In developed countries, municipalities deliver drinking water to constituents through water distribution systems. These transport water from a treatment plant to homes, restaurants, and any other site of end use. Proper water distribution system infrastructure functionality is a critical concern to city planners and managers because component failures within these systems restrict or prevent the ability to deliver water. The reduced capacity to deliver water forces the health and well being of all citizens into jeopardy. The breakdown of a component can even spark the failure of several more components, causing a sequence of cascading failures with catastrophic consequences. To make matters worse, some forms of component failures are unpredictable and it is impossible to foresee every possible failure that could occur. In order to prevent cataclysmic losses that are experienced during system failures, the development of resilient water distribution infrastructure is vital. A resilient water distribution system possesses an adaptive capacity to mitigate the loss of service resulting from component failures. Traditionally, infrastructure resilience research has been retrospective in nature, analyzing the infrastructure system after it suffered a failure event. However, this research project takes water distribution resilience research in a new direction. The research identifies the Sensing Anticipating, Adaptation, and Learning processes that are inherent in the current operations of each component in the water distribution system (pumps, pipes, valves, tanks, nodes). Additional SAAL processes have been recommended for the components that lack adaptive management in current practice. This workis unique in that it applies resilience theory to water distribution systems in an anticipatory manner. This anticipatory application of resilience will provide operators with actionable process for them to implement during failure situations. In this setting, resilience is applied to existing systems for noticeable improvements in operation during failure situations.