Assessing and modelling the water quality in a water distribution system (WDS) are highly important to ensure a reliable supply with sufficient water quality. Owing to the high computational burden of such an analysis, frequently, simplifications are required or surrogate models are used (e.g., reducing the level of detail of the network model), neglecting significant aspects. For large (currently all-pipe) models and/or recurrent simulations (e.g., integrated studies, sensitivity analysis, deep uncertainty analysis, design, and optimization), the computational burden further increases. In this study, a novel complex network analysis-based approach for high-computational efficiency water quality assessment in a WDS is developed and comprehensively tested (R² values in comparison with state-of-the-art nodal water qualities in median of 0.95 are achieved). The proposed model is successfully utilized in a design study to identify the design solutions exceeding water quality thresholds with a correct identification rate between 96% and 100%. The computational efficiency is determined to be a factor 4.2e-06 less than that of state-of-the-art models. Therefore, the proposed model significantly improves the water quality assessment for such tasks in large WDSs.

对配水系统 (WDS) 中的水质进行评估和建模对于确保可靠供应和足够的水质非常重要。由于这种分析的高计算负担，经常需要简化或使用替代模型（例如，降低网络模型的详细程度），而忽略重要方面。对于大型（目前全管道）模型和/或循环模拟（例如，综合研究、敏感性分析、深度不确定性分析、设计和优化），计算负担进一步增加。在这项研究中，开发了一种基于复杂网络分析的新型 WDS 高计算效率水质评估方法并进行了全面测试（R² 值与中值为 0 的最先进节点水质相比）。达到 95 个）。所提出的模型成功地用于设计研究，以识别超过水质阈值的设计解决方案，正确识别率在 96% 到 100% 之间。计算效率被确定为比最先进的模型低 4.2e-06 倍。因此，所提出的模型显着改善了大型 WDS 中此类任务的水质评估。