Date of Award


Document Type


Degree Name

Master of Science


Department of Systems Engineering and Management

First Advisor

Christopher M. Chini, PhD


Water distribution networks are critical infrastructure characterized by difficulties in their assessment and deteriorating performance due to aging components. Resilience analysis of networked infrastructure has replaced traditional risk analysis to focus on performance. Global Resilience Analysis can provide useful information to decision makers and system managers regarding repair and expansion of networks. Network performance has been found to be directly informed by network structure. This work leverages graph theory to assess network qualities that correlate with resiliency characteristics across 69 real world water networks. These networks are then grouped by their structural properties through k-means clustering and compared using parametric and nonparametric tests to assess network profiles and trends. Data for the analysis included shapefiles of water distribution networks converted to simple undirected graphs. The results of the analysis showed three distinct clusters of WDNs, identified conflicts between metrics of efficiency and modularity, and discovered shortfalls of using central point dominance in asset management strategies.

AFIT Designator



A 12-month embargo was observed.

Approved for public release: 88ABW-2023-0296