U.S. Department of the Interior

U.S. Geological Survey

Fact Sheet 2004-3009

April 2004

Potential Effects of Individual Sewage Disposal System 

Density on Ground-Water Quality in the Fractured-Rock 

Aquifer in the Vicinity of Bailey, Park County, Colorado, 

2001-2002 

Printed on recycled paper

Introduction

Park County, about 30 miles southwest of Denver (fig. 1), 

is one of the fastest growing counties in Colorado. With the 

increasing population and development in rural areas comes an 

increase in demand for water resources, the number of individual 

sewage disposal systems (ISDS), and the potential to affect the 

ground-water quality. Health department officials, planners, and 

County Commissioners in Park County are interested in obtaining information regarding water quality in aquifers that serve 

the residents of the county. In 2000, the U.S. Geological Survey 

(USGS), in cooperation with Park County, began a study to 

determine the effects of residential development and the concurrent increase in ISDSs and the density of ISDSs on ground-water 

quality in the various aquifers in Park County that supply water 

to domestic wells. This report provides a preliminary assessment of water-quality data collected in 2001 from domestic 

wells completed in the fractured-rock aquifer in the vicinity of 

Bailey in northeastern Park County (fig. 1). Water samples were 

collected from 57 domestic wells during 2001, once in July and 

once in September. Samples were analyzed for chemicals and 

bacteria that might indicate whether ISDS effluent has caused 

degradation of ground-water quality. This report also describes 

the preliminary results of five water samples collected in 

October 2002 for tritium analysis.

The granitic and metamorphic (crystalline) rocks (Tweto, 

1979) in the Bailey area contain ground water in fractures and 

form the principal aquifer supplying domestic wells. Reported 

well yields for wells drilled into the fractured crystalline rock 

range from less than 1 gallon per minute (gal/min) to 60 gal/min. 

The variability in well yields depends on many things, including the number of fractures intercepted by a well, the degree of 

openness of those fractures, and the length of the open interval 

of the well (fig. 2). Well yields for sampled wells ranged from 

about 0.5 to 25.5 gal/min. Depths for wells chosen for sampling 

ranged from 85 to 752 feet. The well yields and depths for wells 

sampled are representative of most of the wells drilled in the 

crystalline-rock aquifer in the vicinity of Bailey (Colorado 

Division of Water Resources, 2000).

The amount of time it takes for water to recharge the aquifer 

and reach the wells varies with the openness and connectedness 

of the fractures, the distance from the recharge point to the open 

interval of a well, and the rate of water flow in the fractures. 

Because the rate of recharge and flow in the vicinity of each 

well can vary, it is not known whether ISDS effluent can reach 

the ground water before chemical and biological contaminants 

are removed from the effluent or reduced in concentration. 

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Figure 1. Location of study area.

By Daniel L. Brendle
WELL WITH

LOW YIELD

-OPEN TO FEW

FRACTURES WELL WITH

HIGH YIELD

-OPEN TO MANY

FRACTURES

SOIL/

WEATHERED

GRANITE

LEACH FIELDS

UNSATURATED

ZONE

FRACTURES

FILLED WITH

WATER

WATER TABLE

SATURATED

ZONE

OPEN

INTERVAL OPEN

INTERVAL

ISDS

ISDS ISDS

EFFLUENT

This study was designed to assess whether contamination of 

ground water has occurred and to obtain information that might 

help determine the length of time it takes for ISDS effluent to 

recharge the aquifer. The size of the lots in each development, 

and thus the closeness of neighboring wells and ISDSs, 

varies. Each residence has its own ISDS. House densities range 

from several houses per acre to a single house on many acres. 

As houses are built closer to each other and as ISDS density 

increases, there could be a greater potential for degradation of 

ground-water quality.

Potential Effects of Individual Sewage Disposal 

System Effluent on Ground-Water Quality

Geochemical and physical processes occur in the subsoil—

unsaturated zone above the water table and the saturated zone 

below the water table (fig. 2)—that can reduce the concentrations of chemical and biological constituents in ISDS effluent. 

For a properly functioning ISDS, most of the potential contaminants in the effluent are removed by filtration or oxidation in the 

unsaturated zone below the leach field and above the water table 

(Wilhelm and others, 1994). When effluent reaches the unsaturated zone above the water table, it flows through the pores 

between the particles, such as sand and gravel from the weathered crystalline rock, that make up the subsoil. Large particles 

and bacteria in the effluent can be filtered by the subsoil, leaving mostly dissolved compounds in the effluent. As the effluent 

flows through the subsoil and is exposed to oxygen, ammonia is 

oxidized to form nitrate (nitrate plus nitrite, as nitrogen). When 

nitrate reaches the water table, and if dissolved organic carbon 

(DOC) is present and dissolved oxygen is absent, the nitrate 

and DOC may be consumed by denitrifying bacteria to produce 

nitrogen and carbon dioxide gasses. Thus, the concentration of 

nitrate increases beyond the leach field but then decreases as it 

travels through the saturated zone (Robertson and others, 1989).

Caffeine and other organic chemicals can be degraded to 

other compounds by bacteria in the saturated zone in the vicinity of the leach field from which the compounds originated. 

However, organic chemicals can persist in ground water if 

degrading bacteria are not present.

Biological constituents in ISDS effluent that can cause 

disease (pathogenic organisms) include bacteria and viruses. 

These microorganisms have different survival rates and transport properties in the saturated and unsaturated zones below a 

leach field. For example, Escherichia coli (E. coli) can potentially survive for several weeks in the subsurface if conditions 

are favorable (Matthess and Pekdeger, 1981). It is not known 

whether E. coli can survive long enough in a fractured-rock setting to be transported to the water table and eventually to wells. 

Total coliform and E. coli bacteria can be removed from ISDS 

effluent by filtration as the effluent flows through the unsaturated zone (Viraraghavan and Warnock, 1976). However, if the 

water table lies closer to the land surface, the unsaturated zone 

is thinner and more of the bacteria in the effluent can potentially 

reach the ground water (Canter and Knox, 1985).

Indicators of Contamination to the Ground Water

Samples collected from wells were analyzed for chemicals 

and bacteria that can originate from an ISDS. Many of these 

chemicals and bacteria can enter the ground water through 

natural processes, but if they are observed in elevated concentrations it can indicate degraded ground-water quality. Chloride, 

nitrate, nitrite, ammonia, and boron can all occur naturally in 

ground water. These chemicals usually do not occur naturally 

at elevated concentrations because these chemicals come from 

dispersed sources, such as waste from wild animals, decomposition of forest material, deposition from the atmosphere, or from 

weathering of rocks. An ISDS can provide a focused source of 

these chemicals if its leach field pipe is too close to the water 

table or if the infiltration rate and ground-water flow velocity 

are too rapid to allow for proper geochemical or physical treatment of the ISDS effluent. Products that are used in households, 

such as soaps containing boron, dietary salt containing chloride, caffeine, pesticides, perfumes, or human waste containing 

nitrate, nitrite, and ammonia, can enter the ground-water system 

as a more concentrated effluent from an ISDS. Total coliform 

and E. coli bacteria can originate from humans and other warmblooded animals.

Sampling Plan Design and Methods

The plan for collecting ground-water samples was designed 

to allow an evaluation of whether the density of development 

and thus the proximity of wells and ISDSs (ISDS density) is a 

factor in potential degradation of ground-water quality. Private 

wells were used as a surrogate for locating ISDSs because 

those lots having a well and a house also have an ISDS, and 

records for wells are more easily accessible than records of 

ISDSs. Thus, well density is equivalent to ISDS density for the 

purposes of this analysis. Wells listed in Colorado public well 

records (Colorado Division of Water Resources, 2000) were 

divided into four categories based on the number of wells per 

acre: more than one well per acre (high-density); one well in 

3 acres (medium-density); one well in 5 or more acres (lowdensity); and background wells (wells that were not expected to 

be influenced by other wells and ISDSs) (background) (table 1).

Figure 2. Diagram showing the relation of Individual Sewage 

Disposal System, domestic wells, and the water table in a 

fractured-rock ground-water system.
Candidate wells were classified into one of the three density 

categories by plotting their locations on a map and overlaying a 

grid on the map in GIS. Each of the overlay grids was made of 

cells that represent areas of 1 acre, 3 acres, or 5 acres. Well 

density was confirmed by observations made in the field. When 

the list of candidate wells was exhausted, additional wells 

Sample results were compared by using boxplots and testing for 

differences between the groupings of data by using the 

Wilcoxon rank-sum test (Helsel and Hirsch, 1992).

Boxplots provide a visual comparison of the variability 

between data from different density categories and from different months. An example of a boxplot is shown below:

The Wilcoxon rank-sum test is used to determine whether a 

statistical difference exists between two data sets. All possible 

combinations of two data sets for a particular chemical for all 

density categories and months were evaluated using the ranksum test. Differences between data sets were determined to be 

significant when the significance level (p-value) was 0.05 or 

smaller. A p-value of 0.05 means that it can be said with 

95-percent confidence that two data sets being compared are 

different. As the p-value increases, the level of confidence that 

two data sets are different decreases.

Potential Effects of Individual Sewage Disposal 

System Density on Ground-Water Quality

Four of the samples collected in July and four collected in 

September contained bacteria; only one well had detections of 

bacteria in both months. Detections of bacteria indicate contamination of the ground water, but not necessarily from an 

ISDS. Bacteria were present in samples from wells in the low-, 

medium-, and high-density categories. Detections of bacteria 

did not appear to be correlated with ISDS density. Additionally, 

concentrations of the other chemicals associated with ISDSs in 

these samples were not above expected background concentrations.

Samples from four wells in the low-density and background 

categories contained organic chemicals that can originate only 

from an ISDS. One of the 67 organic chemicals was detected 

in each of 3 wells, and 2 of the chemicals were detected in 1 

well. The detections of organic chemicals might be due to ISDS 

contamination, but concentrations of the other chemicals in the 

samples were not elevated above expected background concentrations.

A comparison was made to determine whether there was a 

correlation between concentrations of the various chemicals and 

the depths or yields of wells. This comparison indicated that the 

concentrations of several chemicals were inversely related to the 

depths or yields of wells (as yield or depth increases, concentrations decrease), but the correlations were not very strong.

Data from all wells were plotted on boxplots, and the 

Wilcoxon rank-sum test was used to identify statistically 

significant differences between months for a selected density 

category and chemical, or between density categories for a 

particular month and chemical. Most of the tests indicated no 

needed to complete the sample size for each density category 

were chosen based on field observations. Background wells 

were chosen using the criterion that the wells were located such 

that the water pumped by the wells was not expected to be influenced by ISDSs or other human activities.

Wells were sampled for chemicals and bacteria that can 

originate from septic systems and can be used as indicators of 

ground-water-quality degradation, including boron, chloride, 

fluoride, sulfate, nitrate, ammonia, phosphorus, total coliform 

and E. coli bacteria, and 67 organic chemicals that can only 

originate from households, such as caffeine, perfumes, pharmaceuticals, and the metabolites of organic chemicals (Kolpin 

and others, 2002). Samples were collected from a faucet in the 

plumbing system of each house and the water was pumped by 

the existing pump in each of the wells. Standard USGS protocols for the collection of water-quality samples were followed 

(Wilde and others, 1998). Measurements of the physical characteristics of water, such as pH, dissolved oxygen, and specific 

conductance also were made. Additionally, most wells were 

sampled twice, once each in July and September, to determine 

whether there were detectable variations in water quality with 

time (table 1). Quality-control samples collected in the field 

included eight blank and five replicate samples. Results indicate 

that field procedures did not contaminate the environmental 

samples. Data used in this analysis can be obtained on the Web 

at this URL: http://waterdata.usgs.gov/co/nwis/qwdata (search 

for Park County and the date range when the samples were 

collected). Water samples were analyzed at the USGS National 

Water Quality Laboratory in Denver, Colorado, using methods 

described in Fishman (1993) for inorganic chemicals and in 

Zaugg and others (2002) for organic chemicals.

Methods used to compare data

The results of analysis of the samples were grouped by the 

density categories and the month the well was sampled. The 

concentrations of chemicals and bacteria in the samples were 

then compared to assess whether differences existed between 

the density categories and the month the sample was collected. 

Density 

category

High 14 15

Medium 18 18

Low 16 15

Background 6 6

July September

Table 1. Number of samples in each density 

category for July and September 2001.
significant differences. None of the tests indicated a significant 

difference between July and September for a particular density 

category and chemical. The boxplots are shown only for those 

chemicals that had at least one comparison that was statistically 

significant: nitrate, chloride, and boron. The boxplots indicated 

the lowest concentration for a particular chemical was nearly 

the same for all density categories. These plots also show that 

the difference between the highest and lowest concentrations for 

a particular chemical was greatest for the high-density category 

and smallest for the background category.

Significant differences as determined by the Wilcoxon ranksum test for the nitrate data were found (fig. 3): between the 

high- and low-density categories for July data; and between the 

high- and low-density categories and the high-density and background categories for September data. Figure 3 indicates that 

the median nitrate concentration in the high-density category 

was about 35 percent greater than the median for the mediumdensity category, about 75 percent greater than the median for 

the low-density category, and about 64 percent greater than the 

median for the background category. These comparisons and the 

boxplots indicate nitrate concentrations tended to be higher in 

the high- and medium-density categories than in the low-density or background categories. The comparisons also indicate 

a higher probability of transport of nitrate to the ground water 

in areas with a higher density of houses and their associated 

ISDSs. However, in the high-density category only 7 percent 

(two samples) of the samples had nitrate concentrations greater 

than the U.S. Environmental Protection Agency (USEPA) 

primary drinking-water standard of 10 milligrams per liter 

(mg/L), and 17 percent (five samples) had nitrate concentrations from 9 to 10 mg/L. The maximum nitrate concentration 

was 25.7 mg/L from a well in the high-density category. None 

of the nitrate samples from the low-density category exceeded 

the USEPA standard for nitrate; the maximum nitrate concentration in this density category was 9.2 mg/L. These data indicate 

a propensity for elevated nitrate concentrations in areas where 

ISDS densities are more than one ISDS per 5 acres, but the data 

also indicate that elevated nitrate also occurs in the low-density 

and background categories.

Significant differences as determined by the Wilcoxon 

rank-sum test for the chloride data were found (fig. 4): between 

the high- and low-density categories and the high-density and 

background categories for July data; and between the high- and 

medium-density categories, the high- and low-density categories, and the high-density and background categories for 

September data. Figure 4 indicates that the median chloride 

concentration in the high-density category was about 26 percent 

greater than the median for the medium-density category, about 

65 percent greater than the median for the low-density category, 

and about 69 percent greater than the median for the background category. These comparisons and the boxplots indicate 

chloride concentrations tended to be higher in the high- and 

medium-density categories than in the low-density or background categories. The comparisons also indicate that there may 

be a higher probability of transport of chloride to the ground 

water in areas with higher density of houses and their associated 

ISDSs. However, in the high-density category only 7 percent 

(two samples) of the samples had chloride concentrations 

greater than the USEPA secondary drinking-water standard of 

250 mg/L. None of the chloride samples from the low-density 

category exceeded the USEPA standard for chloride; the maxi0

2

4

6

8

10

12 EXPLANATION

July

September

USEPA standard = 10 mg/L

Maximum nitrate = 25.7 mg/L

DENSITY CATEGORY

DISSOLVED NITRATE, IN 

MILLIGRAMS PER LITER

HIGH MEDIUM LOW BACKGROUND

Figure 3. Boxplot of nitrate data for all density categories and both 

months when samples were collected. See table 1 for the number of 

samples in each category.

Figure 4. Boxplot of chloride data for all density categories and 

both months when samples were collected. See table 1 for the 

number of samples in each category.

EXPLANATION

July

September

Maximum chloride = 886 mg/L

DENSITY CATEGORY

DISSOLVED CHLORIDE, IN 

MILLIGRAMS PER LITER

HIGH MEDIUM LOW BACKGROUND

0

5

10

15

20

25

30

35

40

45

50

55

60

mum chloride concentration in this density category was 

51.3 mg/L. The maximum chloride concentration was 886 mg/L 

for a sample from the high-density category.

Significant differences as determined by the Wilcoxon ranksum test for the boron data were found (fig. 5) only between the 

high- and low-density categories for September 2001 data. 

Figure 5 indicates that the median boron concentration in the 

high-density category was about 24 percent greater than the 

median for the medium-density category and about 39 percent 

greater than the medians for the low-density and background 

categories. The maximum boron concentration was 

144 micrograms per liter (μg/L) for a sample from the 

high-density category.
Five tritium samples were collected between October 11–15, 

2002, to attempt to determine an approximate age, or time since 

recharge, of the ground water pumped by wells. Tritium is used 

as an age-dating tracer because it was produced in relatively 

high concentrations as a result of atmospheric nuclear bomb 

testing beginning in 1954 (Kendall and others, 1998). Concentrations of tritium do not definitively yield the age of the water 

in a sample but must be used with other age-dating chemicals to 

refine the age estimate. Ground water having a certain tritium 

concentration is likely to contain a mixture of waters of different ages that exhibit a composite age based on the proportions 

of different-age waters contributing to a sample. Concentrations of tritium in the samples ranged from 15 to 38 picocuries 

per liter (tritium data can be obtained on the Web at URL http:

//waterdata.usgs.gov/co/nwis/qwdata (search for Park County 

and date range October 11-15, 2002)). Concentrations greater 

than 10 picocuries/liter indicate that recharge to the groundwater system occurred after 1954 (Kendall and others, 1998). 

Additional data analysis of the age-dating chemicals is needed 

to evaluate the age of ground water and the vulnerability of the 

ground water to contamination.

References Cited

Canter, L.W., and Knox, R.C., 1985, Septic tank system effects 

on ground water quality: Chelsea, Mich., Lewis Publishers, 

336 p.

Colorado Division of Water Resources, 2000, public well 

records available from the Division of Water Resources 

Records Section, Denver, Colorado.

Fishman, M.J., ed., 1993, Methods of analysis by the U.S. Geological Survey National Water Quality Laboratory—Determination of inorganic and organic constituents in water and 

fluvial sediments: U.S. Geological Survey Open-File 

Report 93–125, 217 p.

Helsel, D.R., and Hirsch, R.M., 1992, Statistical methods in 

water resources: New York, Elsevier Science Publishing 

Company, Inc., 522 p., 1 diskette.

Kendall, C., and McDonnell, J.J., eds., 1998, Isotope tracers in 

catchment hydrology: New York, Elsevier Science Publishing Company, Inc., 839 p.

Kolpin, D.W., Furlong, E.T., Meyer, M.T., Thurman, E.M., 

Zaugg, S.D., Barber, L.B., and Buxton, H.T., 2002, Pharmaceuticals, hormones, and other organic wastewater compounds in U.S. streams, 1999–2000-A national reconnaissance: Environmental Science and Technology, v. 36, no. 6, 

p. 1202–1211.

Matthess, G., and Pekdeger, A., 1981, Survival and transport of 

pathogenic bacteria and viruses in ground water, in Proceedings, First International Conference on Ground-WaterQuality Research, Houston, Texas, John Wiley and Sons, 

N.Y., p. 472–482

Robertson, W.D., Sudicky, E.A., Cherry, J.A., Rappaport, R.A., 

and Shimp, R.J., 1989, in Kobus, H.E., and Kinzelbach, W., 

eds., Impact of a domestic septic system on an unconfined 

sand aquifer: Proceedings of the international symposium 

on contaminant transport in ground water, Stuttgart, Federal 

Republic of Germany, April 4–6, 1989, v. 3, p. 105–112.

Tweto, Ogden, comp., 1979, Geologic map of Colorado: U.S. 

Geological Survey State Geologic Map, scale 1:500,000 

(reprinted).

Viraraghavan, T., and Warnock, R.G., 1976, Groundwater quality adjacent to a septic tank system: Journal of the American 

Water Works Association, v. 68, no. 11, part 1, p. 611–614.

Wilde, F.D., Radke, D.B., Gibs, J., and Iwatsubo, R.T., 1998, 

National field manual for the collection of water-quality 

data: U.S. Geological Survey Techniques of Water-Resources 

Investigations, book 9, chap. A1–A9.

Wilhelm, S.R., Schiff, S.L., and Cherry, J.A., 1994, Biogeochemical evolution of domestic waste water in septic 

systems, 1. Conceptual model: Ground Water, v. 32, no. 6, 

p. 905–916.

Zaugg, S.D., Smith, S.G., Schroeder, M.P., Barber, L.B., and 

Burkhardt, M.R., 2002, Methods of analysis by the U.S. 

Geological Survey National Water Quality Laboratory—

Determination of wastewater compounds by polystyrenedivinylbenzene solid-phase extraction and capillary-column 

gas chromatography/mass spectrometry: U.S. Geological 

Survey Water-Resources Investigations Report 01–4186, 

37 p.

Maximum boron = 144 μg/L

DENSITY CATEGORY

DISSOLVED BORON, IN 

MICROGRAMS PER LITER

HIGH MEDIUM LOW BACKGROUND

5

0

10

15

20

25

30

35

40

45

50

55

Figure 5. Boxplot of boron data for all density categories 

for samples collected in September. See table 1 for the 

number of samples in each category.