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Gusain H.S.,Snow and Avalanche Study Establishment SASE | Mishra V.D.,Snow and Avalanche Study Establishment SASE | Arora M.K.,Indian Institute of Technology Roorkee | Arora M.K.,PEC University of Technology | And 2 more authors.
Cold Regions Science and Technology | Year: 2016

In this paper, an algorithm is proposed for generation of snow depth maps. The efficacy of the algorithm has been established through a case study in lower and middle Himalayas, India. The algorithm is a modified version of the spatial interpolation method proposed earlier in Swiss Alps. The method uses discrete point data supplemented with remotely sensed derived information data to create snow depth maps at spatial resolution of 0.5 km. In situ snow depth observations from 14 locations, automatic weather station (AWS) recorded snow depth from 9 locations, moderate-resolution imaging spectroradiometer (MODIS) images and shuttle radar topographic mission (SRTM) DEM form the database. The algorithm is based on the dependency of snow depth on elevation above mean sea level, which is later adjusted through the in situ snow depth observations to represent the local and regional characteristics of the snow distribution. The algorithm has been validated for different days of the winter season 2012-2013 using leave-one-out station cross-validation method. The mean absolute error (MAE) and root mean square error (RMSE) in estimation of snow depth have been observed as ~. 34 cm and ~. 42 cm respectively during the season. The snow depth maps generated from the proposed algorithm may be useful in assessment of snow avalanche hazards as well as in various hydrological and glaciological studies in the inaccessible cryospheric region of the Western Himalaya. © 2016 Elsevier B.V.


Mishra V.D.,Snow and Avalanche Study Establishment SASE | Sharma J.K.,Rayat Institute of Engineering and Information Technology | Khanna R.,Thapar University
Annals of Glaciology | Year: 2010

The topographic effects of differential terrain illumination in optical satellite imagery of rugged mountainous regions have serious consequences for qualitative and quantitative analysis for various snow applications. Therefore, effective removal or minimization of topographic effects is necessary in satellite image data of mountainous regions. Different methods for topographic corrections, including C-correction, Minnaert corrections (including slope) and slope-matching method, are analysed in the context of snow reflectance. Combination of dark-object subtraction models DOS1 and DOS3 is used for image-based atmospheric corrections while considering the effect of Rayleigh scattering on the transmissivity in different spectral bands of AWiFS and MODIS image data. The performance of different models is evaluated using (1) visual analysis, (2) change in snow reflectance on sunny and shady slopes after the corrections, (3) validation with in situ observations and (4) graphical analysis. The results show that the slope-matching technique could eliminate most of the shadowing effects in Himalayan rugged terrain and correctly estimate snow reflectance from AWiFS and MODIS imagery. The validation of results with in situ observations for both types of imagery suggests that all other methods significantly underestimate reflectance values after the corrections.


Sharma J.K.,Rayat Institute of Engineering and Information Technology | Mishra V.D.,Snow and Avalanche Study Establishment SASE | Khanna R.,Thapar University
Journal of the Indian Society of Remote Sensing | Year: 2013

The present paper discusses the impact of topography on accuracy for land cover classification and "from-to class change using improved spectral change vector analysis suggested by Chen et al. (2003). Two AWiFS sensor images of different dates are used. Double Window Flexible Pace Search (DFPS) is used to estimate threshold of change magnitude for change/no change classes. The topographic corrections show accuracy of 90% (Kappa coefficient 0.7811) for change/no change area as compared to 82% (Kappa coefficient 0.6512) in uncorrected satellite data. Direction cosines of change vector for determining change direction in n-dimensional spectral space is used for image classification with a minimum distance categorizing technique. The results of change detection are compared (i) Improved CVA with conventional two bands CVA and (ii) Improved CVA before and after topographic corrections. The improved CVA with topographic correction consideration using slope match show maximum accuracy of 90% (Kappa coefficient 0.83) as compared to conventional CVA which show maximum accuracy of 82% (Kappa coefficient 0.6624). The overall accuracy of "from- to class using improved CVA increases from 86% (Kappa coefficient 0.7817) to 90% (Kappa coefficient 0.83) after topographic corrections. The improved CVA with proper topographic corrections is found to be effective for change detection analysis in the rugged Western Himalayan terrain. © 2012 Indian Society of Remote Sensing.


Datt P.,Snow and Avalanche Study Establishment SASE | Kapil J.C.,Snow and Avalanche Study Establishment SASE | Kumar A.,National Institute of Technology Kurukshetra
Cold Regions Science and Technology | Year: 2015

The damage process within snow, a porous sintered multiphase material, results in the emission of weak acoustic signatures. It is also responsible for the failure of weak snow layers on mountain slopes leading to snow slab avalanches release. Monitoring these acoustic emissions and their characterization is useful to understand the complex damage behaviour of snow and also for identifying the relevant parameters associated with in situ snowpack stability assessment. In this paper, we present the outcomes of an acoustic emission (AE) study for the damage analysis of snow subjected to uni-axial compression under controlled laboratory conditions. The distribution of various AE characteristics of snow such as peak amplitudes, hit duration, AE energy and emitted acoustic frequency spectrum corresponding to different displacement rates was analysed. The amplitude, hit duration and AE energy substantially increased with increasing displacement rate. Furthermore, the b-value for different displacement rates was estimated using least square fittings as well as maximum likelihood estimates. The temporal variation of the b-value was also estimated for particular time windows of the time series of AE data for all three displacement rates. The b-values were correlated with the external mechanical loading of the snow and were observed to vary from 3.6 to 2.3 for the displacement rates from 1. mm/min to 10. mm/min. Furthermore, the AE hit duration was found to be an important indicator of the damage behaviour. The AE energy of snow increased for decreasing grain size. Analysing the waveform of the AE signatures revealed that the emitted frequency spectrum was between 30. kHz and 70. kHz. The outcome of this study may be useful to identify the relevant AE parameters associated with evolving damage behaviour of the snowpack and for AE applications towards in-situ monitoring of snowpack stability and subsequent avalanche release. © 2015 Elsevier B.V.


Das R.K.,Snow and Avalanche Study Establishment SASE | Datt P.,Snow and Avalanche Study Establishment SASE | Acharya A.,Snow and Avalanche Study Establishment SASE
Journal of Earth System Science | Year: 2012

Wind caused snow drifting plays a dominant role in the redistribution of snow mass that restructures a snowpack. Strong wind activity at the mountain tops results in uneven distribution of snow with erosion on windward side and deposition on leeward areas. Such snowdrift events are responsible for the formation of cornices, increase in the loading of avalanche release zones on the leeward side and consequent increase in the level of avalanche hazard. In this paper, we present the results of snowdrift measurement using an acoustic snow-drift meter, the FlowCapt, built by IAV Engineering, which was used during winter seasons of 2007-2010 at a field research station of Snow and Avalanche Study Establishment (SASE) in the western Himalayas. The aim of the study was to evaluate the suitability of the instrument in measuring snowdrift in the Himalayan weather conditions. Results proved the utility of the instrument as a useful tool to study drifting snow in remote areas. However, in the absence of conventional snow gauges for validation, the quality of the absolute snow flux data could not be ascertained. © Indian Academy of Sciences.


Datt P.,Snow and Avalanche Study Establishment SASE | Kapil J.C.,Snow and Avalanche Study Establishment SASE | Kumar A.,National Institute of Technology Kurukshetra | Srivastava P.K.,Snow and Avalanche Study Establishment SASE
Applied Acoustics | Year: 2016

Snow is a sound absorbing porous sintered material composed of solid matrix of ice skeleton with air (+water vapour) saturated pores. Investigation of snow acoustic properties is useful to understand the interaction between snow structure and sound waves, which can be further used to devise non-destructive way for exploring physical (non-acoustic) properties of snow. The present paper discusses the experimental measurements of various acoustical properties of snow such as acoustic absorption coefficient, surface impedance and transmission losses across different snow samples, followed by inverse characterization of different geometrical parameters of snow. The snow samples were extracted from a natural snowpack and transported to a nearby controlled environmental facility at Patsio, located in the Great Himalayan range of India. An impedance tube system (ITS), working in the frequency range 63-6300 Hz, was used for acoustic measurements of these snow samples. The acoustic behaviour of snow was observed strongly dependent upon the incident acoustic frequency; for frequencies smaller than 1 kHz, the average acoustic absorption coefficient was found below than 0.4, however, for the frequencies more than 1 kHz it was found to be 0.85. The average acoustic transmission loss was observed from 1.45 dB cm-1 to 3.77 dB cm-1 for the entire frequency range. The real and imaginary components of normalized surface impedance of snow samples varied from 0.02 to 7.77 and -6.05 to 5.69, respectively. Further, the measured acoustic properties of snow were used for inverse characterization of non-acoustic geometrical parameters such as porosity, flow resistivity, tortuosity, viscous and thermal characteristic lengths using the equivalent fluid model proposed by Johnson, Champoux and Allard (JCA). Acoustically derived porosity and flow resistivity were also compared with experimentally measured values and good agreement was observed between them. © 2015 Elsevier Ltd. All rights reserved.


Gusain H.S.,Snow and Avalanche Study Establishment SASE | Mishra V.D.,Snow and Avalanche Study Establishment SASE | Arora M.K.,Indian Institute of Technology Roorkee
Remote Sensing Letters | Year: 2014

The aim of this letter is to estimate incoming and net shortwave radiation fluxes of large snow-covered area of western Himalaya and to evaluate the results with in situ observations. Radiation fluxes are estimated at spatial levels using remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and Shuttle Radar Topographic Mission (SRTM) digital elevation model (DEM), supplemented with sparse field data obtained from automatic weather stations (AWSs). Snow cover albedo has been estimated from MODIS data using narrowband to broadband conversion method for clear sky days. Geospatial maps of air temperature (Ta) and relative humidity (RH) have been generated for the study area using AWS recorded Ta/RH and DEM. Parameterization techniques have been used for estimating incoming and net shortwave radiation fluxes, which have been validated from in situ AWS observations. The root mean square error (RMSE) in estimation of incoming shortwave radiation flux and net shortwave radiation flux has been found to be 75 and 84.9 W m-2, respectively. Further, the higher radiation fluxes have been observed on south aspect slopes than those observed on north aspect slopes. © 2013 Taylor & Francis.


Kapil J.C.,Snow and Avalanche Study Establishment SASE | Prasher C.,Snow and Avalanche Study Establishment SASE | Datt P.,Snow and Avalanche Study Establishment SASE | Satyawali P.K.,Snow and Avalanche Study Establishment SASE
Annals of Glaciology | Year: 2010

Stratigraphic boundaries at fine-to-coarse transitions in snow can introduce impeding layers to infiltrating water. In our present investigation, such impeding horizons were observed within sub-freezing homogeneous snow as a consequence of subsurface melting caused by the penetration of solar radiation. This new texture impeded the further downward flow of meltwater at fine-to-coarse transitions, leading to the formation of low-permeability melt-freeze crusts following multiple melt-freeze cycles. In this work, a large sub-freezing (-68C) homogeneous sample, consisting of small rounded grains, was periodically exposed to intense radiation generated by a sun simulator. Due to the penetration of shortwave radiation into the snow, subsurface melting caused the growth of melt-freeze polycrystals from clustered rounded crystals. Variations in mass growth (%) of melt-freeze polycrystals and mass loss (%) of grain clusters were studied within the sub-freezing snow with respect to different melt-freeze cycles. In this work, we study the growth of melt-freeze polycrystals in the top and bottom sub-layers with respect to collective saturation. Saturation profiles from the snow were recorded with a parallel-probe saturation profiler (PPSP) device, sampling at vertical intervals of 7 mm, after each melting cycle. Intrinsic permeabilities across different stratified sub-layers were monitored in relation to saturation as a function of different melt-freeze cycles. Our observations revealed that there is a significant decrease in intrinsic permeability for the first few top sub-layers. Also, permeability in the second topmost sub-layer was less than that in the topmost sub-layer directly interacting with the radiation. These results support the evolution of a new coarse grain texture within the homogeneous snow that subsequently converts into a layer of low permeability. In the various transects of the snow sample, two melt-freeze crusts and one ice crust were manually identified through stratigraphic mapping. A correlation was also established between the saturation spikes recorded with the help of the PPSP and corresponding depth positions of the crusts.


Singh K.K.,Snow and Avalanche Study Establishment SASE | DewaIi S.K.,Snow and Avalanche Study Establishment SASE | Singh D.K.,Snow and Avalanche Study Establishment SASE | Mishra V.D.,Snow and Avalanche Study Establishment SASE | Kaur M.,Shaheed Bhagat Singh State Technical Campus
Indian Journal of Radio and Space Physics | Year: 2016

Snow surface temperature (SST) is an important snow parameter, which affects the energy balance of the region and thus, acts as an indicator of climate change. In Himalaya, due to ruggedness and inaccessibility of its terrain, it is very difficult to collect the SST data using conventional measurement techniques. Remote sensing based satellite data has the potential and is used widely to estimate SST. In the present study, passive microwave satellite data of Special Sensor Microwave Imager (SSM/I) sensor has been used for monitoring the SST at different locations in North-West (NW) Himalaya. A 85 GHz frequency channel, which provides only the near surface information because of its less penetration power in comparison to other available frequencies of the sensor, is observed best for SST monitoring. The monthly and seasonal average SST values are estimated for the period 1988-2012. The temporal variation of SST values in Pir-Panjal, Great Himalaya and Karakoram Himalayan ranges are analyzed for the period 1988-2012. The geospatial maps of SST are drawn to represent the monthly and seasonal trend of SST values spatially.


Kapil J.C.,Snow and Avalanche Study Establishment SASE | Datt P.,Snow and Avalanche Study Establishment SASE | Kumar A.,National Institute of Technology Kurukshetra | Singh K.,HQ Snow and Avalanche Study Establishment | And 2 more authors.
Cold Regions Science and Technology | Year: 2014

The efficient detection of acoustic emission (AE) activity from snow having porous and fragile character is hindered by the fact that the AE signals have small amplitudes and are typically attenuated within a short distance from the source. We therefore tested seven different types of highly sensitive resonant AE sensors and a multi-channel AE system in a wide frequency range of 1kHz-400kHz to evaluate the performance of multi-sensor coupler and waveguides with varying displacement rates. The AE generated during small fracturing of a natural snowpack, caused by a ram penetrometer, were detected using a cylindrical waveguide and a detection range of up to 16m with detection efficiency of 38dBAE were observed in snow. The AE activities produced by the snowpack were continuously recorded using a 2D-arrestor for AE in relation with the natural melt-freeze process. Prominent AE activity was observed near the phase-transition temperature of snow. Furthermore, spectral analysis of the AE signals generated by snow was carried out using the Short-time Fast Fourier Transform (ST-FFT) method. The AE behavior of snow was observed at different states of stress by varying from low to high, corresponding to different frequency ranges and grain sizes and an empirical relation was established for peak AE rates as a function of displacement rate. Apart from it, an attempt was made to monitor the real time failure of snow sample vis-à-vis AE energy with the help of an AE system and a high-speed camera. Our results are quite encouraging towards application of AE technique in the direction of slope stability evaluation and AE-based non-destructive evaluation of snow under various physical processes. The network of acoustic arrestors and waveguides can be crucial towards prediction of slope stability in view of avalanche release. © 2014 Elsevier B.V.

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