Water Ledger

Methods and sources

How Water Ledger's numbers are made

Model version and data date load below.

What it estimates

For a data center of a given size, cooling design and Michigan climate region, Water Ledger estimates three amounts of water on an average day, on the hottest days (a 1-in-10-year peak day) and over a year:

Water used at power plants to make the electricity is shown separately and never added to these on-site numbers.

How

  1. Weather. Hourly temperature and humidity for 1995–2024 at five Michigan locations (ERA5 reanalysis) ; wet-bulb temperature from Stull's formula .
  2. Heat. Nearly all the electricity a data center's computers use becomes heat that must be removed. Heat rejected = computing energy × a heat factor that is lower in cool weather (free cooling) and higher when chillers run, since chiller compressors can add up to about 20% to the heat a cooling tower handles .
  3. Evaporation. Evaporative cooling removes heat by evaporating water (about 1,050 BTU per pound). The share of heat removed by evaporation rises with air temperature; we use the relation from Rutberg et al. (2011) as given in the U.S. Geological Survey's method for cooling towers .
  4. Blowdown and drift. Towers drain some water to control minerals: blowdown = evaporation ÷ (cycles of concentration − 1) . A small amount escapes as droplets (drift) .
  5. Cooling designs differ in when they evaporate: dry systems not at all; closed loops with evaporative assist only on the hottest hours (Microsoft publishes 85 °F as its threshold ); hybrids in warm weather; cooling towers all year. These follow the system types in the national studies .
  6. Uncertainty. Real designs and operations vary, so every estimate is run 200 times across the published parameter ranges below. The calculator shows the middle result in bold and the middle 80% as the likely range.

Parameters

Results by region (per 100 MW of computing capacity)

Middle result with the likely range (10th–90th percentile). "Water per kWh" is per kilowatt-hour of computing energy: evaporated, and taken (the basis national studies report).

How the estimates compare with published and reported numbers

Most operators do not publish a site's size, so few site-by-site checks are possible. We are not aware of a published study that checks a site-level data center water model against metered use at named sites; we show what we can, with its limits.

Water at power plants

Limitations

Independence and data

Water Ledger is a free public resource from Northline Hydrology. It uses public data only; nothing from client work goes into it. It does not rate projects as good or bad; it shows what they could mean for water so people can decide with numbers instead of guesses.

Changelog

Sources

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