English

Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing

Distributed, Parallel, and Cluster Computing 2025-07-02 v2 Hardware Architecture Computers and Society Machine Learning

Abstract

Water consumption is an increasingly critical dimension of computing sustainability, especially as AI workloads rapidly scale. However, current water impact assessment often overlooks where and when water stress is more severe. To fill in this gap, we present SCARF, the first general framework that evaluates water impact of computing by factoring in both spatial and temporal variations in water stress. SCARF calculates an Adjusted Water Impact (AWI) metric that considers both consumption volume and local water stress over time. Through three case studies on LLM serving, datacenters, and semiconductor fabrication plants, we show the hidden opportunities for reducing water impact by optimizing location and time choices, paving the way for water-sustainable computing. The code is available at https://github.com/jojacola/SCARF.

Keywords

Cite

@article{arxiv.2506.22773,
  title  = {Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing},
  author = {Yanran Wu and Inez Hua and Yi Ding},
  journal= {arXiv preprint arXiv:2506.22773},
  year   = {2025}
}

Comments

7 pages, 9 figures, The 4th Workshop on Sustainable Computer Systems (HotCarbon'25), Cambridge, MA, July 10-11th, 2025