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Impacts of On-site Wastewater Treatment Systems on Water Quality and Quantity in Urbanizing Watersheds

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Mussie Habteselasie

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Impacts of On-site Wastewater Treatment Systems on Water Quality and Quantity in Urbanizing Watersheds

  1. 1. 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 N ov-11 M ar-12 July-12 N ov-12 A pr-13 July-13 N ov-13 M ar-14 july-14 Baseflowyield(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 Baseflowyield(cm/s/km2) b) Evapotranspiration Percolation Surfacerunoff Groundwater Lateralsoil Totalwateryield 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 Copiessec-1km-2 0 10000 20000 30000 40000 50000 60000 R = 0.36 Septic density (units km-2) 0 100 200 300 400 Copiessec-1km-2 0 1000 2000 3000 4000 5000 6000 R = 0.42 Septic Density (units km-2) 0 100 200 300 400 Copiessec-1km-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 Copiessec-1km-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 Copiesseckm 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 Copiessec-1km-2 0 1e+5 2e+5 3e+5 4e+5 5e+5 HD LD B CA Enterococci (spring)E. coli (spring) Human marker (spring) A

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