摘要：
智慧水务的创新应用已成为保障供水设施安全运行、提升运营效率与服务质量的关 键。供水在线水质监测作为其核心支撑技术，通过多源、多尺度数据的连续采集与智能分析， 为水源地与水厂风险预警、管网运行优化、突发污染事件应急处置及科学决策提供技术保障。 本文系统梳理供水行业在线水质监测技术体系的演进，围绕多参数传感器、物联网/边缘计 算架构、大数据与人工智能算法、数字孪生与可视化等关键环节，总结其在以新污染物（如 PFAS、内分泌干扰物、药物与个人护理品等）为代表的新污染物在线识别、异常预警与溯 源，以及管网健康评估、加药与调度优化等典型场景的应用进展与成效。结合典型城市案例， 归纳智能化监测网络在提升供水安全、降低漏损与优化资源调配方面的实践价值。针对传感 器长期稳定性与痕量新污染物检测能力不足、数据孤岛与标准化缺失、边缘侧快速联动与闭 环控制能力有待提升等瓶颈，提出多模态感知融合与特征指标体系构建、统一数据标准与跨 域协同、数字孪生驱动的风险推演与协同治理等发展方向，为供水行业在线监测体系建设与 推广提供参考。
关键词:
智慧水务,
数字孪生,
在线监测,
多参数传感器,
人工智能算法,
新污染物
Abstract:
Innovation in smart water utilities is critical for ensuring the safe operation of water-supply infrastructure and improving operational efficiency，management effectiveness，and service quality. As a cornerstone technology，online water-quality monitoring enables continuous multi-source data acquisition and intelligent analytics，supporting risk early warning at sources and treatment plants，pipe-network optimization，emergency response to contamination incidents， and evidence-based decision making. In China， urban online monitoring is guided mainly by industry and local standards，while national standards remain limited，constraining large-scale deployment. This paper reviews the evolution of online monitoring for water-supply systems and summarizes enabling technologies，including multi-parameter sensors，IoT/edge architectures，
big-data analytics and artificial intelligence ， and digital twins with visualization. Progress is discussed for representative applications such as online identification，anomaly warning，and source tracing of emerging contaminants （ e.g. ， PFAS ， endocrine-disrupting chemicals ， pharmaceuticals and personal care products ） ， as well as network health assessment and optimization of dosing and dispatching. Case studies from typical cities illustrate the practical value of intelligent monitoring networks in enhancing supply safety ， reducing leakage ， and improving resource allocation. Finally，key challenges are highlighted—sensor robustness and trace-level detection ， data silos and insufficient standardization ， and delayed edge-side actuation—and future directions are proposed，including multimodal sensor fusion with indicator frameworks，standardized cross-domain data sharing，and digital-twin-driven risk simulation and collaborative governance.
Key words:
smart water utilities,
digital twin,
online monitoring,
multi-parameter sensors,
artificial intelligence,
emerging contaminants
中图分类号:
刘沛沆 , 刘保森 , 王永磊 , 贾瑞宝 , 刘宝震 , 杜振齐. 智慧水务下水质在线监测体系智能化发展研究进展[J]. 工业水处理, doi: 10.19965/j.cnki.iwt.2026-0027.
LIU Peihang, LIU Baosen WANG Yonglei, JIA Ruibao, LIU Baozhen , DU Zhenqi. Research progress on the intelligent development of online water quality monitoring systems in smart water utilities[J]. Industrial Water Treatment, doi: 10.19965/j.cnki.iwt.2026-0027.