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WR 2022: Eavesdropping on wastewater pollution: Detecting discharge events from river outfalls via fiber-optic distributed acoustic sensing

作者: Zhuo Chen, Cheng-Cheng Zhang, Bin Shi, Tao Xie, Guangqing Wei, Jun-Yi Guo  

刊物信息: Water Research,Volume 250, 15 February 2024, 121069

DOI: https://doi.org/10.1029/2022GL098211

摘要:Wastewater discharge from outfall pipes can significantly impact river water quality and aquatic ecosystems. Effective outfall monitoring is critical for controlling pollution and protecting public health. This study demonstrates a novel distributed acoustic sensing (DAS) approach for detecting wastewater discharge events from outfall pipes located along rivers. Controlled field experiments were conducted in an industrial park river to systematically evaluate DAS performance. DAS detects vibrational signals imparted to suspended fiber-optic cables by turbulent wastewater flows, predominantly within 10–30 Hz, enabling continuous monitoring along entire river lengths. Vibrational power analysis locates outfalls with meter-level accuracy, while time–frequency techniques discern discharge timing and characteristics. Cable type and outfall–fiber separation influence on detection capability was assessed. Thermoplastic-jacketed tight buffer cables optimized detection through enhanced vibrational coupling. Vibrational energy decreased exponentially with separation, highlighting benefits of proximal deployment for sensitivity. However, detection range scales with discharge flow rate. Frequency centroid proved a robust feature with potential for automated discharge identification. Overall, DAS enables high spatiotemporal resolution monitoring to pinpoint concealed outfalls minimally invasively. This positions DAS as a promising tool supporting improved water governance through early pollution warnings and rapid source localization via outfall vibrational signatures emanating across river networks.