A METHODOLOGY TO ESTIMATE WATER DEMAND FOR THERMAL POWER PLANTS IN DATA-SCARCE REGIONS USING SATELLITE IMAGES

The World Resources Institute developed a three-step method to estimate thermal power plant water demand: identifying cooling and fuel types via satellite images, assigning water-use factors from empirical data, and calculating total use based on net generation. Tested on 200 U.S. plants, the method achieved 90% precision in cooling and 89% in fuel identification, though water demand estimation precision was lower at 69%. The authors note limitations regarding image resolution, the inability to distinguish specific generation technologies within a fuel type, and the reliance on U.S.-based water-use factors which may vary globally.

• The proposed methodology consists of three steps: first, using satellite images to identify cooling and fuel types; second, assigning water withdrawal and consumption factors based on those identifications; and third, calculating total water use using net generation data.
• Testing the method against 200 thermal power plants in the United States showed high accuracy in classification, with 90 percent average precision for both fuel and cooling technology identification.
• The methodology's precision in estimating actual water demand was 69 percent, with the highest accuracy found in dry-cooled and recirculating tower plants, and larger disparities occurring in once-through and recirculating pond systems.
• The research identifies specific visual markers for different technologies: coal plants often have black coal fields and conveyor belts; nuclear plants feature large domed towers; and dry cooling systems have 'accordion-like' structures.
• Several limitations affect the method's accuracy, including the inability to distinguish between different generation technologies within the same fuel type (such as subcritical vs. supercritical) and the potential for local variations in water-use factors outside the United States.

APA

LUO, T., KRISHNASWAMI, A., & LI, X. (2018). A METHODOLOGY TO ESTIMATE WATER DEMAND FOR THERMAL POWER PLANTS IN DATA-SCARCE REGIONS USING SATELLITE IMAGES. World Resources Institute. https://wriorg.s3.amazonaws.com/s3fs-public/17_TECH_PowerPlants_V7.pdf

Chicago

LUO, TIANYI, ARJUN KRISHNASWAMI, and XINYUE LI. A METHODOLOGY TO ESTIMATE WATER DEMAND FOR THERMAL POWER PLANTS IN DATA-SCARCE REGIONS USING SATELLITE IMAGES. World Resources Institute, 2018. https://wriorg.s3.amazonaws.com/s3fs-public/17_TECH_PowerPlants_V7.pdf.

Wikipedia

{{cite report |last1=LUO |first1=TIANYI |last2=KRISHNASWAMI |first2=ARJUN |last3=LI |first3=XINYUE |title=A METHODOLOGY TO ESTIMATE WATER DEMAND FOR THERMAL POWER PLANTS IN DATA-SCARCE REGIONS USING SATELLITE IMAGES |publisher=World Resources Institute |date=January 2018 |url=https://wriorg.s3.amazonaws.com/s3fs-public/17_TECH_PowerPlants_V7.pdf |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{luo2018methodology, author = {LUO, TIANYI and KRISHNASWAMI, ARJUN and LI, XINYUE}, title = {{A METHODOLOGY TO ESTIMATE WATER DEMAND FOR THERMAL POWER PLANTS IN DATA-SCARCE REGIONS USING SATELLITE IMAGES}}, institution = {World Resources Institute}, year = {2018}, month = jan, url = {https://wriorg.s3.amazonaws.com/s3fs-public/17_TECH_PowerPlants_V7.pdf}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }