WANGLijian,WANGKai,LIUShurui,et al.Information-based Drainage Network Tracing Analysis Using Aqueous Fluorescence Fingerprinting and Modeling[J].China Water & Wastewater,2026,42(9):129-136.
基于荧光指纹与模型的信息化排水管网溯源分析
- Title:
- Information-based Drainage Network Tracing Analysis Using Aqueous Fluorescence Fingerprinting and Modeling
- 关键词:
- 排水管网; 水质荧光指纹; Simuwater模型; 源头监管; 污染物溯源
- Keywords:
- drainage network; aqueous fluorescence fingerprint; Simuwater model; source supervision; pollutant tracing
- 摘要:
- 河北省某市地势高差显著，存在自然跌水、工业废水违规偷排及雨污混接现象，致使管网污染物成分复杂、溯源困难，污水厂进水水质频繁波动且处理成本激增，亟须构建精准高效的污染溯源技术体系，以破解排水管网隐蔽性污染源监管难题。以该市区市域范围内133 km排水主干管网及100余家排水户为研究对象，构建了融合水质荧光指纹技术与Simuwater模型的源头溯源信息化平台。通过建立水质指纹库、高精度管网模型，并集成物联监测数据，实现了污染源的动态解析与排水户精准监管。实际应用表明，平台可在1.5 h内成功锁定污染源，通过Simuwater模型对污染团扩散路径及浓度变化进行模拟验证，关键节点浓度模拟误差≤5%，可为溯源决策提供依据。该源头溯源信息化平台能够有效破解城市排水管网污染溯源难、监管效率低的问题，推动监管模式由被动应对向主动防控转变，提升了排水系统运行稳定性。
- Abstract:
- A city in Hebei Province exhibits significant topographical elevation differences, characterized by natural waterfalls, illegal discharge of industrial wastewater, and combined sewer overflows. These factors result in complex pollutant compositions within the drainage network, making pollution source tracing challenging. The wastewater treatment plant experiences frequent fluctuations in influent quality and sharply rising treatment costs. There is an urgent need to establish a precise and efficient pollution source tracing technology system to address the oversight challenges posed by concealed pollution sources within the drainage network. Targeting the 133 km main drainage network and over 100 drainage users within the city’s urban area, an information platform integrating aqueous fluorescence fingerprint technology with the Simuwater model was developed for source tracing. By establishing an aqueous fluorescence fingerprint database, constructing a high-precision drainage network model, and integrating IoT monitoring data, the platform enables dynamic analysis of pollution sources and precise oversight of drainage users. The practical application demonstrated that the platform successfully identified the pollution source within 1.5 hours. The Simuwater model further validated the results by simulating dispersion path and concentration variation of pollutant plumes, achieving simulation errors of ≤5% at key nodes, which provided a scientific basis for traceability decision-making. The information platform effectively addresses the challenges of difficult pollution traceability and low supervision efficiency in urban drainage network, promoting a shift from reactive response to proactive prevention in regulatory models, and enhancing the operational stability of drainage systems.
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