Assessing Compounding Risks Across Multiple Systems and Sectors: A Socio-Environmental Systems Risk-Triage Approach

C. Adam Schlosser, Cypress Frankenfeld, Sebastian Eastham, Xiang Gao, Angelo Gurgel, Alyssa McCluskey, Jennifer Morris, Shelli Orzach, Kilian Rouge, Sergey Paltsev, John Reilly

Department of Energy, Office of Science, Earth & Environmental Systems Modeling Program Acknowledged Support: Yes, Multisector Dynamics


Physical and societal risks across the natural, managed, and built environments are becoming increasingly complex, multi-faceted, and compounding. Such risks stem from socio-economic and environmental stresses that co-evolve and force tipping points and instabilities. Robust decision-making necessitates extensive analyses and model assessments for insights toward solutions. However, these exercises are consumptive in terms of computational and investigative resources. In practical terms, such exercises cannot be performed extensively—but selectively in terms of priority and scale. Therefore, an efficient analysis platform is needed through which the variety of multi-systems/sector observational and simulated data can be readily incorporated, combined, diagnosed, visualized, and in doing so, identifies “hotspots” of salient compounding threats. In view of this, we have constructed a “triage-based” visualization and data-sharing platform—the System for the Triage of Risks from Environmental and Socio-Economic Stressors (STRESS)—that brings together data across socio-environmental systems, economics, demographics, health, biodiversity, and infrastructure. Through the STRESS website, users can display risk indices that result from weighted combinations of risk metrics they can select. Currently, these risk metrics include land-, water-, and energy systems, biodiversity, as well as demographics, environmental equity, and transportation networks. We highlight the utility of the STRESS platform through several demonstrative analyses over the United States from the national to county level. The STRESS is an open-science tool and available to the community-at-large. We will continue to develop it with an open, accessible, and interactive approach, including academics, researchers, industry, and the general public.

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