Groundwater infiltration into sanitary sewers increases hydraulic loadings of sewage collection systems and threatens wastewater treatment efficiency. However, cost-effective approach to quantify this important process still needs to be improved in order to better manage this common issue. This paper presents a method for determining the origin and amount of groundwater entering the urban sewer system. On a catchment scale, by measuring and tracking a chemical tracer (i.e., artificial sweetener acesulfame) in the urban sewers, the magnitude of daily groundwater flows in each sub-catchment could be quantified based on a Monte Carlo chemical mass balance approach. For the study site, 7.9% of the sewer length contributed 58% of the total groundwater infiltration. In the identified high-risk sub-catchment, groundwater sources and their spatial-temporal flows could be further pinpointed and elucidated by physically based numerical self-optimization model using microbial genetic algorithm method, which was verified by on-site sewer flow measurements, as well as time-series tracer concentration patterns at the terminal outlet. It was found that the diurnal variations of groundwater seepage into sewer network was linked to the in-pipe water level associated with sewage pumps operation mode, demonstrating the importance of in-pipe water level regulation in controlling groundwater infiltration. Compared with traditional visual inspection or direct flow measurement methods, the proposed approach exhibits distinct advantages in determining groundwater sources and flows in large sewer systems.

地下水渗入下水道增加了污水收集系统的水力负荷，并威胁到废水处理效率。但是，量化这一重要过程的成本有效方法仍然需要改进，以便更好地管理这个常见问题。本文提出了一种确定进入城市下水道系统的地下水来源和数量的方法。在集水区规模上，通过测量和跟踪城市下水道中的化学示踪剂（即人造甜味剂乙酰磺胺酸），可以基于蒙特卡洛化学质量平衡法来量化每个子集水区的每日地下水流量。对于研究地点，下水道长度的7.9％贡献了地下水总渗透量的58％。在确定的高风险子汇水区，利用微生物遗传算法，通过基于物理的数值自优化模型，可以进一步查明和阐明地下水源及其时空流量，并通过现场下水道流量测量以及时间序列示踪剂浓度模式进行了验证。终端插座。研究发现，污水渗入下水道网络的日变化与污水泵运行模式相关的管道内水位有关，这说明了管道内水位调节在控制地下水入渗方面的重要性。与传统的目视检查或直接流量测量方法相比，该方法在确定大型下水道系统中的地下水源和流量方面具有明显的优势。