Balancing Bits and Drops: Stress-Adjusted Water Management for Data Centers
For data center operators and policymakers, this work provides a more accurate method to assess and mitigate the environmental impact of water consumption, addressing a gap in prior research that ignored location- and time-dependent water stress.
This paper introduces a stress-adjusted water framework that incorporates spatial and temporal water stress to quantify the true environmental impact of data center water consumption, and evaluates strategies such as workload scheduling, rainwater harvesting, and dry cooling to reduce stress-adjusted water use.
Data centers are critical to today's digital economy, but are also among the largest industrial consumers of freshwater. Beyond the sheer volume of water use, the environmental impact of data center water consumption varies significantly across locations and seasons, depending on local and regional water stress. However, prior research has largely focused on reducing total water use, overlooking that the same unit of water can have drastically different environmental consequences depending on when and where it is consumed. In this paper, we introduce a stress-adjusted water framework that quantifies the true sustainability impact of data center water consumption by incorporating both spatial and temporal water stress. Using the AWARE-US model, we capture county-level monthly variations in water availability and extend this framework to account for the off-site water footprint of electricity generation. Based on this stress-aware accounting, we analyze stress-adjusted water-computing strategies spanning both the software and infrastructure layers. Specifically, we study workload scheduling policies that jointly optimize water and carbon efficiency, evaluate the potential of rainwater harvesting as a supplemental water source, and investigate the feasibility of dry cooling as a water-free alternative to evaporative cooling.