Policy Document · 2025-05-01
20,000 Kilometers of Code: AI's Secret Voyage Across The Ocean
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Scientific Paper
Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models
Li et al. · 2025-03-26
What it covers
AI models have a significant yet overlooked water footprint, requiring transparency and holistic sustainability efforts alongside carbon reduction.
Who it helps
Intended audience has not been documented.
Limitations
Source-specific limitations have not been reviewed. Inclusion and topic labels do not establish effectiveness or reliability.
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Li et al.. 2025-03-26. Making AI Less “Thirsty”: Uncovering and Addressing the Secret Water Footprint of AI Models. https://arxiv.org/pdf/2304.03271 (AI & Environment Resource Hub; record paper-007; collection snapshot 2026-10-04).
Classification and context
Included in the original Scientific Paper collection. Labels below are metadata based suggestions. They are not verified findings, claims of effectiveness, or endorsements.
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Available source metadata
- Author or creator
- Li et al.
- Publisher
- arXiv
- Publication date
- 2025-03-26
- Date precision
- day
- Geographic scope
- Unknown
- Language
- unknown
- Peer review
- unknown
- Source access
- Reachable at last check
- Metadata confidence
- Required metadata corroborated
- Last verified
- 2026-09-28T20:11:33.502Z
- Snapshot import
- 2026-09-06
- Legacy domain
- Water & Oceans
- Legacy subdomain
- Water Use Efficiency in AI Training
- journal
- arXiv
Provenance and review
- Source access
- Reachable at last check
- Metadata confidence
- Required metadata corroborated
- Editorial relevance
- Relevance has not been separately reviewed.
- Evidence quality
- Evidence quality has not been separately assessed.
Source sheet: Scientific Paper · Row 11 · Original ID: paper-007.
A paper listing is not a quality assessment. Peer review and findings require source-level confirmation. Source link reachable · checked 2026-09-28. Source identity and required metadata verified. The import date is not the original date added.
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Related through shared environmental topics
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Shared topics: Water; Oceans and coasts
Shared topics: Water; Oceans and coasts
Scientific Paper · 2023-12-01
A Case Study Of An Extreme Flooding Episode In Charikar, Eastern Afghanistan
Severe flash floods in Charikar, Afghanistan, on August 26, 2020, were driven by extreme atmospheric instability, deep low-level convergence, and local topography, with climate change intensifying frontal activity and baroclinicity in the region.
Shared topics: Water; Oceans and coasts
Scientific Paper · 2025-04-23
A Deep-Learning Based Parameter Inversion Framework for Large-Scale Groundwater Models
A machine learning framework was developed to efficiently parametrize large-scale hydrogeologic models by learning the relationship between water table depth and hydraulic conductivity from a small number of simulations, enabling realistic predictions with significantly reduced computational cost.
Shared topics: Water; Oceans and coasts
Scientific Paper · 2025-09-25
A Sentinel-3 Foundation Model for Ocean Colour
This study introduces a new foundation model based on the Prithvi-EO Vision Transformer, pre-trained on Sentinel-3 ocean color data, to enhance marine Earth observation. By fine-tuning on chlorophyll and primary production tasks, the model outperforms traditional baselines, showing that self-trained AI can extract detailed spatial patterns from limited labeled data and improve monitoring of ocean ecosystems and climate processes.