Current Science

K. K. Singh ¹, A. Kumar ², A. V. Kulkarni ³, P. Datt ¹, S. K. Dewali ¹, V. Kumar ¹, R. Chauhan ¹

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 National Institute of Technology, Kurukshetra 136 119, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Abstract

Snow depth is an important parameter for avalanche forecast and hydrological studies. In the Himalaya, manual snow depth data collection is difficult due to remote and rugged terrain and the severe weather conditions. However, microwave-based sensors in various satellites have the capability to estimate snow depth in all weather conditions. In the present study, experiments were performed to establish an algorithm for snow depth estimation using ground-based passive microwave radiometer with 6.9, 18.7 and 37 GHz antenna frequencies at Dhundhi and Patseo, Himachal Pradesh, India. Different layers in the snowpack were identified and layer properties, i.e. thickness, density, moisture content, etc. were measured manually and using a snow fork. Brightness temperature (T_B) of the entire snowpack and of the individual snow layers was measured using passive microwave radiometer. It was observed that T_B of the snow is affected by various snow properties such as depth, density, physical temperature and wetness. A decrease in T_B with increase in snow depth was observed for all types of snow. T_B of the snowpack was observed higher at Dhundhi in comparison to Patseo. Based on the measured radiometer data, snow depth algorithms were developed for the Greater Himalaya and Pir-Panjal ranges. These algorithms were validated with ground measurements for snow depth at different observatory locations and a good agreement between the two was observed (absolute error: 7 to 39 cm; correlation: 0.95).

Keywords

Brightness Temperature, Microwave Radiometer, Snow Depth Algorithm, Snowpack.

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K. K. Singh ¹, H. S. Negi ¹, A. Kumar ², A. V. Kulkarni ³, S. K. Dewali ¹, P. Datt ¹, A. Ganju ¹, S. Kumar ¹

Affiliations
1 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
2 National Institute of Technology, Kurukshetra 136 119, IN
3 Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru 560 012, IN

Abstract

In this study an airborne ground penetrating radar (GPR) is used to estimate spatial distribution of snow accumulation in the Samudra Tapu glacier (the Great Himalayan Range), Western Himalaya, India. An impulse radar system with 350 MHz antenna was mounted on a helicopter for the estimation of snow depth. The dielectric properties of snow were measured at a representative site (Patseo Observatory) using a snow fork to calibrate GPR data. The snow depths estimated from GPR signal were found to be in good agreement with those measured on ground with an absolute error of 0.04 m. The GPR survey was conducted over Samudra Tapu glacier in March 2009 and 2010. A kriging-based geostatistical interpolation method was used to generate a spatial snow accumulation map of the glacier with the GPR-collected data. The average accumulated snow depth and snow water equivalent (SWE) for a part of the glacier were found to be 2.23 m and 0.624 m for 2009 and 2.06 m and 0.496 m for 2010 respectively. Further, the snow accumulation data were analysed with various topographical parameters such as altitude, aspect and slope. The accumulated snow depth showed good correlation with altitude, having correlation coefficient varying between 0.57 and 0.84 for different parts of the glacier. Higher snow accumulation was observed in the north- and east-facing regions, and decrease in snow accumulation was found with an increase in the slope of the glacier. Thus, in this study we generate snow accumulation/SWE information using airborne GPR in the Himalayan terrain.

Keywords

Glacier, Ground Penetrating Radar, Snow Accumulation, Snow Water Equivalent.

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