CRISP Type 1: Protecting Coastal Infrastructure in a Changing Climate by Integrating Optimization Modeling and Stakeholder Observations
Interdependent critical infrastructure in coastal regions has long been threatened by storm-induced flooding. Events such as Hurricanes Sandy and Katrina punctuated the need for plans to protect our infrastructure, but these events only reflect a possible future threat and do not fully address the unknown probability and impacts of a future threat. This uncertainty is only made more critical by the addition of climate change to exacerbate and amplify impacts, in particular sea-level rise. The goal of the proposed work is to address the threat from storm-induced flooding to interdependent infrastructure, including transportation and power systems and emergency services, by developing a methodology that can test various adaptation strategies. Strategies in this context include, but are not restricted to, building sea-walls or other physical, protective mechanisms. The proposed methodology would optimize strategies to maximize their protective abilities over time and space constrained by budgetary considerations. To accomplish this the methodology will contain four conceptual steps: (1) formulate a new strategy for adaptation, (2) computationally determine flooding levels given an ensemble of storms representing the likely threat and future sea-level rise, (3) estimate the damage over the ensemble to the infrastructure considered, and (4) using appropriate metrics evaluate the relative suitability of a given strategy including cost and social acceptability. This process would repeat iteratively until a sufficiently optimal strategy is found. Developing such a methodology will be challenging however. The magnitude of the computational effort needed is significant. Using a set of computational models that vary in accuracy and speed, the methodology will swap between models appropriate for the optimization stage. The methodology will also not be successful without stakeholder engagement. For this reason, interviews with key stakeholders will be an important component of the methodology design and implementation. Interviews will inform the identification of critical components of infrastructure and the interdependencies among them that could be affected by coastal flooding, assist in the design of the optimization metrics, and assess how well the output of the methodology matches stakeholder expectations. Community meetings will also be held to introduce and discuss the results of the methodology with local communities who would potentially benefit from the adaptation strategies. Finally, using New York City's complex infrastructure and recent events, the methodology will be validated.
The intellectual merit of the proposed work lies within two primary areas. The first involves the novelty of addressing the computational tractability of the proposed methodology by using multiple computational models of the flood threat. This approach will allow the optimization space to be refined by using the quickly computed model switching to the more expensive but more accurate model when the optimization parameter space has been sufficiently reduced. This also includes the use of adaptive methods and the exploration of metrics for determining when to switch between the models. The second is the incorporation of stakeholder interviews into the methodology both to inform the optimization but also to validate and better understand how the methodological results match stakeholder mental models of the adaptation strategies and infrastructure. Work will be undertaken to understand better how to incorporate these data into the quantitative framework and identify best practices for transferring the methodology to other communities and contexts.
The proposed work will have direct impacts on society by providing pathways to formulate and evaluate adaptation strategies in the face of climate change not only for New York City but throughout the world. Interaction with stakeholders and communities will also raise awareness of the threat, viable solutions, and what considerations need to be made to produce sustainable, actionable, and socially acceptable adaptation strategies that increases resilience to climate change. The project will also train two graduate students, including training across engineering, computational science, and social science disciplines.