Grounding Global Water Risk Assessments in Local Data

The document describes a methodology for bridging the gap between high-level global water risk assessments and local ground truths. Using Unilever as a case study, it illustrates how global tools like Aqueduct provide a necessary starting point for screening hundreds of sites, but require validation through facility manager feedback and expert consultants to correct for limitations in global modeling, such as the inability to account for human-made water transfers or local water quality issues.

• Unilever uses Aqueduct's global indicators to screen over 300 production sites, offices, and warehouses across 100 countries, as relying solely on local data for such a scale would be nearly impossible and could lead to "data quality issues, data definition discrepancies and even data scarcity."
• Global data often aligns with local experience in high-stress areas, such as in Konya, Turkey, where Aqueduct's report of extremely high water stress was confirmed by local staff who observed "sharply declining groundwater tables, erosion and even sinkholes in the landscape."
• Global models can overestimate water stress in freshwater-abundant regions, such as the Great Lakes in North America, because they may not capture "the human transfer and management of water," such as human-made intake points that allow access to supply across shorelines.
• Global models may underestimate water stress by failing to account for local water quality and infrastructure; for example, in a sub-basin near São Paulo, Brazil, local managers reported water shortages and the need to truck in water due to pollution and land degradation that Aqueduct's indicators did not capture.

APA

World Resources Institute (2025). Grounding Global Water Risk Assessments in Local Data. https://www.wri.org/technical-perspectives/grounding-global-water-risk-assessments-local-data

Chicago

World Resources Institute. Grounding Global Water Risk Assessments in Local Data. 2025. https://www.wri.org/technical-perspectives/grounding-global-water-risk-assessments-local-data.

Wikipedia

{{cite report |author=World Resources Institute |title=Grounding Global Water Risk Assessments in Local Data |date=10 July 2025 |url=https://www.wri.org/technical-perspectives/grounding-global-water-risk-assessments-local-data |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldresourcesinstitute2025grounding, author = {{World Resources Institute}}, title = {{Grounding Global Water Risk Assessments in Local Data}}, institution = {World Resources Institute}, year = {2025}, month = jul, url = {https://www.wri.org/technical-perspectives/grounding-global-water-risk-assessments-local-data}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }