Abstrakt: |
Water resources are required for cooling of thermoelectric power plants and in the production of hydroelectricity. Scarcity of water resources impacts the ability to generate electricity in grids across the globe. There is extensive literature and research on the electricity‐water nexus, spanning hydrology, policy, and energy sectors. Existing research often focuses on quantifying a static relationship and rarely accounts for expectations of annual, seasonal, and subseasonal water variability in nexus research. This omission leaves an important, unanswered question in the field: how can the water footprinting framework be operationalized in the electricity‐water nexus with hydroclimatic forecasts? Building off the work by Chowdhury et al. (https://doi.org/10.1029/2020EF001814), we comment on the opportunities for climate‐informed, seasonal, or subannual assessments of the electricity‐water nexus to facilitate decision‐making. Plain Language Summary: Water footprints are a tool to assess the impacts of electricity generation on the local environment. However, studies assessing this relationship often generalize the amount of water consumed by electricity generation to a single number throughout a year. Global climate phenomenon shape water resources availability at monthly and annual time scales. To increase robustness and usability of the water footprint metric for decision‐making, there are opportunities for subannual assessments to be paired with forecasts, enhancing the utility of water footprints for electricity. We expand on the work by Chowdhury et al. (https://doi.org/10.1029/2020EF001814) and discuss the impacts of climate phenomena on water availability and the subsequent impact to the production of electricity. Key Points: Current practices of water footprints in the energy sector are limited with static valuesSeasonal assessments of water footprints for electricity will enhance robustness of the metricOpportunities exist to explore utility of pairing subannual assessments of footprints with forecasts for improved decision‐making [ABSTRACT FROM AUTHOR] |