Crop and Soil Sciences, The University of Georgia Griffin Campus, 1109 Experiment St, Griffin, GA, 30223, USA.
Crop and Soil Sciences, The University of Georgia Griffin Campus, 1109 Experiment St, Griffin, GA, 30223, USA.
Water Res. 2017 Jan 1;108:330-338. doi: 10.1016/j.watres.2016.11.007. Epub 2016 Nov 3.
The presence of multiple sources of fecal pollution at the watershed level presents challenges to efforts aimed at identifying the influence of septic systems. In this study multiple approaches including targeted sampling and monitoring of host-specific Bacteroidales markers were used to identify the impact of septic systems on microbial water quality. Twenty four watersheds with septic density ranging from 8 to 373 septic units/km were monitored for water quality under baseflow conditions over a 3-year period. The levels of the human-associated HF183 marker, as well as total and ruminant Bacteroidales, were quantified using quantitative polymerase chain reaction. Human-associated Bacteroidales yield was significantly higher in high density watersheds compared to low density areas and was negatively correlated (r = -0.64) with the average distance of septic systems to streams in the spring season. The human marker was also positively correlated with the total Bacteroidales marker, suggesting that the human source input was a significant contributor to total fecal pollution in the study area. Multivariable regression analysis indicates that septic systems, along with forest cover, impervious area and specific conductance could explain up to 74% of the variation in human fecal pollution in the spring season. The results suggest septic system impact through contributions to groundwater recharge during baseflow or failing septic system input, especially in areas with >87 septic units/km. This study supports the use of microbial source tracking approaches along with traditional fecal indicator bacteria monitoring and land use characterization in a tiered approach to isolate the influence of septic systems on water quality in mixed-use watersheds.
流域层面存在多种粪便污染源，这给旨在确定化粪池系统影响的工作带来了挑战。在这项研究中，采用了包括靶向采样和监测宿主特异性拟杆菌标记物在内的多种方法，以确定化粪池系统对微生物水质的影响。在 3 年的时间里，监测了 24 个流域的水质，这些流域的化粪池密度范围从 8 到 373 个化粪池/平方公里不等，监测时间为基流条件。使用定量聚合酶链反应定量检测了人类相关的 HF183 标记物以及总拟杆菌和反刍动物拟杆菌的水平。与低密度区域相比，高密度流域中人类相关的拟杆菌产量明显更高，并且与春季化粪池系统到溪流的平均距离呈负相关（r = -0.64）。人类标记物也与总拟杆菌标记物呈正相关，表明人类来源的输入是研究区域总粪便污染的重要贡献者。多元回归分析表明，化粪池系统以及森林覆盖率、不透水面积和电导率可以解释春季人类粪便污染变化的 74%。研究结果表明，化粪池系统通过在基流期间对地下水补给的贡献或失效的化粪池系统输入的方式产生影响，尤其是在化粪池密度大于 87 个/平方公里的地区。本研究支持在混合用途流域中使用微生物源追踪方法，结合传统粪便指示菌监测和土地利用特征化，采用分层方法来分离化粪池系统对水质的影响。
