An integrated supervision framework to safeguard the urban river water quality supported by ICT and models

被引:8
作者
Jiang, Jiping [1 ]
Men, Yunlei [2 ]
Pang, Tianrui [1 ,3 ]
Tang, Sijie [1 ]
Hou, Zhiqiang [4 ]
Luo, Meiyu [2 ]
Sun, Xiaolin [5 ]
Wu, Jinfu [6 ]
Yadav, Soumya [1 ,7 ]
Xiong, Ye [8 ]
Liu, Chongxuan [1 ]
Zheng, Yi [1 ]
机构
[1] Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen Municipal Engn Lab Environm IoT Technol, Shenzhen 518055, Peoples R China
[2] Shenzhen Zhishu Environm Sci & Technol Co Ltd, Shenzhen 518055, Peoples R China
[3] Harbin Inst Technol, Sch Environm, Harbin 150090, Peoples R China
[4] Power China Ecoenvironm Grp Co Ltd, Shenzhen 518101, Peoples R China
[5] ZICT Technol Co Ltd, Shenzhen 518055, Peoples R China
[6] Huayue Inst Ecol Environm Engn Co Ltd, Chongqing 401122, Peoples R China
[7] Indian Inst Technol, Dept Civil Engn, Kharagpur 721302, West Bengal, India
[8] Shenzhen Water Grp Co Ltd, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
Anomaly detection; Data -driven model; Drainage system; Early warning; Pollution source identification; Urban water environment; Water quality; Smart city; POLLUTION SOURCE IDENTIFICATION; NUMERICAL INVERSION METHODS; SAMPLES; STATE;
D O I
10.1016/j.jenvman.2023.117245
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Models and information and communication technology (ICT) can assist in the effective supervision of urban receiving water bodies and drainage systems. Single model-based decision tools, e.g., water quality models and the pollution source identification (PSI) method, have been widely reported in this field. However, a systematic pathway for environmental decision support system (EDSS) construction by integrating advanced single tech-niques has rarely been reported, impeding engineering applications. This paper presents an integrated super-vision framework (UrbanWQEWIS) involving monitoring-early warning-source identification-emergency disposal to safeguard the urban water quality, where the data, model, equipment and knowledge are smoothly and logically linked. The generic architecture, all-in-one equipment and three key model components are introduced. A pilot EDSS is developed and deployed in the Maozhou River, China, with the assistance of envi-ronmental Internet of Things (IoT) technology. These key model components are successfully validated via in situ monitoring data and dye tracing experiments. In particular, fluorescence fingerprint-based qualitative PSI and Bayesian-based quantitative PSI methods are effectively coupled, which can largely reduce system costs and enhance flexibility. The presented supervision framework delivers a state-of-the-art management tool in the digital water era. The proposed technical pathway of EDSS development provides a valuable reference for other regions.
引用
收藏
页数:13
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