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Temporal and spatial variability of instream indicator bacteria (Escherichia coli) and implications for water quality monitoring

机译：上游指示菌（大肠杆菌）的时空变化及其对水质监测的意义

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Many water quality monitoring programs quantify Escherichia coli, an indicator of fecal contamination and potential sewage pollution. However, interpretation of E. coli data can be complex due to abiotic factors that influence its growth and mortality. The goal of this study was to quantify the variability of E. coli in a river and assess the impact of that variability on water quality monitoring study design and sewage pollution source identification. Over 1900 samples were collected and analyzed from 2007 to 2017 in the Norwalk River in Connecticut. Sixty-six percent of the samples collected during weekly to monthly monitoring had E. coli concentrations below 200 CFU/100 mL, indicating that elevated bacteria concentrations were captured infrequently. Patterns observed during daily sampling indicated that the randomization of sampling days within a week may support the identification of pollution sources driven by human behavioral patterns. Spatial autocorrelation in bacteria concentrations was not observed between sites, indicating that the sample locations were not spaced sufficiently close together to be redundant for monitoring. On finer spatial scales however, detection of a known pollution source was found to be challenging at even short distances downstream, with less than 25% of the original source concentration detected at 10 m downstream and less than 10% by 1000 m downstream, suggesting that a high density of study sites may be needed to detect potential sources. These findings can be used to better understand the natural variability of this important indicator organism in freshwater systems, and inform more efficient and effective monitoring.
机译：许多水质监测计划对大肠杆菌进行定量，大肠杆菌是粪便污染和潜在污水污染的指标。但是，由于影响其生长和死亡率的非生物因素，对大肠杆菌数据的解释可能很复杂。这项研究的目的是量化河流中大肠杆菌的变异性，并评估该变异性对水质监测研究设计和污水污染源识别的影响。从2007年到2017年，在康涅狄格州的诺沃克河收集并分析了1900多个样本。每周至每月监测期间收集的样本中有66％的大肠杆菌浓度低于200 CFU / 100 mL，这表明很少捕获到升高的细菌浓度。在日常采样过程中观察到的模式表明，一周内采样天的随机化可以支持对人类行为模式驱动的污染源的识别。在两个位点之间未观察到细菌浓度的空间自相关，这表明样品位置之间的距离不够近，以至于无法进行监视。然而，在更精细的空间尺度上，发现即使在短距离的下游也很难发现已知的污染源，在下游10 m处检测不到原始污染源浓度的25％，在下游1000 m处检测不到原始污染源浓度的10％，这表明可能需要高密度的研究场所来检测潜在来源。这些发现可用于更好地了解淡水系统中该重要指示生物的自然变异性，并提供更有效的监测方法。

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