Emerging hotspots of thermal stress in the Ganga River Valley under climate change using the Universal Thermal Climate Index 1991 to 2024

The assessment of human thermal stress under changing climatic conditions has gained increasing attention in recent decades, particularly in densely populated regions. This study examines the spatio-temporal variability and long-term trends in thermal stress across the Ganga River Valley using the Universal Thermal Climate Index (UTCI) for the period 1991–2024. Daily UTCI data derived from the ERA5-HEAT dataset were aggregated to the district level to evaluate monthly, seasonal, and annual patterns of thermal stress. The frequency of days under different UTCI stress categories was quantified, and temporal trends were assessed using linear regression, the Mann–Kendall test, and Sen’s slope estimator. Results indicate a significant increase in strong heat stress (SHS) days at an average rate of 13.3 days per decade, accompanied by a decline in thermally comfortable conditions. The spatial analysis distinguishes areas of high baseline thermal stress from areas of more rapid thermal-stress intensification. The highest long-term mean annual UTCI values were concentrated primarily in southern West Bengal, whereas stronger increases in thermal-stress frequency were observed in parts of Bundelkhand and central Uttar Pradesh. Trend analysis further shows a statistically significant rise in annual UTCI across most districts, with rates exceeding 0.025 °C yr⁻¹ in several locations. Seasonal analysis indicates that the monsoon and post-monsoon periods contribute substantially to the observed increase in thermal stress. The study finding reveal substantial spatial heterogeneity in both baseline thermal stress and its temporal intensification across the Ganga River Valley, providing a climatological basis for geographically targeted climate adaptation and heat-risk management. As the study assesses thermal hazard rather than population-level health risk, the implications for human health should be interpreted cautiously and require integration with population exposure, vulnerability, and health outcomes.