Murree, called ‘Queen of Mountains’, is a tourist attraction situated at the foothill of (outer) Himalaya. This study assesses the radionuclide concentration in the natural spring water of Murree and the variation of mass-attenuation coefficient in soil with altitude. For this study, 20 natural springs were selected for water sampling while soil samples were collected from 15 sites employing random sampling. The average radionuclide concentration of Radium-226, Thorium-232, and Potassium-40 were 0.43 ± 0.09, 0.52 ± 0.08, and 1.52 ± 0.19 Bq/L respectively. The radionuclide concentration in Murree’s water is above average as compared to the natural radionuclide concentration in spring water worldwide. The radiation hazard indices namely Radium equivalent (Raeq), external and internal hazard index (Hin & Hex), Indoor and outdoor dose (Din & Dout), annual indoor and outdoor effective dose (Eout & Ein), and lifetime cancer risk (LCR) were quantified. The mean values of Raeq, Hex, Hin, Dout, Din, Eout, Ein, LCRout and LCRin are 1.26 Bq/L, 0.003, 0.005, 0.564 nGy/h, 1.067 nGy/h, 0.001 mSv/y, 0.005 mSv/y, 0.002 & 0.018 respectively. The radionuclides concentration revealed that Murree’s natural spring water has above average radionuclides activity, but the health hazards are not alarming. The mass attenuation coefficient was quantified for 356, 661, 1173, and 1332 keV energies experimentally using Ba-133, Cs-137 & Co-60 sources and theoretically using XCOM software. The mean value of mass attenuation for 356, 661, 1173, 1332 keV is 0.097, 0.074, 0.057, 0.054 cm2/g respectively. The radiation attenuation parameters like Half value layer (HVL), Tenth value layer (TVL), Mean free path (MFP), and the thickness of soil required to attenuate 99% of the radiation were also calculated. Comparatively, Murree’s soil showed lower attenuation properties as compared to cement, tiles, concrete, and Egyptian soil. To correlate the data statistical tools Principal Component Analysis (PCA) and Pearson’s Correlation were used. To express the data spatially ESRI ARC-GIS was used employing Inverse Distance Weighting Interpolation (IDW).