Surface monitoring and spatial analysis of terrestrial gamma radiation exposure in a tectonically active Himalayan region and seasonal prediction using random forest modeling.

This study evaluates indoor and outdoor terrestrial gamma dose rates and associated radiological parameters in the Devprayag region of the Garhwal Himalayas, India. Measurements were conducted at 34 georeferenced locations using a portable Geiger-Müller-based dosimeter and GPS mapping. Outdoor dose rates varied between 0.09 ± 0.005 and 0.15 ± 0.007 μSv/h (average 0.12 ± 0.006 μSv/h), while indoor dose rates ranged from 0.10 ± 0.005 to 0.16 ± 0.007 μSv/h (average 0.14 ± 0.006 μSv/h). The corresponding annual effective dose (AED) was found to be 0.60 ± 0.05 to 0.96 ± 0.07 mSv/y with an average of 0.82 ± 0.06 mSv/y, which remains below the recommended public dose limit of 1 mSv/y. Health risk indices were also evaluated. The Radiation Hazard Index (RHI) remained below unity at all sites, confirming that exposures are within permissible safety limits. The Annual Gonadal Dose Equivalent (AGDE) values, though spatially variable, were comparable to international averages and did not exceed reference safety levels. To complement field monitoring, Random Forest Regression (RFR) was applied using climatic parameters (temperature, rainfall, rainy days, and elevation) as predictors. The model achieved robust predictive accuracy (R2 > 0.80), capturing seasonal patterns of dose variation. Results indicated that monsoon conditions corresponded to the lowest predicted dose rates, while other seasons showed moderately higher values, reflecting the influence of rainfall and topography. Overall, the integration of spatial mapping with machine learning provides a cost-effective framework for radiological surveillance in mountainous terrains. The findings confirm that radiation levels in Devprayag are within internationally accepted limits, while highlighting the value of periodic monitoring and predictive modeling for long-term radiation safety management.

• Publication year

  2025

• Venue

  Science of the Total Environment

• Publication date

  2025-11-11

• Fields of study

  Medicine, Environmental Science

• Identifiers
  DOI 10.1016/j.scitotenv.2025.180943PMID 41223553
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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