Embedded resource accounting for coupled natural‐human systems: An application to water resource impacts of the western U.S. electrical energy trade

Abstract

In complex coupled natural-human systems (CNH), multitype networks link social, environmental, and economic systems with flows of matter, energy, information, and value. Embedded Resource Accounting (ERA) is a systems analysis framework that includes the indirect connections of a multitype CNH network. ERA is conditioned on perceived system boundaries, which may vary according to the accountant's point of view. Both direct and indirect impacts are implicit whenever two subnetworks interact in such a system; the ratio of two subnetworks' impacts is the embedded intensity. For trade in the services of water, this is understood as the indirect component of a water footprint, and as ''virtual water'' trade. ERA is a generalization of input-output, footprint, and substance flow methods, and is a type of life cycle analysis. This paper presents results for the water and electrical energy system in the western U.S. This system is dominated by California, which outsources the majority of its water footprint of electrical energy. Electricity trade increases total water consumption for electricity production in the western U.S. by 15% and shifts water use to water-stressed Colorado River Basin States. A systemic underaccounting for water footprints occurs because state-level processes discount a portion of the water footprint occurring outside of the state boundary.

The Hydro-Economic Interdependency of Cities: Virtual Water Connections of the Phoenix, Arizona Metropolitan Area

“…Using the commodity (2.2) and labor (2.3) approaches to calculating virtual water flows, a net water footprint was calculated for each PMA municipality and for the metropolitan area using the Embedded Resources Accounting (ERA) framework [16,17]. Used in this context, ERA is a minor variation on the standard Water Footprint Assessment (WFA) [75] notation that accounts for a hierarchy of nested boundary conditions by disaggregating the internal water footprint term to reveal internal virtual water flows between entities inside a boundary.…”

“…Indirect or virtual water dependencies are concentrated within the same local hydrology and physical water supply upon which the PMA directly depends for its water supply, rather than being spatially distributed to hydrologically diversified regions. This large circular virtual water trade within the PMA and large dependency within the Southwestern US region and Colorado River Basin amplifies the community's hydro-economic exposure to scarcity and disruption of the local water resources [16,17].…”

“…Engineering, game theory, policy, and economic research have examined this problem from the perspective of managing the physical water resources and infrastructure and designing incentives for mutually beneficial cooperation [14,15]. However, this type of examination only reveals reliance on rival and frequently non-excludable [16,17] physical water resources, which are inputs to a city's urban metabolism [18].…”

Water Footprint of Cities: A Review and Suggestions for Future Research

“…Ultimately, network and multi-network approaches provide a mathematical framework for the integrated characterization and modeling of the system (e.g., producers, consumers, transfers, etc.) underlying the WF [35,73]. Additional information and examples of the application of network analysis to WF studies can be found elsewhere [71,[73][74][75].…”

“…Further investigation of grey water analysis in urban regions is needed and a complete urban WF analysis will need to consider all the flows identified in Figure 1. Recently, a generalization of EEIO and EFA methods, termed Embedded Resource Accounting (ERA), was proposed and developed [35,73,141]. ERA makes explicit the assumptions implied by the different footprint standards and methods, and in doing so it not only adds transparency to footprint analysis but it also facilitates the integration of different datasets (e.g., IO tables, commodity flows, etc.).…”