Parameterization Framework and Quantification Approach for Integrated Risk and Resilience Assessments

A growing challenge for risk, vulnerability, and resilience assessment is the ability to understand, characterize, and model the complexities of our joint socioecological systems, often delineated with differing natural (e.g., watershed) and imposed (e.g., political) boundaries at the landscape scale. To effectively manage such systems in the increasingly dynamic, adaptive context of environmental change, we need to understand not just food web interactions of contaminants or the flooding impacts of sea level rise and storm surges, but rather the interplay between social and ecological components within the inherent and induced feedforward and feedback system mechanisms. Risk assessment, in its traditional implementation, is a simplification of a complex problem to understand the basic cause‐and‐effect relationships within a system. This approach allows risk assessors to distill a complex issue into a manageable model that quantifies, or semiquantifies, the effects of an adverse stressor. Alternatively, an integrated risk and resilience assessment moves toward a solution‐based assessment with the incorporation of adaptive management practices as 1 of 4 parts of system resilience (i.e., prepare, absorb, recover, and adapt), and directly considers the complexities of the systems being modeled. We present the Multilevel Risk and Resilience Assessment Parameterization framework for the systematic parameterization and deconstruction of management objectives and goals into assessment metrics and quantifiable risk measurement metrics and complementary resilience measurement metrics. As a proof‐of‐concept, the presented framework is paired with the Bayesian Network–Relative Risk Model for a human‐focused subset of a larger risk and resilience assessment of climate change impacts within the Charleston Harbor Watershed of South Carolina. This new parameterization framework goes beyond traditional simplification and embraces the complexity of the system as a whole, which is necessary for a more representative analysis of an open, dynamic complex system. Integr Environ Assess Manag 2021;17:131–146. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)