Resilience-based Modeling for Water Infrastructure Systems

This project develops, implements and tests a new quantitative resilience modeling framework to support operational and strategic decisions for improving the resilience of water infrastructure systems during normal and emergency operations. This framework integrates conceptual, structural, simulation, and optimal decision-making models for resilience investment prioritization. The newly developed quantitative resilience performance metrics that result from this modeling effort can influence the way that water infrastructure systems resilience investments are evaluated and compared to identify optimal improvement actions. Rapid failures and slow system deterioration in water infrastructure systems continue to present challenges in reliably and cost-effectively meeting service needs. Thus, this scientific research contribution supports NSF's mission to promote the progress of science and to advance our national welfare with benefits that will optimize investments in the nation's critical infrastructures.

This new quantitative resilience modeling framework will: 1) be reusable for multiple hazard and decision scenarios; 2) be able to integrate existing simulation and modeling tools; and 3) be useable within different decision-making strategies. Major contributions include: computational libraries for civil infrastructure resilience analysis using a standardized modeling language to represent inter- and intra-system dependencies; specific instances of these libraries for water infrastructure systems; a prototype of a system simulation model that incorporates SCADA-data-infused hydraulic models for performance assessment for a real system; a set of new quantitative metrics for assessing and comparing alternative plans for improving system-level resilience considering short- and long-term performances; and a case study of the new framework.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.