Application of Neural Networks for Avalanche Forecasting

Application of neural networks is investigated for the prediction of avalanches on Chowkibal-Tangdhar road axis in Jammu and Kashmir. The networks are developed and trained monthwiseusing the past snow and weather parameters recorded at the Stage-II Observatory on the axisto generate an assessment of avalanche and non-avalanche activities. Two approaches havebeen considered for training the network. In the first approach, only avalanche activities observedin the axis were taken for training, and in the second approach, along with the observed activities,the opinion of expert forecasters were also considered. The performance of the networks variesfrom 67 to 82 per cent for correct predictions. Winter data for 2001-2002 has been used to validatethe network performance

Snowcover Simulation Model : A Review

Numerical simulation of seasonal snowcover has attracted the interest of many scientists in the recent past. The present paper summarises chronologically developments in the understanding of snow properties and discusses various modelling approaches towards simulating the snowpack numerically. The authors describe the evolution of snowcover and the intricate relationship between the evolving snowpack and the atmosphere. The governing equations that describe the evolution of snowcover have been discussed. The merits and limitations of each equation pescribing a single process have been explained. Modelling strategies adopted by various workers have been analysed, and lastly the requirements of a perfect model have been brought out. In the absence of complete answers to many other processes, a strategy for the development of an operational snowcover model has been discussed

Measurement of Temperature Gradient in Seasonal Snowpack using Improved Automated Temperature Profiler (Review Paper)

Snow temperature profile is an important input parameter for assessing the thermal state of snowpack. The individual layers of a snowpack can be weakened by various metamorphic processes occurring due to temperature gradient present within the snowpack and may result in avalanche hazard. The profile of snowpack temperatures also affects snowmelt runoff magnitude and timing, and hence, may cause wet avalanches. The design of an automated instrument for the measurement of snow temperature profiles in a snowpack is discussed. The instrument was designed to operate in stand-alone mode and is capable of measuring and logging data of twelve vertical temperature-sensing probes throughout the winter. It is suitable for measurement of snow temperature profiles in areas which are inaccessible to human during winters. The design considerations, field deployment, results, and future scope of work for the instrument is discussed in detail.Defence Science Journal, 2011, 61(6), pp.554-558, DOI:http://dx.doi.org/10.14429/dsj.61.37

Estimating surface ice velocity on Chhota Shigri glacier from satellite data using Particle Image Velocimetry (PIV) technique

Information about the surface ice velocity is one of the important parameters for Mass balance and Glacier dynamics. This study estimates the surface ice velocity of Chhota Shigri glacier using Landsat (TM/ETM+) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) temporal data-sets from a period of 2009 to 2016 and 2006 to 2007, respectively. A correlation based Particle Image Velocimetry (PIV) technique has been used for the estimation of surface ice velocity. This technique uses multiple window sizes in the same data-set. Four window sizes (low, medium, high, very high) are used for each image pair. Estimated results have been compared with the published data. The outcomes attained from the medium window size closely matches with the published results. The estimated mean surface ice velocities of medium window size are 24 and 28.5 myr−1 for 2009/2010 and 2006/2007 images pair. Highest velocity is observed in middle part of the glacier while lowest in the accumulation zone of the glacier

Glacier surface characteristics derivation and monitoring using Hyperspectral datasets: a case study of Gepang Gath glacier, Western Himalaya

Mountain Glaciers are natural resources of fresh water and these affect the stream flow of the rivers, regional climate and further global climate. Observed trends and projected future evolutions of climate and Cryospheric variables clearly suggest a need to monitor these changes. Accordingly, the article presents the glacier features mapping using Hyperspectral remote sensing imagery. A freely available Hyperion satellite imagery acquired over Gepang Gath glacier in Himachal Pradesh, India is used for the study. Each class is identified based on their surface characteristics of spectral reflectance properties. Identification is simplified by demarcating the study glacier into accumulation and ablation areas through snowline. Accumulation area is characterized with high reflectance clean snow/ice and reduced moderate reflectance Snow/firn. The identification of classes in Hyperion imagery is validated using the spectral library from USGS and ASTER, and field spectra obtained from literature

A simple model for estimation of snow/ice surface temperature of Antarctic ice sheet using remotely sensed thermal band data

In this paper a model has been developed to estimate surface temperature of Antarctic ice sheet using thermal bands of MODIS sensor images and in situ surface temperature measurements. The brightness temperature of snow/ice surface of Antarctica has been estimated for MODIS bands 31 and 32 using Planck’s spectral radiation equation. Split window technique has been used to develop the model from brightness temperature and automatic weather station recorded surface temperature. The model has been validated using in situ measurements of surface temperature of the ice sheet near Indian Antarctic Research Station ‘Maitri’. High coefficient of determination (R2 = 0.99) and low root mean square error (0.8°C) have been obtained between modeled and in situ recorded surface temperature. The model is easy to use and can generate the surface temperature maps at spatial resolution of 1.0 km. These maps can be useful in various glaciological, hydrological, climatological and ecological study of the ice sheet

A simple model for estimation of snow/ice surface temperature of Antarctic ice sheet using remotely sensed thermal band data

51-55In this paper, a model has been developed to estimate surface temperature of Antarctic ice sheet using thermal bands of Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images and in situ surface temperature measurements. The brightness temperature of snow/ice surface of Antarctica has been estimated for MODIS bands 31 and 32 using Planck’s spectral radiation equation. Split window technique has been used to develop the model from brightness temperature and Automatic Weather Station recorded surface temperature. The model has been validated using in situ measurements of surface temperature of the ice sheet near Indian Antarctic Research Station ‘Maitri’. High coefficient of determination (R2 in the range 0.952 - 0.99) and low root mean square error (0.8 - 1.2°C) has been obtained between modeled and in situ recorded surface temperature. The model is easy to use and can generate the surface temperature maps at spatial resolution of 1.0 km. These maps can be useful in various glaciological, hydrological, climatological and ecological studies of the ice sheet