BACKGROUND Approximately 42% of housing units use onsite

waste water treatment systems (OWTS, also

known as septic systems) to treat and dispose

wastewater in the southeastern USA, the

national average being 25% (USEPA, 2002).

There is suggestive evidence that septic

systems contribute to widespread fecal

pollution of surface waters and are assumed to

be 100% water consumptive in suburban

watersheds of metro-Atlanta area, GA.

However, the extent of their impact on fecal

pollution at the watershed level is still

uncertain, with the complexity of non-point

sources that make it difficult to isolate their

influence.

Our overall goal was to determine the impact

of septic systems on water quality and quantify

and evaluate the economics and the social

acceptance of technology to reduce pollution

stemming from septic systems. It also includes

education and extension activities on the

impact of septic systems on water resources.

Impacts of On-site Wastewater Treatment Systems on Water Quality and

Quantity in Urbanizing Watersheds

M. Habteselassie1, D. Radcliffe1, E. Bauske2, M. Risse3, J. Mullen4, C. Clarke5, R. Sowah1, N. Hoghooghi1

1Crop and Soil Sciences, 2GA Center for Urban Agriculture, 3GA Sea Grant and Marine Extension, 4Agricultural and Applied Economics, The

University of Georgia, 5USGS Southern Atlantic Water Science Center, Atlanta, Georgia

…RESULTS

The study suggests that septic system density above 100 units km-2 presents potential water quality

problems at watershed level and that the effect is seasonal.

Multiple regression model indicated that septic density together with four other watershed characteristics

accounted for 60% of the variability in fecal pollution in spring (data not shown).

The effect of septic density in spring can be attributed to the shallow seasonal groundwater table (Peck et

al., 2011), which may have promoted the transport of effluent from septic drainfields through groundwater

into receiving streams.

Mean septic systems water use was approximately 5.7% consumptive, contrary to common assumptions

of septic systems by water planning agencies in Georgia.

Online survey of Gwinnet country residents (study area) indicated that residents are willing to pay for

septic systems upgrade to improve water quality and that they prefer to pay equal shares (whether they

use septic systems or not) to fix the problem if it benefits everyone.

Project findings were widely distributed to the public via outreach publications and face-to-face contacts.

Graduate and undergraduate students were also trained under the project.

REFERENCES 1. Landers, M.N. and Ankcorn, P.D. 2008. Methods to evaluate influence of septic

systems on baseflow in selected watersheds in Gwinnett County, GA. USGS.

2. Peck, J.A. et al. 2011. Groundwater Conditions and Studies in Georgia, 2008–

2009. USGS.

3. USEPA. 2002. Onsite Wastewater Treatment Systems Manual. EPA/625/R-

00/008.

ACKNOWLEDGMENT

SUMMARY & CONCLUSION

Figure 3. Stream yield of markers that represent total (A), human (septic; B) and ruminant (C) derived fecal

contaminations in the high or low density watershed groups; B shows only for seasons that tested positive.

A B C

RESULTS Objective 1:– Septic systems impact on water quality and quantity

Objective 2:– Economics and social acceptance of technology to

reduce impact of septic system on water quality

Objective 3:– Education and extension programs on septic systems

Date

Nov-

11

Mar

-12

July

-12

Nov-

12

Apr-

13

July

-13

Nov-

13

Mar

-14

july

-14

Ba

sefl

ow

yie

ld (

cm

.s-1

.Km

-2)

0.000

0.002

0.004

0.006

0.008

0.010

0.012

0.014

0.016

0.018

0.020

LDS

HDS

Sampling date

Bas

eflo

w y

ield

(cm

/s/k

m2)

b)

Ev

apo

tran

spir

atio

n

Per

cola

tion

Su

rfac

e ru

no

ff

Gro

un

dw

ater

Lat

eral

so

il

To

tal

wat

er y

ield

Figure 4.

Correlation

between nitrate

and septic density

(A) and N and O

isotopic signatures

of the water

samples for

source

identification (B)

Figure 1. Study sites and monitoring

stations in metro-Atlanta area, GA

(Landers and Ankcorn, 2008).

The study area (Fig 1) is in the Southern Piedmont region of USA and includes 12 watersheds with high

density (HD: >77 units km-2) and 12 watersheds with low density (LD: <38 units km-2) of septic systems.

Other watershed characteristics for HD septic group include mean septic density (216 units km-2), median

distance from stream (96 m), mean drainage area (2 km2), developed area (69%), agricultural use (4%),

forest cover (25%) and imperviousness (18%). For LD septic group: mean septic density (22 units km-2),

median distance from stream (128 m), mean drainage area (3 km2), developed area (23%), agricultural use

(33%), forest cover (37%) and imperviousness (7%).

On average, stream flow was higher in HD than LD watershed groups, the difference being the highest

during dry season (Fig 5). Model analysis of water balance output variables indicated a 3.1% increase in

total water yield at watershed-scale (Fig 6) and a 5.9% increase at sub-basin scale due to septic systems.

Mean septic systems water use was approximately 5.7% consumptive, contrary to common assumptions by

water planning agencies in Georgia.

Figure 5. Baseflow yield in streams of

watersheds with LD or HD septic systems as

estimated by the velocity meter method.

Figure 6. Watershed scale water balance (a) and %

increase (b) in total flow contributed to stream with or

without septic systems as modeled by SWAT.

Results are based on baseflow samples that were collected seasonally 9 times between 2011 and 2014.

E. coli, enterococci and Bacteroides marker for human-derived contamination (a proxy for septic influence)

showed positive and significant correlation with septic density above 100 units km-2 in spring (Fig 2),

indicating the seasonal nature of the impact of septic systems on water quality.

While both groups of watershed were affected by fecal contamination (Fig 3A), the input from septic

systems was higher in the watersheds with HD of septic systems than those with LD of septic systems. The

fecal contamination in LD watershed group mainly came from ruminants (Fig 3C).

Similar to fecal indicator bacteria data, nitrate-N was strongly and significantly correlated with septic density

above 100 units km-2 (Fig 4A). N and O isotope signatures of the water samples suggested humans and

animals to be the main sources of pollution in HD and LD watershed groups, respectively (Fig 4B),

consistent with results from Bacteroidales markers (Fig 3).

Gwinnett County residents in GA (with in the study site) were recruited to complete an online survey to

examine their perceptions of local water quality and the sources of water quality impairments.

The survey also included a choice experiment in which respondents selected one of three policy options

for addressing water pollution issues due to septic systems.

The respondents’ perception was that septic systems were not among the biggest contributors of water

contamination in the county.

Given a choice between the status quo and two septic systems upgrade programs, respondents tend to

prefer one of the upgrade programs, but enthusiasm wanes as the status quo probability of failure to meet

water quality standards decreases.

There was no clear preference for one funding mechanism over another, implying that both septic systems

and sewer users generally prefer to pay equal shares to fix the problem if it benefits everyone.

Findings of the project were summarized in

extension bulletins and short video that were

distributed to the public in prints and made

available online. Video was shown on public

access TVs in multiple counties in GA.

Seventy one Master Gardener Extension

volunteers from 13 counties of GA received 6

hours of training on septic systems and were

provided with outdoor displays and literature for

use in their programming efforts.

Study findings were also disseminated via

scientific publications (3 journal articles and 4

proceedings) and meetings (>15 abstracts).

Graduate and undergraduate students were also

trained. Two MS students graduated from the

project. Currently, two PhD students are being

trained. Several undergraduate students were

involved in the project as student workers.

Project (2011-51130-

31165) is funded by

USDA/NIFA, National

Integrated Water

Quality Program.

B

Figure 2. Correlation between water quality indicators [E. coli stream yield - A), enterococci stream yield - B,

marker yield for human derived fecal pollution - C] and septic system density

R = 0.67

Septic density (units km-2)

0 100 200 300 400

Co

pie

s s

ec

-1 k

m-2

0

10000

20000

30000

40000

50000

60000

R = 0.36

Septic density (units km-2

)

0 100 200 300 400

Co

pie

s s

ec

-1 k

m-2

0

1000

2000

3000

4000

5000

6000

R = 0.42

Septic Density (units km-2)

0 100 200 300 400

Co

pie

s s

ec-1

km

-2

0

5e+4

1e+5

2e+5

2e+5

3e+5

3e+5

HD

LD

R = 0.32

Septic Density (units km-2)

0 100 200 300 400

Co

pie

s s

ec-1

km

-2

0

1e+5

2e+5

3e+5

4e+5

5e+5

HD

LD

R = 0.42

Septic Density (units km-2)

0 100 200 300 400

Co

pie

s s

ec-1

km

-2

0

5e+4

1e+5

2e+5

2e+5

3e+5

3e+5

HD

LD

R = 0.32

Septic Density (units km-2)

0 100 200 300 400

Co

pie

s s

ec-1

km

-2

0

1e+5

2e+5

3e+5

4e+5

5e+5

HD

LD

B C A Enterococci (spring) E. coli (spring)

Human marker (spring)

A