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ORIGINAL RESEARCH

Modeling the Impact of Clustered Septic Tank Systems on Groundwater Quality

Liping Pang^a,*, Chris Nokes^a, Jirka imnek^b, Heather Kikkert^a and Ross Hector^a

^a Inst. of Environmental Science & Research Ltd., P.O. Box 29181, Christchurch, New Zealand
^b Dep. of Environmental Sciences, Univ. of California, Riverside, CA 92521
^* Corresponding author (liping.pang{at}esr.cri.nz)

Received 6 September 2005.

Contamination of groundwater from onsite disposal of septic tank effluent is an increasing concern. In this study, HYDRUS-2D simulated the impact of clustered disposal systems on NO₃^– and fecal coliforms in groundwater in a rural community near Christchurch, New Zealand. The model included nine disposal boulder pits, embedded 4 m below the surface in alluvial gravel media, in a domain of 3.3 km by 30 m (including both unsaturated and saturated zones). Water movement between the ground surface and the disposal pits was simulated using HYDRUS-1D. The performance of the two-dimensional model was evaluated using monitoring data obtained from a 1977 study. Applying the daily climate data for 1974 to 1977, the simulated NO₃^– and bacteria concentrations in the groundwater were similar to those observed. Both observed and simulated results showed that clustered disposal systems have a significant cumulative impact on NO₃^– concentrations in groundwater, but the impact of fecal coliforms from individual systems is localized. This study further demonstrates that groundwater has a limited ability to dilute NO₃^–, requiring at least 2.9 km for NO₃^– to be reduced to near background levels. Therefore, disposal systems must treat effluent efficiently and water wells downgradient of closely clustered disposal systems must be deep enough to avoid the adverse health effects of NO₃^–. Sensitivity analysis suggests that the model results are most sensitive to changes in hydraulic conductivity, effluent concentrations and discharge rate, and the removal rate of bacteria in the unsaturated zone. Therefore, the accurate estimation of these parameters is a fundamental requirement for the model to produce realistic results.

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