Diagnosis of pipe illicit connections and damaged points in urban stormwater system using an inversed optimization model

• Published in: Journal of cleaner production Vol. 292; p. 126011
• Main Authors: Xu, Zuxin, Qu, Yang, Wang, Siyu, Chu, Wenhai
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 10.04.2021
• Subjects: algorithms; area; China; CMB; computer software; detection; drainage; drainage systems; economic costs; environment; flow; groundwater; Groundwater infiltration; Illicit connection; Inversed optimization model; Location diagnosis method; mass; pipes; pollution; rivers; sewage; simulation models; stormwater management; stormwater sewer systems; sustainable development; United States Environmental Protection Agency; China; CMB; Groundwater infiltration; Inversed optimization model; Location diagnosis method; Illicit connection
• ISSN: 0959-6526; 1879-1786
• DOI: 10.1016/j.jclepro.2021.126011

Pipe illicit connection and pipe damage are common issues in urban stormwater systems. This challenge brings problems that sewage directly discharges into river and groundwater infiltration occupies drainage capacity. The major task of solving these critical issues is to locate these illicit connections and damaged points. However, the conventional method for direct detection of problem points is expensive and ineffective. Therefore, there is an urgent demand for a critical method to diagnose the illicit connections and damaged points of the pipes. This study developed an effective inversed optimization model to easily and precisely diagnose and locate their place. The inversed algorithm in the model is a trial-and-error method using automatic iteration to optimize its calculation. Firstly, a chemical mass balance model1 (CMB) based on Monte Carlo algorithm is built to calculate the overall illicit sewage and groundwater infiltration flow of stormwater system. Then, an inversed optimization model is established to locate the high-risk accumulation areas of illicit connection and pipe damage. The inversed optimization model consists of USEPA Stormwater Management Model2(SWMM), a Python language software package for SWMM3 (PySWMM) and microbial genetic algorithm4 (MGA), called SWMM-PySWMM-MGA. The simple and feasible method was successfully applied in XiaoHecha discharge area of Cihu River in Ma’anshan, Anhui Province, China. The CMB was used to calculate the overall illicit sewage and infiltration flow of the target area. The overall flow calculated by CMB is applied as a constraint condition, which is inputted into the inversed optimization model to simulate the illicit sewage and infiltration flow of each pipe node in stormwater system. The simulation results suggest that the model is well calibrated and validated by root mean square error5 (RMSE), which is used to fit the error between monitored flow and simulated flow. Ultimately, the high-risk illicit connection and damaged accumulation areas can be determined, and the specific points of sewage illicit connection and damaged points can be precisely diagnosed. This study can help define the priority investigation areas and reduce economic cost. Meanwhile, this method provides qualitative and quantitative basis for the pipe reconstruction and rehabilitation, which is essential to reduce river pollution, protect clean water sources, and further promote sustainable development of urban drainage system and water environment. [Display omitted] •A novel diagnosis method by water level monitor and inversed model is proposed.•The method can precisely locate the pipe illicit connections and damaged points.•The method provides data basis for pipe reconstruction and rehabilitation.