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Negi H.S.,Snow and Avalanche Study Establishment | Singh S.K.,Space Applications Center | Kulkarni A.V.,Space Applications Center | Semwal B.S.,Hemwati Nandan Bahuguna Garhwal University
International Journal of Remote Sensing | Year: 2010

In the present study, spectroradiometer (350-2500 nm) experiments are carried out in the field to understand the influence of snow grain size, contamination, moisture, ageing, snow depth, slope / aspect on spectral reflectance and to determine the sensitive wavelengths for mapping of snow and estimation of snow characteristics using satellite data. The observations suggest that, due to ageing and grain-size variation, the maximum variations in reflectance are observed in the near-infrared region, i.e. around 1040-1050 nm. For varying contamination and snow depth, the maximum variations are observed in the visible region, i.e. around 470 and 590 nm, respectively. For the moisture changes, the maximum variations are observed around 980 and 1160 nm. Based on the spectral signatures of seasonal snow, the normalized difference snow index (NDSI) is studied, and snow indexes, such as grain and contamination indexes, are proposed. The study also suggests that the NDSI increases with ageing, grain size and moisture content. The NDSI values remain constant with variations in slope and aspect. Attempts are made to estimate seasonal snow characteristics using multispectral Advanced Wide Field Sensor (AWiFS) Indian Remote Sensing (IRS-P6) and Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite data and validated with snow-meteorological observatory data of the study area. © 2010 Taylor & Francis. Source


Satyawali P.K.,Snow and Avalanche Study Establishment | Schneebeli M.,Institute for Snow and Avalanche Research
Annals of Glaciology | Year: 2010

A method for automated and fast classification of snow texture would be useful for applications where snow structure must be quantified. Large numbers of field measurements were carried out on natural snow in order to investigate small-scale variations of the micro-penetration force. Snow characterization was done for snow from the Himalaya and the Alps, using a high-resolution snow penetrometer (SnowMicroPen). Measurements of snow resistance at equal intervals of 4 mm were geostatistically evaluated. The range parameter (correlation length, or CL) of penetration force was estimated for all major snow classes from the sample semivariogram. Average CL was lowest for new snow and highest for melt-freeze snow. For major snow classes, CL was found to increase with snow density. Ground-perpendicular and ground-parallel snow profiles were also obtained for homogeneous snow, and CL was estimated along these directions. New snow showed larger CL in the ground-parallel direction, and depth-hoar snow showed larger CL in the ground-perpendicular direction. Based on CL, the directional anisotropy was calculated. An attempt was also made to show the relationship between CL and texture index. The semivariogram was used to estimate the fractal dimension. Both CL and fractal dimension were found to be potential parameters to describe snow. Source


Sharma V.,Snow and Avalanche Study Establishment | Mishra V.D.,Snow and Avalanche Study Establishment | Joshi P.K.,TERI University
Journal of Mountain Science | Year: 2012

Snowmelt is an important component of any snow-fed river system. The Jhelum River is one such transnational mountain river flowing through India and Pakistan. The basin is minimally glacierized and its discharge is largely governed by seasonal snow cover and snowmelt. Therefore, accurate estimation of seasonal snow cover dynamics and snowmelt-induced runoff is important for sustainable water resource management in the region. The present study looks into spatio-temporal variations of snow cover for past decade and stream flow simulation in the Jhelum River basin. Snow cover extent (SCE) was estimated using MODIS (Moderate Resolution Imaging Spectrometer) sensor imageries. Normalized Difference Snow Index (NDSI) algorithm was used to generate multi-temporal time series snow cover maps. The results indicate large variation in snow cover distribution pattern and decreasing trend in different sub-basins of the Jhelum River. The relationship between SCE-temperature, SCE-discharge and discharge-precipitation was analyzed for different seasons and shows strong correlation. For streamflow simulation of the entire Jhelum basin Snow melt Runoff Model (SRM) used. A good correlation was observed between simulated stream flow and in-situ discharge. The monthly discharge contribution from different sub-basins to the total discharge of the Jhelum River was estimated using a modified version of runoff model based on temperature-index approach developed for small watersheds. Stream power - an indicator of the erosive capability of streams was also calculated for different sub-basins. © 2012 Science Press, Institute of Mountain Hazards and Environment, CAS and Springer-Verlag Berlin Heidelberg. Source


Joshi J.C.,Snow and Avalanche Study Establishment | Ganju A.,Snow and Avalanche Study Establishment
Journal of Earth System Science | Year: 2010

Temperature and fresh snow are essential inputs in an avalanche forecasting model. Without these parameters, prediction of avalanche occurrence for a region would be very difficult. In the complex terrain of Himalaya, nonavailability of snow and meteorological data of the remote locations during snow storms in the winter is a common occurrence. In view of this persistent problem present study estimates maximum temperature, minimum temperature, ambient temperature and precipitation intensity on different regions of Indian western Himalaya by using similar parameters of the neighbouring regions. The location at which parameters are required and its neighbouring locations should all fall in the same snow climatic zone. Initial step to estimate the parameters at a location, is to shift the parameters of neighbouring regions at a reference height corresponding to the altitude of the location at which parameters are to be estimated. The parameters at this reference height are then spatially interpolated by using Barnes objective analysis. The parameters estimated on different locations are compared with the observed one and the Root Mean Square Errors (RMSE) of the observed and estimated values of the parameters are discussed for the winters of 2007-2008. © Indian Academy of Sciences. Source


Sharma V.,Snow and Avalanche Study Establishment | Mishra V.D.,Snow and Avalanche Study Establishment | Joshi P.K.,TERI University
International Journal of Remote Sensing | Year: 2014

The present study deals with spatio-temporal snow cover distribution in Northwest Himalaya (NWH) in a discourse on regional topography and prevalent climatology. Snow cover variation during 2001-2012 in NWH and eight major river basins was examined using MODIS data on board the Terra satellite. Slope match topographic correction was applied to eliminate the differential illumination effect on satellite imagery. The impact of cloud cover was removed by generating a 10-day maximum snow cover product. Annual and seasonal analysis shows a decreasing trend in snow cover area (SCA) over the entire NWH. Maximal SCA was observed in the windward river basins of the Lower and the Middle Himalayan zones and in the highly glaciated Shyok river basin of the Upper Himalaya. Monthly snow cover duration (SCD) maps revealed the effect of longitudinal variation as well as the strong influence of regional climatology and topography. The relationship of SCA with altitude and aspect was studied in all the river basins of NWH. The study shows a linear increment of SCA/D with increasing respect to elevation in all river basins. The maximum rate of SCA/D change with elevation was observed in the Jhelum river basin. In the Middle Himalayan Zone, an effect of basin orientation in regard to elevation was observed. Mean annual SCA at altitudes of up to 4500 m shows a decreasing trend. Seasonal analysis of aspect-wise snow cover shows that southern slopes have lower SCA during winter months. The difference in SCA between northern and southern slopes is even higher in summer and the monsoon period. © 2014 Taylor & Francis. Source

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