比较了两种不同的饮用水配水系统水质建模方法的公式和计算性能。时间驱动的方法本质上是欧拉方法，随着时间以均匀增量推进，在管道中固定大小的体积段之间移动水。事件驱动方法本质上是拉格朗日方法。它跟踪通过管网的大小可变的水包的位置，仅在新水包到达连接节点时更新条件。这两种方法都被编码到现有的网络仿真模型中，并在多个不同规模的实际配电系统上运行，精度公差相同。 结果表明，两个模型的预测结果非常接近，它们都能够描述观察到的水质行为。事件驱动方法能够更好地跟踪尖锐的浓度前沿，并且在需要高精度时具有更快的求解时间。然而，它确实需要更多的内存使用。

A comparison is made between the formulation and computational performance of two different methods for modeling water quality in drinking water distribution systems. The time-driven method is Eulerian in nature and moves water between fixed-sized volume segments in pipes as time is advanced in uniform increments. The event-driven method is Lagrangian in nature. It follows the positions of variable-sized parcels of water through a pipe network and only updates conditions when a new parcel reaches a junction node. Both methods were encoded into an existing network simulation model and run on several actual distribution systems of varying size under equal accuracy tolerances. Results showed that predictions from both models were quite close and that they both were capable of describing observed water quality behavior. The event-driven method was better able to track sharp concentration fronts and had faster solution times when high accuracy was required. It did, however, require more memory usage.