Estimation of Snow Cover Area, Snow Physical Properties and Glacier Classification in Parts of Western Himalayas Using C-Band SAR Data

This study evaluates the estimates of seasonal snowmelt runoff in the Sutlej, Indus, Kabul and Chenab rivers derived from the model of snow cover area vs. runoff against those obtained from cross correlation of concurrent flows in the rivers. The concurrent flow correlation model explains more than 90 percent of the variability in flow of these rivers. Compared to this model, the model of snow-cover area vs. runoff explains less of the variability in flow. However, unlike the snow-cover model, the concurrent flow correlation model cannot be used for operational forecasting procedures. Where the strength of correlation is high, the concurrent flow correlation model has potential for use in retrospective analysis of flow for estimating missing data, extending time series and for evaluating estimates derived from other models. In the Himalayan basins under study and at least for the period under observation, the concurrent flow correlation model provides a set of results with which to compare the estimates from the snow cover model.

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Linear or Nonlinear Covariance of Seasonal Snowmelt and Snow Cover in Western Himalayas

Hydrology Research ◽

10.2166/nh.1992.0013 ◽

1992 ◽

Vol 23 (3) ◽

pp. 183-192 ◽

Cited By ~ 4

Author(s):

B. Dey ◽

V. K. Sharma ◽

A. Rango

Keyword(s):

Linear Regression ◽

Snow Cover ◽

Regression Models ◽

Early Spring ◽

Senior Author ◽

Snow Accumulation ◽

Western Himalayas ◽

Linear Regression Models ◽

Snow Cover Area ◽

Seasonal Flow

Log-linear, exponential and fractional relations for estimating seasonal snowmelt from early-spring snow accumulation in the Indus and Kabul river basins in the western Himalayas are developed with a view to improve the prediction given by bivariate linear regression models earlier developed by the senior author in collaboration with others. This study shows that although the transformed data may improve the above prediction, they fail to satisfy the condition of nonlinearity; a property that must be borne in mind before recommending any nonlinear regression model. Any further improvement in the prediction of seasonal flow volume from basin snow cover area, therefore, has to come from within the domain of linear regression models only or from improvements in the original input data.

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A Response of Snow Cover to the Climate in the Northwest Himalaya (NWH) Using Satellite Products

Remote Sensing ◽

10.3390/rs13040655 ◽

2021 ◽

Vol 13 (4) ◽

pp. 655

Author(s):

Animesh Choudhury ◽

Avinash Chand Yadav ◽

Stefania Bonafoni

Keyword(s):

Snow Cover ◽

Land Surface ◽

Significant Negative Correlation ◽

Shuttle Radar Topography Mission ◽

Vital Role ◽

Snow Cover Area ◽

Study Region ◽

Northwest Himalaya ◽

The Past ◽

Average Annual Temperature

The Himalayan region is one of the most crucial mountain systems across the globe, which has significant importance in terms of the largest depository of snow and glaciers for fresh water supply, river runoff, hydropower, rich biodiversity, climate, and many more socioeconomic developments. This region directly or indirectly affects millions of lives and their livelihoods but has been considered one of the most climatically sensitive parts of the world. This study investigates the spatiotemporal variation in maximum extent of snow cover area (SCA) and its response to temperature, precipitation, and elevation over the northwest Himalaya (NWH) during 2000–2019. The analysis uses Moderate Resolution Imaging Spectroradiometer (MODIS)/Terra 8-day composite snow Cover product (MOD10A2), MODIS/Terra/V6 daily land surface temperature product (MOD11A1), Climate Hazards Infrared Precipitation with Station data (CHIRPS) precipitation product, and Shuttle Radar Topography Mission (SRTM) DEM product for the investigation. Modified Mann-Kendall (mMK) test and Spearman’s correlation methods were employed to examine the trends and the interrelationships between SCA and climatic parameters. Results indicate a significant increasing trend in annual mean SCA (663.88 km2/year) between 2000 and 2019. The seasonal and monthly analyses were also carried out for the study region. The Zone-wise analysis showed that the lower Himalaya (184.5 km2/year) and the middle Himalaya (232.1 km2/year) revealed significant increasing mean annual SCA trends. In contrast, the upper Himalaya showed no trend during the study period over the NWH region. Statistically significant negative correlation (−0.81) was observed between annual SCA and temperature, whereas a nonsignificant positive correlation (0.47) existed between annual SCA and precipitation in the past 20 years. It was also noticed that the SCA variability over the past 20 years has mainly been driven by temperature, whereas the influence of precipitation has been limited. A decline in average annual temperature (−0.039 °C/year) and a rise in precipitation (24.56 mm/year) was detected over the region. The results indicate that climate plays a vital role in controlling the SCA over the NWH region. The maximum and minimum snow cover frequency (SCF) was observed during the winter (74.42%) and monsoon (46.01%) season, respectively, while the average SCF was recorded to be 59.11% during the study period. Of the SCA, 54.81% had a SCF above 60% and could be considered as the perennial snow. The elevation-based analysis showed that 84% of the upper Himalaya (UH) experienced perennial snow, while the seasonal snow mostly dominated over the lower Himalaya (LH) and the middle Himalaya (MH).

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Assessing the quality of a real-time Snow Cover Area product for hydrological applications

Remote Sensing of Environment ◽

10.1016/j.rse.2012.09.006 ◽

2012 ◽

Vol 127 ◽

pp. 271-287 ◽

Cited By ~ 14

Author(s):

G. Thirel ◽

C. Notarnicola ◽

M. Kalas ◽

M. Zebisch ◽

T. Schellenberger ◽

...

Keyword(s):

Snow Cover ◽

Real Time ◽

Snow Cover Area ◽

Area Product ◽

Hydrological Applications

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The optical behaviour of snow during a melting season at Ny Ålesund (Svalbard, Norway)

10.5194/egusphere-egu21-14667 ◽

2021 ◽

Author(s):

Roberto Salzano ◽

Christian Lanconelli ◽

Giulio Esposito ◽

Marco Giusto ◽

Mauro Montagnoli ◽

...

Keyword(s):

Climate Change ◽

Snow Cover ◽

Full Range ◽

Time Lapse ◽

Test Site ◽

Remotely Sensed ◽

Optical Behaviour ◽

Remotely Sensed Data ◽

Snow Cover Area ◽

Significant Information

Polar areas are the most sensitive targets of the climate change and the continuous monitoring of the cryosphere represents a critical issue. The satellite remote sensing can fill this gap but further integration between remotely-sensed multi-spectral images and field data is crucial to validate retrieval algorithms and climatological models. The optical behaviour of snow, at different wavelengths, provides significant information about the micro-physical characteristics of the surface and this allow to discriminate different snow/ice covers. The aim of this work is to present an approach based on combining unmanned observations on spectral albedo and on the analysis of time-lapse images of sky and ground conditions in an Arctic test-site (Svalbard, Norway). Terrestrial photography can provide, in fact, important information about the cloud cover and support the discrimination between white-sky or clear-sky illuminating conditions. Similarly, time-lapse cameras can provide a detailed description of the snow cover, estimating the fractional snow cover area. The spectral albedo was obtained by a narrow band device that was compared to a full-range commercial system and to remotely sensed data acquired during the 2015 spring/summer period at the Amundsen - Nobile Climate Change Tower (Ny &#197;lesund). The results confirmed the possibility to have continuous observations of the snow surface (microphisical) characteristics and highlighted the opportunity to monitor the spectral variations of snowed surfaces during the melting period. It was possible, therefore, to estimate spectral indexes, such as NDSI and SWIR albedo, and to found interesting links between both features and air/ground temperatures, wind-speed and precipitations. Different melting phases were detected and different processes were associated with the observed spectral variations.

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Model-driven retrieval of fractional snow cover area

Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, 2005. IGARSS '05. ◽

10.1109/igarss.2005.1526391 ◽

2005 ◽

Author(s):

R. Solberg

Keyword(s):

Snow Cover ◽

Snow Cover Area ◽

Model Driven ◽

Fractional Snow Cover

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Snow Cover Monitoring by Synergistic Use of Sentinel-3 Slstr and Sentinel-L Sar Data

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.2018.8518203 ◽

2018 ◽

Cited By ~ 1

Author(s):

Thomas Nagler ◽

Helmut Rott ◽

Joanna Ossowska ◽

Gabriele Schwaizer ◽

David Small ◽

...

Keyword(s):

Snow Cover ◽

Sar Data

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Variation of snow cover in the Nyang River basin of southeastern Tibetan Plateau, China

Journal of Water and Climate Change ◽

10.2166/wcc.2021.037 ◽

2021 ◽

Author(s):

Rui Zhang ◽

Zongxue Xu ◽

Depeng Zuo ◽

Chunguang Ban

Keyword(s):

Snow Cover ◽

River Basin ◽

Snow Water Equivalent ◽

Global Climate ◽

Remote Sensing Data ◽

Significant Negative Correlation ◽

Spatial And Temporal Variation ◽

Snow Cover Area ◽

Northern Edge ◽

Slight Upward Trend

Abstract Snow cover is highly sensitive to global climate change and strongly influences the climate at global and regional scales. Because of limited in situ observations, snow cover dynamics in the Nyang River basin (NRB) have been examined in few studies. Five snow cover indices derived from observation and remote sensing data from 2000 to 2018 were used to investigate the spatial and temporal variation of snow cover in the NRB. There was clear seasonality in the snow cover throughout the entire basin. The maximum snow-covered area was 8,751.35 km2, about 50% of the total basin area, and occurred in March. The maximum snow depth (SD) was 5.35 cm and was found at the northern edge of the middle reaches of the basin. Snow cover frequency, SD, and fraction of snow cover area increased with elevation. The decrease in SD was the most marked in the elevation range of 5,000–6,000 m. Above 6,000 m, the snow water equivalent showed a slight upward trend. There was a significant negative correlation between snow cover and temperature. The results of this study could improve our understanding of changes in snow cover in the NRB from multivariate perspectives. It is better for water resources management.

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The Application of Geographic Information System (GIS) and Remote Sensing in Quantifying Snow Cover and Precipitation in Kabul Basin

Geosfera Indonesia ◽

10.19184/geosi.v5i1.14896 ◽

2020 ◽

Vol 5 (1) ◽

pp. 80 ◽

Cited By ~ 1

Author(s):

Qamar Zaman ◽

Shahid Nawaz Khan

Keyword(s):

Remote Sensing ◽

Water Resources ◽

Snow Cover ◽

Tropical Rainfall Measuring Mission ◽

Well Being ◽

Snow Cover Area ◽

Hydrologic Modelling ◽

Gis And Remote Sensing ◽

Creative Commons ◽

The People

Water Resources availability is very important to social and economic well-being of the people and has huge impacts on the socio-economic scenarios of a country. Precipitation and snow cover area assessment is some of the major inputs in hydrologic modelling and also for assessing and managing water resources in a basin. The change in the water availability in a basin has huge socio-economic impacts because of the water usage for food production, industries, and many others. The main aim of this study was to measure the snow cover area and precipitation from 2001 to 2015 in the Kabul basin. Moderate Resolution Image Spectroradiometer (MODIS) and Tropical Rainfall measuring Mission (TRMM) data were used to study snow cover area and precipitation respectively during 2001-2015. 8-day snow cover product for 15 years (January) was used to analyse the snow cover while monthly data of TRMM (3B43) were used to analyse the rainfall from 2001-2015. Different image processing techniques were applied on the data retrieved using GIS and Remote Sensing softwares. Initially, SCA was seen increasing, but during the last 3-4 years, it kept decreasing gradually. Rainfall was initially recorded as low, while later on, it was recorded high and reached the highest during 2010. Keywords: MODIS; Snow Cover; TRMM; Precipitation; Kabul Basin; Remote Sensing Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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