Spatial Models of Sewer Pipe Leakage Predict the Occurrence of Wastewater Indicators in Shallow Urban Groundwater

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• 作者：Patrick R. Roehrdanz ; Marina Feraud ; Do Gyun Lee ; Jay C. Means ; Shane A. Snyder ; Patricia A. Holden
• 刊名：Environmental Science & Technology
• 出版年：2017
• 出版时间：February 7, 2017
• 年：2017
• 卷：51
• 期：3
• 页码：1213-1223
• 全文大小：545K
• ISSN：1520-5851

文摘

Twentieth century municipal wastewater infrastructure greatly improved U.S. urban public health and water quality. However, sewer pipes deteriorate, and their accumulated structural defects may release untreated wastewater to the environment via acute breaks or insidious exfiltration. Exfiltrated wastewater constitutes a loss of potentially reusable water and delivers a complex and variable mix of contaminants to urban shallow groundwater. Yet, predicting where deteriorated sewers impinge on shallow groundwater has been challenging. Here we develop and test a spatially explicit model of exfiltration probability based on pipe attributes and groundwater elevation without prior knowledge of exfiltrating defect locations. We find that models of exfiltration probability can predict the probable occurrence in underlying shallow groundwater of established wastewater indicators including the artificial sweetener acesulfame, tryptophan-like fluorescent dissolved organic matter, nitrate, and a stable isotope of water (δ¹⁸O). The strength of the association between exfiltration probability and indicators of wastewater increased when multiple pipe attributes, distance weighting, and groundwater flow direction were considered in the model. The results prove that available sanitary sewer databases and groundwater digital elevation data can be analyzed to predict where pipes are likely leaking and contaminating groundwater. Such understanding could direct sewer infrastructure reinvestment toward water resource protection.