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    Area of Science:

    • Environmental Science
    • Systems Engineering
    • Data Science

    Background:

    • Food, energy, and water (FEW) systems exhibit complex interdependencies, creating a nexus with significant strengths and vulnerabilities.
    • Analyzing these FEW nexus interactions is challenging due to the difficulty in observing key variables, hindering cross-sector analysis.
    • Existing methods lack effective tools for exploring and interpreting simulation data from coupled FEW models.

    Purpose of the Study:

    • To present FEWSim, a visual analytics framework designed to support domain experts in exploring and interpreting simulation results from coupled FEW models.
    • To enable robust cross-sector analysis of FEW nexus interactions by overcoming challenges in data observation.
    • To facilitate the evaluation of scenario performance and sustainability within the FEW nexus.

    Main Methods:

    • Developed a three-layer asynchronous architecture: model layer for FEW simulation, middleware layer for scenario management, and visualization layer for interactive exploration.
    • Integrated food, energy, and water models to simulate the FEW nexus.
    • Implemented interactive visualizations for time-series results across FEW sectors and scenario comparison using sustainability indices.

    Main Results:

    • FEWSim provides a framework for domain experts to explore and interpret complex simulation results from coupled FEW models.
    • The visualization layer enables interactive exploration of time-series data and comparison across multiple scenarios.
    • Sustainability indices were used to evaluate scenario differences in performance, demonstrating the utility of the framework.

    Conclusions:

    • FEWSim effectively supports domain experts in analyzing FEW nexus interactions and simulation outcomes.
    • The visual analytics framework enhances understanding of system strengths, vulnerabilities, and scenario impacts.
    • The case study in Phoenix AMA, Arizona, validates the practical application and utility of FEWSim for FEW nexus research.