Introducing Groundsource: Turning news reports into data with Gemini

Groundsource is a Google Research methodology that uses Gemini to convert global news reports into structured historical records of natural disasters. Its first dataset contains 2.6 million flash-flood events across more than 150 countries from 2000 onward, addressing major gaps in conventional flood databases. Google reports that the system can support near-global urban flash-flood forecasts up to 24 hours in advance.

The problem: Limited historical disaster data

• Floods lack the standardized global sensor infrastructure available for hazards such as earthquakes.
• Existing sources, including the Global Flood Database and Dartmouth Flood Observatory, are limited by cloud cover, satellite revisit times, and their focus on large or long-lasting floods.
• GDACS contains roughly 10,000 high-impact disaster records but misses many localized and rapidly developing flash floods.
• This shortage of reliable historical data makes global forecasting, model training, and validation difficult.

How Groundsource processes news

• The system analyzes news articles where flooding is the primary subject.
• Google Read Aloud extracts article text in 80 languages, which is translated into English using Cloud Translation.
• Gemini then applies a verification-oriented prompt to:
  • Distinguish actual past or ongoing floods from warnings, policy discussions, and general risk reports.
  • Resolve relative dates such as “last Tuesday” using the article’s publication date.
  • Identify precise locations, including neighborhoods and streets.
  • Map locations to standardized geographic polygons through Google Maps Platform.

Accuracy and scale

• Manual evaluation found:
  • 60% of events were accurate in both timing and location.
  • 82% were sufficiently accurate for practical analysis, such as identifying the correct administrative district or event day.
• The resulting dataset contains 2.6 million flood events, greatly exceeding traditional monitoring archives.
• Between 2020 and 2026, Groundsource captured 85%–100% of severe flood events listed by GDACS while also recording smaller local incidents.
• Coverage is densest in recent years, particularly from 2020 to 2025, reflecting the growth of digitized news.

Forecasting and future applications

• Groundsource data has enabled near-global urban flash-flood forecasts up to 24 hours ahead.
• These forecasts are being integrated into Google Flood Hub.
• Google plans to improve rural coverage and incorporate additional data sources.
• The same approach could help build historical datasets for droughts, landslides, avalanches, and other hazards with limited ground-truth records.

Groundsource demonstrates that news archives can serve as a large-scale source of disaster history when combined with language models, translation, and geographic verification. Its open flash-flood dataset could improve forecasting and resilience planning, though its reported accuracy levels make continued validation and refinement important.