  The electric power grid is a critical societal resource connecting multiple
infrastructural domains such as agriculture, transportation, and manufacturing.
The electrical grid as an infrastructure is shaped by human activity and public
policy in terms of demand and supply requirements. Further, the grid is subject
to changes and stresses due to solar weather, climate, hydrology, and ecology.
The emerging interconnected and complex network dependencies make such
interactions increasingly dynamic causing potentially large swings, thus
presenting new challenges to manage the coupled human-natural system. This
paper provides a survey of models and methods that seek to explore the
significant interconnected impact of the electric power grid and interdependent
domains. We also provide relevant critical risk indicators (CRIs) across
diverse domains that may influence electric power grid risks, including
climate, ecology, hydrology, finance, space weather, and agriculture. We
discuss the convergence of indicators from individual domains to explore
possible systemic risk, i.e., holistic risk arising from cross-domains
interconnections. Our study provides an important first step towards
data-driven analysis and predictive modeling of risks in the coupled
interconnected systems. Further, we propose a compositional approach to risk
assessment that incorporates diverse domain expertise and information, data
science, and computer science to identify domain-specific CRIs and their union
in systemic risk indicators.
