Abstract

As part of the southeastern United States SPARROW (SPAtially Referenced Regressions On 

Watershed attributes) water-quality model implementation, the U.S. Geological Survey created a 

dataset to characterize the contribution of phosphorus to streams from weathering and erosion of 

surficial geologic materials. SPARROW provides estimates of total nitrogen and phosphorus loads in 

surface waters from point and nonpoint sources. The characterization of the contribution of phosphorus 

from geologic materials is important to help separate the effects of natural or background sources of 

phosphorus from anthropogenic sources of phosphorus, such as municipal wastewater or agricultural 

practices. The potential of a watershed to contribute phosphorus from naturally occurring geologic 

materials to streams was characterized by using geochemical data from bed-sediment samples collected 

from first-order streams in relatively undisturbed watersheds as part of the multiyear U.S. Geological 

Survey National Geochemical Survey. The spatial pattern of bed-sediment phosphorus concentration is 

offered as a tool to represent the best available information at the regional scale. One issue may weaken 

the use of bed-sediment phosphorus concentration as a surrogate for the potential for geologic materials 

in the watershed to contribute to instream levels of phosphorus—an unknown part of the variability 

in bed-sediment phosphorus concentration may be due to the rates of net deposition and processing 

of phosphorus in the streambed rather than to variability in the potential of the watershed’s geologic 

materials to contribute phosphorus to the stream. Two additional datasets were created to represent 

the potential of a watershed to contribute phosphorus from geologic materials disturbed by mining 

activities from active mines and inactive mines.

Introduction

The largest reservoir of phosphorus (P) in the environment is minerals in sedimentary rocks (Mueller 

and Helsel, 1996). Although, in general, phosphorus compounds in rock minerals are relatively insoluble 

and do not readily move in runoff or groundwater, erosion of surface soil and rock may be a substantial 

source of suspended phosphorus in streams in some areas where sedimentary rock is exposed, where 

soils derived from sedimentary rock exist (Dillon and Kirchner, 1975), or especially where deposits of 

phosphorus minerals are mined. Phosphate mineral deposits in consolidated material in the southeastern 

United States generally are of two types—phosphate nodules (oolites, or grains incorporated in sedimentary rocks) and accumulations in residuum derived from the weathering of bedrock (U.S. Geological 

Survey, 1968). In addition, ore-grade deposits of phosphate minerals are present in formations of large 

areal extent in Florida and Tennessee (two areas where phosphate output is the largest in the Nation) 

and in formations of smaller areal extent in North Carolina and Alabama. Data describing phosphate 

mineral content of ore material are available for many mined areas; however, these data cannot be used 

to characterize the mass of P contributed from the watershed without additional information on density 

and distribution of the ore material within the host rock. Phosphorus concentrations in streambed 

sediment, however, may represent average phosphorus levels in the surficial geologic material of 

the contributing watershed and delivery of this material to the stream (Cannon and others, 2003). 

The U.S. Geological Survey (USGS) created a dataset to characterize the potential for a watershed 

to contribute phosphorus to streams from weathering and erosion of surficial geologic materials. 

The motivation for creating this dataset was to support calibration of a phosphorus-transport model 

(SPARROW—SPAtially Referenced Regressions On Watershed attributes) for streams in the southeastern 

United States. SPARROW (Schwarz and others, 2006) provides estimates of total nitrogen and phosphorus loads in streams from point and nonpoint sources, including background, or naturally occurring, 

sources. The data also may be useful for a variety of other purposes, including understanding regional 

background variations in surface-water phosphorus concentrations and developing nutrient criteria.

Mapping Watershed Potential to Contribute Phosphorus from 

Geologic Materials

In order to create a map of bed-sediment phosphorus concentration values that can be applied to 

the entire Southeast, values of phosphorus were compiled and summarized by geologic map units. 

The source data for phosphorus concentration, the method of deriving geologic map units, and the 

identification of phosphorus mine locations are described below.

Bed-Sediment Phosphorus Concentration Source Data

The USGS National Geochemical Survey (NGS) compiles data on geochemistry of stream-channel 

sediment (first-order streams) and soil in order to construct geochemical maps and refine estimates 

of baseline concentrations of chemical elements (U.S. Geological Survey, 2004). Phosphorus data are 

incorporated into the NGS data base primarily from the re-analysis of a subset of samples collected 

between 1976 and 1980 for the National Uranium Resource Evaluation (NURE) Program (Averett, 

1984) and analyses of new samples collected during 1997–1999 and 2004–2006 by the USGS and 

collaborating State agencies. In the Southeast, the NGS contains nine datasets based on NURE samples 

(Alabama I, Alabama II, Coastal 98, Coastal 99, Kentucky, South Carolina, 2000, 2002, and 800) for a 

total of 6,842 samples, and nine State datasets (Alabama, Florida I, Florida II, Georgia, Mississippi I, 

Mississippi II, States 2006a, States 2006b, and Tennessee) for a total of 3,280 samples (U.S. Geological 

Survey, 2004). Thus, 10,122 bed-sediment samples were available across the southeastern U.S. for 

mapping bed-sediment phosphorus concentration (BSPconc; fig. 1). 

to be excluded from the analysis was, in most cases, due to location of the excluded site on a firstorder stream too small for representation by 1:100,000 hydrography. The distribution of land-cover 

characteristics of watersheds for the 5,560 sampling sites confirms that the majority of the sites represent 

basins with little urban development; that is, land cover is less than 0.1-percent developed in half of the 

watersheds and less than 5-percent developed in 90 percent of the watersheds. Although some of the 

sites are affected by agricultural activity (land cover is more than 50-percent agricultural for 10 percent 

of the sites), the majority of the sites are relatively undisturbed (less than 12-percent agricultural in half 

of the watersheds).

Based on the characteristics of the target stream population, several assumptions can be made about 

the bed-sediment BSPconc from this dataset: 

• BSPconc values from the majority of these sites represent conditions with minimal anthropogenic sources in the watershed, and consequently, the average values of BSPconc for different 

subregions indicate spatial variation in the potential of the upstream watershed to contribute P

from naturally occurring geologic materials to the receiving stream channel. 

• BSPconc values represent the potential contribution of P from the local area adjacent to the 

sampling site (Bolivar, 1980). 

• BSPconc values represent streambed conditions in small headwater stream channels. 

All three of these assumptions are critical to the interpretation and application of the data in this report.

Delineating Geologic Map Units

The BSPconc values were grouped into geologic map units (GMUs), defined by using regionalscale geologic features, and averaged to a single value for each GMU. The grouping and averaging 

accomplished two objectives: (1) creating a continuous surface of BSPconc throughout the Southeast 

regardless of sample-site density, and (2) minimizing the effect of BSPconc values that are affected by 

human activity. As previously discussed, the site-selection strategy for the bed-sediment data networks 

in NGS favor sites in relatively undisturbed areas; in practice, however, the BSPconc results at some 

sites may be affected by anthropogenic sources. Potential bias introduced by these sites was minimized 

by averaging values from many sites within a GMU. 

The GMUs were created by delineating zones with similar lithochemistry based on geologic 

age (King and Beikman, 1974) and geomorphic setting (indicated by level IV ecoregions; U.S. 

Environmental Protection Agency, 2007). The digital maps of geologic age and level IV ecoregions were 

overlain and merged to create unique GMUs for each combination of geologic age and ecoregion. This 

combination creates units with similar geologic properties and accounts for regional variations reflected 

by ecoregions. Additional boundaries representing known phosphate-rich formations in Tennessee and 

Florida were incorporated to refine the GMU boundaries in these areas (Smith and Whitlatch, 1940, 

p. 8, 15; Clawges and Price, 1999; fig. 2).

Characterization of Bed-Sediment Phosphorus Concentration Using 

Geologic Map Units

By overlaying and merging digital maps of geologic age, level IV ecoregions, and boundaries of local 

formations, a set of 608 GMUs were delineated for the Southeast. GMUs smaller in area than 30 km2

were combined with an adjacent GMU to remove the artifact of numerous small units created along the 

edges of the intersecting map layers. The GMUs with fewer than three stream sites were considered 

to have insufficient data points to define a representative mean value and, therefore, were classified as 

“data poor.” The 278 GMUs in the data-poor classification compose only about 8 percent of the study 

area. An algorithm was developed to compute new values for the data-poor GMU by averaging the datapoor value with the mean BSPconc value from other GMUs with at least one of the following prioritized 

criteria: (1) GMUs within the same level III ecoregion and of the same geologic age as the data-poor 

GMU; (2) GMUs with the same geologic age (regardless of ecoregion) and adjacent to the data-poor 

GMU; or if these first two conditions fail, (3) using BSPconc values from all adjacent GMUs to calculate 

a mean BSPconc value for the data-poor GMU. A final test was conducted to determine if the new 

BSPconc value assigned to the data-poor GMU differed by more than 500 parts per million (ppm) from 

the original GMU BSPconc values. If this was the case, mean BSPconc values using all three conditions 

were calculated, and the BSPconc value closest to the original value was used. The areal extent and 

location of the data-poor GMUs are summarized in table 2 and displayed in figure 4, respectively.

The spatial pattern in BSPconc was evaluated with respect to the GMU boundaries using one-way 

ANOVA and the Tukey multiple-comparison test. The GMUs explained 56 percent of the total variation 

in BSPconc, and distributions between some GMUs were sufficiently different (at alpha = 0.1) to enable 

division into distinct groupings. Figure 5 displays the mean BSPconc from phosphorus values of bedsediment samples collected in undisturbed, headwater streams within a GMU .

Delineating Areas Affected by Phosphate Mining

In this analysis, P derived from geologic material that has been extracted from a subsurface deposit 

and placed on the land surface was characterized separately from P derived from naturally occurring 

geologic materials in a watershed. The mapped location and description of phosphate mines from the 

Mineral Resources Data System (MRDS; U.S. Geological Survey, 2005b) were used to identify all 

possible areas where disturbed geologic materials may affect instream P concentration. The MRDS 

dataset contains 839 mine sites, active and inactive, in the southeastern United States. The determination 

of mine status is based on information from the active mines and mineral plants in the U.S. dataset 

(U.S. Geological Survey, 2005a), which identifies 19 of the 839 phosphate mines sites as active mines. 

Only two active mine operations were identified outside of Florida, one in Mississippi and one 

in North Carolina. Boundaries of mined land for these operations were estimated by using aerial 

photography (fig. 3A). High-resolution imagery was used to identify the parcels and delineate the 

boundary for the mined areas. 

Because delineations of inactive mine operations were not available outside of west-central Florida, 

and because the land use at the inactive mine locations has been altered making it difficult to identify 

using current aerial photography, an estimate of the area associated with an inactive phosphate mine was 

based on active mining operations within a GMU. The mean area value of mined land (area classified as 

barren land in the NLCD (Homer and others, 2004) observed for a subset of mine operations within the 

GMU was assigned to inactive phosphate mine locations (fig. 3B). For example, inactive mine operations 

in central Tennessee were assigned a mined-land area of 0.1 km2, whereas inactive mine operations in 

southwestern Florida were assigned a mined-land area of 4.3 km2. The areal extent was represented as 

a circular area centered over the coordinate of the point location (from MRDS), with radius sized to 

match the assigned area (for example, radii of 35 or 1,171 meters to correspond with assigned areas of 

0.004 or 4.3 km2). 

For mining operations in west-central Florida, boundaries of mined land were estimated by 

using a combination of geospatial datasets describing location of land parcels and barren land cover 

(fig. 3C). The Mandatory Phosphate Mine Boundaries geospatial dataset from the Florida Department 

of Environmental Protection (2007) was used to delineate land parcels identified as inactive and active 

mining operations. The parcels from this layer were combined with the set of parcels of land disturbed 

by phosphate mining prior to 1975 (Zellar-Williams, Inc., and Conservation Consultants, Inc., 1980), 

some of which represent mines that are still active. Areas of actual mining activities within each of 

these parcels were identified and coded by using the areas classified as barren in the NLCD. For parcels 

identified by the Mandatory Phosphate Mine Boundaries not included in the Zellar-Williams parcels, 

only the sections that were classified as barren were considered to represent the areal extent of mined 

land. For parcels identified by the Zellar-Williams report, which explicitly delineate disturbed land, 

the entire parcel area (not just NLCD barren land) was used to represent the areal extent of mined land. 

Characterization of Contribution of Phosphorus to Streams from 

Geologic Materials Disturbed by Mining Activities

During phosphate mining activity, phosphate-rich mineral deposits are disturbed and can affect the 

concentration of P in nearby streams. Estimates of the potential of an upstream watershed to contribute P 

to streams from runoff from areas of disturbed geologic materials can be developed as a simple function 

of areal extent of mined land in the watershed, or as a combined function of areal extent of the mined 

land and the level of phosphate enrichment in the mined deposit. Following the second approach, a 

series of graded step functions was developed by assigning zero for areas mapped as undisturbed and by 

assigning a gradient of values in disturbed areas that reflects the varying levels of phosphate enrichment 

in mined deposits. A value for potential was assigned to each mined area in the Southeast by associating 

the estimated mined-area polygon with the overlapping GMUs. The method may assign a value to a mine 

based on bed-sediment sampling sites outside the estimated mined-area polygon (fig. 6A, B), depending 

on the location of the maximum BSPconc in the GMU relative to the polygon. 

The status of a mining operation was used to weight the value associated to a mine. An active mine is 

assigned the maximum value within the GMU that its areal extent overlaps, whereas an inactive mine is 

assigned a value midway between the maximum and mean value of the GMU that its areal extent overlaps. 

This is illustrated in figure 6C, for a GMU for which the maximum BSPconc for bed-sediment sampling 

sites is 9,176 ppm and the average BSPconc is 708 ppm. The GMU contains mine polygons that fall in 

both active and inactive mining activity zones; active mines were assigned the value 9,176 ppm (GMU 

maximum) and inactive mines were assigned the value of 4,942 ppm (average of 9,176 and 708 ppm). 

This approach makes two assumptions, both with unknown validity: (1) ore of similar phosphatemineral content is extracted from mines within the same GMU, and (2) the BSPconc for at least one 

sample within the GMU reflects the influence of phosphate-mining activity. Estimates of BSPconc 

therefore, may be less reliable in areas with high density of mined land, as the density of geochemical 

survey data is insufficient to determine variable loading rates among individual mines or to differentiate 

contributions from mined-land from contributions from natural, undisturbed land in these areas.

Using Regionalized Bed-Sediment Phosphorus Concentration in Watershed Models to Characterize Contribution of Phosphorus to Streams 

Calibration and application of watershed models of instream transport and concentration of P require 

characterization of the potential of the upstream watershed to contribute P from naturally occurring 

geologic materials in the watershed to instream (water-column) P flux in the receiving stream. For an 

empirical watershed model such as SPARROW, characterizing potential contribution in absolute mass 

units is not necessary; rather, characterizing the relative variability, or gradient, of contribution across 

the region is sufficient. SPARROW’s regression analysis determines the appropriate functional relation 

between the explanatory variable (for example, BSPconc) and the mass contributed to instream P flux. 

The spatial distribution of BSPconc from the NGS dataset, which represents headwater streams 

draining relatively undisturbed watersheds, is useful for modeling the gradient in potential to contribute 

P to streambed sediments in headwater streams. The response variable of interest in watershed models, 

however, generally is contribution to instream flux rather than contribution to streambed sediments, 

and it is not clear that spatial distribution of BSPconc is useful in modeling instream P flux. Instream 

P flux and BSPconc in headwater streams are influenced by several of the same factors—variation 

in availability of P in geologic materials in the watershed and variation in basin rates of erosion and 

transport of P to the edge of the stream. BSPconc is influenced further by variation in the rates of net 

deposition and processing of P in the streambed (McDowell and Sharpley, 2001; Walling and others, 

2003). The spatial pattern of BSPconc, therefore, is useful as a surrogate for watershed contribution to 

instream P flux only under the assumptions of (1) equal rates across all headwater streams in the region, 

(2) net deposition from the water column, and (3) processing within the streambed sediment. Such 

assumptions are challenged by known variability among headwater streams in frequency of flushing, 

occurrence of low dissolved-oxygen conditions, and aquatic-plant processing. The spatial pattern of 

BSPconc is offered as a tool, representing the best available information at the regional scale, with the 

caveat that the surrogate relation is weakened by not accounting for variability in headwater streams in 

the rates of net deposition and processing of P in the streambed. 

Data Layer Products

This study has resulted in three separate spatial data layers. “Pconc_background” characterizes the 

potential of a watershed to contribute P to streams from geologic materials that are undisturbed by mining or 

other human activities (fig. 5). “Pconc_active_mined” and “Pconc_inactive_mined” characterize the potential 

of a watershed to contribute P to streams from geologic materials that have been disturbed by mining activities 

(fig. 6). The data layers were each allocated to 8,404 individual watershed segments in the southeastern 

SPARROW study area for use as variables in the model to predict contribution of phosphorus to a stream 

from these two separate source categories. Data layers are available upon request from the USGS North 

Carolina Water Science Center (request form available at http://nc.water.usgs.gov/about/inforequests.html).

Acknowledgments

The authors gratefully acknowledge Dr. Jeffrey Grossman, USGS, for providing data and technical 

guidance throughout this study. The authors also thank Dr. Gerard McMahon and Michael Wieczorek of 

the USGS for their review of the manuscript. 

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and potential to influence stream P concentrations: Aquatic Geochemistry, v. 7, no. 4, p. 255–265.

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Streams for bed-sediment sampling in the Southeast for the NURE program were selected randomly 

from topographic maps marked with grids that cover 10 to 30 square kilometers (km2), with an average 

density of one site per 13 km2. If possible, no sites were selected that were closer than 1.5 kilometer 

(km) to another site, and the area drained was no more than three times the area of the grid so that the 

maximum size of a basin draining to a site would be 90 km2. The largest headwater stream within the grid 

was chosen if the site was accessible to field personnel (Bolivar, 1980), and an attempt to sample most 

streams draining from 8 to 26 km2 (3 to 10 square miles) was made (Ferguson and others, 1976). Samples 

were collected upstream from roads, ponds or other disturbances that could have altered the sampling 

results, and samples were collected outside of populated areas (Information Systems Programs, Energy 

Resources Institute, 1985) in order to accurately represent the local-scale variation in sediment mineral 

composition with surficial geology or other geographical characteristics. In the development of datasets 

for the NGS, NURE samples in most areas were selected randomly for re-analysis in order to achieve a 

density of approximately one sample per 289 km2; however, in densely sampled areas in Kentucky and 

Alabama, all of the NURE samples were re-analyzed. 

In order to verify that samples were in general from small, undisturbed basins, basin drainage area 

and watershed percentage of developed and agricultural area at each sampling site in the Southeast 

SPARROW study area (7,421 of the 10,122 sampling sites) were examined using the National 

Hydrography Dataset Plus (NHDPlus, 2009). The NHDPlus maintains tables that include cumulative 

drainage area and basin characteristics derived from the 1992 National Land-Cover Data (NLCD; 

Vogelmann and others, 2001) for every stream segment. Because most samples were taken before 1997, 

the 1992 land-cover data were most appropriate to use for evaluating anthropogenic effects.

Of the 7,421 sampling sites within 

the SPARROW study area, 5,560 could 

be assigned with confidence (within 

200 meters) to an individual stream segment 

on the 1:100,000-scale NHDPlus. The size 

distribution of watersheds for these sites 

confirms that the sites drain small areas;

half of the sites drain areas smaller 

than 9.1 km2

 and 90 percent of the 

sites drain areas smaller than 47 km2

(table 1). Presumably these values would 

be even lower had all 7,421 sampling 

sites been included in the analysis; the 

lack of association with the 1:100,000-

scale NHDPlus that caused 1,861 sites 

Bed-sediment sampling site

EXPLANATION

ATLANTIC

OCEAN

GULF OF MEXICO

Base modified from U.S. Geological Survey

National Elevation Dataset, 100-meter resolution

Table 1.  Basin drainage areas and percentages of agricultural

land and developed land for National Geochemical Survey

stream sites sampled for bed-sediment phosphorus content

in the southeastern United States.

Percentile

Cumulative 

drainage 

area, in 

square 

kilometers

Agricultural 

land

Developed 

land

Forested 

land

Percentage in 1992

10th 2.2 0 0 2

25th 4.2 2.1 0 18.9

50th 9.1 12 0.1 37.9

75th 19.3 30.5 0.9 53.2

90th 46.6 50.3 5.1 67.2

Mean 56.4 19.2 2.4 36.9

A

B

Data-sufficiency classification

EXPLANATION

Poor (0 data points)

Poor (1–2 data points)

Sufficient, no adjustment

(3–805 data points)

Table 2.  Data sufficiency classification and methods for assigning average bed-sediment phosphorus concentrations to

geologic mapping units.

[GMU, geologic map unit; BSPconc, bed-sediment phosphorus concentration; definition of data sufficiency classification: sufficient—sufficient number 

of sampling points (three or more) within the GMU to represent the average condition and no adjustments to mean value, poor—insufficient number of 

sampling points (less than three) to represent the average condition and adjustment to the original mean value was applied; percentages may not add up to 

100 because of rounding]

Data 

sufficiency 

classification

Number of 

GMUs in 

classification

Area, 

in square 

kilometers

Percentage 

of study 

area

Method for assigning an average 

BSPconc value for the GMU

Sufficient 329 993,908 91.7 Average the BSPconc of samples from within the GMU

Poor 244 85,652 7.9 Average the BSPconc of samples from within the GMU 

with average BSPconc from GMUs in same level III 

ecoregion that have the same geologic age

Poor 26 3,279 0.3 Average the BSPconc of samples from within the GMU 

with average BSPconc from adjacent GMUs with the 

same geologic age (regardless of ecoregion)

Poor 9 667 0.1 Average the BSPconc of samples from within the GMU 

with average BSPconc from adjacent GMUs (regardless 

of geologic age and ecoregion)

Total 608 1,083,506 100

90° 88° 86° 84° 82° 80° 78° 76°

40°

38°

36°

34°

32°

30°

28°

26°

Mean bed-sediment phosphorus 

 concentration, in parts per 

 million, by geologic map unit

EXPLANATION

Less than 200.0

200.1 to 300.0

300.1 to 400.0

400.1 to 500.0

500.1 to 700.0

700.1 to 900.0

900.1 to 18,150.0

VIRGINIA

WEST

VIRGINIA

OHIO

ILLINOIS

INDIANA

MISSOURI

ARKANSAS

LOUISIANA

KENTUCKY

TENNESSEE

NORTH CAROLINA

MISSISSIPPI

ALABAMA

GEORGIA

FLORIDA

SOUTH CAROLINA

0 100 200 300 KILOMETERS

0

Base modified from U.S. Geological Survey, National Atlas, 1:2,000,000 scale, 1972

50 100 150 MILES

A T L A N T I C

O C E A N

G U L F O F M E X I C O

A B C

VIRGINIA

KENTUCKY

TENNESSEE

NORTH CAROLINA

MISSISSIPPI ALABAMA

GEORGIA

SOUTH

CAROLINA

FLORIDA

950 9,176

1,890

4,330

28,000

Bed-sediment phosphorus 

 concentration in mined 

 land, in parts per million

Geologic map unit that overlaps 

 areal extent of phosphate-

 mined land

Bed-sediment sampling site and 

 phosphorus concentration, in 

 parts per million—Site with 

 highest concentration value 

 within a geologic map unit

Phosphate mine operations 

 in Florida—Map B

Inactive

Active

Disburbed mine area

EXPLANATION

950

615.0 to 900.0

900.1 to 1,800.0

1,800.1 to 2,700.0

2,700.1 to 4,500.0

4,500.1 to 7,200.0

7,200.1 to 11,700.0

11,700.1 to 19,772.7

A

B C

Mapping Watershed Potential to Contribute Phosphorus from Geologic Materials to Receiving Streams, Southeastern United States

By

Silvia Terziotti, Anne B. Hoos, Douglas A. Harned, and Ana Maria Garcia

U.S. DEPARTMENT OF THE INTERIOR

U.S. GEOLOGICAL SURVEY

SCIENTIFIC INVESTIGATIONS MAP 3102

Mapping Watershed Potential to Contribute Phosphorus, Southeastern United States—SHEET 1 OF 1

Terziotti, Silvia, Hoos, A.B., Harned, D.A., and Garcia, A.M, 2010, Mapping watershed potential to contribute

phosphorus from geologic materials to receiving streams, southeastern United States

Figure 1.  Locations of stream sites sampled for bed-sediment phosphorus concentrations in the

southeastern United States as part of the U.S. Geological Survey National Geochemical Survey.

Figure 2. (A) Level IV

ecoregions (data from U.S.

Environmental Protection

Agency, Level IV Ecoregions,

1:250,000 scale, 2007) and

(B) geology in the southeastern United States (data

from U.S. Geological Survey,

Geologic map of the United

States, 1:2,500,000 scale,

1974. [Colors are used

to illustrate the relative

number of distinct classes,

not to distinguish individual

features].

Figure 3.  Representations of the areal extent of mined land within a phosphate-mine operation. (A) Based

on aerial photography, active mine delineation in North Carolina (red lines indicate areal extent of mined land);

(B) based on average size of barren land polygons within a geologic map unit, inactive mines in Tennessee

(yellow lines represent the geologic map unit boundaries); and (C) based on land parcels and barren land

cover, active and inactive mines in west-central Florida (red lines indicate areal extent of mined land).

Figure 4.  Geologic map

units for which mean

value of bed-sediment

phosphorus concentration

was adjusted because of

insufficient bed-sediment

sampling sites.

Figure 5.  Mean 

Figure 6.  Areal extent of phosphate-mined

land in the southeastern United States

and geologic map units that overlap the

mined land, with estimates of bed-sediment

phosphorus contribution to streams, and

(A) example in Tennessee showing the

locations of phosphate-mined land relative

to the locations of three geologic map units

that overlap the phosphate-mined land, and

the locations of three bed-sediment sampling

sites from which the geologic map unit

maximum concentration value was derived;

(B) example in Florida showing parcels that

contain inactive and active mine operations,

with hachures indicating the disturbed mine

areas within the parcels; and (C) example in

Florida showing how mine operation status

is used to weight the value associated to a

phosphate-mined land area.