Published July 14, 2026
| Version v3
Dataset
Restricted
Global Data Center Water Use and Scarcity Analysis
Authors/Creators
Description
Repository Structure
Data Organization
Inputs
2_energy_and_water_use/: Contains reference data for energy and water calculations
- Power plant databases: Data is from the WRI global power plant database version 1.30 (Byers et al., 2018; download [here]
- Electricity grid maps: Power grid geojson from here
- Climate zone data: Köppen climate zone 1991-2020 tif from Beck et al., 2023
- Power plant water intensity: Based off of Jin et al., 2019
- PUE and WUE scenario definitions: Derived from Lei & Masanet, 2022
3_water_scarcity: PCR-GLOBWB model outputs for water scarcity analysis, from Barbarossa et al., 2021
- *Note*: inputs are not included in downloads due to their size (30 GB). The dataset can be found through the publication above.
4_figures: Basin data for visualization, based on Pfafstetter watershed sub-basin level 5, from HydroBASINS
common: Country boundaries from Natural Earth Data
Outputs
0_webscraping: Raw data collected from data center directories
1_data_etl: Processed and cleaned data center information
- Geocoded data center locations
- Pre- and post-manual editing versions
- Fuzzy matching results
- Merging data sources
- Multiple imputation scenarios (min, max, average, baseline) for Big Tech companies
2_energy_and_water_use: Calculated energy and water use of data centers globally
- Imputed power capacity from floor area
- Assigned power and water use efficiencies per data center
- Direct impact assessments
- Assigned power grids to data centers
- Indirect water use of data centers
3_water_scarcity: Water scarcity analysis results
- Data center water extraction location mappings
- PCR-GLOBWB extracted values for discharge and abstraction
- Water scarcity summaries for different climate scenarios (1.5°C, 2.0°C, 3.2°C) at data center locations
- Water scarcity increases from data-center-driven water use
Files
Additional details
Software
- Repository URL
- https://github.com/amwientjes/data-center-water-footprint
- Programming language
- Python , Jupyter Notebook