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11.
The attenuation properties have been estimated in the Nubra-Siachen region situated in the highly mountainous region of Himalayan belt. Coda wave quality factor (Qc) has been determined for this virgin region by using the single backscattering method. A total of thirty earthquakes recorded in this region, which fall in the epicentral distance range of 3 to 115km have been used for the present work. A 30 sec window length of coda waves at different central frequencies 1.5, 3.0, 6.0, 9.0, 12.0, 18.0 and 24.0 Hz have been studied to determine Qc at different recording stations. The frequency dependent coda wave quality factor relationships of the form Qc(f) = Qofn, have been computed at each recording stations separately: BASE: Qc(f) = (137 ± 4.2) f(0.99 ± 0.12), CHALUNKA: Qc(f) = (116±3.8)f(1.0±0.05), PARTA: Qc(f) = (122±3.0)f(1.0±0.02), and SASOMA: Qc(f) = (111±4.1)f(1.0±0.03). A regional Qc relation has been developed for the Nubra-Siachen region by using the average value of Qc at different frequencies obtained at each recording station of the form Qc(f) = (121±7.2)f(1.0±0.04). The average Qc values vary from 183 at 1.5 Hz to 3684 at 24 Hz central frequencies. The present regional relation developed for Nubra-Siachen region indicates heterogeneous and tectonically active region.  相似文献   
12.
Avalanche activities in the Indian Himalaya cause the majority of fatalities and responsible for heavy damage to the property. Avalanche susceptibility maps assist decision-makers and planners to execute suitable measures to reduce the avalanche risk. In the present study, a probabilistic data-driven geospatial fuzzy–frequency ratio (fuzzy–FR) model is proposed and developed for avalanche susceptibility mapping, especially for the large undocumented region. The fuzzy–FR model for avalanche susceptibility mapping is initially developed and applied for Lahaul-Spiti region. The fuzzy–FR model utilized the six avalanche occurrence factors (i.e. slope, aspect, curvature, elevation, terrain roughness and vegetation cover) and one referent avalanche inventory map to generate the avalanche susceptibility map. Amongst 292 documented avalanche locations from the avalanche inventory map, 233 (80%) were used for training the model and remaining 59 (20%) were used for validation of the map. The avalanche susceptibility map is validated by calculating the area under the receiver operating characteristic curve (ROC-AUC) technique. For validation of the results using ROC-AUC technique, the success rate and prediction rate were calculated. The values of success rate and prediction rate were 94.07% and 91.76%, respectively. The validation of results using ROC-AUC indicated the fuzzy–FR model is appropriate for avalanche susceptibility mapping.  相似文献   
13.
This work provides an overview of various methods for estimating snow cover and properties in high mountains using remote sensing techniques involving microwaves. Satellite-based remote sensing with its characteristics such as synoptic view, repetitive coverage and uniformity over large areas has great potential for identifying the temporal snow cover. Many sensors have been used in the past with various algorithms and accuracies for this purpose. These methods have been improving with the use of Synthetic Aperture Radar sensors, working in different microwave frequencies, polarisation and acquisition modes. The limitations, advantages and drawbacks are illustrated while error sources and strategies on how to ease their impacts are also reviewed. An extensive list of references, with an emphasis on studies since 1990s, allows the reader to delve into specific topics.  相似文献   
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15.
Independent test results of four different weather forecast models [climatological, persistence, analogue, and regional mesoscale weather simulation (MM5) model] have been compared for four past winters (winter 2003–2004 to winter 2006–2007) for qualitative weather (snow day/no snow day) and quantitative categorical snowfall prediction at six different areas in northwest Himalaya (NW-Himalaya) in India. Weather forecast guidance provided by the MM5 model at 10 km resolution was taken for the study. Test results of MM5 and the analogue model were compared for a limited number of days (with irregular gaps) due to lack of availability of MM5 weather forecast guidance for complete winter periods. Forecasts based on the persistence, climatological, and analogue models were compared for day 1 predictions only. Performance of the analogue model for qualitative weather prediction was found to be comparable to that of the MM5 model for day 1 prediction. However, for day 2 and day 3, performance of the MM5 model was found to be marginally better than that of the analogue model. Marginal difference in overall accuracy of the analogue and MM5 models was found for quantitative categorical snowfall prediction for day 3. The quantitative categorical snowfall forecast error of the MM5 model was found to be greater than that for the analogue model for all three days. Comparative study of the performance of the climatological, persistence, and analogue models showed that the analogue model performs better than the persistence and climatological models for day 1 predictions. The results of this study suggest that the analogue model shows some capability for weather prediction and, along with the MM5 model, could be a useful tool for weather forecasters. Comparative study of the performance of the MM5 model at high resolution (about 2–3 km) and the analogue model for complete winter period may provide some interesting and fruitful results.  相似文献   
16.
Radar remote sensing has great potential to determine the extent and properties of snow cover. Availability of space-borne sensor dual-polarization C-band data of environmental satellite- (ENVISAT-) advanced synthetic aperture radar (ASAR) can enhance the accuracy in measurement of snow physical parameters as compared with single polarization data measurement. This study shows the capability of C-band synthetic aperture radar (SAR) data for estimating dry snow density over snow covered rugged terrain in Himalayan region. The snow density is an important parameter for the snow hydrology and avalanche forecasting related studies. An algorithm has been developed for estimating snow density, based on snow volume scattering and snow-ground scattering components. The radar backscattering coefficients of both horizontal–horizontal (hh) and vertical–vertical (vv) polarization and incidence angle are used as inputs in the algorithm to provide the snow dielectric constant which can be used to derive snow density using Looyenga's semi-empirical formula. Comparison was made between snow density estimated from algorithm using ENVISAT-ASAR hh and vv polarization data and the measured field value. The mean absolute error between estimated and measured snow density was found to be 0.024 g/cm3.  相似文献   
17.
Bhaga Basin has complex mountainous terrain; little study has been done on the spatial and temporal characteristics of snow cover in the region. The Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day snow cover products between 2001 and 2012 for winter period (November–April) have been used to study the variation in snow cover area (SCA). The statistical analysis based on non-parametric Mann Kendall and Sen’s slope methods have been used for detecting and estimating trends for climatic variables (temperature and snowfall) and SCA for winter period. Results of statistical analysis indicate rise in minimum temperature (0.02 °C year?1) and fall in maximum temperature (0.17 °C year?1). It also shows decrease in mean seasonal snowfall (0.07 cm year?1). The seasonal SCA was found to decrease at the rate of 0.002% year?1. This study indicates that the climate change is probably one of the major causes for depleting SCA.  相似文献   
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