Not All Water Consumption Is Equal: A Water Stress Weighted Metric for Sustainable Computing
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Abstract (arXiv)
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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 6 of its 48 references that are in the map. First posted on arXiv 28 Jun 2025.
Builds on
6 of 48 references.
References · 6
- 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
- 2025Holistically Evaluating the Environmental Impact of Creating Language Modelscited by 26
- 2023Towards Environmentally Equitable AI via Geographical Load Balancingcited by 10
- 2023Beyond CO2 Emissions: The Overlooked Impact of Water Consumption of Information Retrieval Modelscited by 6
- 2024A Dataset for Research on Water Sustainabilitycited by 4
- 2025WaterWise: Co-optimizing Carbon- and Water-Footprint Toward Environmentally Sustainable Cloud Computingcited by 2
Built on by
Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2025Systematic Characterization of LLM Quantization: A Performance, Energy, and Quality Perspectivecited by 9
- 2026BIRDS: Characterizing and Understanding Biodiversity Impact of Large Language Model Servingcited by 1
- 2026Beyond PUE: A Local Impact Audit Framework for Data Center Environmental Accountabilitycited by 0
- 2026Beyond Energy: When Sustainability Dimensions Reshape LLM Serving Decisionscited by 0
- 2026Beyond Energy: When Sustainability Dimensions Reshape LLM Serving Decisions28 Sep 2026
- 2026Beyond PUE: A Local Impact Audit Framework for Data Center Environmental Accountability20 Sep 2026
- 2026BIRDS: Characterizing and Understanding Biodiversity Impact of Large Language Model Serving26 May 2026
- 2025Systematic Characterization of LLM Quantization: A Performance, Energy, and Quality Perspective22 Aug 2025
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