Cities throughout the globe are expanding due to rapid urbanization. The risk associated with heat on residents is increasing and thus requires interventions at an intraurban level. This study aims to determine the spatial distribution of the heat stress risk index (HSRI) in an urban area of Delhi (India). This study illustrates a novel technique using meteorological variables simulated from a numerical weather prediction urban canopy model (WRF-UCM) to generate the Universal Thermal Climate Index (UTCI) in the city of Delhi at a resolution of 333 m. The estimated UTCI is then optimally blended with the socioeconomic vulnerability and exposure indices generated through the identification of suitable parameters via principal component analysis (PCA). The analysis based on the high-resolution UTCI risk index showed that within the existing framework, 88 % of the city falls under a heat stress risk above the “Moderate to Highest” category of stress values, which explicitly affects the population and requires urgent interventions for the development of a resilient and sustainable city. The study also revealed that the areas with the highest UTCIs may not correspond to the zones related to the highest heat stress risk. This suggests that the HSRI rather than the UTCI alone should be the optimal indicator for consideration by stakeholders when developing policies to mitigate heat stress-related issues in urban areas under changing climate.
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