Fine-resolution Modeling of Urban-Energy Systems' Water Footprint in River Networks

Characterizing the interplay between urbanization, energy production, and water resources is essential for ensuring sustainable population growth. In order to balance limited water supplies, competing users must account for their realized and virtual water footprint, i.e. the total direct and indirect amount of water used, respectively. Unfortunately, publicly reported US water use estimates are spatially coarse, temporally static, and completely ignore returns of water to rivers after use. These estimates are insufficient to account for the high spatial and temporal heterogeneity of water budgets in urbanizing systems. Likewise, urbanizing areas are supported by competing sources of energy production, which also have heterogeneous water footprints. Hence, a fundamental challenge of planning for sustainable urban growth and decision-making across disparate policy sectors lies in characterizing inter-dependencies among urban systems, energy producers, and water resources. A modeling framework is presented that provides a novel approach to integrate urban-energy infrastructure into a spatial accounting network that accurately measures water footprints as changes in the quantity and quality of river flows. River networks (RNs), i.e. networks of branching tributaries nested within larger rivers, provide a spatial structure to measure water budgets by modeling hydrology and accounting for use and returns from urbanizing areas and energy producers. We quantify urban-energy water footprints for Atlanta, GA and Knoxville, TN (USA) based on changes in hydrology in RNs. Although water intakes providing supply to metropolitan areas were proximate to metropolitan areas, power plants contributing to energy demand in Knoxville and Atlanta, occurred 30 and 90km outside the metropolitan boundary, respectively. Direct water footprints from urban landcover primarily comprised smaller streams whereas indirect footprints from water supply reservoirs and energy producers included larger river systems. By using projections in urban populations for 2030 and 2050, we estimated scenarios of expansion in water footprints depending on urban growth policies and energy production technology. We provide examples of how this framework can be used to minimize water footprints and impacts to aquatic biodiversity.