Quantitation of sewer inflow and infiltration (I/I) is important for maintaining efficient wastewater transport and treatment. I/I flows can be quantified based on flow rate and water quality measurements. Flow rate-based methods require continuous monitoring of flow rates using flow meters that are costly and prone to fouling. In comparison, conductivity and temperature, as simple water quality parameters, are more easily measurable with more cost-effective and reliable sensors. In this study, a data-driven methodology is developed for estimating I/I flows based on online conductivity and temperature measurements. A Prophet-model-based analytic algorithm is first developed to reconstruct the temperature and conductivity profiles of the base wastewater flow (BWF) from the measured temperature and conductivity time series. The algorithm is shown to be able to reconstruct the BWF temperature and conductivity profiles in two monitored catchments. The reconstructed BWF data are then incorporated into mass/energy balance equations for estimating I/I flows from the measured temperature and conductivity data. The overall I/I quantification method is finally demonstrated using simulation studies of a real-life sewer network and validated against the known I/I flows. This work provides a reliable method for I/I quantification based on simple measurements.

中文翻译：

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基于温度和电导率监测的数据驱动估算下水道流入和渗透的方法


下水道流入和渗透 (I/I) 的定量对于维持高效的废水运输和处理非常重要。 I/I 流量可以根据流量和水质测量进行量化。基于流量的方法需要使用流量计连续监测流量，流量计成本高昂且容易结垢。相比之下，电导率和温度作为简单的水质参数，更容易使用更具成本效益和可靠的传感器进行测量。在本研究中，开发了一种数据驱动的方法，用于根据在线电导率和温度测量来估计 I/I 流量。首先开发了基于 Prophet 模型的分析算法，根据测量的温度和电导率时间序列重建基本废水流 (BWF) 的温度和电导率曲线。该算法被证明能够重建两个受监测流域的 BWF 温度和电导率剖面。然后将重建的 BWF 数据合并到质量/能量平衡方程中，以便根据测量的温度和电导率数据估计 I/I 流量。最终通过对现实生活污水网络的模拟研究来演示总体 I/I 量化方法，并根据已知的 I/I 流量进行验证。这项工作为基于简单测量的 I/I 量化提供了一种可靠的方法。