interflow: A Python package to organize, calculate, and visualize sectoral interdependency flow data

Kendall L. Mongird, Konstantinos Oikonomou, Juliet S. Homer, and Jennie S. Rice

Department of Energy, Office of Science, Earth & Environmental Systems Modeling, MultiSector Dynamics Program Acknowledged Support: No, other Non-MSD source of support

DOI: 10.21105/joss.04336


Many economic sectors rely on an uninterrupted “upstream” supply of a resource to conduct
their primary functions, leaving them vulnerable to adverse effects should that resource flow be
interrupted or compromised (OECD, 2017; U.S. EPA, 2010). Well-known examples of these
relationships include water demand by the energy sector (e.g., thermoelectric cooling for nuclear
generation) (Grubert & Sanders, 2018; Webber, 2017) and energy demand by the water sector
(e.g., electricity required to treat or move water in the public water sector) (Congressional
Research Service, 2017) though many others exist. Being able to calculate and document
these interdependencies and evaluate where the greatest cross-sectoral intensities and flows
exist can reveal opportunities to enhance the overall network. Despite the implications and
potential impacts, however, these interconnections and flows have been historically complex to
analyze and understand.

The interflow package provides a flexible tool to organize, calculate, and visualize (using
Sankey diagrams and other visualizations) sectoral interdependency flows for multiple subsectors
and resources (Figure 1). This tool can help decision-makers, researchers, and other audiences
more easily pull meaning from these interdependencies to reveal multi-faceted opportunities
and risks. interflow can help investigate questions such as (1) which sectors have high
cross-resource dependencies, (2) how does demand for a resource in various sectors compare
across regions, and (3) where the sectoral and regional opportunities are for enhanced efficiency,
security, and resiliency.

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