CRISP 2.0 Type 2: Collaborative Research: Integrated Socio-Technical Modeling Framework to Evaluate and Enhance Resiliency in Islanded Communities (ERIC)

Recent catastrophic events in the coastal tropics and sub-tropics highlight the impact of the interdependencies of critical infrastructure systems and how those interdependencies cause failures of physical assets, leading to adverse impacts on the health and socio-economic wellbeing of the communities in those regions. Islanded communities, defined as remote, self-contained regions, with low or intermittent physical (or cyber) connectivity, are especially vulnerable to natural disasters.

A recent example is the extraordinary case of the island of Puerto Rico (PR), in the direct path of Hurricane Maria, and the near total failure of lifeline infrastructures. This event also exemplifies how extreme events compound endemic physical, social and economic vulnerabilities often present in remote or isolated communities. The associated cascading impacts, prior to and after Hurricane Maria, are clear evidence of our limited knowledge and readiness to anticipate risks in these complex engineered, physical and human systems.

This reveals the urgent need to develop scientific and social frameworks and methodologies by which islanded communities can assess their existing preparedness to extreme climatic events, and through a multi-stakeholder engagement process and engineering analysis, evaluate and implement alternative measures to enhance the resiliency of such communities. Using PR as the case study, this Critical Resilient Interdependent Infrastructure Systems and Processes (CRISP) project will develop a data-driven modeling framework for understanding the complex physical and social vulnerabilities, and interdependencies that can and have resulted in near total failure of infrastructure systems.

The research questions that will be addressed include: a) How do socio-economic stability, governance and baseline conditions of infrastructure impact performance and resiliency of critical interdependent infrastructure systems in extreme weather conditions? b) What knowledge and methods are needed to guide strategies for enhancing system resiliency and restoration in islanded communities? c) How can experts and stakeholders be engaged and informed about enhancing resiliency and effective failure mitigation strategies? The plan to achieve these objectives is by first implementing a data-driven process of gathering human narratives as social data and a source of information to recreate the timeline and experience of Hurricane Maria, before, during and after the event.

Next, the project team will develop an integrated modeling and simulation framework, based on multi-layer distribution network theory. This framework will include structural-based assessment results in the modeling of infrastructure behavior during and after a disaster. The focus of study will be on the interdependencies of the electrical power, water distribution and communications systems.

An objective is to recreate, via simulation, the event using a combination of system network models, geophysical data, and community data, to capture the sequence of the cascading failures and the corresponding societal impact as the event unfolded and during post-event recovery efforts. The project team seeks to arrive at a level of understanding of this system of systems that will lead to informed solutions and recommendations that will minimize adverse impact, disruption, loss of life and suffering, in the face of future extreme events.

The research builds on a wealth of expertise in weather and climate processes in the Caribbean, understanding of local critical infrastructure, experience in mining community narrative, and from proven methodologies for rebuilding resilient communities in post-Hurricane Sandy in the New York and New Jersey Metro Area.

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.