season

> 19% urban, dry season

> 19% urban, wet season

Total monthly flow for each subbasin was estimated using Equation (1) with the

appropriate parameter estimates. The next step of estimating pollutant loads was to

estimate the fraction of the total subbasin flo w that originated from each land use.

The total subbasin flow was apportioned am ong the constituent land use categories

within each subbasin as follows:



# ∑ =

i i i i i

i 

### R A R A FLOW FLOW

* * * (Equation 3)

where

FLOW i 

### = the total nonpoint source flow (m/mo) from land use category

i

,

FLOW = the total nonpoint source flow (m/mo) from a subbasin,

A i 

### = area (acres) in land use category i , and

R i 

### = the runoff coefficient (fraction of rainfall that runs off) for land

use category i

.

The above calculation resulted in the di saggregation of the total nonpoint source

flow for a subbasin into flows generated by individual land use types.

Subbasin pollutant loads were then estimated by land use using land use/soilspecific runoff coefficients and land use-spec ific pollutant concentrations. Nonpoint

source runoff generated by an indivi dual land use type within a basin was

calculated by prorating the total flow usin g land use-specific runoff coefficients and

the area of that land use type within the basin (Equation 3). Nonpoint source

pollutant loads for specific land uses we re then estimated for the desired time

period according to the following equation:

Pollutant loading for land use i = Flow LU i 

### * PC Lui 

### (Equation 4)

where:

PC LU i 

### =Average pollutant concentration for land use i and

6-5

### Flow LU i 

### =Total flow from land use i.

The land use-specific pollutant loads were th en summed to yield a total load for the

subbasin. Subbasins within a larger area (jurisdictional area or bay segment major

basin) were then summed as appropriate to obtain the loading estimates at their

desired spatial scale.

6.2 2010 Conditions Nonpoint S ources Loading Estimates

All nonpoint source loads for projected future conditions were model-based.

Projected future condition loads were estimated on a monthly basis for twelve

calendar months and then summed to yield a representative annual load for the year

2010.

6.2.1 Data Sources

Average monthly rainfall was calculated using the same NWS data that were used

for the 1992-94 conditions load estimates. The monthly rainfall amounts were used

to drive the empirical model. All future condition loading estimates were modelbased, and were calculated in the same manner as existing condition loadings. The

future and existing loadings were calculate d by changing only the land use, and by

applying pollutant loading attenuation fact ors to the new urban land uses to account

for surface water permit tr eatment requirements.

A previous study by the TBNEP (Zarbock et al., 1996a) developed projections of

2010 land use conditions to estimate future nonpoint source pollutant loadings. For

that work, 1990 land use data obtained fr om SWFWMD was used as a base, and

was changed to future conditions (2010) after consultation with local planning

agencies. The methods used to estimat e future land use coverage within the

watershed (by basin) were based on 1990 land use coverage, popul ation projections

for 2010 developed by the U.S. Census Bureau, and population and employment

information obtained from local planning agencies.

Changes in projected 2010 la nd uses may be the result of changes between the

District’s 1990 GIS land use coverage and the newer “current conditions” (1995)

land use coverage. Changes also may result from revised population and housing

projections developed by local planning agencies or from changes in mapping

boundaries.

Local government planners were interviewe d, and provided with the estimates of

2010 land use previously derived (Zarboc k et al., 1996a) and with the 1995 land

use. In addition to the in terviews, local planning department documents, maps, and

population projections were evaluated. I ndividuals from Hillsborough, Pinellas,

6-6

### Manatee, Pasco, and Polk counties were in terviewed to obtain local expertise with

respect to projected spatial and temporal growth trends for incorporated and

unincorporated jurisdictions within the wa tershed. Some local governments used

U.S. Census Bureau information or tre nds in land use changes to project where

future growth would occur. Other jurisd ictions used transpor tation-based analyses

for their land use trend analysis. Informa tion sources, individuals interviewed from

each local government, and assumptions us ed to make the land use projections are

discussed below.

Pinellas County and Incorporated Jurisdictions

Population and employment projections for Pinellas County, Clearwater, St.

Petersburg, and other incorporated jurisd ictions within the county were obtained

from the Pinellas County Planning Depart ment (1998). Revised projections had

been developed by the department in 1998, and were enumerated by the 12

Planning Sectors in the county (Beardslee, pers. comm.).

The 1995 GIS land use coverage had some si gnificant differences compared to the

1990 coverage. Medium density residentia l in St. Petersburg (Middle Tampa Bay

and Boca Ciega Bay basins) declined 60%, according to the GIS coverage. This is

likely either an artifact of the methods us ed to develop the two coverages or a result

of reclassification of existing residential areas within the city, and may not reflect

actual changes in land cover. However, this did result in changes to the future land

use estimates.

Projected changes in population within each Planning Sector between 1995 and

2010 were determined. For drainage basi ns that encompassed more than one

Planning Sector, a composite population change for the basin was estimated by

weighting the contributions of each Pla nning Sector, based on area. Assumptions

used for the Pinellas County projections include:

• Because 1997 population was the earliest reported by the county and

the land use base used for update was based on 1995 aerial

photography, the projected 1997- 2010 population changes were

increased by 8% to account for the two year difference in time period.

• Within each planning unit, all re sidential and commercial land uses

were assumed to change at a rate sufficient to accommodate projected

population changes.

• Industrial and institutional land us es were assumed to change on a

site-specific basis.

• Agricultural, forested, and open la nds were assumed to decrease

corresponding to the urban land increase.

6-7

### • Open water and wetlands were assumed to not change.

Hillsborough County and Incorporated Jurisdictions

Revised population, housing, and employme nt projections for Hillsborough County,

Tampa, and other incorporated jurisdictions within the county (Plant City, Temple

Terrace) were obtained from the Hills borough County City County Planning

Commission (1999a, 1999b). Projections had b een developed by the agency using

U.S. Census Bureau data, land use chan ge trends, occupancy change rates, and

other sources (Cullen, pers. comm.). Data for 1995 and 2010 were obtained by

census tract and Planning Area.

The population estimates for the north-cen tral portion of th e County and “New

Tampa” were revised upwards from the earlie r estimates. Higher growth rates in the

Cypress Creek and upper Hillsborough River Ba sins resulted in revisions to the

future land use estimates.

Projected changes in population within each Planning Area between 1995 and

2010 were determined. For drainage basi ns that encompassed more than one

Planning Area, a composite population ch ange for the basin was estimated by

weighting the contributions of each Pla nning Area, based on area. Assumptions

used for the Hillsborough County projections include:

• Within each planning unit, all re sidential and commercial land uses

were assumed to change at a rate sufficient to accommodate projected

population changes.

• Industrial and institutional land us es were assumed to change on a

site-specific basis.

• Agricultural, forested, and open la nds were assumed to decrease

corresponding to the urban land increase.

• Open water and wetlands were assumed to not change.

Manatee County and Bradenton

Revised population and employment pr ojections for Manatee County and

Bradenton were obtained from the Mana tee County Planning Department (1999).

Projections had been develope d by the department using U.S. Census Bureau data,

land use change trends, occupancy change ra tes, and other sources (Kotecki, pers.

comm.). Population estimates and projec tions for 1995 and 2010 were obtained by

Planning Sub-Areas.

It should be noted that the latest population and building projections are

substantially higher than the projections used for the original future land use

6-8

### estimates (Kotecki, pers. comm.). Reside ntial land use estimates for 2010 rose 28%

using the new revised population projec tions. Also, there were significant

differences in the baseline land use cover age for Manatee River basin. The 1995

land use coverage showed a 34% increase in medium density residential land uses

over the 1990 coverage, which likely are th e result of both actual land use changes,

and differences in photo-interp retation. Both these factors contributed to the revised

estimates of urban land use in the Manat ee River basin increasing substantially.

Projected changes in population within each Sub-Area between 1995 and 2010

were determined. For drainage basins that encompassed more than one Sub-Area, a

composite population change for the basi n was estimated by weighting the

contributions of each Sub-Area, based on land area. Assumptions used for the

Manatee County projections include:

• Within each planning unit, all re sidential and commercial land uses

were assumed to change at a rate sufficient to accommodate projected

population changes.

• Industrial and institutional land us es were assumed to change on a

site-specific basis.

• Agricultural, forested, and open la nds were assumed to decrease

corresponding to the urban land increase.

• Open water and wetlands were assumed to not change.

Pasco County and Incorporated Areas

Population and industrial, commercial, and service employment projections for

Pasco County and incorporated jurisdictions within the county were obtained from

the County Planning Department (1999). Projections had been developed by the

department using U. S. Ce nsus Bureau data, land use change trends, occupancy

change rates, and other sources (Burbr idge, pers. comm.). Data for 1995 and 2010

projected populations were obtained by census tract and Planning Division.

Projected changes in population within each Planning Division between 1995 and

2020 were determined. All Planning Divisi ons fell within a single basin, so no

weighting of land use change rates was re quired. Assumptions used for the Pasco

County projections include:

• Within each planning unit, all re sidential and commercial land uses

were assumed to change at a rate sufficient to accommodate projected

population changes.

• Industrial and institutional land us es were assumed to change on a

site-specific basis.

6-9

### • Agricultural, forested, and open la nds were assumed to decrease

corresponding to the urban land increase.

• Open water and wetlands were assumed to not change.

Polk County

No population projections other than at a county-wide scale were available from

Polk County (Hommel, pers. comm.). Because of the lack of spatially- appropriate

data, land use changes in the area of the Tampa Bay Watershed encompassed by

Polk County were assumed to change at th e same rate as lands in Pasco and

Hillsborough counties within the same basin (upper Hillsborough River).

The updated 2010 land use estimates are pr esented in Appendix 5. The most

common land use type projected for the yea r 2010 is pasture, at 14% of the total

watershed area. All types of agriculture combined encomp ass 29% of the total area.

Residential land uses account for over 18% of the total area. All urban land uses

combined (except mining at 7%) make up 26% of the total area. It should be noted

that the watershed acreage includes Tampa Bay itself, and not only the watershed.

The bay comprises 13% of the total area.

A comparison of the 1990 and 1995 land use coverages, and of the original (1996)

and revised (2000) 2010 land us e projections, are include d in Appendix 5. As

stated above, changes between coverages of land use acreages in various categories

account for some of the differences in the original and new 2010 land use

projections. As can be seen, on a watershed–wide scale, the 1990 and 1995

coverages do not differ greatly, generally under 10% for most major urban and

agricultural land use types. One exception to this is row crops, which covers 58%

more land in the 1995 coverage than in the 1990 coverage. Additionally, several

wetland types are very different. Diffe rences are more pronounced on a major

basin or basin level.

Reasons for the differences could include changes in methodologies for mapping

and photo-interpretation, real land use ch anges, or changes in the boundary of the

mapping. Boundary changes are most evide nt for open salt water and tidal flats,

which were not included in the 1990 coverage but were in the 1995 coverage.

A comparison of the original (1996) a nd revised (2000) 2010 la nd use projections

reveals a fairly good agreement in most urban and agricultural categories. On a

watershed scale, urban land uses differe d by under 15%. Row crops differed by

53%, but this can be accounted for by the differences in baseline coverages.

The assumptions used in making the proj ections were the same in both cases, so

differences in upland land us es are the result of changes in the baseline coverage,

and in the updated population, employment, and building projections made by the

6-10

### local planning agencies. Differences in wetland and water land covers are thought

to be attributable mainly to chan ges in mapping methodologies and photointerpretation, real land use changes, or changes in the boundary of the mapping.

There are two areas of the watershed wher e future land use projections changed the

most: in the north-central Hillsborough County/New Tampa/south-central Pasco

County area, and in western and central Manatee County. Both these areas have

experienced accelerated growth during the past five years, necessitating substantial

revisions to population and land use pr ojections. For example, the revised

residential projections for 2010 in the Mana tee River basin incr eased by 28% over

the original projections, with corollary re ductions in range and pasture land uses.

These increases reflect curre nt conditions and were verified by discussions with

County planners.

A comparison of the acreages of aggregated land use types in the watershed of each

bay segment from the 1990 and 1995 land use coverages, a nd the previously

developed and updated 2010 land use, is provided in Table 6-1. In the watershed

of each bay segment, the updated 2010 land us e shows more urban area than from

the previous 2010 effort. Additionally, the updated 2010 land use shows greater

areas of agricultural land use in the H illsborough Bay, Middle Tampa Bay, Terra

Ceia Bay, and Manatee River watersheds. Concomitantly, within the watersheds of

almost all bay segments, pasture and ran geland and forested areas are less in the

updated 2010 estimate than in that developed previously.

6.2.2 Methods

Future condition nonpoint source loads fo r the entire watershed were estimated

using the same empirical hydrologic mode l that was used to estimate flows and

loads for current. Model inputs included monthly rainfall, land use, soils, land usespecific runoff coefficients and water quality concentrations, and subbasin

delineation. Monthly nonpoint source loads for 2010 were estimated using the

same NWS data, those for 1992-1994, which were used for existing conditions.

Therefore, for the future c onditions loadings, only the land use was different from

the existing conditions. The resultant twel ve monthly loads were summed to yield a

representative annual load for 2010.

After the future land use-based loads we re estimated, the fu ture loads were

subtracted from current (1992-94) loads. The difference between the existing and

future loads represented new urban land. The loads associated with the new urban

land were then attenuated to account for water quality treatments that will be

required for new development through su rface water permit requirements.

Attenuation rates were 35% for TN loads, and were based on values of typical

treatment efficiencies for stormwater be st management practices (BMPs) obtained

from a literature review (Coastal Environmental, 1995).

6-11

### Table 6-1. Comparison of land use proportions (% of s egment watershed) for 1990,

1995, previous 2010 estimate, and update d 2010 estimate, by bay segment.

Old Tampa Bay

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 5 1

. 8 5 2

. 2 5 4

. 1 5 6

. 4

A g r i c u l t u r a l 1

. 9 2

. 0 1

. 7 1

. 7

Pasture & R a n g e l a n d 1 9

. 1 1 6

. 9 1 6

. 9 1 4

. 0

M i n i n g 0

. 3 0

. 3 0

. 3 0

. 3

F o r e s t & B a r r e n 7

. 7 7

. 1 7

. 1 6

. 1

Freshwater & W e t l a n d s 2 0

. 3 2 1

. 6 2 0

. 3 2 1

. 5

Hillsborough Bay

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 2 1

. 2 2 2

. 5 2 4

. 2 2 6

. 8

A g r i c u l t u r a l 5

. 4 6

. 6 1

. 7 6

. 2

Pasture & R a n g e l a n d 3 2

. 0 2 9

. 7 3 0

. 8 2 6

. 2

M i n i n g 1 1

. 9 1 2

. 3 1 2

. 1 1 2

. 3

Forest & Barren 10.3 9.8 9.7 9.4

Freshwater & W e t l a n d s 1 9

. 3 1 9

. 1 1 7

. 6 1 9

. 1

Middle Tampa Bay

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 1 7

. 7 1 8

. 3 1 9

. 2 2 0

. 1

A g r i c u l t u r a l 1 5

. 0 2 0

. 5 1 4

. 7 1 9

. 4

Pasture & R a n g e l a n d 3 9

. 9 3 3

. 6 3 9

. 1 3 0

. 9

M i n i n g 2

. 0 2

. 9 2

. 0 5

. 4

F o r e s t & B a r r e n 9

. 2 9

. 0 8

. 7 8

. 4

Freshwater & W e t l a n d s 1 6

. 3 1 5

. 7 1 6

. 3 1 5

. 9

Lower Tampa Bay

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 2 1

. 0 2 2

. 8 2 4

. 7 2 9

. 1

A g r i c u l t u r a l 2 4

. 8 2 3

. 1 2 4

. 6 2 2

. 9

Pasture & R a n g e l a n d 2 7

. 0 2 7

. 0 2 3

. 6 2 1

. 1

M i n i n g 2

. 4 2

. 4 2

. 4 2

. 6

F o r e s t & B a r r e n 3

. 8 4

. 2 3

. 6 3

. 5

Freshwater & W e t l a n d s 2 1

. 1 2 0

. 5 2 1

. 0 2 0

. 7

6-12Boca Ciega Bay

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 8 4

. 2 8 4

. 3 8 3

. 8 8 7

. 4

A g r i c u l t u r a l 0

. 2 0

. 3 1

. 3 0

. 2

Pasture & R a n g e l a n d 9

. 0 8

. 2 7

. 7 5

. 5

M i n i n g 0

. 0 0

. 0 0

. 0 0

. 0

F o r e s t & B a r r e n 3

. 1 2

. 6 3

. 3 2

. 2

F r e s h w a t e r & W e t l a n d s 3

. 5 4

. 6 3

. 9 4

. 7

Terra Ceia Bay

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 4 3

. 3 4 5

. 4 5 0

. 0 5 7

. 1

A g r i c u l t u r a l 8

. 7 1 0

. 0 8

. 7 9

. 2

Pasture & R a n g e l a n d 2 9

. 9 2 7

. 7 2 4

. 0 1 7

. 7

M i n i n g 0

. 0 0

. 0 0

. 0 0

. 0

F o r e s t & B a r r e n 7

. 0 7

. 8 6

. 3 7

. 1

F r e s h w a t e r & W e t l a n d s 1 1

. 1 9

. 0 1 1

. 1 9

. 0

Manatee River

Land Use Type Land Use Type

1990 1995 Previous 2010 Updated 2010

U r b a n 1 1

. 2 1 2

. 6 1 5

. 6 2 0

. 2

A g r i c u l t u r a l 1 3

. 2 1 8

. 5 1 2

. 8 1 6

. 7

Pasture & R a n g e l a n d 4 3

. 7 4 0

. 8 4 0

. 3 3 5

. 6

M i n i n g 1

. 2 1

. 3 1

. 2 1

. 4

F o r e s t & B a r r e n 1 5

. 7 1 1

. 7 1 5

. 0 1 1

. 0

Freshwater & W e t l a n d s 1 5

. 1 1 5

. 1 1 5

. 1 1 5

. 1

6-13

# 7. RESULTS OF LOADING ANALYSIS

Current and projected future TN loadings to Tampa Bay were estimated for bay segments

by source and by local government jurisdiction, as discussed in the following section.

These model-based loading estimates have been developed to assist the TBEP in setting

living resource targets and in working with local governments to reexamine allocation of

pollutant load reductions set previously.

In the following discussion, ba y s e g m e n t l o a d i n g s b y s o u r c e included major external

sources of TN inputs (atmospheric deposition, nonpoint sources, dom estic and industrial

point sources, material losses of fertilizer p r o d u c t

, g r o u n d w a t e r

, a n d s p r i n g s )

. L o a d i n g s b y jurisdiction included only land-based, manageable loadings (nonpoint sources, point

sources, and material losses ). Because groundwater, springs, and atmospheric deposition

loadings cannot be accurately apportioned am ong jurisdictions, they were not accounted

for in the jurisdictional loading tables.

7.1 Current Conditions

Current Conditions Bay Segment Loadings by Source

For the current period, an annual load of appr oximately 3,666 tons of TN reached the bay.

Current condition TN loading estimates are pres ented by source and bay segment in Table

7-1. For comparison purpos es, the previously estimated 1994 conditions loadings using

the 1990 landuse (Zarbock et al., 1996a) are shown in Table 7-2. Note that rounding to

whole number tons and percentages may cau se summation discrepancies. From the

updated estimate of current c onditions, nonpoint sources had th e highest contribution with

1,427 tons/year (39% of the total external load). Atmospheric deposition had the second

highest contribution with 1,142 tons/year (31%). Domestic and industrial point sources

contributed approximately 436 (12%) and 382 t ons/year (10%), respectively. Material

losses of fertilizer products totaled 32 tons/ year (1%). Groundwater and spring loadings

totaled 247 tons/year (7%), with the great majo rity of that (approximately 245 tons/year)

originating from springs.

Of the seven major bay segments, Hillsborough Ba y (HB) received the highest TN loadings

from the watershed, approximat ely 1,369 tons/year (37% of th e total bay-wide loading).

The sources with the highest contributions to Hillsborough Bay included nonpoint source

(487 tons/year, or 36%), domes tic point sources (281 tons/ year, or 21%), and groundwater

and springs (246 tons/year, or 18%). Industrial point sour ces (202 tons/year, or 15%),

material losses (32 tons/year, or 2%), and atmospheric deposition ( 121 tons/year, or 9%)

made up the balance of the TN load to Hillsborough Bay.

Middle Tampa Bay (MTB) received the next highest TN loading for existing conditions

(approximately 695 tons/year). The largest contributors in cluded atmospheric deposition

(322 tons/year, or 47%), nonpoint source (290 tons /year, or 42%), and industrial point

7-1

### sources (60 tons/year, or 9%). No other source contributed more that 3% to this bay

segment. Atmospheric deposition loading was th e largest external TN source for this

segment because of the large open water area of that segment with respect to the

contributing watershed-based inputs.

Old Tampa Bay (OTB) received the next high est TN loading for existing conditions (516

tons/year). The highest source -specific load was atmospheri c deposition (258 tons/year, or

50%). Atmospheric deposition loading was a significant external source for Old Tampa

Bay because of the relatively large open water area of that segment with respect to the size

of the watershed. The sec ond highest contributor was nonpoint source (167 tons/year, or

32%). Domestic point source (87 tons/year, or 17%) was the only other significant TN

source to Old Tampa Bay.

The Manatee River (MR) segmen t received approximately 464 tons TN/year for the current

period. Nonpoint source loads were most sign ificant (379 tons/year, or 82% of the total).

Industrial and domestic point s ource contributed 12 tons/year (3%) and 27 tons/year (6%),

respectively. Atmospheric deposition contri buted 47 tons/year (10%). These loadings

reflect the Manatee River’s large tributar y basin with respect to other inputs.

Lower Tampa Bay (LTB) received 400 tons/year for the current period, with 277 tons/year

(69%) of that total from atmospheric deposition. Again, the large surface area of water with

respect to watershed area, and the lack of other significant sources, makes atmospheric

deposition by far the most important exter nal source for this bay segment.

Boca Ciega Bay received a total TN load of 193 tons/year, with 99 tons/year (51%)

originating from atmospheric deposition and 79 tons/year (41%) fr om nonpoint sources.

Domestic point sources contributed approximately 14 tons/year (7%).

Terra Ceia Bay had the smallest TN loading of the bay segments, with only 28 tons/year.

Of that amount, approximately 19 tons/year ( 68%) originated as atmospheric deposition, 6

tons/year (21%) was from nonpoint sources, and 4 tons/year (14%) resulted from domestic

point sources.

Differences between the updated current conditi ons loadings and thos e previously derived

in Zarbock et al. (1996a) for 1994 total about 204 tons, with the updated loadings higher

than those estimated previously . This difference results from both the increased point

source and springs loading estimates for th e updated current conditions loadings, and the

large decline in material losses. The loads from these sources are representative of those of

the most recent year for which data exist, 1998, as described in Pribble et al. (2001). This

time period included the high rainfall period of the winter of 1997-1998 associated with

the El Niño event. The elevated loadings for the updated current conditions are at least

partially related to this event.

7-2Table 7-1. Updated current conditions annual TNloading by source and bay segment (all sources).BAY SEGMENTSOURCEOTBHBMTBLTBBCBTCBMRTOTALtons2581213222779919471142Atmospheric Deposition%509476951681031tons8728123114427436Domestic Point Source%17213<1714612tons4202601030012382Industrial Point Source%11592600310tons0320<100032Material Losses%020<10001tons167487290197963791427Nonpoint Source%323642541218239tons<1246<1<1<1<1<1247Groundwater+Springs%<118<1<1<1<1<17tons5161369695400193284643666TOTAL%143719115113100Table 7-2. Previous 1994 conditions annual TN loading by source and bay segment (all sources) (Zarbock et al., 1996a).BAY SEGMENTSOURCEOTBHBMTBLTBBCBTCBMRTOTALtons2271153062889320541102Atmospheric Deposition%508488651671230tons8522020115416362Domestic Point Source%19163<1815410tons08258<10011151Industrial Point Source%069<10024tons0233024000257Material Losses%017070007tons145534254207453601392Nonpoint Source%323940641188240tons<1196<1<1<1<1<1197Groundwater+Springs%<114<1<1<1<1<16tons4571381638334182304403462TOTAL%1340181051131007-3

### Current Conditions Bay Segment Loadings by Jurisdiction

The updated current conditions land-based TN lo adings are presented by bay segment for

each jurisdiction in Table 7-3. For co mparison purposes, the pr eviously estimated 1994

conditions loadings using th e 1990 landuse (Zarbock et al., 1996a) are shown in Table 7-4.

Atmospheric deposition and gr oundwater+springs were not included because it is not

feasible to apportion those loads to a jurisdiction. It should be noted that Pasco, Polk, and

Sarasota counties are included in Tables 7-3 a nd 7-4. Although these jurisdictions have not

been active in the TBEP allocation process, th eir contributions are shown for reference and

for accounting purposes. Land-based loads co mbined for approximately 2,277 tons/year

for the updated current conditions.

For allocating all land-based, manageable load s to local governments , it was necessary to

apportion all nonpoint source, point source, and material loss loadings to a jurisdiction.

For example, although MacDill Air Force Base is owned by the Federal government,

loadings from the base’s wastewater treatment plant were assigned to the City of Tampa.

Local jurisdictions were also assigned i ndustrial point source loadings for facilities

discharging within the governmental boundaries. One exception is material loss loadings

to Hillsborough Bay, which were assigned to Hillsborough County. This was done

because of the active role that the county plays in regulating the phosphate industry and

this source of nutrient loads.

Of the participating jurisdictions (Pinella s, Hillsborough, and Manatee counties and the

cities of Tampa, St. Petersburg, Clearwater , and Bradenton), Hillsborough County had the

highest contribution at 804 tons /year (35% of the bay-wide total). Of this load, 436

tons/year entered Hillsboroug h Bay, 275 tons/year entered Middle Tampa Bay, and 93

tons/year entered Old Tampa Bay.

Manatee County had the second highest contribu tion, with 543 tons/yea r (24% of the baywide total). Manatee County’s loads were di spersed to four bay segments, including

Manatee River (366 tons/year), Lower Tampa Bay (123 tons/year), Middle Tampa Bay (44

tons/year), and Terra Ceia Bay (10 tons/year). The City of Tampa generated approximately

14% of the bay-wide load, contributin g 303 tons/year to Hillsborough Bay and 25

tons/year to Old Tampa Bay. The City of St. Petersburg contri buted approximately 122

tons/year (5%) of the total existing conditions TN load, di stributed between Middle Tampa

Bay (55 tons/year), Boca Ciega Bay (47 tons/year), and Old Tampa Bay (20 tons/year).

Pinellas County contributed 119 tons/year (5% of the total TN load), distributed between

Old Tampa Bay (73 tons/year) a nd Boca Ciega Bay (46 tons/year ). The City of Clearwater

contributed approximately 2% of the total TN load, all 44 tons/year going to Old Tampa

Bay. The City of Bradenton contributed approx imately 2% of the total TN load, with all 47

tons/year going to the Manatee River.

Differences between the updated current cond itions loadings by jurisdiction and those

previously derived in Zarbock et al. ( 1996a) for 1994 total about 114 tons, with the

7-4

### updated loadings higher than those estimated previously. This differenc e is largely due to

the increased point source loading estimates for the updated existing conditions loadings.

The loads from these sources are representative of those of the most recent year for which

data exist, 1998, as described in Pribble et al. (2001). This time period included the high

rainfall period of the winter of 1997-1998 associ ated with the El Niño event. The elevated

loadings for the updated current conditions ar e at least partially related to this event.

Table 7-3. Updated current conditions annual TN loading by bay segment and jurisdiction

(land-based sources).

BAY SEGMENT JURISDICTION O T B H B M T B L T B B C B T C B M R T O T A L

t o n s 9 3 4 3 6 2 7 5 0 0 0 0 8 0 4 Hillsborough County

% 3 6 4 4 7 3 0 0 0 0 3 5

t o n s 7 3 0 0 < 1 4 6 0 0 1 1 9 Pinellas County

% 2 8 0 0 < 1 4 9 0 0 5

t o n s 0 0 4 4 1 2 3 0 1 0 3 6 6 5 4 3 Manatee County % 0 0 1 2 1 0 0 0 1 0 0 8 7 2 4

t o n s 2 5 3 0 3 0 0 0 0 0 3 2 9 Tampa % 1 0 3 0 0 0 0 0 0 1 4

t o n s 2 0 0 5 5 0 4 7 0 0 1 2 2 St. Petersburg

% 8 0 1 5 0 5 1 0 0 5

t o n s 4 4 0 0 0 0 0 0 4 4

Clearwater

% 1 7 0 0 0 0 0 0 2

t o n s 0 0 0 0 0 0 4 7 4 7

Bradenton

% 0 0 0 0 0 0 1 1 2

t o n s 0 2 3 1 0 0 0 0 0 2 3 1 Polk County

% 0 2 3 0 0 0 0 0 1 0

t o n s 1 3 1 0 0 0 0 0 3 3 Pasco County % 1 3 0 0 0 0 0 1

t o n s 0 0 0 0 0 0 5 5 Sarasota County % 0 0 0 0 0 0 1 < 1

t o n s 2 5 8 1 0 0 2 3 7 4 1 2 3 9 3 1 0 4 1 8 2 2 7 7

Total

% 1 1 4 4 1 6 5 4 < 1 1 8 1 0 0

7-5

### Table 7-4. Previous existing conditions (1994) annual TN lo ading by bay segment and

jurisdiction (land-based sources) (Zarbock et al., 1996a).

BAY SEGMENT JURISDICTION O T B H B M T B L T B B C B T C B M R T O T A L

t o n s 8 5 5 4 0 2 3 8 0 0 0 0 8 6 2 Hillsborough County

% 3 7 5 1 7 2 0 0 0 0 4 0

t o n s 6 3 0 0 0 4 0 0 0 1 0 3 Pinellas County

% 2 7 0 0 0 4 5 0 0 5

t o n s 0 0 4 1 4 6 0 1 0 3 5 1 4 4 7 Manatee County % 0 0 1 2 1 0 0 0 1 0 0 9 1 2 1

t o n s 2 4 2 8 3 1 0 0 0 0 3 0 7 Tampa % 1 0 2 6 < 1 0 0 0 0 1 4

t o n s 1 5 0 5 3 0 4 9 0 0 1 1 8 St. Petersburg

% 7 0 1 6 0 5 5 0 0 5

t o n s 4 1 0 0 0 0 0 0 4 1

Clearwater

% 1 8 0 0 0 0 0 0 2

t o n s 0 0 0 0 0 0 3 1 3 1

Bradenton

% 0 0 0 0 0 0 8 1

t o n s 0 2 1 6 0 0 0 0 0 2 1 6 Polk County

% 0 2 0 0 0 0 0 0 1 0

t o n s 2 3 1 0 0 0 0 0 3 3 Pasco County % 1 3 0 0 0 0 0 2

t o n s 0 0 0 0 0 0 5 5 Sarasota County % 0 0 0 0 0 0 1 < 1

t o n s 2 3 0 1 0 7 0 3 3 2 4 6 8 9 1 0 3 8 7 2 1 6 3

Total

% 1 1 5 0 1 5 2 4 < 1 1 8 1 0 0

7-6

### 7.2 2010 Conditions

Future Conditions Bay Segment Loadings by Source

For the period ca. 2010, an estim ated average annual load of 3,132 tons/year of TN is

projected to reach the bay. Projected future condition TN loadings ar e presented by source

and bay segment in Table 7-5. For compar ison purposes, the previous ly estimated future

conditions loadings (Zarbock et al., 1996a) ar e shown in Table 7-6. From the updated

future estimate, nonpoint sources were projec ted to have the highest contribution with

approximately 1,432 tons/year (49%), and at mospheric deposition was projected to have

the second highest contribution with 578 tons /year (20% of the total external load).

Domestic and industrial point sources were estimated to contri bute approximately 453

(15%) and 204 tons/year (7%), respectively. Material losses of fertilizer products were

estimated to total 36 tons/year (1%). Groundwat er and springs loadings were estimated to

total 247 tons/year (8%), with much of that (a bout 246 tons/year) originating from springs.

Of the bay segments, Hillsborough Bay was exp ected to receive the highest future TN

loading, estimated at 1,257 t ons/year. The sources with the highest expected future

contributions to Hillsborough Bay included nonpoint source (502 tons/yea r, or 40% of the

total), domestic point sources (283 tons/year, or 23% of the total), and industrial point

sources (130 tons/year, 10% of the total). Springs and groundwater were projected to

contribute 246 tons/year (20%), atmospheric deposition 60 tons/year (5%), and material

losses 36 tons/year (3%).

Middle Tampa Bay was projected to have the second highest future condition TN loading

(515 tons/year). Nonpoint sources were estimat ed to be the most significant TN loading

source (265 tons/year, or 51% of the total). Atmospheric deposition was estimated to be

another significant source, cont ributing 159 tons/year, or 31% of the total. Industrial and

domestic point sources combined for 89 t ons/year, or 17% of the total load.

The Manatee River segment was projected to re ceive the next highest loading for future

conditions, approximately 438 tons /year. Nonpoint source loads were expected to be most

significant (366 tons/year, or 84% of the segment total). Industrial and domestic point

sources were expected to contribute 11 tons/yea r (3%) and 31 tons/year (7%), respectively,

and atmospheric deposition approx imately 29 tons/year (7% of the total to that segment).

Old Tampa Bay was expected to receive the next highest TN loading for future conditions

(388 tons/year). The highest source-specific load was pr ojected to be from nonpoint

sources (183 tons/year, or 47% ). Atmospheric deposition loads were estimated to be 117

tons year (30% of the total). Atmospheri c deposition will continue to be a significant

external TN source for Old Tampa Bay because of the relatively lar ge open water area of

that segment, and because of the small cont ributions of other sources (small tributary

drainage area and few poi nt sources). Domestic point s ources (84 tons/year, or 22%) and

7-7

### industrial point sources (4 tons/year, or 1%) were the only other significant TN sources to

Old Tampa Bay.

Lower Tampa Bay was expected to receive an average of approximately 176 tons/year for

ca. 2010, with 153 tons/year (87% ) of that total from atmos pheric deposition. Again, the

large surface area of water and the lack of other significant sources made atmospheric

deposition by far the most im portant external source for this bay segment. Of the

remainder, 21 tons/year (10%) is expected to be from nonpoint sources, with 2 tons/year

(1%) from domestic point sour ces. Less than 1 ton/year is expected from the material

losses at Port Manatee.

Boca Ciega Bay was projected to receive a total TN load of 150 tons/year, with 88

tons/year (59%) from nonpoint sources a nd 48 tons/year (32%) originating from

atmospheric deposition. Domes tic point sources were expected to contribute about 14

tons/year (9%). Terra Ceia Bay had the smalle st projected future TN loading of the bay

segments, with almost 26 tons/year. Of that amount, approximately 11 tons/year (42%)

was expected to originate as atmospheric deposition and 7 tons/yea r (27%) from nonpoint

sources.

The updated future loading estimate is approx imately 720 tons less th an those from the

previous estimate. This differenc e is largely due to the decreases in atmospheric deposition

loading predicted for the period. The decr eased nitrogen emissions resulting from the

TECO facilities are expected to decrease at mospheric nitrogen concentrations. As

discussed previously, for the update d future loading estimate, a decrease in concentrations

of 46% is assumed. This re duction leads to predicted atmospheric deposition loads of

approximately half of those from the previous predic tion. Further differences between the

updated and previous future loading estimates result from the decrease in the predicted

material losses loading. This decrease results from the improved handling operations and

refined loss estimates compared to those used previously. The lower loss rate was applied

after discussions with phosphate industry representatives (Pribble et al., 2001).

As discussed previously, three methods of estimating 2010 atmospheric deposition were

utilized to provide some bounds on expecte d changes in deposition due to emission

reductions. The results of the method usin g a 46% reduction in atmospheric nitrogen

concentration, proportional to the 46% reduc tion in emissions, are shown in Table 7-5

below. The second method used estimated a 1-ton reduction in deposition for a 400-ton

reduction in emissions. The third method a ssumed no changes in atmospheric nitrogen

concentrations from 1998 levels. A comparison of the results of th ese methods are shown

below:

Method Deposition

Percentage reduction: 578 tons/yr

400:1 ratio: 898 tons/yr

No change in deposition: 1142 tons/yr

7-8Table 7-5. Updated future conditions annual TNloading by source and bay segment (all sources).BAY SEGMENTSOURCEOTBHBMTBLTBBCBTCBMRTOTALtons11760159153481129578Atmospheric Deposition%30531873242720tons8428332214731453Domestic Point Source%222361927715tons41305800011204Industrial Point Source%11011<10037tons0360<100036Material Losses%030<10001tons183502265218883661432Nonpoint Source%4740511259318449tons<1246<1<1<1<1<1247Groundwater+Springs%<120<1<1<1<1<18tons3881257515176150264382950TOTAL%13431765115100Table 7-6. Previous future conditions annual TN loading bysource and bay segment (all sources) (Zarbock et al., 1996a).BAY SEGMENTSOURCEOTBHBMTBLTBBCBTCBMRTOTALtons24912633631710223591213Atmospheric Deposition%549508653771233tons4728320315021390Domestic Point Source%10193170511tons07758<10011147Industrial Point Source%059<10024tons0247026000273Material Losses%017070007tons165540256237873811451Nonpoint Source%363738640238140tons<1196<1<1<1<1<1197Groundwater+Springs%<113<1<1<1<1<15tons4631470670369195294733670TOTAL%1340181051131007-9

### Future Conditions Bay Segment Loadings by Jurisdiction

The updated future conditions TN land-based lo adings by bay segment and jurisdiction are

presented in Table 7-7. For comparison purposes, the previously estimated future

conditions loadings using th e 1990 landuse (Zarbock et al., 1996a) are shown in Table 7-8.

As with existing conditions, atmospheric deposition and groundwater +springs are not

included because it is not feasib le to apportion those loads to a jurisdiction. It should be

noted that Pasco, Polk, and Sarasota counties are included in Tables 7-7 and 7-8. Although

these jurisdictions have not been active in the TBEP process, their contributions to Tampa

Bay loadings are shown for reference and for accounting purposes.

Of the participating jurisdictions (Pinella s, Hillsborough, and Manatee counties and the

cities of Tampa, St. Petersburg, Clearwater , and Bradenton), Hillsborough County had the

highest contribution, at 741 tons/year (35% of the total load to the bay). Of this load, 378

tons/year were expected to go to Hillsboroug h Bay, 267 tons/year to Middle Tampa Bay,

and 97 tons/year to Old Tampa Bay. The la rge proportion of projected future loadings

from Hillsborough County resulted from a la rge contributing land area, and significant

point source inflows.

Manatee County had the second highest expecte d contribution, with 434 tons/year (20%).

Manatee County’s loads were dispersed to f our bay segments, including Manatee River

(365 tons/year), Middle Tampa Bay (31 tons/year), Lower Ta mpa Bay (23 tons/year), and

Terra Ceia Bay (15 tons/year).

The City of Tampa was expected to generate approximately 16% (331 tons/year) of the

total bay-wide load, with 303 tons/year goin g to Hillsborough Bay and 28 tons/year going

to Old Tampa Bay. The City of St. Pe tersburg was expected to contribute 6% (128

tons/year) of the future TN load, distribut ed between Middle Tampa Bay (57 tons/year),

Boca Ciega Bay (51 tons/year), and Old Tamp a Bay (21 tons/year). Pinellas County was

expected to contribute 5% (110 tons/year) of the future TN load, distributed between Old

Tampa Bay (59 tons/year), and Boca Ciega Bay (51 tons/year).

The City of Bradenton was projected to contri bute approximately 2% of the total future TN

load, with all 39 tons/year going to the Ma natee River. The City of Clearwater was

projected to contribute approxim ately 3% of the total TN load, all 65 tons/year going to

Old Tampa Bay. Polk, Pasco, and Saraso ta counties combined for an additional 275

tons/year, or approximately 12% of the total future bay loading.

Differences between the updated future cond itions loadings by jurisdiction and those

previously derived in Zarbock et al. ( 1996a) total about 135 tons, with the updated

loadings higher than those estimated previously. This diffe rence is largely due to the

increased point source loadin g estimates for the updated future conditions loadings. As

described in Pribble et al. (2001), six industria l sources were identified for inclusion in the

updated future loading estimate that were not included in th e previous estimate, including

7-11

### five in the Hillsborough Bay watershed and one in the Old Tampa Bay watershed.

Additionally, revisions to planned increases in domestic point source loadings, resulting

from the interviews described in Appendix 1, led to increased loadings. Both industrial

and domestic point source cont ributions were higher in the updated future estimate than

previously.

Table 7-7. Updated future conditions annua l TN loading by bay segment and jurisdiction

(land-based sources).

BAY SEGMENT JURISDICTION O T B H B M T B B C B T C B M R T O T A L

t o n s 9 7 3 7 8 2 6 7 0 0 0 0 7 4 1 Hillsborough County

% 3 6 4 0 7 5 0 0 0 0 3 5

t o n s 5 9 0 0 < 1 5 1 0 0 1 1 0 Pinellas County

% 0 0 < 1 5 0 0 0 5

t o n s 0 0 3 1 2 3 0 1 5 3 6 5 4 3 4 Manatee County % 0 9 1 0 0 0 1 0 0 8 9 2 0

t o n s 2 8 3 0 3 0 0 0 0 0 3 3 1 Tampa % 3 2 0 0 0 0 0 1 6

t o n s 2 1 0 5 7 0 5 1 0 0 1 2 8 St. Petersburg

% 0 1 6 0 5 0 0 0 6

t o n s 6 5 0 0 0 0 0 0 6 5

Clearwater

% 0 0 0 0 0 0 3

t o n s 0 0 0 0 0 0 3 9 3 9

Bradenton

% 0 0 0 0 0 1 0 2

t o n s 0 2 1 9 0 0 0 0 0 2 1 9 Polk County

% 2 3 0 0 0 0 0 1 0

t o n s 1 4 1 0 0 0 0 0 5 2 Pasco County % 4 0 0 0 0 0 2

t o n s 0 0 0 Sarasota County 

### L T B

2 2

0

1 0

8

2 4

0

0

< 1

0 0 0 4 4

% 0 0 0 0 0 0 1 < 1

t o n s 2 7 1 9 5 1 3 5 5 2 3 1 0 2 1 5 4 0 9 2 1 2 5

Total

% 1 3 4 5 1 7 1 5 < 1 1 9 1 0 0

7-12

### Table 7-8. Previous future conditions annual TN loading by bay segment and jurisdiction

(land-based sources) (Zarbock et al., 1996a).

BAY SEGMENT JURISDICTION O T B H B M T B L T B B C B T C B M R T O T A L

t o n s 8 7 5 3 0 2 3 7 0 0 0 0 8 5 5 Hillsborough County

% 4 1 4 0 7 1 0 0 0 0 3 8

t o n s 4 4 0 0 0 4 0 0 0 8 3 Pinellas County

% 2 7 0 0 0 4 3 0 0 4

t o n s 0 0 4 0 5 3 0 7 3 7 2 4 7 2 Manatee County % 0 0 1 2 1 0 0 0 1 0 0 9 0 2 1

t o n s 2 4 3 6 5 1 0 0 0 0 3 9 0 Tampa % 1 1 3 2 < 1 0 0 0 0 1 7

t o n s 1 6 0 5 6 0 5 3 0 0 1 2 5 St. Petersburg

% 8 0 1 7 0 5 7 0 0 5

t o n s 4 0 0 0 0 0 0 0 4 0

Clearwater

% 1 3 0 0 0 0 0 0 2

t o n s 0 0 0 0 0 0 3 6 3 6

Bradenton

% 0 0 0 0 0 0 9 2

t o n s 0 2 2 2 0 0 0 0 0 2 2 2 Polk County

% 0 1 9 0 0 0 0 0 1 0

t o n s 2 3 0 0 0 0 0 0 3 2 Pasco County % 1 3 0 0 0 0 0 1

t o n s 0 0 0 0 0 0 6 6 Sarasota County % 0 0 0 0 0 0 1 < 1

t o n s 2 1 3 1 1 4 8 3 3 4 5 3 9 2 7 4 1 4 2 2 6 0

Total

% 9 5 1 1 5 2 4 < 1 1 8 1 0 0

7-13

# 8. CONCLUSIONS

To attain its seagrass restoration goal, th e TBNEP developed the Nitrogen Management

Strategy. The Strategy seeks to prevent future impacts due to excessive nitrogen loadings to

Tampa Bay. To provide quantifiable goals fo r the Strategy, a suite of models were

developed relating total nitrogen loading to chlorophyll concentrations in the bay and

chlorophyll concentrations to light attenua tion. These models suggested that light

availability necessary for obtaini ng seagrass restoration goals could be met by establishing

a “hold the line” strategy for nitrogen lo ads. The Tampa Bay Nitrogen Management

Consortium adopted this strategy in 1996.

To implement this strategy, local government pa rtners agreed to pr eclude increases in

future nitrogen loadings to the bay. The ca. 2010 total nitrogen loading estimates

presented in Zarbock et al. (1996a) were developed to quantify expected TN loading

increases, and were used for the TBNEP A llocation Workshops. Thi s report presents the

results of an update of the ca. 2010 total n itrogen loadings for use in reviewing the

previous allocations for load preclusion.

The following provides the conclusions from this update.

• The greatest difference in predicted fu ture loadings from any source is for

atmospheric deposition. As a result of planned decreases in nitrogen

emissions from TECO facilities, the update d load is approximately half of the

previously predicted load. A more conservative method of deposition

reduction estimation (400:1 ratio) still resu lts in a reduction of 25% from that

predicted previously.

• The updated future loading predictions from domestic and industrial point

sources are higher than previously. Revised estimates for domestic facilities

include recent modifications to planne d future operations. Revised estimates

for industrial facilities include six add itional facilities that were not included

in the previous estimate.

• The updated future loading predictions from material losses are less than

those predicted previously. This is lar gely the result of improved operations

at several facilities, resulting in lower material losses, and improved loss

estimation methods.

• The updated future nonpoint source lo adings did not change appreciably

from the previous prediction, despite an update of the future land use

showing a larger proportion of urban land use than previously predicted.

This is likely due to the load attenuation from any new development

incorporated into the estimate.

8-1

# 9. LITERATURE CITED

Beardslee, Gordon. 2000. Pinellas County Planning Department. Personal

Communication.

Burbridge, Katherine. 2000. Pasco C ounty Development Services Branch. Personal

Communication.

Brooks, G.R., T.L. Dix, and L.J. Doyle. 1993. Groundwater/surface water interactions in

Tampa Bay and implications for nutrient fluxes . Prepared for: Tampa Bay National Estuary

Program. St. Petersburg, Florida. 44 p.

Coastal Environmental, Inc. 1995. Guidebook to Stormwater Best Management Practices

in the Tampa Bay and Central Florida Regions . Prepared for Tampa Bay National Estuary

Program. St. Petersburg, Florida.

Cullen, Terry. 2000. Hillsborough County City-County Planning Commission. Personal

Communication.

Environmental Science & Engineering, Inc. 1987. Florida Acid Deposition Study – Fiveyear data summary. Prepared for: Florida Electric Power Coordi nating Group. Tampa,

Florida.

Florida Department of Environmental Prot ection (FDEP). 2000. Personal communication

with R. Pribble, Janicki Environmenta l, from Tom Rogers, FDEP, 5 June 2000.

Florida Department of Transportation Thema tic Mapping Section (FDOT). 1985. Florida

land use, cover and forms classification system . Second ed. Tallahassee, Florida. 81 p.

Foose, D. 1993. U.S. Geol ogical Survey WRD. Personal communication. Tallahassee,

Florida.

Freeze and Cherry. 1979. Groundwater . Prentice-Hall, Inc. Englewood Cliffs, NJ. 604 p.

Hillsborough County City-County Planning Commission. 1999a. 1999 Population and

Housing Estimates by Jurisdic tion and Census Tract. Prep ared for Hillsborough Country

Board of County Commissioners. Tampa, FL.

Hillsborough County City-County Planning Commission. 1999b. 2020 Population and

Housing Projections by Jurisdiction and Cens us Tract. Prepared for Hillsborough Country

Board of County Commissioners. Tampa, FL.

Hommel, Christina. 2000. Polk County Planni ng Department. Personal Communication.

9-1

### Hutchinson, C.B. 1983. Assessment of the interconnection between Tampa Bay and the

Floridan Aquifer, Florida. U.S. Geologi cal Survey Water Resources Investigations Report

82-54. Tallahassee, Florida. 61 p.

Janicki, A. and D. Wade. 1996. Estimating cr itical external nitrogen loads for the Tampa

Bay estuary: An empirically based approach to setting management targets. Prepared for:

Tampa Bay National Estuary Program. Prepar ed by: Coastal Environmental, Inc. Tampa

Bay National Estuary Program Technical Publication #06-96.

Kotecki, Leon. 2000. Manatee County Planning Department. Personal Communication.

Manatee County Planning Department. 1999. Resident Population Projections and

Distribution, 1990-2025 Manatee C ounty, Florida. . Prepared for Manatee Country Board

of County Commissioners. Bradenton, FL.

Morrison, G., and R. Eckenrod. 1994. Pe rsonal Communication. Estimated Fugitive

Emissions to Tampa Bay, 1985 to 1991. Tampa, Florida.

Pasco County Development Services Branch . 1999. Population and Employment

Projections Pasco County, 1997-2020. Prepared for Pasco County Board of County

Commissioners. New Port Richey, FL

Pinellas County Planning Department. 1998. Population and Employment Projections

Pinellas County, 1997-2030. Prepared for Pinellas County Board of County

Commissioners. Clearwater, FL.

Pribble, R., A. Janicki, S. Janicki, and M. Wi nowitch. 2001. Estimates of total nitrogen,

total phosphorus, total suspended solids, a nd biochemical oxygen demand loadings to

Tampa Bay, Florida: 1995-1998. Draft Report. Prepared for: Tampa Bay Estuary Program.

Prepared by: Janicki Environmental, Inc.

Southwest Florida Water Management Dist rict – Mapping and GIS Section 1992.

Geographic Information System Data Distri bution Procedures. Subbasin boundary ARC

INFO coverage. Brooksville, Florida.

St. Petersburg, City of. 1993. Reclaimed wa ter and injection well monitoring data for

1986 to 1992. Department of Sanitary Sewers. St. Petersburg, Florida.

Tampa Bay Estuary Program (TBEP). 1999. Partnership for Progress, the Tampa Bay

Nitrogen Management Consortium Action Plan 1995-1999. Tampa Bay Estuary Program,

St. Petersburg, FL.

9-2

### Tampa Bay National Estuary Program (TBNEP). 1996. Charting the Course for Tampa Bay,

the Comprehensive Conservation and Managem ent Plan for Tampa Bay. Tampa Bay

National Estuary Program in cooperation with the US Environmental Protection Agency,

Region IV. St. Petersburg, FL.

Tampa Electric Company (TECO). 2000. Pr esentation at the 28 January 2000 Tampa Bay

Nitrogen Management Consortium meeting, St. Petersburg, FL. Presen ted by Greg Nelson,

Manager, Environmental Planning Department, TECO.

Zarbock, H., A. Janicki, D. Wade, D. Heimbuc h, and H. Wilson. 1994. Estimates of Total

Nitrogen, Total Phosphorus, and Tot al Suspended Solids Loadings to Tampa Bay, Florida.

Technical Publication #04-94. Prepared by Coastal Environmental, Inc. Prepared for

Tampa Bay National Estuary Program. St. Petersburg, FL.

Zarbock, H., A. Janicki, D. Wade, S. Jani cki, and R. Pribble. 1996a. Model-based

estimates of total nitrogen lo ading to Tampa Bay. Prepared for: Tampa Bay National

Estuary Program. Prepared by : Coastal Environmental, Inc. Tampa Bay National Estuary

Program Technical Publication #05-96.

Zarbock, H., A. Janicki, and S. Janicki. 1996. Estimates of Total Nitrogen, Total

Phosphorus, and Total Suspended Solids Loadings to Tampa, Bay, Florida. Technical

Appendix: 1992-94 Total Nitrogen Loads to Ta mpa Bay. Technical Publication #19-96.

Prepared by Coastal Environmental, Inc. Prepared for Tampa Bay National Estuary

Program. St. Petersburg, FL.

9-3

# APPENDIX 1

INDIVIDUALS CONTACTED FOR FUTURE CONDITIONS POINT SOURCE

INFORMATION AND SUMMARY OF INTERVIEWS

1

### Domestic Point Sources Projected Plans for 2010

City of St. Petersburg Southwest

City of St. Petersburg Albert Whitted

City of St. Petersburg Northeast

City of St. Petersburg Northwest

In 2000 spoke to Mr. Bill Johnson of the City of St. Petersburg and he stated that the

predictions from previous interview with Mr . Dave Schulmister (1995) are still the same.

City of Largo

Spoke to Brian Dean of the City of Largo Plan t. Said that Plant capacity did increase to 18

MGD (i1997). Reclaimed water (reuse) is hoped to be at 70% reuse by 2005 and 90%

reuse by 2010. Do not foresee any changes in nutrient loading and have no plans to

expand the plant.

City of Clearwater Northeast

City of Clearwater East

Spoke to Mr. Joe Reckenwald in 2000. He st ated that the NE plant 2010 predictions will

remain the same from his previous interview in 1996. Says that East plant is currently at

50% reclaimed and anticipates that number increasing to 75% by 2010.

City of Lakeland

Mr. Don Schulender, Planning Engineer for Wa stewater Division of the City of Lakeland,

was contacted in 2000. He stated that out of 10 MGD, 25%-33% will goto Reuse. There

is a possiblity that the city is expanding th eir power plant and will take all of the effluent,

so 100% reuse. Mr. Schulender still anticipat es no modifications in effluent quality from

the plant.

Bradenton

Mr. John W. Cumming, Director of Public Work s, was contacted in August of 2000. Mr.

Cumming related that the City plan to expa nd the system, with SWFMD assistance, is a

multi-year plan reaching about four years (2004) into the future. That plan calls for

addition of transmission piping, storage and pumpi ng facilities. The original plan calls for

system extensions to agricultural lands to the southeast and to a manmade wetland

2

### discharging to the Braden River downstream of th e City’s drinking water reservoir. Recent

events and additional demands for reclaime d water have, however, brought about some

change to the plan and may result in more changes.

A major change has been the inclusion of Tropi cana Products as a major user of reclaimed

water. A project now under construction w ill provide Tropicana with approximately 1.2

MGD of the City’s reclaimed water. Other industrial users have begun discussion with the

City regarding use of 2.0 to 4.0 MGD of recl aimed water. That need may occur by early

2004. Should such be the case, the manmade wetland may be replaced by a user or users

that would otherwise require ground or surface water supplies. The Florida Power and

Light orimulsion conversion mention in the last report, did not come to pass so there is no

proposed use at that location.

The following information was received from Mr. Cumming in August 2000.

Year Population Functional

Population Estimated ADF

(MGD)

2000 50,500 57,065 6.13

2005 53,000 59,880 6.43

2010 55,500 62,715 6.74

Manatee County Southeast

North County Regional (Manatee)

Mr. Leon Kotecki, Planning, was contacted in August 2000. Mr. Kotecki related that the

Manatee County SE area has had lot of d evelopment since 1995, such as Lakewood Ranch

and six other developments. He also states th at there are no changes in discharge methods

or treatment methods.

Below is a information provided by Mr. Kotecki:

Facility Year Population Population

plus Snowbirds

SE 2010 98,332 114,884

N 2010 40,082 52,707

Usage Rate: 105 GPD

Figure Snowbirds are around for 6 months/year.

3

### City of Oldsmar

Mr. Jerry Wein was contacted in Septemb er 2000, who said there were no changes

anticipated from the previous estimate.

City of Mulberry

Mr. Troy Cassidy was contacted in August 2000 and stated that there were no changes

from what was last reported. The dischar ge from the plant would be approximately 0.415

MGD by 2016. No changes in effluent quality were expected.

Plant City

Spoke to Steve Saffels, said they have a new permit as of January 1997, going to have an

annual of 2.68MGD by 2010. All discharge should be to reuse. The plant is allowed an

emergency pop-off of 30% of its annual total flow to the East Side Canal. Reuse will be for

industrial purposed, with approximately 2 MGD to CF Industries. Projected flows for 2012

were 5.0 MGD. Effluent quality woul d remain the same for the future.

City of Palmetto

Mr. Don Patterson, Interm Public Works Direct or, said they are permitted for 2.4 MGD but

currently averages 1.2 MGD over the year. Currently they discharge 50% to Bay (2000)

hopes by year 2004 have 100% reuse. Predicts flow of plant to be 2.36MGD by 2010

4

### Dale Mabry

Van Dyke

Northwest Regional Water Reclamation Facility

River Oaks

Falkenburg

Valrico

South County

Summerfield

Eagles

Ms. Carole Awad, Senior Engineer, Water/Re claimed Water Planning Team, Mr. Nick

Leprici, Engineer II, Wastewater Planning, a nd Ms. Anita Wang, Engineer II, Wastewater

Planning, of Hillsborough County, were contact ed in August 2000 for information relating

to the plants of the county.

Ms. Awad stated that no changes in water quality would occur, as most of the plants were

already AWT, with the exceptions of Summerfield and Van Dyke, both of which were

secondary plants. The Van Dyke plant, with a ll effluent used for spray irrigation, and the

Eagles plant, with all discharge to a percolation pond, were on-line in 1995. Van Dyke

was previously a private plant, with 1.5 MGD capacity and approximately 0.6 MGD flow.

According to Mr. Garrett, the Eagles plant in 1995 had flow of only 0.02 MGD. Ms. Awad

related that the Summerfield plant is scheduled to go off-line in 1998, with its flow diverted

to the Falkenburg and Valrico plants. Ms. Aw ad also stated that the Southern Regional

facility scheduled to come on-line in 2005 was longer planned.

Information on the changes in discharge and the modifications in effluent reuse

percentages were calculated from graphs and tables obtained in a visit with the abovementioned contacts. The county's go al is to have 100% reuse by 2015.

The following information was obtained from th e graphs and tables provided by Ms. Awad

and Mr. Leprici.

Hillsborough County Domestic Facilities

Dale Mabry

1995 2000 2005 2010 2015 2020

Plant Capacity (MGD) 6 6 6 6 6 6

Plant ADF 3.86 4.35 4.48 4.72 4.96 5.19

Total Reuse ADF 3.43 * * * * *

Non-Reuse ADF 0.43 * * * * *

5

### Van Dyke

1995 2000 2005 2010 2015 2020

Plant Capacity (all MGD) 1.5 1.5 1.5 1.5 1.5 1.5

Plant ADF 0.62 0.7 0.9 1.1 1.3 1.5

Total Reuse ADF 0.62 * * * * *

Non-Reuse ADF 0 * * * * *

Northwest Regional Water Reclamation Facility

River Oaks

NW & River Oaks 1995 2000 2005 2010 2015 2020

NW Plant Capacity (MGD) 5 5 5 5 5 5

NW Plant ADF 2.49 3.5 3.76 4.02 4.28 4.54

RO Plant Capacity 10 10 10 10 10 10

RO Plant ADF 8.14 6.33 7.08 7.41 7.74 8.07

NW/RO Total Reuse ADF 1.69 * * * * *

NW/RO Non-Reuse ADF 8.94 * * * * *

Combined Total Northwest

Plant ADF 15.11 14.88 16.22 17.25 18.28

Reuse ADF 5.74 6.53 11.47 13.12 14.09 14.61

Non-Reuse ADF 9.37 8. 35 4.75 4.13 4.19 4.69

* In 2000, the Northwest WWTP reuse syst ems were interconnected and flows were

transferred throughout reuse systems. Re use & Non-Reuse ADF shown is for entire

Northwest area

Falkenburg

Valrico

Falkenburg & Valrico 1995 2000 2005 2010 2015 2020

F Plant Capacity (all MGD) 6 6 9 9 9 12

F Plant ADF 3.8 4.87 6.34 6.56 8.45 10.35

V Plant Capacity 3 4 6 12 12 12

V Plant ADF 2.7 3.72 4.76 6.94 8.38 9.55

TOT Total Reuse ADF 3.58 * * * * *

TOT Non-Reuse ADF 2.92 * * * * *

6

### * Combined Valrico and Falkenburg

Val/Falk Plant Flow 6.5 8.59 11.1 13.5 16.83 19.9

Val/Falk Reuse ADF 3.58 6.51 * * * 22.6

Val/Falk Non-Reuse ADF 2.92 4.97 * * * 1.6

*In 1998, the Valrico and Falkenburg reuse systems were interconnected.

149A,B - South County

South County 1995 2000 2005 2010 2015 2020

Plant Capacity (all MGD) 4.5 4.5 4.5 4.5 4.5 4.5

Plant Flow ADF 2.7 2.88 3.89 4.5 4.5 4.5

Plant Reuse ADF 2.4 2.42 * * * *

Plant Non-Reuse ADF 0.3 0.46 * * * *

* Combined Central and South Reuse Systems

S-C Plant ADF 9.2 11.47 14.99 18 21.33 24.4

S-C Reuse 5.98 8.93 14.12 17.68 20.12 22.72

S-C Non-Reuse ADF 3.22 2.54 0.87 0.32 1.21 1.68

* In 2002, WWTP's in the South/Central area are anticipated to be interconnected. Reuse

& Non-Reuse ADF shown is for entire South/Central area

Summerfield - Offline in 1998

Eagles

Summerfield 1995 2000 2005 2010 2015 2020

Plant Capacity 0.75 0.75

Demand 0.12 0.22

Eagles 1995 2000 2005 2010 2015 2020

Plant Capacity 0.15 0.3 0.3 0.3 0.3 0.3

Demand 0.01 0.12 0.17 0.22 0.24 0.24

Eastlake Woodlands

Pine Ridge

Tarpon Woods

Tarpon Lake Village

No changes to current discharge rate. 100% reclaimed.

By 2010, Tarpon Lake & Tarpon Woods are to be diverted to the NW Facility.

7

### MacDill

Mr. Mike Harr, Water Program Manager was contact ed in 2000. He stated that the plant

capacity will remain the same, and effluent quantity will as well. Currently at 100% reuse.

Howard Curren

Spoke to Mr. Bill Schafer, Head of Planning, said in the next 10 years the plant will remain

the same.

The following information on projected growth demand (MGD) was obtained from the

Tampa Comprehensive Plan:

Year 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

ADF 0.54 0.75 0.96 1.07 1. 13 1.19 1.25 1.31 1.37 1.43

Extrapolations to 2010 were as follows:

Year 2005 2006 2007 2008 2009 2010

ADF 1.49 1.55 1.61 1.67 1.73 1.79

8

### Industrial Point Sources Projected Plans for 2010

IMC AGRICO - Kingsford

IMC AGRICO - Four Corners

IMC AGRICO - Port Sutton

IMC AGRICO - Lonesome

Received no information regarding any chan ges from Mr. Greg Williams, Environmental

Superintendent.

CF Industries - Plant City

Corresponded with Mr. Tom Edwards, Superint endent, who stated that the Plant City

facility does plan on increasing production and does expect an increase in the volume of

nutrients produced. He also stated that th ey do not anticipate any extra runoff due to the

closing of a gypsum stack by 2004. They exp ect to be very dynamic over the next 10

years which will keep the quality and quantity of nitrogen from their facility to be the

same.

Pakhoed Dry Bulk Terminals -

Spoke to Mr. Chris Tolbert, Manager of Environm ental Safety and Health and he anticipates

no increase in quality or quantity nitrogen from their facility.

Farmland Hydro - Green Bay Plant

Mr. Chuck Jenkins, Manager of Environment and Safety Services, stated that they have

decreased nitrogen output over the past four years and he anticipates no increase in quality

or quantity of nitrogen from their facility.

Tropicana

Contacted Mr. Doug Foster, Environmental Affa irs Manager, who said that they plan to be

100% deep well injection by end of 2000. They anticipate no other changes.

9

### AGRIFOS – Nichols Mine

Spoke to Mr. Tom Abel, Environmental Engin eer, who said the facility was closed on 6

August 2000 and there is no anticipated reopening date at the time. He also stated that if

the facility did reopen that they expect no chan ges that would affect nitrogen loadings.

CARGILL – East Tampa

Ms. Melody Foley was contacted in September 2000, and anticipates no increase in the

quality or quantity of nitrogen from their facility.

TECO - Gannon Station

TECO - Big Bend Station

Contacted Mr. Stan Maloy who anticipates no in crease in quality or quantity of nitrogen

from their facility.

Bridgeway Acres Class I Landfill

Spoke with Ms. Kelsy Oswald, Solid Waste Specialist, who stated that the landfill is

currently changing intake structures to decr ease turbidity which should then decrease

metals in their runoff. She stated that their runo ff is rainfall driven so it is difficult to predict

completely runoff amounts. Ms. Oswald also stated that they are starting new plans to

have 0% of wastewater to go offsite. This should all take place before 2010.

DEP Stock Enhancement Program

Corresponded with Frank Courtney, Assistant Rese arch Scientist, who said that any changes

to the Stock Enhancement Research facility are funding dependent. If increase funding,

plan to increase stock production. Along with that there would be an increase to the

wastewater treatment systems. They do plan to implement better treatment methods if this

expansion does happen.

Florida Juice

Was being sold as of August 1999 and was unable to reach anyone other than the

receptionist who had no comment.

10

### Mulberry Phosphates

Spoke with Mr. Paul Moore who anticipates no increase in quality or quantity of nitrogen

from their facility.

Nitram Chemical

Mr. Dan Ross was contacted, and anticipates no in crease in quality or quantity of nitrogen

from their facility.

Coronet Industries

Spoke with Mr. Viet Ta, Environmental Manager , who anticipates no increase in quality or

quantity of nitrogen from their facility.

11

# APPENDIX 2

AGGREGATED FLORIDA LAND USE AND COVER CLASSIFICATION

SYSTEM CATEGORIES

1URBAN LAND USE CATEGORIES

Coastal Land Use Code FLUCCS Code

1 - Low Density Residential 1100

2 - Medium Density Residential 1200

3 - High Density Residential 1300

4 - Commercial 1400

5 - Industrial 1500

7 - Institutional, Transportation, Utilities 1700

8100

8200

8300

AGRICULTURAL LAND USE CATEGORIES

Coastal Land Use Code FLUCCS Code

6 - Mining 1600

11 - Groves 2200

2210

2220

2230

12 - Feedlots 2300

13 - Nursery 2400

14 - Row and Field Crops 2100

2140

2150

2440

2UPLAND FORESTED LAND USE CATEGORIES

Coastal Land Use Categories FLUCCS Code

8 - Range Lands 1480

1800

1900

2420

2600

3100

3200

3300

9 - Barren Lands 7100

7200

7300

7400

10 - Pasture 2110

2120

2130

15 - Upland Forests 4100

4110

4120

4200

4300

4340

4400

3WATER AND WETLANDS LAND USE CATEGORIES

Coastal Land Use Categories FLUCCS Code

16 - Freshwater 2500

2540

2550

5100

5200

5210

5220

5230

5240

5300

5310

5320

5330

5340

5500

5600

6440

6450

17 - Saltwater 5400

9113

9116

9121

18 - Forested Freshwater Wetlands 6100

6110

6150

6200

6210

6240

6300

19 - Saltwater Wetlands 6120

6420

20 - Non-forested Freshwater Wetlands 6400, 6410,

6411, 6430

6530

21 - Tidal Flats 6500, 6510

6520

4

# APPENDIX 3

LAND USE-SPECIFIC SEASONAL RUNOFF COEFFICIENTS

1

### Seasonal Land Use-Specific

Runoff Coefficients

Coastal Land Use Classification and

Land Use Type Hydrologic

Soil

Group Dry

Season

Runoff

Coefficient Wet

Season

Runoff

Coefficient

1) Single Family Residential A 0.15 0.25

B 0.18 0.28

C 0.21 0.31

D 0.24 0.34

2) Medium Density Residential A 0.25 0.35

B 0.30 0.40

C 0.35 0.45

D 0.40 0.50

3) Multifamily Residential A 0.35 0.50

B 0.42 0.57

C 0.50 0.65

D 0.58 0.75

4) Commercial A 0.70 0.79

B 0.74 0.83

C 0.78 0.97

D 0.82 0.91

5) Industrial A 0.65 0.75

B 0.70 0.80

C 0.75 0.85

D 0.80 0.90

6) Mining A 0.20 0.20

B 0.30 0.30

C 0.40 0.40

D 0.50 0.50

2

### Seasonal Land Use-Specific

Runoff Coefficients

Coastal Land Use Classification and

Land Use Type Hydrologic

Soil

Group Dry

Season

Runoff

Coefficient Wet

Season

Runoff

Coefficient

7) Institutional, Transportation Utils. A 0.40 0.50

B 0.45 0.55

C 0.50 0.60

D 0.55 0.65

8) Range Lands A 0.10 0.18

B 0.14 0.22

C 0.18 0.26

D 0.22 0.30

9) Barren Lands A 0.45 0.55

B 0.50 0.60

C 0.55 0.65

D 0.60 0.70

10) Agricultural - Pasture A 0.10 0.18

B 0.14 0.22

C 0.18 0.26

D 0.22 0.30

11) Agricultural - Groves A 0.20 0.26

B 0.23 0.29

C 0.26 0.32

D 0.29 0.33

12) Agricultural - Feedlots A 0.35 0.45

B 0.40 0.50

C 0.45 0.55

D 0.50 0.60

3

### Seasonal Land Use-Specific

Runoff Coefficients

Coastal Land Use Classification and

Land Use Type Hydrologic

Soil

Group Dry

Season

Runoff

Coefficient Wet

Season

Runoff

Coefficient

13) Agricultural - Nursery A 0.20 0.30

B 0.25 0.35

C 0.30 0.40

D 0.35 0.45

14) Agricultural - Row and Field Crops A 0.20 0.30

B 0.25 0.35

C 0.30 0.40

D 0.35 0.45

15) Upland Forested A 0.10 0.15

B 0.13 0.18

C 0.16 0.21

D 0.19 0.24

16) Freshwater - Open Water A 0.80 0.90

B 0.80 0.90

C 0.80 0.90

D 0.80 0.90

17) Saltwater - Open Water A 1.0 1.0

B 1.0 1.0

C 1.0 1.0

D 1.0 1.0

18) Forested Freshwater Wetlands A 0.50 .60

B 0.55 0.65

C 0.60 0.70

D 0.65 0.75

4

### Seasonal Land Use-Specific

Runoff Coefficients

Coastal Land Use Classification and

Land Use Type Hydrologic

Soil

Group Dry

Season

Runoff

Coefficient Wet

Season

Runoff

Coefficient

19) Saltwater Wetlands A 0.95 0.95

B 0.95 0.95

C 0.95 0.95

D 0.95 0.95

20) Non-forested Freshwater Wetlands A 0.45 0.55

B 0.50 0.60

C 0.55 0.65

D 0.60 0.70

21) Tidal Flats A 1.0 1.0

B 1.0 1.0

C 1.0 1.0

D 1.0 1.0

5

# APPENDIX 4

LAND USE-SPECIFIC RUNOFF WATER QUALITY CONCENTRATIONS

### Land Use-Specific Nonpoint Source Water Quality Concentrations

URBAN LAND USES

Land Use Classification Land Use-Specific Water Quality

Concentrations

Coastal

Land Use

Classification Land Use

Description Reference TN

(mg/L) TP

(mg/L) TSS

(mg/L) BOD

(mg/L)

1

(LDR) Low Density

Single Family

Residential

(SFR) (1)

(1)

(1)

(1)

(1)

(1)

(4)

(8)

(9)

(10)

(11)

(13) 2.31

2.14

0.605

1.18

3.0

2.2

1.87

1.46

1.56

2.04

2.88

- 0.40

0.32

0.073

0.307

0.45

0.25

0.39

0.401

0.27

0.593

0.72

- 33.0

28.0

7.2

3.5

-

-

-

19.0

20.8

49.7

56.8

- -

-

-

-

-

-

-

-

-

-

-

4.4

min

mean

max 0.605

1.93

2.88 0.073

0.380

0.598 3.5

27.3

56.8 -

4.4

-

2

(MDR) Medium

Density

(See notes) mean 2.04 0.44 33.5 -

7.4

-

3

(HDR) Multifamily

Residential (1)

(1)

(1)

(1)

(1)

(1)

(4)

(8)

(9)

(10)

(11)

(13) 1.61

2.57

4.68

1.91

1.02

1.91

1.65

2.05

2.04

2.05

2.00

- 0.33

0.45

0.72

0.73

0.033

0.51

0.33

1.34

0.282

0.150

0.56

- 53.0

36.8

95.6

-

67.6

14.3

-

29.0

10.7

8.3

41

- -

-

-

-

-

-

-

-

-

-

-

11.0

min

mean

max 1.02

2.14

4.68 0.033

0.49

1.34 8.3

39.6

95.6 -

11.0

-

### Coastal

Land Use

Classification Land Use

Description Reference TN

(mg/L) TP

(mg/L) TSS

(mg/L) BOD

(mg/L)

4 Low Intensity

Commercial

High Intensity

Commercial

Commercial

(Office)

Commercial

(Retail) (1)

(1)

(1)

(1)

(1)

(8)

(9)

(10)

(11)

(8)

(10)

(11) 1.19

1.10

2.81

3.53

2.15

2.38

1.08

1.40

1.05

1.69

1.28

2.12 0.15

0.10

0.31

0.82

0.15

0.305

0.495

0.113

0.145

0.253

0.177

0.22 22.0

45.0

94.3

-

-

36.5

50.6

6.2

13.8

9.3

14.5

36.3 -

-

-

-

-

-

-

-

-

-

-

-

Combined

Commercial min

mean

max 1.05

1.82

3.53 0.100

0.270

0.495 6.2

32.9

94.3 -

17.2

-

5 Industrial (1)

(1)

(4)

(8)

(9)

(10)

(11)

(13) 1.42

1.42

1.18

2.28

1.77

1.92

3.00

- 0.19

0.31

0.15

0.332

0.465

0.490

0.503

- 71.8

102.0

-

18.2

28.3

84.3

70.0

- -

-

-

-

-

-

-

9.6

6 Mining (4)

(13) 1.18

- 0.15

- 35 (e)

- -

9.6

7 Institutional (4)

(13) 1.18

- 0.15

- 35 (e)

- -

8.2

### AGRICULTURAL LAND USES

Land Use

Classification Land Use-Specific

Water Quality Concentrations

Coastal

Land Use

Classification Land Use

Description Reference TN

(mg/L) TP

(mg/L) TSS

(mg/L) BOD

(mg/L)

10 Pasture (1)

(1)

(2)

(3)

(4)

(5)

(13) 2.37

2.48

2.0

3.0

1.02

5.1

- 0.697

0.27

0.3

0.25

0.16

3.2

- -

8.6

-

-

-

-

- -

-

-

-

-

-

5.1

11 Grove (7)

(13) 2.31

- 0.10

- -

- -

2.55

11,13 Grove,

Nursery (4)

(13) 0.92

- 0.41

- -

- -

2.55

12 Feed Lot (3)

(3)

(5)

(13) 29.3

3.74

26.0

- 5.1

1.13

5.1

- -

-

-

- -

-

-

5.1

14 Field Crop (2)

(3)

(4)

(13) 2.5

2.5

3.75

- 0.25

2.5

1.13

- -

-

-

- -

-

-

5.1

Mixed Agricultural

10,11 Citrus+

Pasture (1)

(1)

(1)

(1)

(1) 1.57

1.33

2.58

2.68

3.26 0.09

0.09

0.046

0.562

0.24 -

4.6

180

-

28.0 -

-

-

-

-

11,14 Citrus+ Row

Crops (6) 1.78 0.3 5.6

-

(See following page for summarized agri cultural water quality concentrations.)

### SUMMARIZED AGRICULTURAL LAND USE DATA

Land Use

Classification Land Use-Specific

Water Quality Concentrations

Coastal

Land Use

Classification Land Use

Description Reference TN

(mg/L) TP

(mg/L) TSS

(mg/L) BOD

(mg/L)

8 Range min

mean

max 0.90

1.24

1.47 0.02

0.01

0.21 4.8

11.0

17.3 -

1.45

-

10 Pasture min

mean

max 1.0

2.66

5.1 0.16

0.81

3.2 8.6

8.6

8.6 -

5.1

-

11 Grove min

mean

max 0.92

1.67

2.31 0.10

0.27

0.41 5.0

5.3

5.6 -

2.55

-

12 Feed Lot min

mean

max 3.74

19.7

29.3 1.13

3.8

5.1 50(e) -

5.1

-

13 Nursery

(See notes) mean 1.67(e) 0.27(e) 5.3(e) 2.55

14 Row Crop

(See notes) mean 2.91 0.54 10 5.1

### WATER/WETLAND AND FOREST/UNDEVELOPED LAND USES

Land Use

Classification Land Use-Specific

Water Quality Concentrations

Coastal

Land Use

Classification Land Use

Description Reference TN

(mg/L) TP

(mg/L) TSS

(mg/L) BOD

(mg/L)

8 Open Space/

Non-forested (1)

(1)

(1)

(4)

(13) 1.38

0.90

1.47

1.02

- 0.07

0.02

0.07

0.16

- 17.3

4.8

-

-

- -

-

-

-

1.45

15 Upland Forest (2)

(3)

(4)

(13) 0.1

0.2

1.02

- 0.007

0.007

0.16

- -

-

-

- -

-

-

1.45

16,17 Open Water (1)

(1)

(1)

(13) 0.79

0.73

2.22

- 0.17

0.04

-

- -

0.00

6.2

- -

-

-

0.00

18,20 Freshwater

Wetland (1)

(1)

(1)

(1)

(4)

(13) 2.26

1.02

1.24

1.88

0.79

- 0.09

0.16

0.018

0.33

0.17

- 13.4

-

4.6

12.7

-

- -

-

-

-

-

4.63

17 Saltwater NA NA NA NA

19 Saltwater

Wetlands NA NA NA NA

21 Tidal Flats NA NA NA NA

### Notes: • Concentrations for CLUCCS code 2 (MDR) are an average of CLUCCS codes

1 (LDR) and 3 (HDR).

• Concentrations for CLUCCS code 4 (Commercial) are an average of reported

values for "low intensity" and "high intensity" commercial.

• Estimated (e) agricultural values were based on similar land uses data when

no land use specific data were identified.

• Row crop data were often reported with other agricultural uses.

• Saltwater and saltwater wetlands were assigned zero loads.

### References

(1) Harper, H.H. 1991. Estimation of Loading Rate Parameters for Tampa Bay Watershed.

Southwest Florida Water Management District. Brooksville, Florida.

(2) Delwiche, Lora L.D. and D.A. Haith. 1983. Loading Functions for Predicting Nutrient

Losses from Complex Watersheds. Water Resources Bulletin vol. 19, no. 6. p. 951-959.

(3) Haith, D. A. and L.L. Shoemaker. 1987. Generalized Watershed Loading Function for

Stream Flow Nutrients. Water Resour ces Bulletin. vol. 23, no. 3. p. 471-477.

(4) Camp, Dresser, & McKee. 1992. Point/Non-Poi nt Source Loading Assessment for Sarasota

Bay. SBNEP, Sarasota, Florida.

(5) Andrews, W.J. 1992. Reconnaissance of Wa ter Quality at Nine Dairy Farms in North

Florida, 1990-1991. USGS WRI 92- 4058. Tallahassee, Florida.

(6) Flannery, M.S. et al. 1991. Increased Nu trient Loading and Baseflow Supplementation in

the Little Manatee Watershed. in: Treat, F.S. and P.A. Clark (eds.) Proceedings, Tampa Bay

Area Scientific Information Symposium 2. 1991 Feb ruary 27-March 1. Tampa, Florida. p.

369-396.

(7) Allhands, M. 1993. Water Quality Data for Gator Slough Groves. Agricultural

Management Services. Punta Gorda, Florida.

(8) Hillsborough County Engineering Services. 1993. NPDES Part 2 Application. Tampa, FL.

(9) City of Tampa Stormwater Management Divi sion. 1994. NPDES Part 2 Application.

Tampa, FL.

(10) Pinellas County Department of Envir onmental Management. 1993. NPDES Part 2

Application. Clearwater, FL.

(11) City of St. Petersburg Engineering Depart ment. 1993. NPDES Part 2 Application. St.

Petersburg, FL.

(12) Carr, D.W. and B.T. Rushton. 1995. Integrating a Native Herbaceous Wetland into

Stormwater Management. Southwest Florid a Water Management District Stormwater

Research Program. Brooksville, FL.

(13) Harper, H.H. 1994. Stormwater Loading Ra te Parameters for Central and South Florida.

Environmental Research & Design, Inc. Orlando, FL.

# APPENDIX 5

EXISTING AND PROJECTED FUTURE LAND USE ACREAGES, FROM PREVIOUS STUDY

(ZARBOCK ET AL., 1996A) AND UPDATEDPrevious Analysis - Tampa Bay Watershed,1990 Land Use (Acres) bySegment and BasinBaySegmentBasinSingleFamilyRes.MediumDensityHighDensityRes.Comm.Indust.MiningInst.Trans.UtilityRangeBarrenLandPastureGroveFeedlotNurseryRowCropsUplandForestFreshWaterForestWetl.SaltWetl.Non-forest.FreshWetl.TotalOTB023066477301647320585061719445412821179249037034015237380122100230700020502989500739215634885468260268051201202492927444809070628779023073591844203126915055203324853094127301080296119585451072223237206-144922158468553685143983497291572205316016506459277958404933100082841LTARPON862989357154051752264412601208624142005014011063HB0230070040923015110419783792425058011158597293421225161480050918417023010004541584045761779829171187147554716220820224701264475194354747621802153292399023013001570004155911012142057343202000261546954370618360700230150039531472442352374130661934603571647955772352791537662014309468018579516502301695467140055711300140581329196060225157257017344660230175041118639871073207101638488292212213870560362121021493230230300010246926036861971151227032426211383364616443517563767241519629052422226711154685023033301189248022068150666162713551490252331261480118998431489671297531540615610067502304500687781785227278566929043742555260828662384612121460817975527631985010003153250204-219056161467413623835953973941237465229910562106401109459083114047051205-210049610588331815227158991820200303743734305618059206-2208619487799425220361560606262031213652013313311511241741855682112778048790TBYPASS22551629142616165871741231227515418105301236401006742999047117092MTB02300500816274851120229318514411463545994433412355869428431110104032109592002300530038941155001671047048200541236032161102244763203-31876134293435211313096356063781193371361984899476610554614742160540758206-3C061430026775220000051468151724104221206-3E1181178642191261238924218354756767611826249365551688316913620549206-3W82125612966234763702009183560004408368575107479724229LTB206-480979449316667448152823262126253724101706476696352915191931720283BCB206-529308125190005669471000001711014253504041207-5987219124933495421361635693417531843301622714118558449609647062TCB206-6600379107328839030175601094409010627432130516603376790MR02299950000001120127161060979027310052967021611710355241844202-748152909821320958822132584116759122644515673950299841101817181132916723706101945EVERSRES479221119830012455486426198194322017305773511104284312200135067LMANATEE2050000013210156521008125538030458854144617390225640527TOTAL642666526211925337283151601017545044118600847582832986407452024263404331413714430614512019030502891441571FreshRes.25426652766PreviousAnalysis- Tampa Bay Watershed FutureConditions(circa 2010), Land Use (Acres) by MajorBasinBaySegmentBasinSingleFamilyRes.MediumDensityRes.HighDensityRes.CommIndust.MiningInst.Trans.UtilityRangeBarrenLandPastureGroveFeedlotNurseryRowCropsUplandForestFreshWaterForestFreshWetl.SaltWetl.Non-forest.Fresh.Wetl.Total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pdated Analysis- Tampa Bay Watershed FutureConditions(circa 2010), Land Use (Acres) by MajorBasinBaySegmentBasinSingleFamilyRes.Med.DensityRes.HighDensityRes.Comm.Indust.MiningInst.Trans.UtilityRangeBarrenLandPastureGroveFeedlotNurseryRowCropUplandForestFreshWaterOpenSaltwaterForestFreshWetl.SaltWetl.Non-forest.Fresh.Wetl.TidalFlatTotalOTB0230664720833600976711104587639045109016030014920734014201220902307000193738616064470101121198359002021694099066429160445307262880402307359232226633741907722522780309312190122027732066052780726023235206-12735490623247772239752171072372814618252910109051982992465125631517912218270138082LTARPON92416833267443205631010085200705672982019600198013712HB0230070065642728816335141427191512342712435173476921246230143805610184260230100058717581590118810172930142491701101135851711618776551230500193508642902301300315310130188628383805112281073214819896130477604450360740230150051832047175436288414946693255237146916134178942569562921550850301480095215023016955101800903130001611780847901001761480220079044780230175043921151638138327090682574421250100398420010902690230300012851107875260268118242737316718300425505117343142682963023289066450154712023033301479263012576210376667217081031417523811451815477927878798324901551005911010492602304500106411361878294238848557587214797146242315360732556151789059850308684299190153782204-224677127115550392296697267310112816672853091105977713425114324891151247780205-21195051113836091611015812720022020124650562044518310206-22405205890274512232711816266467767860592871215817143382343198508101329897421673608TBYPASS242117501622179063317013071875916884566756139491151010430492017492MTB023005001368448130185368169320100056229180101433528210906811945050936002708179597902300530435211311820017489105210022872763460642021504762203-322911536119336412520014353673125775346540200583611511391452279815444940259206-3C050026668615000049484604831438132040976893333911192611661549121713500374981651173197901620118414463647247108523279206-3W73189145832445668019991536200044066491222195247937951927250LTB206-41199451135118414045019931583172392366710188420685709599962664227141587781661BCB206-53833164297005948922200000174991143132638036816059207-585813212780152552287735641865301545008381670912340866010430956213TCB206-6732526144537146037134010737443010984201383855361786494710793MR022999500000013372751557007453386200205864521510257702115041849202-78502577614551344311922203540620359164145278361341112187099181176161038317123917217109853EVERSRES921155227521780150097656823573813830532456202142302782122417037446LMANATEE5891905000211969401014134190206637424716310238001492040530TOTAL8413883584146477453991738311126457576138336177523521464256226839515886512374251646157296154193187704816375861636472672021026961091132091299846570270206-3E 26454Updated Analysis - Tampa Bay Watershed,1995 Land Use (Acres) bySegment and BasinBaySegmentBasinSingleFamilyRes.MedDensityRes.HighDensityRes.CommIndust.MiningInst.Trans.UtilityRangeBarrenLandPastureGroveFeedlotNurseryRowCropsUplandForestFreshWaterOpenSaltwaterForestFreshWetl.SaltWetl.Non-forest.Fresh.Wetl.TidalFlatTotalOTB0230664774619843000929697104534104006415602703341658073402030122090230700021523677505344791124025023777710124078129160445307260288040230735920192048250127716125900343713540136030812066052780726023235206-12604446022140702037862171021390229121473240136061162992465125631517912218270138082LTARPON840153029704032046915000121200707092982019600198013712HB023007004182722621092294356212812370712435173476922366230143805610184260230100055927220536113296929301200244731701147835851711620866551230506961019350864280230130017817070190544783805112281073214861304776044503607402301500471218611753632404234160833562371499658411782446562921550850300952150230169542515007041090016144502799901002201480220015804477023017503661922109213172506971324773625001005680009113023030001070989894384152022812639203342046250511791234399815085296302328906645015471202303330118345041206116836136721366114601752560953151939743484977532490155100591101049260230450070949078559230277075074517191211833230859551212556151789059850308684299190153783204-2205661971050457722965812970101197270235630911051029213425114324891151247779205-21114721060633731511015819070022020309650562044518310206-22291187182064297211511815967577284863263191516419045662343198508101329897421673609TBYPASS230515911544170560317011892083171875507133621510061151010430492017492MTB0230050091229986124224085200111176230883101433528212118902245050936002708179597902300530274910281660015895405490023193063460642021504762203-3208310853311142009444591126417385040200517411511391452279815444942378206-3C005002666150000494846048314381320409768933206-3E20025784819812611749221544044119075146949620118414463647247108523279206-3W721851429723976550199918532000440699912221952479351927250LTB206-49513581461114501581200617299036671018842076170959996227141587781662BCB206-53732159494005719592200000183991143132638036816059207-582512702673150532199735113109301564077010481670912340866010430956213TCB206-658141811472944202945611011344920109104671383855361786494710793MR022999500000013371361570807453386200205864521510257702115041849202-750013398856022969172202950827084236106598722487131987887181176161038317123917217109853EVERSRES5767761720990136481363433582013830536056892142302782122417037446LMANATEE3931204200141989101031131090206637447016310238001492040529Total681116818212782039867157331071525117216038020612647706746328844433640711319425181222417415419318770483032007916933711198019899414804201092692234139664842786033667910722664