Dr Iram Ali ^1* Aparna Shukla ² Shakil Ahmad Romshoo ³ Farooq Ahmad Lone ¹ Purushottam Kumar Garg ⁴ Bisma Yousuf ¹

• ¹ Sher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir, Srinagar, India
• ² Ministry of Earth Sciences, New Delhi, National Capital Territory of Delhi, India
• ³ Islamic University of Science and Technology, Awantipora, Jammu and Kashmir, India
• ⁴ Pant National Institute of Himalayan Environment, Ladakh Regional Centre, Leh Ladakh, India

Supraglacial debris modulates thermal regime and alters glacial melt rates depending on its thickness. Estimation of debris thickness thus becomes imperative for prediction of hydrological response and dynamics of such glaciers. This paper tests the performance of empirical and thermal resistance-based debris thickness approaches against fieldmeasurements on the Hoksar glacier, Kashmir Himalaya. The aim was accomplished by using thermal imageries (Landsat-OLI, 2017 and AST08, 2017) and reanalysis ERA-5 datasets. The spatially resolved estimates of debris thickness for entire debris-covered zone was firstly achieved by establishing an empirical relationship between debris thickness and debris surface temperature (both field and satellite thermal imageries). Secondly, debris thickness for every pixel of thermal imagery was executed by calculating thermal resistance from energy balance model incorporating major inputs from (ERA-5), debris temperature (AST08, Landsat OLI) and thermal conductivity. On comparison with field temperature and thickness measurements with satellite temperature, homogenous debris thickness pixels showed an excellent coherence (r=0.9 p value< 0. 001 for TAST08 and r=0.88 p value< 0.001 for TLandsat OLI for temperature) and (r= 0.9; p value< 0.001 for TAST08 and r= 0.87; p value< 0.002 for TLandsat OLI for debris thickness). Both the approaches effectively captured the spatial pattern of debris thickness using Landsat OLI and AST08 datasets. However, results specify an average debris thickness of 18.9 ±7.9 cm from field which empirical approach underestimated by (12% for AST08 and 28% for Landsat OLI) and thermal resistance approach overestimated by (6.2% for AST08 and 5.1% for Landsat OLI) respectively. Debris thickness estimates from thermal resistance approach (deviation 11.2% for AST08 and 11.6% for Landsat OLI) closely mirrors to fieldmeasurements compared to empirical approach (deviation 26.9% for AST08 and 35% for Landsat OLI). Thus, thermal resistance approach can solve spatial variability in debris thickness on different heavily debris-covered glaciers globally without the knowledge of field measurements.