arXiv:2610.41050v1 Announce Type: new Abstract: The integration of information technology and operational technology in water infrastructure creates pathways through which cyber compromise may affect physical service delivery. This study revisits the Applied Cybersecurity Gap (ACG) framework by evaluating an experimental Applied Cybersecurity Gap Index (ACGI) alongside the Cyber-to-Physical Propagation Rate (CPPR), defined as the proportion of initially compromised trials that produce a specified physical-impact outcome. The expanded evaluation comprises 2,160 synthetic trials across three water-network benchmarks, including EPANET Example Network 3 (Net3), and couples declared cyber-attack progression rules with hydraulic simulations. A source-trained machine-learning model evaluated on 247 compromised Net3 trials achieved ROC-AUC 0.772, PR-AUC 0.775, and F1 0.733, compared with 0.661, 0.642, and 0.704 for a scenario-only baseline. The configuration-cluster bootstrap interval for the ROC-AUC difference was 0.038--0.183. A separate 720-run Net3 hydraulic operating-point sensitivity analysis achieved the study's exploratory baseline pressure criterion in all reruns, preserved 717 of 720 physical-impact labels, and produced ROC-AUC 0.791 with the frozen source-trained model. Additional analyses examine the sensitivity of CPPR to the physical-impact threshold and assumed control-blocking probabilities, and demonstrate that the ACGI--CPPR association is partly induced by the simulation design rather than independently validated. The findings establish a reproducible simulation-based assessment workflow, but do not constitute field calibration of cybersecurity-control effectiveness or prediction of real-world utility incidents.