#S

#S #S

#S

#S

#S

#S

#S

#S

#S

#S #S #S

#S

#S #S #S #S

#S #S #S#S

#S

#S#S

#S

#S

#S

#S#S

#S #S #S

#S

#S

#S

#S#S

#S

#S

#Y

#Y

#Y #Y

#Y

#Y

LS20 (1276)

LS19 (1253)

LS13 (1351)

LS14 (1412)

LS04 (1417)

LS22 (1460)

LS05 (1411)

LS17 (1475)

LS10 (1496)

LS06 (1535)

LS02 (1466)

LS32 (1542)

BOG 2-7 (1534)

LS26 (1470)

LS25 (1511)

LS12 (1543)

BOG 2-1 (1554)

BOG 6-4 (1559)

LS08 (1573)

LS11 (1613)

LS15 (1556)

LS29 (7862)

LS28 (7861)

LS27 (7860)

LS16 (1625)

LS03 (1656)

LS23 (1550)

LS09 (1557)

BOG 2-2 (1561)

BOG 2-3 (1568)

BOG 6-1 (1640)

LS21 (1569)

BOG 6-3 (1584)

BOG 2-4 (1595)

BOG 4-1 (1599)

BOG 2-6 (1614)

BOG 2-5 (1608)

LS07 (1609)

LS24 (1590)

Lake

 Munson

/(319

Springhill Rd.

Lake Bradford Rd.

Capital Circle SW

Lake

 Bradford

TALLAHASSEE REGIONAL

 AIRPORT

Capital Circle SW

SF04 (7831)

SF05 (7832)

SF06 (7833)

SF01 (1512)

SF03 (1663)

SF02 (1685)

#S Southwest Monitor Well Sites

N

0 0.5 1

Miles

1999 Imagery (DOQQ's)

SOUTHWEST SPRAYFIELD AND RESIDUAL DISPOSAL AREA MONITOR WELL LOCATIONS

#Y Residuals Area Monitor Well Sites

01-06-025

FIGURE 49
 84

Figure 50. Southwest Sprayfield Monitor Well Nitrate Concentrations (as N, mg/L). 

LS21 (1569)

0

1

2

3

4

5

6

19741976197819801982198419861988199019921994199619982000

LS25 (1511)

0

2

4

6

8

10

12

14

1975197719791981198319851987198919911993199519971999

LS32 (1542)

0

2

4

6

8

10

12

14

16

1972197519781981198419871990199319961999
 85

Figure 51. Residual Disposal Area Monitor Well NO2+NO3-N Concentrations (mg/L). 

SF06 (7833)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

199219931994199519961997199819992000

SF05 (7832)

0

0.2

0.4

0.6

0.8

1

1.2

1.4

199219931994199519961997199819992000

SF04 (7831)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

199419951995199619961997199719981998199919992000

SF03 (1663)

0

1

2

3

4

5

6

197919811983198519871989199119931995

SF01 (1512)

0

5

10

15

20

19791981198319851987198919911993199519971999
 86

percentage of the total WWTF flow that they represent, no attempt was made to estimate the 

residual nitrogen loading from facilities other than the City of Tallahassee. 

Table 7. Estimated 1999 Nitrogen Loading from WWTF Residuals. 

Area Residuals (kg-N/Yr) 

Leon Semi-confined 0 

Leon Unconfined 78,000 

Wakulla Unconfined 99,000 
 87

On-Site Disposal Systems

OSDS include septic tanks, cesspits and other non-sewered disposal of domestic wastewater. 

One of the objectives of this study was to estimate the current number of OSDS in Leon and 

Wakulla counties and to quantify the role of these systems in the nitrogen budget of the study 

area. While the City of Tallahassee is fully sewered, much of surrounding Leon County is not. 

Virtually none of Wakulla County is sewered, the exceptions being St. Marks, Panacea and 

Crawfordville. St. Marks and Panacea have been sewered since the late 1980s. Crawfordville 

recently made use of grant funds to sewer their main commercial/industrial area. Residential 

hook-ups to the Crawfordville system are made on voluntary basis. 

According to U.S. Census Bureau data, the population in Leon County grew by 24 percent 

between 1990 and 2000, from 192,493 to 239,452 (Figure 52). During the same period, the 

population in Wakulla County increased by 61 percent, from 14,202 to 22,863. The 1990 

Census provides the number of OSDS operating in each county but the 2000 OSDS census 

figures were not available in time to assist with this project. However, using population, per 

capita and OSDS data from 1990 and population and per capita data from 2000, an estimate of 

the number of OSDS in both counties in 2000 was made. 

According to the 1990 Census, Leon County had 22,090 active OSDS and a household 

occupancy rate of 2.42 persons. Wakulla County had 5,645 OSDS and a household occupancy 

rate of 2.71. These numbers were multiplied together to estimate the number of persons using 

an OSDS in each county in 1990. In Leon County the estimated 1990 population dependent on 

an OSDS was 53,460. The 1990 OSDS population estimate for Wakulla County was 15,300. 

These estimates were then compared to the 1990 total population of each county to determine 

the percentage of the population reliant on an OSDS. These percentages were applied to the 

2000 census population data and the results were divided by the 2000 census occupancy rates 

(2.34 in Leon County and 2.57 in Wakulla County). Based on this approach, during 2000 an 

estimated 28,417 OSDS were in use in Leon County and 8,896 were in use in Wakulla County. 

In order to get the required sense of the spatial distribution of OSDS; a second estimation 

technique was employed. This approach was based on tax roll parcel data. It was presumed 

that all parcels with improvements (valued at $400 or greater) required the disposal of sewage. 

For Leon County, two GIS coverages were obtained from the City of Tallahassee/Leon County 

Geographic Information Systems department. The first was a map coverage showing both 

parcels with improvements (valued at $400 or greater) and parcels codes institutional. The 

second was a point coverage of geo-coded City of Tallahassee sewer billing addresses. The 

geo-coded billing addresses were intersected with the parcel coverage. All parcels with a City 

of Tallahassee sewer billing address were presumed not to have an OSDS. A scattering of 

parcels without a geo-coded billing address remained within the city limits. These were 

presumed to be sewered and were excluded. This process yielded a total of 27,404 parcels in 

Leon County that are potential OSDS sites. Of these an estimated 3,100 are known to be 

served by the sewer services of Talquin Electric Cooperative (TEC). TEC operates three 

WWTF serving Killearn Lakes, neighborhoods on the southwest side of Lake Jackson and 

Fallschase. Deletion of households served by TEC yields an estimate of 24,304 OSDS in Leon 

County (as of 1999) by the parcel-counting technique. 

In Wakulla County, a different approach was required. 1999 tax data were obtained from the 

Florida Department of Revenue. Hardcopy plat maps were obtained from the Wakulla County 

Property Appraiser’s Office. In 1999 there were a total of 8,267 improved parcels in Wakulla 

County. Of these, only those in the study area were of interest. Using 1994 digital orthoquads 
 88

Figure 52. Population Increase in Leon and Wakulla Counties since 1900. 

1910 1920 1930 1940 1950 1960 1970 1980 1990 2000

Date

LeonWakulla
 89

as a base map, the locations of all improved parcels in the study area were manually georeferenced using parcel identification numbers and hardcopy plat maps. The result was point 

coverage of all improved parcels in the study area (6,632 parcels). Of these, 119 were served 

by a WWTF. The remaining 6,513 parcels were presumed to have an OSDS. The number of 

improved parcels outside the study area was 1,635. 

Because the OSDS were given a geographic location, it was possible to disaggregate them 

according to whether they overlay semi-confined, unconfined or confined portions of the 

Floridan Aquifer (Figure 53). Leon County was divided into three areas according to the relative 

permeability of the sediments overlying the Floridan Aquifer. The eastern portion of the county 

(north of the Cody Scarp) is considered to be under conditions of semi-confinement of the 

Floridan Aquifer. Southeast Leon County (south of the Cody Scarp) is considered to be under 

unconfined conditions. Southwest Leon County is considered to be under confined conditions. 

Based on the delineations found in Figure 53: 17,498 OSDS in Leon County lie in the semiconfined area; 4,290 OSDS lie in the unconfined area; 2,516 OSDS lie in the confined area of 

the county (total of 24,304). Wakulla County was divided into either unconfined or confined 

areas (Figure 1). Within the study area in Wakulla County, 6,429 OSDS lie in the unconfined 

area and 84 lie in the confined area (total of 6,513). 

Sarac et al. (2001) examined the behavior of 20 OSDS at a study site in New South Wales, 

Australia. Based on sampling data from six systems, they calculated annual per capita TN 

generation rates “at the outlet of the septic tank” averaging 4.0 kg-N/year per capita. They also 

cite Griffiths (1997) as giving annual TN loading rates ranging between 4.2 and 5.5 kg-N/year 

per capita. 

Horsley and Witten (2000), citing six papers, give a range of total nitrogen concentrations in 

OSDS effluent of between 23 mg/L and 40 mg/L. They define “in effluent” based on samples 

taken “from the leaching area or from ground water immediately below the leaching area”. 

Based on a wastewater flow rate of 208 l/d per capita (55 gal/d per capita) and an average 

effluent total nitrogen concentration of 35 mg/L, they estimated an OSDS effluent load of 7 gmN/d per capita (2.6 kg/N/year per capita). Based on a comparison of estimated nitrogen inputs 

and observed ground water concentrations at six sites (containing 55 residential lots and 34 

OSDS), they estimated a 45 percent to 98 percent attenuation of nitrogen contributed to their 

study area. Ninety-three percent of the total nitrogen load was estimated to come from the 34 

OSDS in their study area. 

Otis et al. (1993) give a literature-based range of TN concentrations in OSDS influent of 

between 35 mg/L and 100 mg/L. Based on a wastewater flow rate of 170 l/d per capita (45 

gal/d per capita), these concentrations yield OSDS influent load estimates of between 6 and 17 

gm-N/d per capita. These equate to annual loads ranging between 2.2 kg-N/year per capita and 

6.2 kg-N/year per capita. Otis et al. cite others to observe that OSDS effluent can undergo 

denitrification in soils beneath the drain field that removes up to 20 percent of the effluent 

nitrogen. They also observe that fine-grained and/or organic rich soils facilitate denitrification. 

Based on Otis et al. (1993), Katz et al. (1999) used 4.09 kg-N/year per capita to estimate 

nitrogen loads emanating from OSDS within the Suwannee River Basin. The midpoint of the 

Otis et al. range (4.2 kg-N/year per capita) is used below to estimate OSDS loads in Leon and 

Wakulla counties (Table 8). 
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 Springs

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WAKULLA CO.

Lake 

Munson

TAYLOR

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JEFFERSON CO.

LOCATION OF OSDS IN SEMI-CONFINED AND UNCONFINED PORTIONS

 OF LEON AND WAKULLA COUNTIES

N

U.S. Highways

State/County Roads

Major Lakes

Rivers

OSDS Locations (X

Incorporated Areas

Public Lands

Floridan Aquifer Semi-Confined

Floridan Aquifer Unconfined

Miles

0 5 10

FIGURE 53

01-06-026
 91

Table 8. Estimated 1999 Nitrogen Loads from OSDS. 

Area # OSDS Household occupancy Kg-N/cap/yr Kg-N/Yr 

Leon Semi-confined 17,498 2.34 4.2 172,000 

Leon Unconfined 4,290 2.34 4.2 42,000 

Wakulla Unconfined 6,429 2.57 4.2 69,000 

Annual OSDS TN load estimates (Figure 45) were prepared by linearly interpolating between 

the 1970 census OSDS count, the 1980 census OSDS count and the 1999 OSDS parcel-based 

count described above. The 1970 and 1980 OSDS counts represent the number of OSDS in 

the entirety of Leon and Wakulla counties whereas the 1999 OSDS number is only for the semiconfined and unconfined portions of each county. The number of persons per household was 

acquired from the census for years 1970, 1980, 1990 and 1999. All other years were 

interpolated from these. The number of OSDS multiplied by the number of persons per 

household yields the population utilizing OSDS. Multiplying the population times the per capita 

load gives the total load for each year. 
 92

 Commercial Fertilizer Application

Commercial fertilizers represent a significant source of inorganic nitrogen (IN) in the study area. 

Department of Commerce (DoC) Census of Agriculture (CoA) census data for fertilized acres 

and for harvested acres show a growth of agriculture in Leon and Wakulla counties from the 

early 1900s to a peak in the early to mid-1980s. The United States Department of Agriculture 

(USDA), the DoC CoA, and the Florida Department of Agriculture and Consumer Services 

(DACS) maintain records of fertilizer sales and distributions within the state. USDA records, 

covering the period 1945 through 1973, provide annual statewide total fertilizer distributions, as 

nitrogen in tons. CoA data for 1964, 1969, 1974, 1978, 1982, 1987, 1992, 1997 provide 

fertilizer expenditures on a county-by-county and statewide basis. DACS records, from 1974 

through 1999, give statewide total fertilizer distributions on a county-by-county basis. Annual 

TN load estimates based on these data are given in Figure 45. 

With no by-county fertilizer sales data prior to 1974, countywide loads were estimated using the 

same method as Battaglin and Goolsby (1994). State tonnages of total N for each year were 

obtained from the USDA and converted to kg/yr. These data were then multiplied by the ratio of 

county expenditures to state expenditures. For example, in 1964 the Leon County expenditure 

for nitrogen fertilizer was $314,648 and the Wakulla County expenditure was $22,967. Dividing 

these numbers by the statewide expenditure of $84,570,575 yields county/state ratios of 3.72 

X10-3 for Leon County and 2.72x10-4 for Wakulla County. Multiplying the USDS statewide 

nitrogen total (117,729,907 kg-N) by these ratios results in an approximate application of 

438,073 kg-N in Leon County and 32,022 kg-N in Wakulla County in 1964. For the years 1945 

to 1964, the 1964 expenditure ratios were used. From 1965 to 1973, the 1969 county/state 

expenditure ratios of 3.85x10-3 for Leon County and 2.73x10-4 for Wakulla County were used. 

More recent data, from 1974 to present, are derived from reported county tonnages for different 

types of fertilizer, as reported by fertilizer distributors to DACS. Multi-nutrient fertilizer tonnages 

were multiplied by the percent nitrogen in each to estimate total N. Assumptions were required 

regarding the percent nitrogen in: liquid fertilizers, nitrogen solutions, and miscellaneous 

formulations (20 percent each); urea (46 percent); and ammonium nitrate, anhydrous ammonia 

and ammonium Poly-P (32 percent each) (Bill Cox, DACS, personal communication, 2000). 

The resulting nitrogen tonnages were subsequently converted to kg/yr. 

Both the USDA and DACS numbers are reported distribution amounts from fertilizer 

distributors/manufacturers and are reported by fertilizer years (July 1 to June 30). The numbers 

do not account for fertilizer sold in one county and used in another. They assume that fertilizer 

distributed to a particular county is used in that county. There is also no differentiation between 

fertilizer used for agriculture purposes and that used for lawn, golf course, recreation area, or 

other purposes. It is assumed that the predominant use is agricultural in nature. However, to 

the extent that large, non-farm retailers purchase fertilizer through distributors reporting to 

DACS, these figures capture fertilizer sold for application in residential settings. It is believed 

that most of the fertilizer destined for residential application is included in the DACS data. 

DACS data for the 1992, 1994, and 1996 fertilizer years were incomplete and no values are 

provided for those years. 

To apportion the nitrogen fertilizer application between the unconfined and semi-confined 

portions of the study area, GIS land-use maps were used to calculate the total area of “pasture 

and cropland” land use within each county. Land use data were as of 1994-1995. The total 

area in “pasture and cropland” was further disaggregated into what lies within the semiconfined, unconfined and confined portions of the two counties. Leon County had a total of 
 93

14,272 ha of “pasture and cropland”, with 13,002 ha (91 percent) lying in the semi-confined area 

and 1,071 ha (7.5 percent) in the unconfined area. The remainder (199 ha or 1.5 percent) lies 

in the confined portion of the county. The attribution of most of the county’s pasture and 

cultivable land to the semi-confined area is consistent with the disparity in soil suitability for 

agriculture between unconfined and semi-confined areas. These areal weightings were 

subsequently applied to the 1999 DACS countywide nitrogen application of 197,000 kg-N. This 

approach resulted in an estimated 179,000 kg-N having been applied to the semi-confined 

portion of Leon County and 15,000 kg-N in the unconfined portion of the county in 2000. 

This disaggregation of commercial fertilizer use between semi-confined and unconfined 

underestimates the actual application to the unconfined area, as based on fertilizer application 

data for the SESF (provided by the City of Tallahassee). According to the “pasture and 

cropland” land use data available for the unconfined portion of Leon County, SESF is the only 

such land use. City of Tallahassee records indicate a 1999 nitrogen application of 44,000 kg-N 

to 691 ha at their facility. Since SESF is the only area designated “pasture and cropland” in the 

unconfined portion of the Leon County, the nitrogen application to SESF is assumed to 

represent the entirety of commercial fertilizer applied to this area (Table 9). Inherent in this 

approach is the assumption that there is no other significant fertilizer application in the 

unconfined portion of Leon County. The application to the semi-confined portion of Leon 

County was estimated at 150,000 kg-N. This is the result of 194,000 kg-N (98.5 percent of the 

countywide total) less that previously attributed to the unconfined portion of the county (44,000 

kg-N). 

2,294 ha (82 percent) of Wakulla County’s total 2,787 ha of “pasture and cropland” lie within the 

unconfined portion of the county. The estimated nitrogen application to this area was 18,000 

kg-N (82 percent) of the county total 1999 application of 22,000 kg-N. 

Table 9. Estimated 1999 Nitrogen (IN) Loads from Commercial Fertilizer. 

Area Kg-N/Yr 

Leon Semi-confined 150,000 

Leon Unconfined 44,000 

Wakulla Unconfined 18,000 
 94

Livestock

Animal waste is a source of organic nitrogen (ON). In other areas of the state, elevated levels 

of nitrogen in ground water have been seen beneath concentrated animal populations such as 

dairies, feed lots and chicken sheds. To estimate the total nitrogen load from this source, CoA 

livestock population data were multiplied by the estimated nitrogen mass discharged in waste 

for each type of livestock. Annual total ON load estimates based on these data are given in 

Figure 45. 

Due to the small number of livestock operations in Leon and Wakulla counties, CoA withheld 

data for many years to avoid disclosure of information for individual farms. The most recently 

available data were used to provide estimates of “current” N loads from this source. This means 

that, in Leon County, 1992 data were used to estimate current populations of beef cattle, 1992 

data for dairy cattle, 1987 data for broiler chickens, 1997 data for layer chickens, and 1997 data 

for swine. In Wakulla County, 1987 data were used to estimate populations of beef cattle, 1982 

data for dairy cattle, 1992 data for broiler chickens, 1992 data for layer chickens, and 1997 data 

for swine. Empirically, this approach probably overestimates “current” N loads from this source, 

given land use changes that have occurred in Leon and Wakulla counties since these 

population data were collected. Uncertainty in estimates based on these data is an unavoidable 

consequence of the limitations associated with these data. 

Based on 454 kg (1,000 pounds) of each type of animal, the following daily nitrogen discharges 

were estimated (American Society of Agricultural Engineers, 1996): (1) dairy cattle—0.18 kgN/day; (2) beef cattle and broiler chickens—0.5 kg/N/day; (3) egg-laying chickens—0.38 kgN/day; (4) swine—0.24 kg-N/day. The following average animal masses, in kg, were also 

assumed: (1) dairy cattle—635 kg; (2) beef cattle—364 kg; (3) broiler chickens—0.9 kg; (4) egglaying chickens—1.4 kg; (5) swine—61 kg (American Society of Agricultural Engineers, 1996). 

Combining numbers of animals, average animal mass and N yield per unit animal mass, annual 

total N loads from this source were estimated. 

Using land use mapping and GIS techniques described previously, the countywide total “pasture 

and cropland” acreage in each county was disaggregated into those portions lying within the 

semi-confined and unconfined areas. In Leon County 91 percent of “pasture and cropland” lies 

in the semi-confined area and 7.5 percent in the unconfined area. In Wakulla County 82 

percent of the “pasture and cropland” lies in the unconfined area. In Leon County, the 

countywide total livestock N load was linearly apportioned to semi-confined and unconfined 

areas based on the above percentages (Table 10). In Wakulla County, this entire load was 

empirically attributed to the unconfined area. 

Table 10. Estimated “Recent” Nitrogen (ON) Loads from Livestock. 

Area % of County LU 

Pasture Land 

Kg-N/Yr 

Leon Semi-confined 91 124,000 

Leon Unconfined 7.5 10,000 

Wakulla Unconfined 82 23,000 
 95

Sinking Streams

Four significant sinking streams flow into the Floridan Aquifer from the surrounding landscape. 

These include Munson Slough and Fisher, Black and Lost creeks. Munson Slough drains much 

of the southern portion of the City of Tallahassee, eventually sinking at Ames Sink. There are 

13 years of continuous streamflow data for Munson Slough at Capital Circle (1987-2000), one 

mile north of Lake Munson. These data were collected by the NWFWMD. Fisher, Black and 

Lost creeks flow east through wet pine flatwoods west of the Woodville Karst Plain, eventually 

sinking on the plain’s western edge. Lost Creek has a short period of USGS continuous stream 

flow data. Fisher and Black creeks have no continuous data and only a few instantaneous data. 

Nitrogen is present in these sinking surface waters, almost exclusively in organic form. 

Inorganic nitrogen is typically present at only very low concentrations. It is believed that the 

conversion of organic nitrogen to inorganic forms is relatively inefficient within the Floridan 

Aquifer. As a consequence, sinking streams were not considered to represent a significant 

loading of inorganic nitrogen to ground waters. Nonetheless, and in attempt to be complete, an 

effort was made to estimate the total nitrogen load from these sources using existing, limited 

flow and concentration data (Table 11). 

Munson Slough and Ames Sink 

Much of the water conveyed south through Munson Slough is stormwater runoff originating from 

the southern portion of the City of Tallahassee. Ultimately, Munson Slough discharges to the 

Floridan Aquifer via Ames Sink in southern Leon County. Prior to discharging to the Floridan 

Aquifer, surface waters flow through Lake Munson and, further south, through Eightmile Pond. 

Lake Munson is about four miles north of Ames Sink. Eightmile Pond is about a mile north of 

the sink. 

The Lake Munson Basin has an area of 17,800 ha or 68.75 mi2

 (Bartel et al., 1991). Of this 

area, only about 75 percent (13,350 ha) is thought to contribute stormwater runoff to the lake. 

The remainder of the basin consists of sub-basins closed in all but the most extreme hydrologic 

conditions. Bartel et al. (1991) state that, based on long-term hydrologic modeling, only about 

12 percent of the total volume of water entering the basin leaves as surface water runoff through 

Eightmile Pond. The remaining 88 percent evaporates, transpires or recharges ground water as 

leakage through the beds of Lake Munson and Eightmile Pond. 

The majority of water leaving Eightmile Pond flows into the Floridan Aquifer via Ames Sink. 

Assuming an effective basin area of 13,350 ha and an average rainfall depth of 63 inches, this 

equates to an average runoff of 29 cfs or 7.6 inches per year. The observed daily mean flow at 

the point where Munson Slough crosses Highway 319 (about one mile north of the lake) is 44.7 

cfs (period of record 1987—2000). Considering evaporation and subsurface infiltration from the 

lake, the lower of these two estimations was considered more accurate and 30 cfs was used to 

estimate the long-term surface water inflow at this point to the Floridan Aquifer. 

Nitrogen samples were collected from Munson Slough at Oak Ridge Road by the NWFWMD 

between 02/00 to 01/01. These data had a median total nitrogen concentration of 0.51 mg-N/L 

(mean=0.57, stdev=0.16, n=7). The median NH4-N concentration was 0.018 mg/L 

(mean=0.039, stdev=0.042). The median TKN-N concentration was 0.50 mg/L (mean=0.55, 

stdev=0.15). The median NO2+NO3-N concentration was 0.015 mg/L (mean=0.014, 

stdev=0.011). The TN median concentration was multiplied by the estimated long-term average 

flow of 30 cfs to yield an annual load estimate of 13,600 kg-N/yr. 
 96

Fisher Creek 

Fisher Creek has a basin area of about 11,084 ha (42.8 mi2

). It sinks at a sinkhole located 

within the Leon Sinks Geologic Area, approximately 0.7 miles due west of Crawfordville Hwy. 

(30°18’35.115”/84°21’22.783”). Through mid-2001, no continuous streamflow monitoring has 

been conducted on Fisher Creek. However, a limited number of instantaneous discharge 

measurements are available. These data were collected by the NWFWMD in the early 1980s at 

various locations along the lower end of the creek, at or east of the Springhill Road Bridge and 

by the FDEP at the Springhill Road Bridge. Flow data collection during the study period was 

beyond the scope of this investigation. Fisher Creek is believed to discharge to the Floridan 

Aquifer within the Wakulla Springs capture zone. 

Fisher Creek at Springhill Road Bridge 03.04.1982 19.8 cfs 

Fisher Creek at Springhill Road Bridge 04.07.1982 20.7 cfs 

Fisher Creek at Springhill Road Bridge 05.06.1982 3.1 cfs 

Fisher Creek 2.7 miles east of Springhill Rd 06.10.1982 4.7 cfs 

Fisher Creek at Springhill Road Bridge* 03.07.1997 18.5 cfs 

Fisher Creek at Springhill Road Bridge* 08.04.1999 26.6 cfs 

Fisher Creek at Springhill Road Bridge* 02.29.2000 4.1 cfs 

*Obtained from Richard Wieckowicz, FDEP, personal communication, 2001. 

Nitrogen samples were collected from Fisher Creek at Springhill Road by the NWFWMD 

between 02/00 to 01/01. These data had a median total nitrogen concentration of 0.74 mg-N/L 

(mean=0.74, stdev=0.18, n=9). The median NH4-N concentration was 0.017 mg/L 

(mean=0.016, stdev=0.005). The median TKN-N concentration was 0.72 mg/L (mean=0.73, 

stdev=0.18). The median NO2+NO3-N concentration was 0.004 mg/L (mean=0.008, 

stdev=0.008). The median of six flow measurements at the Springhill Road Bridge is 19.2 cfs. 

Multiplying the estimated long-term average flow of 20 cfs by the observed median TN 

concentration (0.74 mg/L) resulted in a total N load estimate for Fisher Creek of 13,200 kg-N/yr. 

Black Creek 

Black Creek has a basin area of about 3,800 ha (14.7 mi2

). It sinks at a sinkhole located 

approximately two miles northwest of the intersection of Crawfordville Hwy and Bloxham Cutoff 

(30°17’15”/84°22’39”). To date, no continuous flow data has been collected on Black Creek; 

however, a few miscellaneous measurements are available. Black Creek is believed to 

discharge to the Floridan Aquifer within the Wakulla Springs capture zone. 

Black Creek above sink at culvert 03.03.1982 7.1 cfs 

Black Creek above sink at culvert 04.06.1982 14.2 cfs 

Black Creek near New Light Church 05.05.1982 1.9 cfs 

Black Creek near New Light Church 06.08.1982 0.0 cfs 

Black Creek at SR 267* 02.29.2000 6.5 cfs 

*Obtained from Richard Wieckowicz, FDEP, personal communication, 2001. 

Nitrogen samples were collected from Black Creek by the NWFWMD between 02/00 to 01/01. 

These data had a median total nitrogen concentration of 1.0 mg-N/L (mean=1.06, stdev=0.23, 

n=9). The median NH4-N concentration was 0.017 mg/L (mean=0.072, stdev=0.126). The 

median TKN-N concentration was 1.0 mg/L (mean=1.05, stdev=0.23). The median NO2+NO3-N 

concentration was 0.008 mg/L (mean=0.014, stdev=0.01). The median of the above five flow 

measurements is 6.5 cfs. Multiplying the estimated long-term average flow of 6.5 cfs by the 
 97

median TN concentration (1.0 mg/L) yields an estimated N load of 5,800 kg-N/yr from Black 

Creek. 

Lost Creek 

Lost Creek has a basin area of about 18,130 ha (70.4 mi2

). It drains into a sinkhole located on 

the north side of County Road 374 (30°09’57”/84°23’43”). The USGS has made miscellaneous 

discharge measurements since 1928. Daily mean flows have been collected since October 

1998. For water year 1999, the annual mean flow was 57 cfs (Franklin et al., 1999). This 

estimated flow may be somewhat low due to low rainfall conditions. At the Tallahassee Airport, 

1998 and 1999 experienced a two-year cumulative deficit of 16.6 inches (13 percent of normal 

rainfall). 

Water quality data for Lost Creek are extremely limited. In order to estimate the total N load in 

the stream, the median TN concentration from Fisher Creek was used to estimate that for Lost 

Creek. Multiplying the Fisher Creek concentration (0.74 mg/L) by a flow of 60 cfs resulted in an 

annual TN load of 39,600 kg-N/yr for Lost Creek. Lost Creek is believed to discharge to the 

Floridan Aquifer outside the Wakulla Springs capture zone. 

From anecdotal data and observation, Floridan Aquifer inflow from the sinking streams is quite 

variable. These streams are often dry during periods of below normal rainfall. During and 

directly following periods of intense rainfall, the streams may flood and drown the sinks. The 

water subsides rapidly, however, and inflow returns to relatively low levels. Wakulla Springs’ 

reaction to high inflows from sinking streams is muted by an overall discharge increase caused 

by rising ground water levels associated with intense rainfall. Figure 29 shows that the 

conductivity of water discharging from Wakulla Springs dropped 20 percent while the 

velocity/discharge more than tripled following Tropical Storm Helene. If this increase in 

discharge had been caused by a significant influx of surface water, conductivity would have 

been depressed to a value nearer that of surface water. 

Ammonia and NO3-N levels are typically very low in the sinking inflow from surface water 

bodies. Most of the total nitrogen present in sinking streams is organic in nature and is believed 

to be mechanically removed from the flow system. The organic N is usually bound up in largemolecule tannins and lignins. These humics are sensitive to pH and tend to flocculate when the 

surface water encounters more alkaline ground water. Some of the organic N sorbs readily onto 

colloids. Only a small percentage of the organic N associated with sinking streams is believed 

to be transformed, through bacterial digestion, into ammonia and made available for nitrification 

within the Floridan Aquifer. 

As part of the study, a high-flow sampling event was conducted at Wakulla Springs. It was 

found that nitrate concentrations in water discharging from Wakulla Springs was slightly reduced 

when compared to the low-flow sampling event. This was despite (or perhaps due to) a 

relatively high inflow rate from sinking streams. All indications are that water entering the 

ground water flow system from sinking streams travels quickly and its affect on Wakulla Springs 

water quality is ephimeral. The transient, variable influx from these sinking streams is believed 

to have a minor effect on the quality of water discharging from Wakulla Springs. 
 98

Table 11. Estimated “Recent” Nitrogen Loads from Sinking Streams. 

Area Surface Water Body Flow (cfs) Median Concentration 

(mg-N/L) 

Load (kg-N/yr)

Leon Semi-confined none 0 -- 0 

Leon Unconfined Munson Slough 30 0.51 13,600 

Wakulla Unconfined Fisher Creek 20 0.74 13,200 

Wakulla Unconfined Black Creek 6.5 1.0 5,800 

Wakulla Unconfined Lost Creek 60 0.74 39,600 
 99

Landfills

There are 31 active landfills in Leon and Wakulla counties. Twenty-four (24) are construction 

and demolition landfills and three are household garbage disposal sites (the Highway 27 landfill 

in Leon County and the Lower Bridge and Medart landfills in Wakulla County). There is also a 

waste tire disposal facility, a transfer station, a land clearing debris disposal, and an unclassified 

landfill (total of 31). For the 31 active landfills, there are a total of 29 ground water monitoring 

wells and two surface water monitoring sites. These monitoring sites are located at the three 

household garbage disposal sites. In addition, there are 26 ground water wells monitoring 33 

inactive or closed landfills. 

Forty-nine landfills, active and inactive, lie within the semi-confined and unconfined portions of 

the study area. Seventeen are in the semi-confined area and 32 are in the unconfined area 

plain. Ground water quality sampling results indicate that the landfills contribute nitrogen to 

ground water in the form of NH4 and NO3. However, no data are available with which to 

estimate a total nitrogen load emanating from any of these sites. Accordingly, no effort to do so 

was made as a part of this investigation. At the scale of the study area, landfills are not 

believed to be a significant source of nitrogen in the Floridan Aquifer. 
 100

Summary

TN loads to the landscape in the semi-confined and unconfined portions of the study area under 

recent conditions are summarized in Table 12. The various approaches used to spatially 

apportion load estimates to these areas were discussed previously. Figures in this table 

summarize N loads contributed to the landscape (but not necessarily to the Floridan Aquifer) 

within the semi-confined and unconfined portions of the study area. 

Table 12. Estimated 1999 Nitrogen Loading to the Study Area by Geographic Subdivision. 

Source Predominant 

form 

Semi-confined 

(kg-N/yr) 

Unconfined 

(kg-N/yr) 

Total (kg-N/yr) 

Atmospheric Deposition IN 479,000 523,000 1,002,000 

WWTF Effluent IN 9,000 331,000 340,000 

WWTF Residuals indeterminate 0 177,000 177,000 

OSDS IN 172,000 111,000 283,000 

Commercial Fertilizer IN 150,000 62,000 212,000 

Livestock ON 124,000 33,000 157,000 

Sinking Streams ON 0 72,000 72,000 

Total 934,000 1,309,000 2,243,000 

For each loading class (excepting OSDS, sinking streams and livestock), the average annual 

load (1990 through 1999) was calculated (Table 13). Figure 54 includes the estimated 

contributions attributable to atmospheric deposition and sinking streams; Figure 55 does not. 

OSDS and livestock data were heavily interpolated during that period. As a result, their 

respective 1999 values are cited in the above table. Effluent data for the small WWTFs were 

not readily available for 1990 and 1991. Instead, the 1992 small WWTF value was substituted 

for the two missing years. Average values for atmospheric deposition, WWTF (effluent and 

residuals) and commercial fertilizer were calculated directly from previously described data. 

Table 13. Ten-Year Average Annual Nitrogen Load to the Study Area by Geographic 

Subdivision. 

Source Predominant 

form 

Semi-confined 

(kg-N/yr) 

Unconfined 

(kg-N/yr) 

Total (kg-N/yr) 

Atmospheric Deposition IN 619,000 675,000 1,294,000 

WWTF Effluent IN 8,000 363,000 371,000 

WWTF Residuals indeterminate 0 154,000 154,000 

OSDS* IN 172,000 111,000 283,000 

Commercial Fertilizer IN 211,000 104,000 315,000 

Livestock* ON 124,000 33,000 157,000 

Sinking Streams* ON 0 72,000 72,000 

Total 1,134,000 1,512,000 2,646,000 

*1999 values. 
 101

WWTF

14%

Residuals Disposal

6%

Commercial Fertilizer

12%

Livestock

6% Sinking Streams

3%

Atmospheric Deposition

48%

OSDS

11%

Figure 54. Relative Contribution from Inventoried Nitrogen Sources to 1990-1999 Average 

N Loading in Semi-confined and Unconfined Portions of Leon and Wakulla Counties. 

Figure 55. Relative Contribution from Anthropogenic Sources to 1990-1999 Average 

N Loading in Semi-confined and Unconfined Portions of Leon and Wakulla Counties.

WWTF

29%

Residuals Disposal

12%

Commercial Fertilizer

25%

Livestock

12%

OSDS

22%
 102

Total nitrogen load by source from 1970 to 1999 is given in Figure 45. Open markers on the 

timelines represent interpolated or estimated data. Atmospheric deposition data prior to 1984 is 

represented by the period-of-record median. The commercial fertilizer data has several early 

years of data calculated from State of Florida data, as explained previously. OSDS and 

livestock time series involve interpolation between decadal census data. Early WWTF effluent 

data calculations required assumptions that lent uncertainty. Early residuals data was not 

available and no attempt was undertaken to estimate it. Flow and sampling data from sinking 

streams were not sufficient to estimate a time series. 
 103

NITROGEN FATE MODELING 

One task of this project was to integrate Floridan Aquifer water budget data and information on 

the fate of nitrogen applied to the landscape into a simple descriptive model. Key aspects of the 

model are the water budget of a specified aquifer volume, the nitrogen load advected into this 

volume from up-gradient, and the nitrogen load that originates within the volume. The intent of 

the model is to anticipate how changes in the nitrogen loading to the landscape could translate 

into impacts on receiving surface waters. The approach is constrained by the assumptions 

inherent to the water budget and by an empirically derived model of the landscape’s capacity to 

provide denitrification. Of necessity, this capacity is reduced to a linear relationship. Further, 

denitrification of all anthropogenic nitrogen sources is modeled by the same linear relationship. 

The model is developed for an area in relatively close proximity to Wakulla Springs. This choice 

removes a number of assumptions required if a larger volume of the aquifer is evaluated. The 

area of interest is bounded on the north by the Cody Scarp and on the east, south and west by 

a line that defines the downgradient limit of the Wakulla Springs “contributory zone”. This is the 

aquifer volume thought to contribute and/or convey ground water to the spring. Definition of the 

volume is based on the observed and simulated Floridan Aquifer potentiometric surfaces in near 

proximity to the spring. Limitations on the flow system conceptualization around the spring are 

discussed in the following sections. 

Water Budget for Wakulla Springs

Davis (1996) describes a calibrated, steady state regional model of the Floridan Aquifer 

centered on Leon County. That work serves as the basis of efforts to develop a ground water 

budget for Wakulla Springs below the Cody Scarp. Davis’ work was regional in nature. He did 

not specifically attempt to develop the capability to simulate local-scale flow in the immediate 

vicinity of the spring. Attempting to do so here goes somewhat beyond the limits of Davis’ 

model. However, there presently exists no better representation of the near-vicinity Floridan 

Aquifer ground-water flow around the spring. Davis’ model was calibrated to October and 

November 1991 conditions. At this time, generally dry conditions prevailed and inflows to 

sinking streams were minimal (Davis, personal communication, 2001). 

The program “Zonebudget” (Harbaugh, 1990) was used to estimate ground water inflows and 

outflows to the area around Wakulla Springs. Application of Zonebudget requires the definition 

of an aquifer volume of interest. The model uses the simulated cell-by-cell flow terms from the 

MODFLOW output file to summate inflows and outflows to the volume of interest. The volume 

of interest (contributory area) is outlined in Figure 56 and has an area of 38,825 ha. It consists 

of the Floridan Aquifer bounded by the Cody Scarp on the north, by the boundary between 

confined and unconfined Floridan Aquifer in Wakulla County on the west and by what was 

initially conceptualized as a no-flow boundary on the south and east. Wakulla Springs is located 

within the volume of interest. The eastern boundary was positioned on the basis of 

potentiometric surface maps described earlier. Key to positioning a no-flow boundary in the 

Floridan Aquifer west of Wakulla Springs is the assumption that the Big Dismal—Turner Sink 

conduit system eventually flows to Wakulla Springs and, further, that it completely captures 

Floridan Aquifer ground water flow in its vicinity. This volume was, accordingly, considered to 

constitute the Wakulla Springs ground water capture zone in the near vicinity of the spring. 

Obviously, the Wakulla Springs capture zone extends far to the northeast, north and northwest, 

beneath semi-confined Leon County and confined portions of Leon and Wakulla counties. 
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Y

RECHARGE

219 CFS

St. Marks

Wakulla 

 Springs

Sopchoppy

Panacea

#

#

Wakulla

River

Tallahassee

LEON CO.

WAKULLA CO.

St.

Marks

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A P A L A C H E E

B A Y

LEON CO.

WAKULLA CO.

GEORGIA

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GADSDEN CO.

JEFFERSON CO.

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River

River

Ochlockonee

45 CFS

INFLOW

36 CFS

INFLOW

201 CFS

INFLOW

53 CFS

OUTFLOW

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RECHARGE

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INFLOW

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OUTFLOW 160 CFS

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LEAKAGE

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CODY SCARP

CODY SCARP

N

Incorporated Areas

Contributory Area

Delineation Contour Lines

(1 ft. intervals) 20

WATER BUDGET FOR WAKULLA SPRINGS CONTRIBUTORY AREA

0 510

Miles

District Boundary

County Boundary

U.S. Highways

Rivers

Conduit System

Cody Scarp State/County Roads

Semiconfined/ Unconfined

Boundary 01-06-027

FIGURE 56
 105

The conceptualization of the southern and eastern boundary as no-flow was overturned when 

Davis’ simulated two-ft contours were plotted over the volume (Figure 56). Compared to the 

contours of Davis, there is good agreement between his flow field and the volume boundary 

defined east of Wakulla Springs. The conceptualization breaks down west of the spring. Here 

Davis’ model shows significant flow of ground water to the south, past Wakulla Springs and 

toward Spring Creek. This outflow is consistent with the mapped Floridan Aquifer 

potentiometric surfaces given earlier. All show a hydraulic gradient to the southwest, away from 

a line connecting Big Dismal and Wakulla Springs. Indeed, Wakulla Springs itself imparts no 

perturbation to the potentiometric surface, given the data available to map it. 

Likely, ground water flow on the western edge of the Woodville Karst Plain is quite convoluted. 

Sinking streams have provided large quantities of acidic recharge to the Floridan Aquifer for 

long periods of time. This has undoubtedly enhanced the development of complex, threedimensional cavern systems along the boundary where the sinking occurs. The Big Dismal—

Turner Sink conduit system may be but one of several systems along this physiographic 

boundary. It may be that flow in this system entirely bypasses Wakulla Springs. It is possible 

that the ground water capture zones for Wakulla Springs and Spring Creek overlap in this area 

with Wakulla capturing water from shallow portions of the Floridan Aquifer and Spring Creek 

drawing flow from the deeper portions (Figure 57). 

Under the presumption that at least part of the water flowing through the Big Dismal—Turner 

Sink system discharges in Wakulla Springs, positioning a no-flow boundary west of the conduit 

system is reasonable. However, given the complexity of flow in such a system, the entire 

concept of being able to locate the two-dimensional expression of a “no-flow” boundary over a 

complex three-dimensional system may be of limited utility. Thus, while the volume defined 

earlier is not, in the strictest sense, a “capture zone”, it is deemed to be of some utility in 

defining the area in which land-surface activities influence the quality of water discharged from 

Wakulla Springs. 

Davis simulated the Floridan Aquifer as consisting of two layers. With Zonebudget the layers 

were aggregated together into one zone and layer inflows and outflows combined. Per Davis’ 

model, four sources of water contribute inflow to the designated volume: 

• up-gradient underflow across the Cody Scarp—201 cfs; 

• direct recharge within the designated volume—178 cfs; 

• leakage through the confining unit on the western edge of the volume—9 cfs; 

• up-gradient underflow from beneath the confining unit in western Wakulla County—7 cfs. 

Inflows equate to 395 cfs. The bulk of the inflow is derived from two sources, underflow across 

the Cody Scarp and recharge on the karst plain within the designated volume. Inflows are 

balanced by: 

• outflow within the estimated contributory area to river nodes simulating Wakulla Springs—

160 cfs; 

• outflow that bypasses the drain cells that represent Wakulla Springs—234 cfs. 

These outflows equal the simulated inflow. 

Davis conceptualized the Wakulla River as a collection of drain (river) cells extending several 

miles from the headspring toward the confluence of the Wakulla and St. Marks rivers. The 
 106

aggregate discharge to these cells is 356 cfs. As noted in Figure 56, some of this discharge 

occurs within the designated contribution area and some occurs outside. However, in 

aggregation, the simulated Wakulla Springs/River discharge equates to the observed calibration 

target of 350 cfs. Recalling the regional scale of the model, it was quite sufficient to have the 

discharge from the spring occur along the reach of the river, as opposed to being concentrated 

at the headspring. In reality, most of the discharge to the river does occur at the main spring 

vent. 

One way to reconcile the difference between the simulated spring discharge within the 

contributory area (160 cfs) and the observed discharge (~350 cfs), is to assume that some 

water simulated as bypassing the spring on the west actually discharges through the spring. 

This is as opposed to it flowing further south and discharging into the gulf. This equates to 

assuming that some fraction of the simulated by-pass water eventually discharges from the 

model via drain (river) cells south of (and outside) the defined aquifer volume. In the absence of 

a re-calibration of Davis’ model (or development of a new model) to the local vicinity of Wakulla 

Springs, this question is impossible to answer. 

For the present discussion, the relevant question is how much of the 200 cfs simulated as 

crossing the Cody Scarp actually discharges through Wakulla Springs. The most conservative 

approach is to assume the majority of it discharges through the spring. In this way the nitrogen 

it carries also discharges through the spring. To the extent this water bypasses the spring, both 

the water volume and nitrogen mass originating within the contributory area must increase, to 

balance the spring outflow. To the extent this water bypasses the spring on the west, the 

contributory area must rotate to the east and/or get smaller to facilitate the by-pass flow. 
 107

Nutrient Budget for Wakulla Springs

Developing a nutrient budget for a discrete volume of the Floridan Aquifer entails a number of 

conceptual difficulties. In addition, a number of simplifying assumptions are required. Given the 

assumptions and limitations associated with this effort, the budget presented here should be 

viewed as a first-order approximation of a highly complicated, generally poorly understood 

hydrodynamic system. Key processes known to be highly variable in time and/or space are (of 

necessity) reduced to simple approximations. In spite of this, the general framework 

(distribution of nitrogen sources, nitrate concentrations in ground water and ground water fluxes) 

is believed to be sufficiently well understood to permit construction of a simple nutrient budget 

for Wakulla Springs. 

Inventoried nitrogen sources include predominantly inorganic sources, predominantly organic 

sources and mixtures of the two. The nitrogen load discharged from Wakulla Springs is 

predominantly inorganic, in the form of NO3. Predominantly inorganic sources include 

atmospheric deposition, commercial fertilizer, OSDS and WWTF effluent. Predominantly 

organic sources include livestock, WWTF residuals and sinking streams. In addition to being 

partitioned between organic and inorganic forms, nitrogen goes onto the landscape at various 

locations throughout the study area. Some of it goes onto the ground in places where the 

Floridan Aquifer is poorly confined or unconfined. In these areas it is reasonable to presume 

short vertical travel times for infiltrating water and relatively efficient delivery of dissolved 

nitrogen to the water table. In other areas, low-permeability materials that slow the vertical 

transit of water overburden the Floridan Aquifer. 

In addition, there are a host of uptakes, transformations and sequestrations that act on 

mobilized N as it transits the environment. However, little is known about the relative efficiency 

of these processes at denitrifying various forms of mobilized N at the scale of this particular 

study area. Presumptively, organic N is relatively inefficiently converted to inorganic forms 

within the hydrosphere and, by inference, is less likely to become part of the inorganic N load 

being discharged from the Floridan Aquifer. Presumptively, N applied to the unconfined 

Floridan Aquifer is relatively more efficiently delivered further down-gradient than is N applied on 

the semi-confined areas. Presumptively, atmospheric deposition, with its low application rate 

per unit area, is more efficiently denitrified in the soil than are other sources. However, the 

veracity of these assumptions is difficult to assess. 

Clearly, the water quality of Wakulla Springs has been adversely influenced by anthropogenic 

impacts. NO3 concentrations have tripled since the late 1970s. Over the same period it is 

reasonable to assume that the N load discharged through the spring has also tripled. Further, 

the increase has occurred over a fairly short time period, on the order of ten years or less. 

These changes represent a significant impact. Key (and obvious) assumptions are that the 

nitrogen load discharging through the spring is the product of nitrogen additions to the 

landscape up-gradient of the spring and that N loadings to the landscape have increased with 

time. 

Because NO3 comprised the greatest fraction of mobilized N in the Floridan Aquifer, the nitrogen 

balance is expressed in terms of NO3. The budget presented here consists of the following 

components: (1) defining a volume of the Floridan Aquifer that contributes water to the spring, 

(2) estimating the mass of NO3 passing into the aquifer volume from up-gradient portions of the 

Floridan Aquifer, (3) estimating the mass of NO3 discharging from the spring (4) defining the 

NO3 load originating within the volume as the difference between the mass discharged from the 

spring and that advected in from up-gradient, and (5) assuming that the NO3 mass originating 
 108

within the aquifer volume is derivative of the total N mass applied to the landscape on top of the 

volume. Conceptual limitations and assumptions associated with this effort are outlined below. 

Conceptual limitations

• Nitrogen is highly reactive in the hydrosphere. 

• Wakulla Springs integrates flow system components over a wide range of time scales. 

• The efficiency of de-nitrification processes acting on various anthropogenic N sources is 

poorly understood. 

• The impact of conduit systems on ground-water flow and contaminant transport is poorly 

understood. 

Assumptions

• Water discharging from Wakulla Springs is almost exclusively derived from the Floridan 

Aquifer much of the time and predominantly from the Floridan Aquifer all of the time. 

• Nitrogen sources applied to the landscape in Leon and Wakulla counties are adequately 

characterized in both time and space. 

• Lacking discrete removal efficiencies for each anthropogenic source, removal efficiencies 

were assumed to be uniform. 

• Under steady-state conditions, the flux of Floridan Aquifer water crossing the Cody Scarp that 

ultimately discharges from Wakulla Springs is about 200 cfs. This is assumed to be about 

half the steady-state discharge from the spring. 

• Within the designated area around Wakulla Springs, recharge to the Floridan Aquifer that 

ultimately discharges from Wakulla Springs is about 180 cfs. This is assumed to be about 

half the steady-state discharge from the spring. 

• 0.48 mg-N/L is representative of nitrate concentrations in Floridan Aquifer water crossing the 

Cody Scarp, both presently and in the recent past. 

• 0.89 mg-N/L is representative of nitrate concentrations in Floridan Aquifer ground waters 

discharging from Wakulla Springs, both presently and in the recent past. 

• In the near vicinity of Wakulla Springs, nutrients reaching the water table relatively quickly 

transit the Floridan Aquifer and discharge to surface waters. The presence of conduit flow 

shortens contaminant travel times relative to a porous media conceptualization. 

• The area designated around Wakulla Springs adequately characterizes that portion of the 

Woodville Karst plain where land use can affect the quality of water discharged from the 

spring. 
 109

• Underflow from beneath the confining unit on the western edge of the karst plain contributes 

relatively little flow or nutrients to the discharge of Wakulla Springs. 

Conceptual Model of Nutrient Budget

The nutrient budgeting effort reduced to an attempt to balance (on a mass basis) the inflow of 

nitrate into the area defined around Wakulla Springs with the outflow from the spring. The 

inflow is further divided into two components; underflow from beneath the Cody Scarp and 

recharge occurring on the karst plain within the contributory area defined around the spring. 

Csemi-confinedVsemi-confined + ClocalVlocal = CspringVspring 

In this expression C is concentration (mass/volume) and V is ground water flux (volume/time). 

The expression defines a steady state, instantaneous mixing model of flow and solute transport 

in an aquifer volume containing Wakulla Springs. In a greatly simplified manner, it 

approximates the flux of mass into and out of the volume of interest. 

One presumptive “known” is the mass of NO3 discharged from Wakulla Springs (CspringVspring). 

Based on 266 instantaneous discharge measurements made between 1907 and 1999, Wakulla 

Springs has a median flow of 340 cfs. For the purpose of budget development, this flow is used 

as Vspring. As the balance is steady state, use of this flow constrains the inflow (Vsemi-confined + 

Vlocal) to the same value. For comparison, Davis (1996) calibrated a steady state Floridan 

Aquifer discharge to the Wakulla River of 356 cfs. For the recent past (1989 to 2000) the 

median Wakulla Springs NO3 concentration (Cspring) is 0.89 mg-N/L (n=26). Combining these 

data (340 cfs and 0.89 mg/L) gives an estimate of the current annual NO3 load (CspringVspring) 

discharging from the spring, 270,000 kg-N/yr. 

A second presumptive known is the NO3 mass (Csemi-confinedVsemi-confined) flowing south of the Cody 

Scarp. Combining the model-simulated flow across this boundary with the estimated 

representative concentration yields an estimate of this mass. The median NO3 concentration of 

0.48 mg-N/L (n=208, mean=0.48, stdev=0.16) from the six southernmost City of Tallahassee 

wells in the semi-confined portion of the Floridan Aquifer is used for Csemi-confined. Reasons why 

these data are considered to be broadly representative of conditions in the ground water 

discharging from beneath the semi-confining unit in Leon County include: relatively long openhole intervals; wide dispersal of wells; regular pumping at high rates; relatively time-invariant 

data going as far back as 20 years and relatively small variance in space. 

The previously described water budget (Davis, 1996) for the area defined around the spring was 

395 cfs, of which 201 cfs represents underflow from the semi-confined area and 178 cfs 

represents direct recharge. As V has already been constrained to 340 cfs, the model simulated 

underflow (201 cfs) and local recharge (178 cfs) cannot be directly applied to the balance. For 

the purpose of budget development and referencing Davis’ approximate 50-50 split between 

underflow and recharge, 340 cfs was equally divided between underflow and direct recharge. 

Using the NO3 median concentration (Csemi-confined) of 0.48 mg-N/L and 170 cfs (Vsemi-confined), a 

load (Csemi-confinedVsemi-confined) of 73,000 kg-N/yr was estimated to discharge across the Cody 

Scarp into the Wakulla Springs contributory area. 

The discrepancy (ClocalVlocal or 197,000 kg-N/yr) between the NO3 mass originating from beneath 

the semi-confined area and the mass discharged at the spring vent, of necessity, means that a 
 110

significant portion of the mass discharged from the spring originates on the karst plain (Figure 

56). Whereas, the recharge rate for the contributory area is estimated to be 170 cfs (Vlocal), 

there is no equivalent area-wide median NO3 concentration associable with this recharge. 

However, the combination of this mass flux and volumetric flux equates to an effective NO3

recharge concentration (distributed over the entire contributory area) of 1.3 mg-N/L. 

In an effort to gain insight into nitrate-contributing sources, each of the seven principal nitrogen 

sources was spatially apportioned as being either inside the Wakulla Springs contributory area 

or outside it according to the following (Table 24). 

• WWTF effluent is the annual average (1990-1999) N load discharged from the City of 

Tallahassee facilities and three small package plants located within the contributory area. 

The average load from these facilities is 360,000 kg-N/yr. 

• Atmospheric deposition is the contributory area (38,825 ha) multiplied by the estimated 

average (1990-1999) N deposition (wet + dry) per unit area (5.98 kg-N/yr), or 232,000 kgN/yr. The median loading rate over the same period was 5.89 kg-N/yr. 

• The WWTF residuals load is the (1990-1999) average of N amounts reported by the City of 

Tallahassee as being spread at the airport sites within the contributory area, or 130,000 kgN/yr. 

• OSDS is the estimated total number of systems presently found in the contributory area 

(5,600) multiplied by a loading rate of 4.2 kg-N/yr per capita multiplied by an occupancy rate 

of 2.4, or 56,000 kg-N/yr. 

• Commercial fertilizer is based on N amounts sold in Wakulla County, as reported by DACS 

and actual SESF usage obtained from the City of Tallahassee. The load applied to the 

Wakulla County portion of the contributory area is estimated by calculating the percentage 

of the total countywide agricultural land area in the contributory area and multiplying that 

percentage by the county total average N sales for 1990-1999. The load applied to the 

Leon County portion of the contributory area is solely the average (1990-1999) N load 

applied at the SESF as reported by the farm manager. The (1990-1999) estimated average 

N load applied to the contributory area in both counties is 60,000 kg-N/yr. 

• Sinking streams is the sum of the estimated annual load for Munson Slough at Ames Sink, 

and Fisher and Black creeks, or 32,600 kg-N/yr. 

• Livestock is the number of each type of livestock in each county (per the Census of 

Agriculture) multiplied by literature based loads per animal. These amounts were then 

disaggregated using the percent of county pastureland within the contributory area in each 

county. The total for both counties is 14,000 kg-N/yr. 

Within the contributory area the 1990-1999 average aggregate load from the above seven 

sources is about 885,000 kg-N/yr (Table 14). For the purposes of comparison, 1990-1999 

median values were calculated and are also presented in this table. The percent apportionment 

of this load is illustrated in Figure 58. 
 111

Table 14. Ten-Year Average and Median Annual Nitrogen Loads to the 

Wakulla Springs Contributory Area. 

Source Average N Load 

(kg/yr) 

Median N Load 

(kg/yr) 

Percent of Total 

WWTF Effluent 360,000 345,000 40 

Atmospheric Deposition 232,000 229,000 26 

WWTF Residuals 130,000 126,000 15 

OSDS 56,000 56,000 6 

Commercial Fertilizer 60,000 65,000 7 

Sinking Streams 33,000 33,000 4 

Livestock 14,000 14,000 2 

Total 885,000 868,000 100 

OSDS

6%

WWTF

40%

Commercial Fertilizer

7%

Livestock

2%

Sinking Streams

4%

Atmospheric Deposition

26%

Residuals Disposal

15%

Figure 58. Relative Contribution from Inventoried Nitrogen Sources to 

1990-1999 Average N Loading in the Wakulla Springs Contributory Area. 

885,000 kg-N/yr represents the 1990-1999 average nitrogen load applied to the landscape 

within the contributory area. Obviously, this load is subject to de-nitrification as it reacts with the 

landscape and the hydrosphere. Under the presumption that the nitrogen load applied to the 

landscape is responsible for nitrate load applied to the underlying ground water, it is possible to 

estimate the nitrogen removal efficiency of the landscape and the hydrosphere. 
 112

Katz et al. (1999) conducted a study of the sources and fate of anthropogenic nitrogen in a 

similar hydrologic setting within the Suwannee River Water Management District. Specifically, 

they undertook a comparison of long-term nitrate concentrations in Floridan Aquifer ground 

water discharging from springs and estimated nitrogen inputs to the landscape up-gradient of 

the springs. Nitrogen loads identified in their study were principally derivative of agricultural 

fertilizers. By assuming that the entire fertilizer N load applied to the landscape was converted 

to nitrate and dissolved in recharge water, they estimated nitrogen removal efficiencies between 

the point of application and the point of discharge ranging between 50 and 66 percent. When all 

nitrogen sources (including atmospheric deposition) were considered, they estimated N removal 

efficiencies ranging between 66 and 75 percent. Under a similar set of assumptions, and 

assuming that both the estimated annual N landscape load and the estimated annual Wakulla 

Springs N discharge load are representative of the recent past, the N removal efficiency within 

the Wakulla Springs contributory area is approximately 78 percent. 

That portion of the total Wakulla Springs N load estimated to derive from the contributory area 

(ClocalVlocal or 197,000 kg-N/yr) is assumed to originate from the N load applied to this area. 

Further, when estimating the removal efficiency it is assumed that local N sources have fully 

broken through into the spring. That is, sufficient time has elapsed for plumes derivative of 

these sources to reach the spring and become part of the discharged N load. Put another way, 

no N released from these local sources is going into storage within the Floridan Aquifer. While 

there is no way to prove the hypothesis regarding the in=out nature of local N loading to the 

Floridan Aquifer, to assume otherwise implies that N loads discharged through the spring will 

increase as more sources break through. 

As noted above, nitrogen is applied to the contributory area in a variety of forms (DIN, DON, 

PIN, and PON). Depending on the form, some sources have a greater potential to impact 

ground waters than others do. However, little is known about source specific removals. 

Atmospheric deposition (DIN and PIN) appears to be subject to removals of at least 80 percent 

between the land surface and immediately underlying ground waters. Based on comparisons 

between TN in WWTF effluent and DIN in underlying ground waters, effluent is subject to at 

least a 50-percent removal efficiency between land surface and the water table. PON applied to 

the land surface is presumed to be inefficiently converted to DIN that eventually reaches ground 

water, but how poorly is unknown. OSDS are efficient at converting ON to DIN. They are less 

efficient at de-nitrifying and are relatively efficient at delivering DIN to ground water, particularly 

in the unconfined part of the sturdy area. The efficiency of de-nitrification within the Floridan 

Aquifer is virtually unknown. The 77 percent removal efficiency estimated here is an integration 

of all processes (conversion to DIN and de-nitrification) acting on N applied to the landscape. It 

appears to be consistent with both the limited information regarding local-scale, source-specific 

removals and with global-scale removals estimated elsewhere in similar settings. 

Based on the load magnitudes involved it seems reasonable to assume that all available 

sources are required to account for the N load discharged from Wakulla Springs. Three 

individual sources (OSDS, commercial fertilizer and livestock) are collectively insufficient to 

account of the spring load, even assuming 100 percent conversion to DIN and zero denitrification. If atmospheric deposition were a principal source, DIN concentrations in Middle 

River Sink would be more similar to those observed in Wakulla Springs. Although the 

apportionment of impacts at Wakulla Springs to specific sources is beyond both the scope of 

this work and the limitations of existing data, there is evidence development (including WWTFs 

and OSDS in Leon and Wakulla counties) is having an impact on the quality of water discharged 

from the spring. 
 113

CONCLUSIONS AND RECOMMENDATIONS 

• The quality of water discharged from Wakulla Springs is predominantly determined by the 

quality of ground water in the Floridan Aquifer. Under low-flow conditions, discharge from 

Wakulla Springs is composed almost entirely of ground water from the Floridan Aquifer. 

Under high-flow conditions, discharge from Wakulla Springs is still primarily composed of 

Floridan Aquifer ground water. Surface water inputs (via sinking streams and other direct, 

conduit-type inputs to the Floridan Aquifer) at all times constitute a relatively small fraction of 

the total discharge from the spring. 

• The capture zone for Floridan Aquifer discharge features in coastal Wakulla County extends 

as far north as Mitchell County in southwest Georgia. Volumetrically, most of the water 

discharged through Wakulla Springs is recharge that occurs on the Woodville Karst plain 

near the spring or further north in Leon County. The spring is imbedded in a zone of very 

high Floridan Aquifer hydraulic conductivity that funnels water to the spring from the 

northwest, north and northeast. The cities of Tallahassee and Woodville, suburbanized 

Leon County and developing portions of Wakulla County overlie the spring capture zone. 

 

• Given its proximity to both the spring and to the high hydraulic conductivity zone lying north 

of the spring, it is a virtual certainty that Ames Sink contributes water to Wakulla Springs. 

Fisher and Black creeks, which lie near the presumptive western edge of the capture zone 

probably contribute water to Wakulla Springs. Lost Creek sinks too far south to contribute 

water to the spring. This water likely discharges through the Spring Creek group. 

• Potentiometric surface mapping efforts suggest a significant ground water bypass flow 

occurring west of Wakulla Springs. To date, efforts to prove the existence of a direct 

connection between the Big Dismal—Turner Sink conduit system and Wakulla Springs have 

been unsuccessful. Management and protection efforts for Wakulla Springs will benefit from 

resolution of this question. 

• Based on measurements of stream condition index and other observations, the biota of 

Wakulla Springs and the upper river have been adversely perturbed by anthropogenic 

impacts. These appear to result from the introduction of invasive exotic plants and 

increased nutrient discharge from the spring. Effective efforts to manage Wakulla Springs 

as an esthetic and recreational resource require an improved understanding of the complex 

interrelationship between nutrient concentrations in spring water and attendant biological 

perturbations. 

• Existing data indicate that nitrate concentrations in waters discharging from Wakulla Springs 

have increased threefold in the past 25 years. This represents a tripling of the total nitrate-N 

mass discharged from the spring, from an estimated 80,000 kg-N/yr in the mid- to late 1970s 

to an estimated 270,000 kg-N/yr presently. Isotopic analyses indicate that both inorganic 

and organic sources contribute to the nitrogen load discharged by the spring. 

• Assuming that removal efficiencies remain at present levels, the nitrogen load discharged 

through the spring will increase as the population of Leon and Wakulla counties increases. 

• Existing data indicate that nitrate concentrations in Floridan Aquifer ground waters beneath 

the semi-confined potion of Leon County have been constant or slightly increasing over the 
 114

past 20 years. This implies that the flux of nitrate-N from the semi-confined Floridan Aquifer 

into the unconfined Floridan Aquifer (along the Cody Scarp) has been relatively constant 

over this period. The estimated nitrate-N mass flux across this boundary under present 

conditions is 73,000 kg-N/yr. 

• Analyses presented here indicate that the increase in nitrate-N output from Wakulla Springs 

over the past 25 years is largely attributable to nitrogen inputs that have occurred south of 

the Cody Scarp. 

• At the scale of the entire study area and under current conditions, atmospheric deposition 

accounts for about half the total N load applied to the landscape. OSDS, WWTF, 

commercial fertilizer, livestock and sinking streams account for the other half. Ignoring 

atmospheric deposition and sinking stream inputs, OSDS, livestock and commercial 

fertilizers are estimated to contribute about 60 percent of the total nitrogen load applied to 

the landscape. WWTFs contribute the remaining 40 percent. 

• At the scale of the Wakulla Springs contributory area and under current conditions, WWTFs 

are estimated to contribute just over half of the nitrogen load applied to the landscape. 

Atmospheric deposition, OSDS, livestock, commercial fertilizer and sinking streams 

contribute the remainder. 

• The analysis presented here presumes a state of quasi-equilibrium between nitrogen 

applications to the landscape and nitrogen loads discharged through downgradient springs. 

Assuming that the ability of the landscape and hydrosphere to provide de-nitrification is 

more or less constant, decreasing the nutrient discharge from springs will require reducing 

nitrogen loads to the landscape. 

• Technologies that provide for OSDS de-nitrification (beyond what currently applied 

technologies give) should be encouraged, particularly south of the Cody Scarp and within 

the Wakulla Springs contributory area. To the extent they reduce potential numbers of 

OSDS (or other pollution sources), land acquisitions provide positive water quality benefits. 

• If additional de-nitrification of large, more concentrated sources (e.g. WWTFs) is 

contemplated, this should be preceded by consideration of the benefit likely to be derived. 

Effective cost-benefit analysis presumes a better understanding of both the fate and 

transport of nutrients derivative of these facilities and the adverse effect of elevated nutrient 

levels on receiving surface waters. 

• Nitrogen introduced to the environment via WWTF effluent and residuals disposal comprises 

a relatively large fraction of the total nutrient budget of the study area. The fate of nitrogen 

introduced to ground water from these sites is poorly understood, beyond the immediate site 

perimeters. While the nitrogen budget presented here assumes this nitrogen is reaching 

Wakulla Springs, there is no direct evidence for this. Additional data collection and 

monitoring will be required to prove this hypothesis. 

• Monitoring the evolution of nutrient plumes emanating from concentrated points of 

application is not a trivial undertaking. The effort is significantly complicated by the length 

scales involved and by the cryptic way in which conduit flow in a karst environment 

influences contaminant transport. 
 115

• Continuing, long-term monitoring of streamflow and water quality (potentially Munson 

Slough, Black, Fisher and Lost creeks, and St. Marks River) and spring flow (Wakulla 

Springs and St. Marks Rise) will provide a better understanding of ground-water/surfacewater interactions on the Woodville Karst Plain. 

• The age dating of ground and surface waters is an important tool in the identification ground 

water/surface water interactions (and associated time scales). Continued speciation of 

nitrogen isotopes will further elucidate the significance of various inputs of organic and 

inorganic nitrogen to ground waters. 

• This study greatly benefited from accurate and precise data on effluent and residual loads. 

Future studies in this (and other areas) will benefit from similar high quality data for other 

nitrogen streams, in addition to effluent and residuals. 
 116

REFERENCES 

Baker, L.A., 1991, “Regional Estimates of Atmospheric Dry Deposition”, in Charles, D.F., ed., 

“Acidic Deposition and Aquatic Ecosystems: Regional Case Studies: New York”, Spring-Verlag, 

app. B., p. 645-653. 

Bartel, R.L., et al., “City of Tallahassee and Leon County Stormwater Management Plan Volume 

I: Executive Summary”, Northwest Florida Water Management District, Water Resources 

Assessment 91-1, 1991-Revised 1992, 53 pp. 

Bartel, R.L., et al., “City of Tallahassee and Leon County Stormwater Management Plan Volume 

II: Lake Munson Basin Plan”, Northwest Florida Water Management District, Water Resources 

Assessment 91-1, 1991-Revised 1992, 265 pp. 

Battaglin, W.A. and Goolsby, D.A., “Spatial Data in Geographic Information System Format on 

Agricultural Chemical Use, Land Use, and Cropping Practices in the United States”, U.S. 

Geological Survey, Water-Resources Investigations Report 94-4176, 1994. 

Beck, “Conditions of Lake Munson”, memorandum to the Florida Board of Health, 1963. 

Berndt, M.P., “Sources and Distribution of Nitrate in Ground Water at a Farmed Field Irrigated 

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 122

APPENDIX A 
 123

Table A1. Construction Details of Wells Used for Water Level Monitoring.

NWF ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

372 300645084223701 AAA0525 WAKULLA PK REC WELL 120 35 32.14 300654.83 842236.93 

467 300907084172701 WELCH WELL 185 26 20.64 300904.695 841727.756

507 300930084210301 AAA6529 R. BREG 100 28 20.72 300931.168 842105.795

554 301008084123801 AAA0526 PURDOM #4 106 71 11 301008.08 841238.12 

556 301011084190401 AAA6514 P. HAND 90 19 25.54 301008.561 841859.923

585 301032084144001 AAA6530 T&T HIDEAWAY 100 60 3.95 301033.448 841440.886

607 301053084192101 AAA6769 N. WOOTEN 98 40 20.94 301053.145 841923.184

613 301059084204002 AAA6499 D. BRAZIER 35 13.87 301104.351 842040.028

635 301115084241201 AAA0523 USGS ARRAN WORK CTR 129 75 32.23 301114.08 842412.23 

654 301130084215801 AAA6526 R. WARREN 70 60 27.56 301125.886 842155.712

663 301145084192201 AAA6527 N. GARCIA 60 38 23.39 301144.655 841925.53 

671 301156084103501 AAA0527 NEWPORT RECREATION 69 12 6.96 301156.1 841035.73 

705 301300084152501 AAA0245 GODARD PLANTATION 48 21 21.04 301258.45 841524.41 

713 301315084202801 AAA6506 CLEMENS / HICKS 60 40 15.58 301311.397 842026.961

715 301323084133001 RUTHERFORD WELL 0 0 14.53 301319.582 841327.906

728 301337084204001 AAA6522 R. MCKEITHON 75 36 18.32 301335.989 842039.067

746 301402084222801 AAA6521 P. CAUSSEAUX 60 23 21.26 301402.922 842227.469

769 301427084144601 AAA6534 PENNINGTON,DAU-VAUSE 65 37 18.08 301426.367 841439.587

802 301505084200801 AAA6516 C WELCH 57 25 14.96 301503.678 842017.345

876 301700084205201 AAA6519 MARSHALL WELL 70 42 20.17 301701.015 842052.088

900 301725084122601 AAA0296 WALTER GERREL 70 40 30.26 301725.62 841227.07 

977 301844084173501 AAA6984 CHARLES DONAHUE 80 56 25.69 301840.88 841738.27 

978 301844084173502 AAA6985 C DONAHUE DEEP 157 113 25.21 301839.49 841738.07 

1003 301857084180401 AAA0262 SPRIGGS AG WELL 148 110 25.04 301857.52 841804.01 

1017 301904084183601 AAA6778 S CAMPELL 80 36 23.27 301903.86 841835.75 

1028 301910084174901 AAA0260 J. LEWIS 50 35 23.03 301909.74 841748.59 

1164 302051084120901 AAA2999 SE22 (1164) 127 102 27.96 302051.093 841208.793

1204 302109084154701 AAA0281 BIKE TRAIL WELL 90 80 37.33 302110.05 841543.34 

1276 302135084202001 AAA0258 LS20 (1276) 145 145 29.24 302133.76 842019.13 

1344 302203084110001 AAA2976 SE48 (1344) 95 89 54.18 302148.151 841039.476

1417 302235084190301 AAA0255 LS04 (1417) 53 38 44.56 302235.53 841902.33 

1427 302237084211301 BETTY KELLY 160 33.1 302236.977 842112.247

1569 302315084192801 AAA2936 LS21 (1569) 248 247 58.32 302317.474 841927.976

6101 301230084215001 AAA2122 JIMMIE PETTY 80 29 18.54 301238.69 842147.05 

6102 301322084204001 AAA2121 DENHARDT 140 32 19.34 301324.65 842040.19 

6105 300755084211301 AAB2403 JAMES EMMONS 60 38 20.43 300750.85 842121.78 

6108 301104084255401 AAB2406 RICHARD SANDERS 74 52 44.87 301059.8 842546.52 

6127 301242084213201 AAB2407 J.W. COOPER 80 28 24.85 301744.96 842132.05 

6128 301736084194601 AAB2408 J.J. FLORES 60 20 17.22 301742.67 841950.64 

6135 301712084211401 AAB2409 A. SCOTT 28 22 24.05 301714.09 842115.9 

6200 301819084134001 AAA3053 DISC VILLAGE 140 40 44.13 301819.865 841340.22 

6282 301050084150101 AAB2413 CHRIS RACKLEY 80 60 10.52 301050.04 841501.09 

6311 301230084214001 AAB2411 MARK SMITH 65 55 24.91 301226.4 842131.96 

7105 301422084183601 AAA6779 WAKULLA SPRINGS PARK 65 57 16.01 301423.212 841837.263

7221 301546084163001 ROBERT SMITH 100 30 34.83 301617.703 841542.005

7222 301158084135501 AAA3011 MARTHA DINGLER 100 21 13.99 301158.51 841355.74 

7223 302050084110502 SE53 (7223) 100 93 27.9 302050.127 841105.812
 124

Table A1. Construction Details of Wells Used for Water Level Monitoring [cont].

NWF ID Site ID FLUID Well Name

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude

7234 301550084153001 AAA7793 KATHY CAUSSEAX 99 42 26.96 301550.14 841530.16

7238 301815084092601 AAG8892 DICK WEST 56 26 21.30 301829.703 840926.607

7239 301548084130301 AAA7822 WINCO #1 150 60 41.2 301548.337 841303.009

7492 300911084162301 AAB2437 NITRATE #1 247 229 16.97 300911.978 841623.956

7493 300915084162501 AAB2438 NITRATE #2 120 105 16.36 300915.464 841625.286

7494 301446084184601 AAB2439 NITRATE #3 270 250 13.12 301446.984 841846.815

7495 301448084184601 AAB2440 NITRATE #4 70 50 13.46 301448.235 841846.882

7498 302037084082701 AAB2441 NITRATE #5 270 253 28.56 302037.881 840827.329

7499 302039084082601 AAB2442 NITRATE #6 90 70 28.35 302039.364 840826.19
 125

Table A2. Construction Details for Wells Used in 1997 Sampling Event. 

NWF ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

231 295953084290101 AAA0524 OCHLOCKONEE ST PK #1 74 41 11.54 295957.743 842859.776 

251 300117084330501 AAA6504 J. GLOW 142 116 10 300120.271 843303.995 

276 300320084285201 AAA6775 GRIFFIN HM & CRM STR 110 60 17 300319.068 842850.962 

278 300328084292201 AAA6770 REVELL WELL BACKYARD 181 131 28 300328.311 842920.746 

280 300330084301501 AAA6502 B. PORTER 100 97 12 300327.271 843013.751 

313 300422084304001 AAA6771 F. LAWHON 153 123 30 300441.358 843103.182 

325 300500084232001 AAA6776 BROWN TRLR & SEAFOOD 95 78 34 300500.706 842319.066 

326 300500084373501 AAA6512 L ROBERTS 210 166 35 300501.748 843740.395 

330 300516084311101 AAA6772 J CRAIG 98 65 15 300511.885 843108.078 

334 300526084300301 AAA6503 PATRICK HARRINGTON 140 66 40 300520.051 842956.618 

338 300529084321501 AAA6773 MCCAULEY FLOWER SHOP 139 88 43 300527.213 843215.796 

339 300530084221501 AAA6508 MCDONALD #2 63 52 32 300534.588 842220.049 

343 300550084224401 M. WIGGINS 120 60 37 300550 842244 

344 300550084315201 AAA6501 B. AREND 123 100 35 300550.623 843156.107 

351 300618084193801 AAA7842 TEC-GULF COAST 1 205 131 14.07 300614.746 841936.133 

354 300628084213801 AAA6538 J. EWING 127 68 27 300622.036 842143.617 

356 300629084294701 AAA6510 LYNN FORMERLY QUIGG 120 70 45 300626.297 842948.062 

363 300638084223101 AAA6537 GAIL DEFEND 190 37 35 300643.443 842227.557 

372 300645084223701 AAA0525 WAKULLA PK REC WELL 120 35 32.14 300654.83 842236.93 

381 300705084220901 AAA6774 CRONAN 80 40 28 300708.737 842207.477 

391 300740084235201 AAA6536 D. SHORES 41 32 25 300739.691 842354.6 

399 300755084184801 AAA6531 C. COOMBS 150 38 23 300754.644 841848.801 

402 300757084240501 AAA6524 R. GILLESPIE 70 58 43 300751.153 842422.741 

412 300810084202501 AAA6532 R. HUGUENIN 90 87 10 300812.514 842030.139 

507 300930084210301 AAA6529 R. BREG 100 28 20.72 300931.168 842105.795 

527 300943084234301 AAA6535 W. HARVEY 55 23 23 300940.245 842342.519 

544 300957084240901 AAA6539 J. REEVES 118 97 32 300956.55 842409.692 

547 300959084244701 AAA6513 VIRGO IS THE BUILDER 106 66 37 301005.715 842435.674 

564 301018084242301 AAA6498 S. EDWARDS 95 55 35 301017.629 842424.071 

607 301053084192101 AAA6769 N. WOOTEN 98 40 20.94 301053.145 841923.184 

613 301059084204002 AAA6499 D. BRAZIER 35 13.87 301104.351 842040.028 

635 301115084241201 AAA0523 USGS ARRAN WORK CTR 129 75 32.23 301114.08 842412.23 

641 301119084210601 AAA6525 D. BLACKSTAD 60 44 18 301120.086 842103.815 

648 301124084153701 GODDARD PLANT. #1 45 18 6 301124 841537 

653 301128084251401 AAA6515 DONNIE SPARKMAN WELL 105 76 41 301134.741 842520.629 

654 301130084215801 AAA6526 R. WARREN 70 60 27.56 301125.886 842155.712 

658 301135084183402 AAA7841 TEC-GULF COAST #3 322 140 27 301134.067 841833.519 

663 301145084192201 AAA6527 N. GARCIA 60 38 23.39 301144.655 841925.53 

674 301200084183601 AAA6528 JOHNSON, THOMAS 86 22 25.46 301201.552 841835.776 

698 301252084214101 AAA6523 G. RUIS 48 36 18 301251.137 842141.247 

701 301256084202001 AAA6500 A. CONNER 49 25 17 301253.909 842028.474 

702 301256084202501 AAA6509 K. KEY 50 16 16 301253.123 842028.908 

710 301310084402001 AAA6511 M. BERG 170 94 60 301311.632 844020.202 

713 301315084202801 AAA6506 CLEMENS / HICKS 60 40 15.58 301311.397 842026.961 

717 301324084132601 AAA6517 S. B. SMITH 50 18 17 301323.868 841427.306 

728 301337084204001 AAA6522 R. MCKEITHON 75 36 18.32 301335.989 842039.067 

746 301402084222801 AAA6521 P. CAUSSEAUX 60 23 21.26 301402.922 842227.469 

769 301427084144601 AAA6534 PENNINGTON,DAU-VAUSE 65 37 18.08 301426.367 841439.587 
 126

NWF ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

801 301505084080401 AAA6505 NETTLES 43 12 301505.123 840905.821 

802 301505084200801 AAA6516 C WELCH 57 25 14.96 301503.678 842017.345 

831 301609084145201 AAA6518 J. MCCABE 115 39 43 301604.597 841453.6 

977 301844084173501 AAA6984 CHARLES DONAHUE 80 56 25.69 301840.88 841738.27 

978 301844084173502 AAA6985 C DONAHUE DEEP 157 113 25.21 301839.49 841738.07 

998 301855084145001 AAA3056 WOODVILLE #1 199 117 35 301900.12 841449.564 

1007 301900084141801 AAA3055 WOODVILLE #2 200 122 35 301859.579 841419.674 

1020 301905084201701 TEC-SOUTHERN PINES 287 286 35 301905.23 842018.305 

1056 301930084185801 TEC-FOREST PARK #1 200 112 27 301941.204 841923.219 

1103 302007084231901 AAA0290 TROUT POND 340 307 92 302008.47 842317.96 

1156 302049084120901 AAA2994 SE02 (1156) 46 42 26.05 302049.917 841208.043 

1164 302051084120901 AAA2999 SE22 (1164) 127 102 27.96 302051.093 841208.793 

1166 302051084123502 AAA2996 SE16 (1166) 70 60 29.84 302052.148 841234.927 

1233 302116084123701 AAA2960 SE01 (1233) 71 57 20.38 302115.897 841237.083 

1240 302117084113801 AAA2989 SE19 (1240) 74 52 46.88 302117.909 841137.766 

1290 302141084123602 AAA2962 SE15 (1209) 102 96 34.8 302141.996 841234.172 

1511 302303084190901 AAA2937 LS25 (1511) 69 54 65 302303.984 841909.125 

1512 302303084213701 SF01 (1512) 40 26 35.28 302304.129 842136.789 

1542 302309084185701 AAA8325 LS32 (1542) 80 58 64.05 302317.474 841927.976 

1569 302315084192801 AAA2936 LS21 (1569) 248 247 58.32 302334 842229 

1663 302334084222901 SF03 (1663) 88 60 76.73 302442.119 841536.721 

2043 302445084154501 AAA3695 TALLAHASSEE #27 316 150 70 302454 842004 

2106 302513084160901 AAA3697 TALLAHASSEE #12 365 192 125 302536.846 841328.567 

2196 302535084132902 AAA3702 TALLAHASSEE #17 483 314 210 302559.878 841628.907 

2333 302558084162601 AAA3698 TALLAHASSEE #3 380 185 150 302609.601 841853.267 

2375 302607084185201 AAA3696 TALLAHASSEE #15 315 127 116 302609.243 841640.086 

2377 302608084164101 AAA3084 TALLAHASSEE #1 341 176 125 302644.516 841701.674 

2573 302644084170101 AAA3704 TALLAHASSEE #9 347 187 140 302655 840730 

2621 302655084175502 AAA3707 TALLAHASSEE #5 390 222 141 302710.797 841633.961 

2692 302710084163002 AAA3083 TALLAHASSEE #2 415 213 186.82 302713.682 841627.121 

2706 302714084162701 AAA3703 TALLAHASSEE #4 424 228 193 302713.684 841709.227 

2707 302714084170701 AAA3705 TALLAHASSEE #7 355 170 162 302713.684 841723.288 

2708 302714084172301 AAA3706 TALLAHASSEE #6 281 150 137.5 302723.4 841838.16 

2742 302722084184101 AAA3157 TALLAHASSEE #13 365 192 157 302727 841111 

2782 302731084154301 AAA3699 TALLAHASSEE #10 442 242 192 302802.278 841632.149 

2863 302801084163401 AAA3082 TALLAHASSEE #8 466 233 187 302829 841233 

2957 302838084204302 AAA3087 TALLAHASSEE #23 410 250 120 302858.44 841146.667 

2990 302856084112101 AAA3694 TALLAHASSEE #22 190 101 90 302905.283 841009.465 

3013 302903084101001 AAA3085 TALLAHASSEE #21 280 180 110 302940.199 842018.96 

3021 302908084202002 AAA3700 TALLAHASSEE #19 428 290 193 302909.603 841054.482 

3028 302910084105601 AAA3693 TALLAHASSEE #20 245 151 145 302936.243 841710.326 

3108 302939084164301 AAA3692 TALLAHASSEE #11 454 274 230 303010.799 841354.468 

3181 303012084135302 AAA3088 TALLAHASSEE #16 310 257 180 303030 841734 

3379 303126084141302 AAA3086 TALLAHASSEE #18 388 267 185 303206 840744 

3522 303225084103001 AAA3089 TALLAHASSEE #29 405 250 158 303228 841827 

3691 303335084163701 AAA3691 TALLAHASSEE #25 450 305 235 303347 841938 

3946 303522084154401 AAA3090 TALLAHASSEE #31—AH2 317 190 206 302847.275 841903.349 

5851 302847084190502 AAA3156 TALLAHASSEE #26 407 309 135 302050.127 841105.812 

7223 302050084110502 SE53 (7223) 100 93 27.9 302146 841103 

7268 302146084110301 AAA3011 SE11N (7268) 70 55.23 302146 841103 

7269 302146084110302 AAA3012 SE11S (7269) 88 55.21 302051.303 841205.68 
 127

NWF ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

7270 302051084120501 AAA2969 SE22A (7270) 121 31.87 302050.365 841105.868 

7285 302050084110501 AAA2972 SE52 (7285) 53 29.41 302838.317 840422.761 

7796 301408084180501 WAKULLA BOAT DOCK 2 301900 841835 

7831 302325084221701 SF04 (7831) 98 90 100.02 302230.12 842131.32 

7832 302230084213101 SF05 (7832) 29 35.17 302303.84 842110.86 

7833 302303084211001 SF06 (7833) 63 60.26 302304.05 841857.76 
 128

Table A3. Construction Details for Project Sampling Sites. 

NWF ID Site ID FLUID Well Name 

Total 

Depth 

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

318 300436084251902 AAA0244 SOPCHOPPY #2 200 85 25.35 300437.24 842511.27 

329 300516084094801 AAA0528 REFUGE HEADQUARTERS 65 45 13 300532.287 840942.005

351 300618084193801 AAA7842 TEC-GULF COAST #1 205 131 14.07 300614.746 841936.133

372 300645084223701 AAA0525 WAKULLA PK REC WELL 120 35 32.14 300654.83 842236.93 

391 300740084235201 AAA6536 D. SHORES 41 32 25 300739.691 842354.6 

544 300957084240901 AAA6539 J. REEVES 118 97 32 300956.55 842409.692

564 301018084242301 AAA6498 S. EDWARDS 95 55 35 301017.629 842424.071

607 301053084192101 AAA6769 N. WOOTEN 98 40 20.94 301053.145 841923.184

635 301115084241201 AAA0523 USGS ARRAN WORK CTR 129 75 32.23 301114.08 842412.23 

641 301119084210601 AAA6525 D. BLACKSTAD 60 44 18 301120.086 842103.815

650 301126084050601 AAB2427 GAME CHECK STATION 36 14 14.78 301128.601 840505.59 

653 301128084251401 AAA6515 DONNIE SPARKMAN WELL 105 76 41 301134.741 842520.629

658 301135084183402 AAA7841 TEC-GULF COAST #3 322 140 27 301134.067 841833.519

663 301145084192201 AAA6527 N. GARCIA 60 38 23.39 301144.655 841925.53 

674 301200084183601 AAA6528 THOMAS JOHNSON 86 22 25.46 301201.552 841835.776

705 301300084152501 AAA0245 GODARD PLANTATION 48 21 21.04 301258.45 841524.41 

713 301315084202801 AAA6506 CLEMENS / HICKS 60 40 15.58 301311.397 842026.961

717 301324084132601 AAA6517 S. B. SMITH 50 18 17 301323.868 841427.306

774 301430084184001 SALLY WARD 55 5 301430 841840 

801 301505084080401 AAA6505 NETTLES 43 12 301505.123 840905.821

900 301725084122601 AAA0296 WALTER GERREL 70 40 30.26 301725.62 841227.07 

1020 301905084201701 TEC-SOUTHERN PINES 287 286 35 301905.23 842018.305

1056 301930084185801 TEC-FOREST PARK #1 200 112 27 301941.204 841923.219

1176 302056084214901 BRATCHER 80 45.9 302055.312 842150.846

1261 302125084182301 HIERS 100 27 302126.483 841822.072

1399 302229084064902 AAA0297 TUNNINGTON NEW 211 150 150 302231.686 840644.565

1427 302237084211301 BETTY KELLY 160 33.1 302236.977 842112.247

2045 302445084194101 AAA6767 GOLF COURSE WELL 80 60 38.38 302445.46 841940.72 

2562 302642084041501 WINDHAM 73 66 151.27 302641.718 840412.345

2749 302724084114501 AAA3064 MEADOW HILL S/D 253 123 135 302736.426 841150.216

2923 302829084123301 JIM GREGORY 187 97 120 302829 841233 

6493 301542084213501 AAA1786 K.L. CLAYCOMB 180 25 301542.415 842135.071

7240 301547084131101 AAA7823 WINCO #2 160 60 20 301547.687 841311.714

7261 300007084283801 AAA7844 OCHLOCKONEE ST PK #2 80 66 10 300007.797 842838.855

7348 300826084175301 AAB1683 STEVE GRANTHAM 142 25 13 300826.9 841753.49 

7353 300844084183001 CHARLIE MILLER 151 148 25 300846.008 841831.956

7492 300911084162301 AAB2437 NITRATE #1 247 229 16.97 300911.978 841623.956

7493 300915084162501 AAB2438 NITRATE #2 120 105 16.36 300915.464 841625.286

7494 301446084184601 AAB2439 NITRATE #3 270 250 13.12 301446.984 841846.815

7495 301448084184601 AAB2440 NITRATE #4 70 50 13.46 301448.235 841846.882

7498 302037084082701 AAB2441 NITRATE #5 270 253 28.56 302037.881 840827.329

7499 302039084082601 AAB2442 NITRATE #6 90 70 28.35 302039.364 840826.19 

7734 301421084161201 MCBRIDE SLOUGH 7 301421 841612 

7735 301033084240101 LOST CREEK @FR13 17 301033 842401 

7736 301926084182001 MUNSON SL@OAKRIDGE R 13 301926 841820 

7737 301848084233601 FISHER CR@SPGHILL R 37 301848 842336 

7757 301636084202701 MIDDLE RIVER SINK 5 301636.24 842027.396

7796 301408084180501 WAKULLA BOAT DOCK 2 301408.381 841805.199
 129

Table A4. Project Sampling Results. 

N NAME DATE 

Temperature oC SC DO pH CA MG NA K NH4-N

NH4+ONN 

NO2+NO3-

N 

CL SO4 HCO3 F PO4-P DOC SIO2 

 STATE PARK 2 03/08/99 25.0 530 0.1 7.2 66 7.7 28 1.7 0.10 <0.20 <0.02 39.0 1.7 257 <0.10 0.02 1.9 6.8 

ELL 2 03/08/99 20.5 238 0.1 7.8 43 1 3.4 0.7 0.10 <0.20 <0.02 5.6 2.8 135 0.13 0.18 0.5 11.0

UARTERS 03/17/99 21.6 635 0.1 7.2 55 7.8 58 2.7 0.30 0.52 <0.02 83.0 7.7 222 <0.10 0.64 9.0 8.5 

ST 03/10/99 20.9 356 0.1 7.6 48 3.4 16 0.8 0.04 <0.20 <0.02 30.0 11.0 149 <0.10 0.07 0.5 5.5 

S AND REC 03/08/99 22.7 204 8.3 7.8 36 0.7 1.6 0.4 <0.01 <0.20 4.00 6.3 7.6 84 <0.10 0.04 <0.1 6.0 

S 03/08/99 21.1 224 5.0 7.8 39 1.4 3.8 0.4 <0.01 <0.20 0.24 6.7 4.2 122 <0.10 0.02 <0.1 5.9 

AM 08/11/99 20.6 354 0.7 7.3 64 2.8 3.8 1.4 0.20 <0.20 <0.02 7.9 8.5 199 0.41 0.27 1.8 16.0

R 08/11/99 21.0 264 0.4 7.5 50 1.2 3 0.7 0.20 0.21 <0.02 4.1 1.0 158 0.55 0.24 1.0 9.5 

02/14/00 21.1 583 0.6 7.6 62 11 33 1.5 0.02 <0.20 0.66 62.0 18.0 207 0.13 0.07 0.2 8.4 10/11/00 21.1 635 0.7 7.6 69 11 39 1.9 <0.01 <0.20 1.10 71.0 20.0 235 0.1 0.06 0.5 8.5 02/14/00 20.8 454 0.1 7.2 78 6.2 5.3 1.6 0.08 <0.20 <0.02 10.0 1.9 268 0.35 0.03 1.6 24.010/11/00 20.7 455 0.2 7.1 76 6.5 5.3 1.8 0.06 <0.20 <0.02 10.0 1.7 272 0.3 0.02 2.1 24.0

WELL 03/11/99 20.8 359 0.1 7.4 69 0.9 2.7 0.4 0.05 <0.20 <0.02 3.9 0.1 223 <0.10 0.07 1.5 9.2 

DS JR WELL 03/11/99 21.0 226 11.9 7.5 41 0.5 3.5 0.7 0.06 <0.20 0.04 3.8 5.1 129 <0.10 0.04 0.6 7.9 

 ARRAN FL 02/17/99 13.0 41 9.3 5.3 6.2 0.4 2 0.05 0.02 0.72 <0.02 3.9 1.2 10 <0.10 0.04 31.0 7.1 

03/11/99 20.2 382 3.6 7.4 71 2.6 2.9 0.4 0.02 <0.20 0.52 6.2 5.4 228 0.11 0.04 <0.1 10.0

ENTER 03/18/99 22.7 274 0.1 7.5 53 0.7 2.7 0.5 0.05 <0.20 <0.02 3.6 1.9 166 <0.10 0.04 1.6 7.8 

TEAD WELL 03/11/99 20.5 291 1.3 7.7 53 1 3.1 0.6 <0.01 0.280 1.40 7.0 11.0 149 <0.10 0.01 <0.1 5.7 

TATION 03/31/99 20.9 519 0.1 7.1 95 5.3 4 0.4 0.20 <0.20 <0.02 8.5 0.1 322 0.17 0.02 7.5 16.0

MAN WELL 03/11/99 21.1 182 0.2 7.9 34 0.5 1.7 0.6 0.03 <0.20 <0.02 3.3 3.5 104 <0.10 0.03 0.2 6.8 

ST 3 03/10/99 20.8 304 0.1 7.6 46 7.2 3.8 0.4 <0.01 <0.20 0.05 6.6 8.2 173 0.12 0.03 0.5 9.3 

03/18/99 21.1 306 3.9 7.4 53 4.1 3.6 0.4 <0.01 <0.20 0.34 6.2 9.5 169 <0.10 0.03 0.3 8.5 

ON 03/18/99 21.5 321 7.3 7.5 54 3.4 2.9 1.4 <0.01 <0.20 7.30 9.1 7.4 138 <0.10 0.02 0.3 9.0 

TATION 03/17/99 21.0 318 1.1 7.4 54 5.3 3.1 0.3 0.02 <0.20 0.18 5.0 7.7 184 0.1 0.02 0.5 9.4 

S/HICKS 03/10/99 21.1 358 10.6 7.4 63 3.1 4.5 0.6 <0.01 <0.20 0.34 8.1 11.0 200 <0.10 0.02 0.2 8.6 

03/18/99 20.3 503 1.5 7.1 97 2.7 4.4 0.6 <0.01 <0.20 0.97 8.0 6.8 301 0.11 0.02 0.6 14.0

NGS 03/19/99 20.7 211 1.0 7.0 43 9.7 5.5 0.5 0.20 <0.20 0.86 8.1 9.9 169 0.14 0.04 0.2 12.0NGS 02/17/00 20.6 268 6.2 7.9 42 9.3 5.4 0.6 0.02 <0.20 0.83 7.8 11.0 171 0.14 0.03 0.5 11.0

NGS 10/05/00 20.9 282 1.8 7.5 41 8.90 4.70 0.50 0.02 <0.20 0.70 7.7 9.2 156 0.10 0.02 3.7 11.0
 130

Table A4. Project Sampling Results [cont]. 

N NAME DATE 

Temperature oC SC DO pH CA MG NA K NH4-N

NH4+ONN 

NO2+NO3-

N 

CL SO4 HCO3 F PO4-P DOC SIO2 

GH 02/17/99 20.0 337 4.0 6.7 53 7.1 4.2 0.5 0.02 <0.20 0.58 6.5 10.3 190 0.13 0.05 0.1 11.0

PRING 03/19/99 20.9 211 1.5 7.5 42 10 5.5 0.5 <0.01 <0.20 1.00 8.1 9.6 167 0.14 0.03 0.3 12.0

02/15/00 21.1 268 0.1 8.1 37 8.5 3.6 1.1 0.02 <0.20 <0.02 5.0 8.8 146 0.16 0.02 <0.1 11.010/11/00 21.2 269 0.1 8.2 35 8.5 4.2 3.7 0.02 <0.20 <0.02 5.5 11.0 149 0.2 0.02 0.4 11.002/15/00 20.4 385 0.1 7.3 71 3.5 2.6 1 0.02 <0.20 <0.02 4.2 2.5 232 0.1 0.02 0.2 10.010/11/00 20.6 377 0.1 7.3 68 3.6 2.6 1 <0.01 <0.20 <0.02 4.5 2.9 232 0.1 0.01 0.3 11.0

03/17/99 20.0 1180 0.1 6.8 130 8.1 84 1.2 0.06 0.26 <0.02 210.0 2.4 337 0.2 0.01 5.8 20.0

LL 03/18/99 22.1 274 6.2 7.5 42 6.6 2.8 0.5 <0.01 <0.20 1.60 4.8 7.1 149 <0.10 0.03 0.2 7.2 

06/23/99 20.2 282 0.3 7.4 44 6.4 3.3 0.4 0.02 <0.20 0.14 4.8 8.3 160 0.12 0.04 0.5 11.0

NK 02/19/99 20.0 226 1.6 7.2 29 6.80 5.00 0.30 0.02 <0.20 0.19 8.0 11.0 110 <0.10 0.04 1.8 7.3 NK 02/14/00 20.0 222 3.5 7.7 30 6.8 4.9 0.3 0.02 <0.20 0.20 7.5 11.0 113 <0.10 0.02 2.6 7.1 

NK 10/05/00 21.1 151.0 1.6 6.8 22 4.5 3.7 0.3 0.02 <0.20 0.12 5.9 6.8 76 <0.10 <0.01 18.0 6.6 

L 03/17/99 21.2 332 2.2 7.5 50 8.2 3.7 0.5 <0.01 0.30 0.59 6.1 9.5 184 0.17 0.02 0.1 14.0

02/16/99 12.5 56 9.2 3.5 0 0.2 1.8 0.05 0.02 0.61 <0.02 3.6 0.7 1 <0.10 0.04 24.0 7.5 

 PINES 03/10/99 21.2 204 1.2 7.8 28 6.4 3 0.2 <0.01 <0.20 0.24 5.3 6.0 112 <0.10 0.02 <0.1 6.9 

GH-8 02/18/99 16.0 130 3.7 6.4 12 3 6.9 2.5 0.03 0.40 <0.02 10.7 1.3 55 <0.10 0.06 6.6 0.3 

RK 1 03/10/99 21.0 169 3.4 7.9 26 3.6 1.8 0.2 <0.01 <0.20 0.31 3.0 1.1 99 <0.10 0.01 <0.1 5.7 

02/15/00 21.1 291 0.3 7.6 43 7.4 3.5 0.9 0.03 <0.20 0.17 4.5 13.0 158 0.16 0.04 0.6 12.0

10/12/00 20.9 298 0.2 7.5 44 7.9 3.4 0.5 <0.01 <0.20 0.19 5.3 12.0 166 0.2 0.04 1.3 13.002/15/00 20.6 293 0.1 7.4 54 2.6 1.8 0.4 0.02 <0.20 <0.02 2.7 1.0 232 0.11 0.01 0.7 11.010/12/00 20.6 294 0.2 7.4 53 2.7 1.9 0.4 <0.01 <0.20 <0.02 3.0 1.0 232 0.11 0.01 1.6 11.0

ER 03/05/99 21.7 193 7.0 8.1 25 6.5 3.3 0.3 <0.01 <0.20 0.68 4.9 2.0 107 <0.10 0.01 <0.1 8.8 

03/05/99 20.9 219 2.8 7.9 35 2.8 4.2 0.3 <0.01 <0.20 0.76 6.7 1.6 121 <0.10 0.02 <0.1 6.0 

TON WELL 03/04/99 21.3 170 6.3 8.2 25 4.1 2.4 0.3 <0.01 <0.20 1.20 4.8 4.9 85 0.1 0.02 <0.1 10.0

ELL 03/05/99 21.8 215 1.8 8.0 28 7.8 2.7 0.3 <0.01 <0.20 0.63 3.8 6.4 118 <0.10 0.02 <0.1 7.4 

F COURSE 04/12/99 21.3 60 0.1 5.3 4 1.3 3.2 1.1 0.02 <0.20 0.07 9.7 0.7 12 <0.10 0.02 1.5 9.4 

 03/31/99 20.7 152 8.5 7.9 20 4.9 2.5 0.6 <0.01 <0.20 0.70 4.0 0.5 84 0.3 0.02 <0.1 32.0

UBDIVISION 04/12/99 21.0 280 5.6 7.8 36 11 2.9 0.4 <0.01 <0.20 0.58 4.5 12.0 154 0.16 0.05 0.2 13.0

03/04/99 20.7 288 7.2 7.7 43 7.9 3.2 0.5 <0.01 <0.20 0.38 5.6 2.0 172 0.11 0.03 <0.1 14.0
 131

Table A5. Construction Details for City of Tallahassee Public Supply Wells. 

NWF ID Site ID FLUID Well Name 

Total 

Depth 

Casing 

Depth 

Land 

Surface 

Elevation Latitude Longitude 

998 301855084145001 AAA3056 WOODVILLE #1 199 117 35 301900.12 841449.564

1007 301900084141801 AAA3055 WOODVILLE #2 200 122 35 301859.579 841419.674

2043 302445084154501 AAA3695 TALLAHASSEE #27 316 150 70 302442.119 841536.721

2106 302513084160901 AAA3697 TALLAHASSEE #12 365 192 125 302513.796 841609.845

2196 302535084132902 AAA3702 TALLAHASSEE #17 483 314 210 302536.846 841328.567

2333 302558084162601 AAA3698 TALLAHASSEE #3 380 185 150 302559.878 841628.907

2375 302607084185201 AAA3696 TALLAHASSEE #15 315 127 116 302609.601 841853.267

2377 302608084164101 AAA3084 TALLAHASSEE #1 341 176 125 302609.243 841640.086

2573 302644084170101 AAA3704 TALLAHASSEE #9 347 187 140 302644.516 841701.674

2621 302655084175502 AAA3707 TALLAHASSEE #5 390 222 141 302655.673 841754.244

2692 302710084163002 AAA3083 TALLAHASSEE #2 415 213 186.82 302710.797 841633.961

2706 302714084162701 AAA3703 TALLAHASSEE #4 424 228 193 302713.682 841627.121

2707 302714084170701 AAA3705 TALLAHASSEE #7 355 170 162 302713.684 841709.227

2708 302714084172301 AAA3706 TALLAHASSEE #6 281 150 137.5 302713.684 841723.288

2742 302722084184101 AAA3157 TALLAHASSEE #13 365 192 157 302723.4 841838.16 

2782 302731084154301 AAA3699 TALLAHASSEE #10 442 242 192 302731.677 841541.39 

2863 302801084163401 AAA3082 TALLAHASSEE #8 466 233 187 302802.278 841632.149

2957 302838084204302 AAA3087 TALLAHASSEE #23 410 250 120 302836.487 842041.646

2990 302856084112101 AAA3694 TALLAHASSEE #22 190 101 90 302858.44 841146.667

3013 302903084101001 AAA3085 TALLAHASSEE #21 280 180 110 302905.283 841009.465

3021 302908084202002 AAA3700 TALLAHASSEE #19 428 290 193 302940.199 842018.96 

3028 302910084105601 AAA3693 TALLAHASSEE #20 245 151 145 302909.603 841054.482

3108 302939084164301 AAA3692 TALLAHASSEE #11 454 274 230 302936.243 841710.326

3181 303012084135302 AAA3088 TALLAHASSEE #16 310 257 180 303010.799 841354.468

3379 303126084141302 AAA3086 TALLAHASSEE #18 388 267 185 303126.4 841413.197

3522 303225084103001 AAA3089 TALLAHASSEE #29 405 250 158 303227.239 841033.61 

3691 303335084163701 AAA3691 TALLAHASSEE #25 450 305 235 303344.997 841636.844

3940 303520084153501 TALLAHASSEE #30 315 186 224 303520 841535 

5851 302847084190502 AAA3156 TALLAHASSEE #26 407 309 135 302847.275 841903.349
 132

Table A6. WWTFs in Leon and Wakulla Counties (from FDEP permitting records) 

ME PERMIT NO. COUNTY

FACILITY 

TYPE 

OWNER 

TYPE 

DESIGN 

CAPACITY 

DISPOSAL 

METHOD FACILITY STATUS* DD_LAT DD_LONG DATUM

G STATION FL0025518 Leon Industrial City 1.87 Surface water Active 30.4509 -84.3997 83

FLA010136 Leon Domestic Public 0.01 Reuse system Active 30.3139 -84.2466 83

FLA010137 Leon Domestic Public 0.02 Spray Active 30.3046 -84.2285 83

CHOOL FLA010138 Leon Domestic Public 0.011 Percolation Active 30.4404 -84.5161 83

ON FACILITY FLA010139 Leon Domestic Public 27.5 Spray Active 30.3915 -84.3225 83

FLA010140 Leon Domestic Public 4.5 Spray Active 30.4262 -84.3014 83

ORT STP FLA010141 Leon Domestic Public 0.06 Percolation Active 30.4076 -84.3557 83

NTER FLA010143 Leon Industrial Private 30.4306 -84.3361 

FLA010144 Leon Industrial Private 30.4303 -84.3528 

FLA010145 Leon Industrial Private 30.4569 -84.3572 

K FLA010146 Leon Domestic Private 0.015 30.4428 -84.4033 

 FLA010148 Leon Domestic Private 0.036 Percolation Active 30.4067 -84.3240 83

FLA010149 Leon Industrial Private Drainfield 30.4351 -84.3729 

FLA010150 Leon Industrial Private 30.4585 -84.4543 

K FLA010151 Leon Domestic Private 0.015 Reuse system Active 30.4579 -84.3737 83

FLA010152 Leon Domestic Private 0.02 Reuse system Active 30.4351 -84.3729 83

FLA010153 Leon Industrial Private 30.4314 -84.1886 

FLA010154 Leon Industrial Private 0.001 Drainfield Active 30.4566 -84.3704 83

VC STORAGE FLA010155 Leon Industrial Private 0.0013 Drainfield Active 30.3266 -84.2498 83

FLA010156 Leon Industrial Private 0.0027 Drainfield Active 30.3181 -84.2486 83

AL FLA010158 Leon Industrial Private 0.0005 Drainfield Active 30.4940 -84.3255 83

F FLA010159 Leon Domestic Private 0.07 Reuse system Active 30.4216 -84.1362 83

FLA010160 Leon Industrial Private Recycle Active 30.4582 -84.3817 83

FLA010161 Leon Industrial Private Recycle Active 30.4403 -84.3141 83FLA010162 Leon Industrial Private Recycle Active 30.4377 -84.2701 83

FLA010163 Leon Industrial Private Recycle Active 30.4025 -84.3518 83

FLA010164 Leon Industrial Private 30.4389 -84.3347 

FLA010165 Leon Industrial Private Closed Active 30.5648 -84.2145 83

RON) FLA010166 Leon Industrial Private 30.4000 -84.2667 

FLA010167 Leon Domestic Private 0.0707 Percolation Active 30.4347 -84.3954 83

SEE FLA010168 Leon Industrial Private 0.8146 Percolation Active 30.4344 -84.2988 83

N FLA010169 Leon Industrial Private 30.4117 -84.3036 

AKEWOOD) FLA010171 Leon Domestic Private 0.3 Reuse system Active 30.5357 -84.3668 83

FLA010172 Leon Domestic Private 0.175 Percolation Active 30.4632 -84.2129 83

FLA010173 Leon Domestic Private 0.7 Spray/perc Active 30.5931 -84.2202 83
 133

Table A6. WWTFs in Leon and Wakulla Counties (from FDEP permitting records) [cont] 

ME PERMIT NO. COUNTY

FACILITY 

TYPE 

OWNER 

TYPE 

DESIGN 

CAPACITY 

DISPOSAL 

METHOD FACILITY STATUS DD_LAT DD_LONG DATUM

LD LAB – FSU FLA016533 Leon Industrial State 0.075 Spray Active 30.4246 -84.3265 83

SEE FLA016653 Leon Industrial Private Percolation Active 30.4350 -84.2969 83

AHASSEE PLANT FLA016709 Leon Industrial Private Percolation Active 30.3770 -84.2731 83

RPORATION FLA016876 Leon Industrial Private Recycle Under Construction 30.4359 -84.3639 83

FLA016985 Leon Industrial Private Recycle Under Construction 30.4370 -84.3499 83

CT OFFICE FLA017296 Leon Industrial State Recycle Under Construction 30.4566 -84.3999 83

FLA181803 Leon Industrial Private Active 30.5263 -84.0254 83

FLA188590 Leon Industrial Private Under Construction 30.3863 -84.2746 

FLG910291 Leon Industrial Private Drainfield Active 30.4802 -84.3039 83

E FARM FLG910616 Leon Industrial State Drainfield Active 30.6605 -84.1897 83

FLG910976 Leon Industrial Private Drainfield Active 30.4699 -84.3609 83

FL0002518 Wakulla Industrial Private 0.79 Surface wat Active 30.1810 -84.2201 83

FL0025526 Wakulla Industrial City Active 30.1630 -84.1992 83

FL0032433 Wakulla Industrial Private Spray Active 30.1670 -84.2006 83

FL0035220 Wakulla Industrial Private 0.03 Surface wat Active 30.1647 -84.2065 83

FL0042161 Wakulla Industrial Private Surface wat Active 30.1600 -84.1992 83

FLA010225 Wakulla Domestic Public 0.2 Sprayfield Active 30.0821 -84.4168 83

FLA010226 Wakulla Domestic Public 0.018 Active 30.1063 -84.3749 83

TF FLA010227 Wakulla Domestic Public 0.016 Percolation Active 30.2150 -84.3203 83

CEMENT CTR FLA010228 Wakulla Domestic Public 0.02 30.1929 -84.3722 83

FLA010229 Wakulla Domestic Public 0.018 Reuse system Active 30.1268 -84.3722 83

FLA010232 Wakulla Industrial Private 0.0068 Active 30.1846 -84.3745 83

FLA010233 Wakulla Industrial Private 30.2114 -84.3703 

FLA010237 Wakulla Domestic Private 0.06 Reuse system Active 30.0670 -84.2967 83

FLA010238 Wakulla Domestic Private 0.024 Reuse system Active 30.0849 -84.3869 83

LUBE FLA010239 Wakulla Industrial Private Active 30.2066 -84.3660 83

FLA010240 Wakulla Industrial Private Active 30.1603 -84.2918 83

WWTP FLA010241 Wakulla Domestic Private 0.025 Percolation Active 30.2050 -84.2517 83

FLA010242 Wakulla Domestic Private 0.024 Percolation Active 30.0587 -84.2895 83

FLA016544 Wakulla Domestic Private 0.495 Sprayfield Active 30.2566 -84.2184 83

FLA102318 Wakulla Domestic City 0.05 Industrial reuse 30.1532 -84.2076 

 & LAUNDROMAT FLA185965 Wakulla Industrial Private 0.003 Under Construction 30.2329 -84.2304 83

OCESSING FACILITY FLA188824 Wakulla Industrial Private 0.0005 Active 30.0608 -84.4897 83

FLG110265 Wakulla Industrial Private Active 30.0363 -84.2882 
 134

Table A7. Domestic WWTF Effluent Total Nitrogen (kg-N/yr) Loading Rates. 

PERMIT NO. COUNTY

METHOD DATA SOURCE FACTOR 

USED** 

1992 1993 1994 1995 1996 1997 1998 1999 

FLA010137 LEON design flow factor Wakulla High School 2 343 390 254 284 512 235

FLA010172 LEON design flow factor Wakulla County 0.87 1025* 2367* 

FLA010173 LEON design flow factor Lake Jackson 1.17 5221 3676 4288 3916 3532 3076

 FLA010148 LEON design flow factor Shadeville Elem 2.25 346 634 235 204

FLA010171 LEON concentration sub T.P. Smith 4462 3142 3665 3347 3018 2629

F FLA010159 LEON design flow factor St. Marks 1.2 231

FLA010139 LEON 283431 193830 253445 202634 226619 258305 213391 222624 

FLA010140 LEON 127932 128941 96726 108424 87554 95080 124146 102184 

ORT FLA010141 LEON 1186 1436 1191 1179 1129 1058

FLA010136 LEON design flow factor Shadeville Elem 0.62 95 175 65 56

FLA010237 WAKULLA design flow factor St. Marks 1 193

WWTP FLA010241 WAKULLA design flow factor Shell Point 1 220 147 96 100 206 141

FLA010242 WAKULLA concentration sub T.P. Smith 220 147 96 100 206 141

FLA010225 WAKULLA concentration sub T.P. Smith 2087 1861 1881 1963 1827 2085 1059 1853 

TF FLA010227 WAKULLA 154 282 104 90

FL0040835 WAKULLA 193

FLA010226 WAKULLA concentration sub Shadeville Elem 172 195 127 142 256 118

FLA010228 WAKULLA 147 81 80 290 182 146 173* 

FLA010238 WAKULLA 202* 301

FLA010229 WAKULLA concentration sub Shadeville Elem 190 230 112 82 78 122 108* FLA016544 WAKULLA concentration sub T.P. Smith 478* 1313 1219 

than six months data 

ased on design capacity 
 135

Table A8. Construction Details for Southeast Sprayfield Monitor Wells.

NWF ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

1148 302045084120901 AAA2956 SE04 (1148) 47 42 27.57 302044.638 841207.691

1149 302045084123701 AAA2955 SE23 (1149) 57 48 32.48 302047.191 841235.817

1150 302045084123702 AAA2953 SE50 (1150) 129 125 32.93 302047.313 841235.897

1153 302046084113801 AAA2954 SE24 (1153) 58 56 24.55 302046.749 841137.816

1154 302046084113802 AAA2952 SE51 (1154) 170 146 25.67 302046.916 841137.904

1156 302049084120901 AAA2994 SE02 (1156) 46 42 26.05 302049.917 841208.043

1162 302051084113801 AAA2992 SE21 (1162) 139 125 27 302051.579 841138.048

1163 302051084113802 AAA2991 SE20 (1163) 53 50 30.22 302051.808 841138.317

1164 302051084120901 AAA2999 SE22 (1164) 127 102 27.96 302051.093 841208.793

1165 302051084123501 AAA2998 SE17 (1165) 122 112 31.38 302051.713 841235.515

1166 302051084123502 AAA2996 SE16 (1166) 70 60 29.84 302052.148 841234.927

1171 302053084115101 AAA3023 SE09 (1171) 52 51 36.99 302052.479 841151.201

1172 302053084115102 AAA3022 SE10 (1172) 133 124 39.2 302052.57 841151.771

1183 302058084105101 AAA3018 SE46 (1183) 174 171 27.41 302059.351 841051.024

1184 302058084105102 AAA3019 SE47 (1184) 45 31 27.71 302059.351 841051.024

1185 302058084105103 SE57 (1185) 25 20 29.32 302058 841051 

1208 302110084110601 AAA2975 SE43 (1208) 183 174 40.3 302112 841107 

1209 302110084110602 AAA2974 SE44 (1209) 120 109 41.67 302112 841107 

1210 302110084110603 AAA2973 SE45 (1210) 72 55 42.39 302112 841107 

1223 302114084105201 AAA3015 SE37 (1223) 240 191 32.17 302118.416 841052.563

1224 302114084105202 AAA3017 SE38 (1224) 115 101 32.73 302118.254 841052.177

1225 302114084105203 AAA3016 SE39 (1225) 73 63 32.28 302118.038 841052.56 

1232 302116084120701 AAA2957 SE03 (1232) 62 54 42.02 302115.355 841203.194

1233 302116084123701 AAA2960 SE01 (1233) 71 57 20.38 302115.897 841237.083

1240 302117084113801 AAA2989 SE19 (1240) 74 52 46.88 302117.909 841137.766

1288 302141084114001 AAA2965 SE18 (1288) 62 52 59.44 302141.89 841139.696

1289 302141084123601 AAA2963 SE14 (1289) 51 47 35.44 302142.681 841234.201

1290 302141084123602 AAA2962 SE15 (1209) 102 96 34.8 302141.996 841234.172

1291 302141084123603 AAA2961 SE68 (1291) 35 35 36.28 302142.166 841234.472

1307 302150084103801 AAA3014 SE49 (1307) 55 47 33.41 302148.119 841039.432

1311 302151084111901 AAA2906 SE40 (1311) 194 164 47.2 302149.645 841120.318

1312 302151084111902 AAA2907 SE41 (1312) 134 120 47.27 302149.458 841120.009

1313 302151084111903 AAA2908 SE42 (1313) 65 43 47.84 302149.328 841120.355

1333 302157084115101 AAA2968 SE06 (1333) 102 101 50.16 302159.494 841151.288

1334 302157084115102 AAA2967 SE07 (1334) 242 214 51.11 302159.468 841151.772

1344 302203084110001 AAA2976 SE48 (1344) 95 89 54.18 302148.151 841039.476

1348 302204084102401 SE05 (1348) 122 120 40 302204 841024 

1352 302208084123801 AAA2964 SE12 (1352) 55 51 46.56 302208.894 841236.845

7223 302050084110502 SE53 (7223) 100 93 27.9 302050.127 841105.812

7268 302146084110301 AAA3011 SE11N (7268) 70 55.23 302146 841103 

7269 302146084110302 AAA3012 SE11S (7269) 88 55.21 302146 841103 

7270 302051084120501 AAA2969 SE22A (7270) 121 31.87 302051.303 841205.68 

7279 302115084120501 AAA2958 SE28 (7279) 23 42 302115.361 841205.867

7280 302051084113803 AAA2993 SE29 (7280) 22 30.21 302051.58 841138.098

7281 302049084120902 AAA3000 SE30 (7281) 12 29.64 302050.58 841208.6 

7282 302118084113701 AAA2990 SE31 (7282) 22 49.16 302118.086 841137.566

7283 302101084123701 AAA2995 SE33 (7283) 17 26.95 302104.299 841237.055

7284 302051084123503 AAA2997 SE34 (7284) 22 33.77 302051.972 841235.078
 136

Table A8. Construction Details for Southeast Sprayfield Monitor Wells [cont].

7285 302050084110501 AAA2972 SE52 (7285) 53 29.41 302050.365 841105.868

7290 302157084115104 AAA2966 SE54 (7290) 43 52.89 302159.744 841151.771

7291 302045084120902 AAA2951 SE55 (7291) 34 29.39 302044.723 841207.765

7292 302053084115103 AAA3021 SE56 (7292) 35 39.09 302052.661 841151.623

7293 302114084105204 SE58 (7293) 36 33.45 302114 841052 

7294 302150084103802 AAA3013 SE59 (7294) 30 34.65 302148.06 841039.423

7295 302117084113803 AAA2988 SE60 (7295) 36 44 302117.732 841137.152

7296 302125084120601 AAA2956 SE61 (7296) 35 29 47 302210.84 841143.83 

7297 302212084114402 AAA3010 SE62 (7297) 35 26 45 302210.845 841143.83 

7298 302209084123601 AAA2935 SE63 (7298) 46 302209.044 841236.278

7299 302123084120901 AAA2950 SE64 (7299) 32 27 38 302117.359 841207.807

7300 302110084110604 SE65 (7300) 30 25 42.28 302110 841106 

7301 302050084115101 AAA3020 SE66 (7301) 35 30 33.27 302049.772 841151.545

7302 302050084110503 AAA2970 SE67 (7302) 35 30 29 302050.312 841106.025

7303 302048084115101 AAA2909 SE69 (7303) 30 25 22.9 302047.489 841151.558

7304 302046084113803 AAA2949 SE70 (7304) 17 12 27.13 302046.81 841137.788

7836 302212084114401 SES (7836) 200 84 46.61 302210.5 841144.04 

7864 302129084091701 SE75 (7864) 32 22 36.69 302129.52 840917.94 

7865 302129084091801 SE76 (7865) 57 47 36.04 302129.46 840918.78 

7866 302053084100401 SE77 (7866) 57 47 32.17 302053.76 841004.56 

7867 302153084100402 SE78 (7867) 127 105 32.9 302053.64 841004.74 

7868 302104084094801 SE79 (7868) 43 34 45.35 302104.2 840948.6 

7869 302102084094801 SE80 (7869) 57 47 44.97 302102.76 840948.3 

7870 302149084094201 SE81 (7870) 37 27 33.7 302149.32 840942.48 

7871 302148084094101 SE82 (7871) 50 40 33.41 302148.06 840941.58 

7872 302202084091901 SE83 (7872) 27 17 36.77 302202.04 840919.2 

7873 302204084091901 SE84 (7873) 45 35 36.22 302204.32 840919.5 

7874 302100084092401 SE85 (7874) 17 7 28.65 302100.48 840924 

7875 302100084092001 SE86(7875) 127 105 30.33 302100 840920 

7888 302208084114101 SE FARMERS (7888) 50 302208.478 841141.726

7889 302209084084801 MESSER WELL (7889) 40 302209.628 840848.056

7890 302236084075601 BARKER WELL (7890) 120 302236.119 840756.475
 137

Table A9. Construction Details for Southwest Sprayfield Monitor Wells. 

NWF 

ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

1253 302122084194001 LS19 (1253) 80 78 39.34 302122 841940 

1276 302135084202001 AAA0258 LS20 (1276) 145 145 29.24 302133.76 842019.13 

1351 302206084194001 LS13 (1351) 37 35 42.2 302206 841940 

1411 302233084194101 LS05 (1411) 51 33 50.37 302256 841935 

1412 302234084193901 LS14 (1412) 55 53 44.52 302234 841939 

1417 302235084190301 AAA0255 LS04 (1417) 53 38 44.56 302235.53 841902.33 

1460 302252084192901 LS22 (1460) 268 268 48.64 302252 841929 

1466 302256084185801 LS02 (1466) 75 51 52.05 302256 841858 

1470 302257084191101 LS26 (1470) 185 185 55 302257 841911 

1474 302258084193001 LS17 (1475) 152 152 48.73 302258 841930 

1496 302301084192901 LS10 (1496) 43 41 58 302301 841929 

1497 302301084192902 LS18 (1497) 160 54 58.25 302301 841929 

1511 302303084190901 AAA2937 LS25 (1511) 69 54 65 302303.984 841909.125

1534 302308084185601 BOG 2-7 (1534) 36 34 63.7 302308 841856 

1535 302308084195301 LS06 (1535) 45 35 40.58 302308 841953 

1542 302309084185701 AAA8325 LS32 (1542) 80 58 64.05 302304.059 841857.765

1543 302309084191101 LS12 (1543) 50 48 58.36 302309 841911 

1550 302310084191901 LS23 (1550) 240 240 52.48 302310 841919 

1554 302313084191001 BOG 2-1 (1554) 25 23 55.57 302313 841910 

1555 302313084191301 LS01 (1555) 61 45 56.32 302313 841913 

1556 302313084191302 LS15 (1556) 47 45 55.6 302313 841913 

1557 302313084192201 LS09 (1557) 42 40 48.54 302313 841922 

1559 302314084190901 BOG 6-4 (1559) 43 41 55.57 302314 841909 

1560 302314084190902 BOG 4-2 (1560) 70 60 55 302314 841909 

1561 302314084192201 BOG 2-2 (1561) 22 20 69 302314 841922 

1568 302315084192401 BOG 2-3 (1568) 26 24 56.6 302315 841924 

1569 302315084192801 AAA2936 LS21 (1569) 248 247 58.32 302317.474 841927.976

1573 302316084191101 LS08 (1573) 49 47 57.3 302316 841911 

1584 302318084192801 BOG 6-3 (1584) 52 44 60.21 302318 841928 

1590 302319084220601 LS24 (1590) 260 260 105.5 302319 842206 

1595 302320084192901 BOG 2-4 (1595) 48 46 55.95 302320 841929 

1599 302321084193001 BOG 4-1 (1599) 89 87 57.37 302321 841930 

1608 302322084193201 BOG 2-5 (1608) 49 47 54.75 302322 841932 

1609 302322084193601 LS07 (1609) 35 27 37.42 302322 841936 

1613 302323084191201 LS11 (1613) 40 38 51.72 302323 841912 

1614 302323084193001 BOG 2-6 (1614) 50 48 61.15 302323 841930 

1625 302325084191601 LS16 (1625) 67 65 58.54 302325 841916 

1640 302328084192701 BOG 6-1 (1640) 292 80 67.43 302328 841927 

1656 302332084191901 LS03 (1656) 104 93 69 302332 841919 

7860 302314084191501 LS27 (7860) 150 54 302315 841915 

7861 302314084191502 LS28 (7861) 158 145 54 302314 841915 

7862 302312084191301 LS29 (7862) 250 153 54 302312 841916 

7863 302206084194002 LS30 (7863) 150 148 42 302206 841940 
 138

Table A10. Construction Details for Residual Disposal Monitor Wells.

NWF ID Site ID FLUID Well Name 

Total 

Depth

Casing 

Depth

Land 

Surface 

Elevation Latitude Longitude 

1512 302303084213701 SF01 (1512) 40 26 35.28 302304.129 842136.789

1663 302334084222901 SF03 (1663) 88 60 76.73 302334 842229 

1685 302341084222501 SF02 (1685) 102 94 40 302341 842225 

7831 302325084221701 SF04 (7831) 98 90 100.02 302325.98 842217.34 

7832 302230084213101 SF05 (7832) 29 35.17 302230.12 842131.32 

7833 302303084211001 SF06 (7833) 63 60.26 302303.84 842110.86 

7838 302351084200701 T01 (7838) 62 72.9 302351.24 842007.62 

7839 302341084195201 T02 (7839) 79 44.96 302342.96 841953.58 

7840 302336084201101 T03 (7840) 31 50 302336 842011 

7841 302335084193801 T04 (7841) 44 60 302335 841938 

7842 302324084194501 T05 (7842) 39 40 302324 841945 

7843 302323084195401 T06 (7843) 40 35.83 302322.56 841949.44 

7844 302325084201001 T07 (7844) 65 40 302325 842010 

7845 302327084200801 T08 (7845) 40 40 302327 842008 

7846 302327084200802 T09 (7846) 16 40 302327 842008 

7847 302328084201201 T10 (7847) 42 40 302328 842012 

7848 302336084201301 T12 (7848) 56 50 302336 842013 

7849 302335084193601 T13 (7849) 50 60 302335 841936 

7850 302335084193602 T14 (7850) 45 60 302335 841936 

7851 302321084194701 T15 (7851) 47 30 302321 841947 

7852 302321084194702 T16 (7852) 29 30 302321 841947 

7853 302320084194401 T17 (7853) 31 30 302320 841944 

7854 302320084194402 T18 (7854) 16 30 302320 841944 

7855 302318084194901 T19 (7855) 34 30 302318 841949 

7856 302318084194902 T20 (7856) 14 50 302318 841945 

7857 302328084201203 T23 (7857) 99 35.4 302325.38 842012.12 

7858 302343084195101 T24 (7858) 81 70 302343 841951 

7859 302343084195102 T25 (7859) 52 70 302342 841951 

7879 300904084212001 YOUNG FARM (7879) 15 300903.598 842119.924

7880 300833084214401 DAVIS FARM (7880) 20 300832.997 842144.419

7881 300859084215501 COUNCIL #1 (7881) 15 300859.743 842155.49 

7882 300848084215101 COUNCIL #2 (7882) 15 300848.291 842151.568

7883 301410084210601 RAKER FARM (7883) 20 301409.894 842106.477

7884 300844084172701 LAWHON WELL 15 300844.13 841727.396

7885 300901084175401 PETTY #1 (7885) 25 300900.872 841753.735

7886 300906084174101 PETTY #2 (7886) 25 300906.068 841741.803

7887 300941084172201 PETTY #3 (7887) 25 300941.748 841722.382