DOI: 10.3390/pr14162624 ISSN: 2227-9717

Water Quality Evolution in a Mixed Pressurized and Non-Pressurized Water Conveyance System Based on SWMM–EPANET Segmented Simulation

Boran Zhu, Shilei Zhang, Xiaodong Xu, Yang Shao, Haitao Wang, Junqiang Lin, Chunhao Fang, Chenchen Ji, Zihan Chen, Youzhi Liu

Complex water conveyance systems often involve mixed flow conditions comprising pressurized pipe networks and free-surface open channels. Every single model has its limitations in long-distance and complex water transfer projects; coupling different models can leverage their respective advantages. For this reason, this study proposes an integrated modeling framework that couples the Storm Water Management Model (SWMM) and Environmental Protection Agency Network Evaluation Tool (EPANET) models to simulate water quality in pressurized–unpressurized coupled systems. Taking the typical Yin Chao Ji Liao water diversion project as a case study, total nitrogen (TN) and total dissolved solids (TDS) were selected as representative pollutants. A total of 32 simulation scenarios were systematically evaluated across four concentration levels at four distinct monitoring points. During this synthesis, key emergency response indicators, specifically T0 (optimal gate-opening time) and T2 (drainage operation duration), were quantified. The results indicate that pollutant dispersion in the unpressurised tunnel section is primarily governed by pollutant loading, whereas in the pressurised pipeline section, it is controlled by flow velocity and pressure differentials. High-concentration pollution in the tunnel section allows for a relatively longer emergency response time (T0 = 453 min). In contrast, due to rapid transport in the pipeline section, emergency operations must be completed swiftly (≤30 min). This coupled approach effectively addresses the challenge of water quality simulation in cross-regime conveyance systems. Future research will focus on integrating real-time sensor monitoring data with this coupled model to further optimize automated early warning protocols for long-distance diversion projects.

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