Global water-risk signals and public search interest: a country-year analysis of NASA POWER hydroclimate indices and google trends, 2004–2025

Abstract Public attention to water-related hazards is shaped by the interaction of physical conditions, lived experience, media coverage, institutional communication, and access to digital information. This study examines how hydroclimatic anomalies correspond with public information-seeking behavior by constructing a global country-year panel covering 2004–2025. Six hydroclimatic screening indices derived from NASA POWER meteorological data, including drought, flood and extreme rainfall, water deficit, heat-related water stress, hydroclimatic volatility, and overall water risk, are matched with corresponding Google Trends topics. Heat-related water stress shows the strongest contemporaneous association with search interest, followed by flood and extreme rainfall, indicating that visible and immediately experienced hazards are particularly likely to stimulate online information seeking. The fixed-effects results reinforce this ordering and show that changes in hydroclimatic conditions are reflected in variations in search salience within countries over time. The analysis also reveals substantial geographical heterogeneity, demonstrating that the relationship between physical anomalies and public attention depends on national and local contexts. Country-year comparisons identify both convergence, where elevated hydroclimatic risk coincides with heightened search interest, and divergence, where environmental and informational signals follow different trajectories. These findings contribute to socio-hydrological research by integrating physical and digital indicators within a harmonized global framework. Google Trends is most valuable as a complementary measure of public information seeking that can help identify where hydroclimatic conditions become socially visible and where mismatches warrant closer investigation using local environmental, institutional, media, and communication data.