Snow Cover Area Changes in the Changme Khangpu Basin during 2002-2019, North Sikkim Himalaya, India

2021 ◽  
Vol 7 (2) ◽  
pp. 27-34
Author(s):  
Amrita Singh ◽  
Rakesh K. Ranjan ◽  
Uttam Lal
Keyword(s):  
Snow Cover ◽  
Meteorological Parameter ◽  
Temporal Variations ◽  
Small Rivers ◽  
Snow Cover Area ◽  
Sikkim Himalaya ◽  
The People ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
June July

The Himalayan region is characterised by snow-covered mountains and glacierised basins which directly or indirectly regulates many large to small rivers downstream. To simulate and forecast stream-flow in these glacierised basins, an accurate snow cover area (SCA) estimation is of utmost importance. The present study assesses the snow cover dynamics (monthly, annual and seasonal) in the Changme Khangpu Basin (CKB) for almost two decades, from 2002 to 2019. The spatial and temporal variations in the SCA have been estimated using Moderate Resolution Imaging Spectro-radiometer (MODIS) 8-day maximum composite snow cover products from Terra (MOD10A2). Further, the SCA change has been compared with a remotely sensed meteorological parameter like temperature. The result shows a decreasing trend in annual mean SCA of the basin in the last two decades and an increase in seasonal mean SCA in the ablation period (May, June, July, August and September), whereas a decrease in seasonal mean SCA in accumulation period has been observed. The seasonal change in SCA will help in estimating the availability of water in the region for the people residing downward in the valley.

scholarly journals Estimating spatial distribution of daily snow depth with kriging methods: combination of MODIS snow cover area data and ground-based observations

2015 ◽  
Vol 9 (5) ◽  
pp. 4997-5020 ◽  
Author(s):  
C. L. Huang ◽  
H. W. Wang ◽  
J. L. Hou
Keyword(s):  
Spatial Distribution ◽  
Snow Cover ◽  
Snow Depth ◽  
Western China ◽  
Kriging Interpolation ◽  
Snow Cover Area ◽  
Smoothing Effects ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Accurately measuring the spatial distribution of the snow depth is difficult because stations are sparse, particularly in western China. In this study, we develop a novel scheme that produces a reasonable spatial distribution of the daily snow depth using kriging interpolation methods. These methods combine the effects of elevation with information from Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover area (SCA) products. The scheme uses snow-free pixels in MODIS SCA images with clouds removed to identify virtual stations, or areas with zero snow depth, to compensate for the scarcity and uneven distribution of stations. Four types of kriging methods are tested: ordinary kriging (OK), universal kriging (UK), ordinary co-kriging (OCK), and universal co-kriging (UCK). These methods are applied to daily snow depth observations at 50 meteorological stations in northern Xinjiang Province, China. The results show that the spatial distribution of snow depth can be accurately reconstructed using these kriging methods. The added virtual stations improve the distribution of the snow depth and reduce the smoothing effects of the kriging process. The best performance is achieved by the OK method in cases with shallow snow cover and by the UCK method when snow cover is widespread.

scholarly journals Probabilistic Snow Cover and Ensemble Streamflow Estimations in the Upper Euphrates Basin

2019 ◽  
Vol 67 (1) ◽  
pp. 82-92 ◽  
Author(s):  
A. Arda Şorman ◽  
Gökçen Uysal ◽  
Aynur Şensoy
Keyword(s):  
Snow Cover ◽  
Probabilistic Approach ◽  
Temporal Variations ◽  
Melting Characteristics ◽  
Modis Imagery ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Runoff Model

Abstract Predicting snow cover dynamics and relevant streamflow due to snowmelt is a challenging issue in mountainous basins. Spatio-temporal variations of snow extent can be analyzed using probabilistic snow cover maps derived from satellite images within a relatively long period. In this study, Probabilistic Snow Depletion Curves (P-SDCs) and Probabilistic Snow Lines (P-SLs) are acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-filtered daily snow cover images. Analyses of P-SDCs show a strong correlation with average daily runoff (R2 = 0.90) and temperature (R2 = 0.96). On the other hand, the challenge lies in developing noteworthy methods to use P-SDCs in streamflow estimations. Therefore, the main objective is to explore the feasibility of producing probabilistic runoff forecasts with P-SDC forcing in a snow dominated basin. Upper Euphrates Basin in Turkey has large snow extent and high snowmelt contribution during spring and summer periods. The melting characteristics are defined by P-SDCs using MODIS imagery for 2001-2012. The value of snow probability maps on ensemble runoff predictions is shown with Snowmelt Runoff Model (SRM) during 2013-2015 where the estimated runoff values indicate good consistency (NSE: 0.47-0.93) with forecasts based on the derived P-SDCs. Therefore, the probabilistic approach distinguishes the snow cover characteristics for a region and promotes a useful methodology on the application of probabilistic runoff predictions especially for snow dominated areas.

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

2020 ◽  
Vol 5 (1) ◽  
pp. 80 ◽  
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

scholarly journals Cross-Comparison between MODIS and VIIRS Snow Cover Products for the 2016 Hydrological Year

Climate ◽  
2019 ◽  
Vol 7 (4) ◽  
pp. 57 ◽  
Author(s):  
Shubhechchha Thapa ◽  
Parveen K. Chhetri ◽  
Andrew G. Klein
Keyword(s):  
Snow Cover ◽  
Infrared Imaging ◽  
Environmental Data ◽  
Data Series ◽  
Climate Data ◽  
Snow Cover Area ◽  
Transition Zones ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Normalized Difference Snow Index

The VIIRS (Visible Infrared Imaging Radiometer Suite) instrument on board the Suomi-NPP (National Polar-Orbiting Partnership) satellite aims to provide long-term continuity of several environmental data series including snow cover initiated with MODIS (Moderate Resolution Imaging Spectroradiometer). Although it is speculated that MODIS and VIIRS snow cover products may differ because of their differing spatial resolutions and spectral coverage, quantitative comparisons between their snow products are currently limited. Therefore, this study intercompares MODIS and VIIRS snow products for the 2016 Hydrological Year over the Midwestern United States and southern Canada. Two hundred and forty-four swath snow products from MODIS/Aqua (MYD10L2) and the VIIRS EDR (Environmental Data Records) (VSCMO/binary) were intercompared using confusion matrices, comparison maps and false color imagery. Thresholding the MODIS NDSI (Normalized Difference Snow Index) Snow Cover product at a snow cover fraction of 30% generated binary snow maps are most comparable to the NOAA VIIRS binary snow product. Overall agreement between MODIS and VIIRS was found to be approximately 98%. This exceeds the VIIRS accuracy requirements of 90% probability of correct typing. The agreement was highest during the winter but lower during late fall and spring. MODIS and VIIRS often mapped snow/no-snow transition zones as a cloud. The assessment of total snow and cloud pixels and comparison snow maps of MODIS and VIIRS indicate that VIIRS is mapping more snow cover and less cloud cover compared to MODIS. This is evidenced by the average area of snow in MYD10L2 and VSCMO being 5.72% and 11.43%, no-snow 26.65% and 28.67% and cloud 65.02% and 59.91%, respectively. While VIIRS and MODIS have a similar capacity to map snow cover, VIIRS has the potential to map snow cover area more accurately, for the successful development of climate data records.

scholarly journals Satellite monitoring of blue-ice extent near Byrd Glacier, Antarctica

2004 ◽  
Vol 39 ◽  
pp. 223-230 ◽  
Author(s):  
Ian C. Brown ◽  
Ted A. Scambos
Keyword(s):  
Snow Cover ◽  
Satellite Monitoring ◽  
Landsat Images ◽  
Moderate Resolution ◽  
Summer Maximum ◽  
Resolution Imaging ◽  
Snowfall Event ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Seasonal And Interannual Variations

AbstractWe use satellite images to track seasonal and interannual variations in blue-ice extent over the past 30 years near Byrd Glacier on the East Antarctic plateau. The study areas have low slope and few nearby nunataks, which may increase their climate sensitivity. A threshold-based algorithm sensitive to snow grain-size is used to analyze 56 Moderate Resolution Imaging Spectroradiometer (MODIS) images over three recent summer seasons. Seasonal blue-ice exposure grows rapidly in late spring, and peaks by late December. Exposure is relatively constant between late December and mid-January, then declines in February. We interpret this cycle as due to removal and re-accumulation of patchy snow. Interannual changes in blue-ice area may be estimated by tracking the near-constant summer maximum extent period. Fifteen mid-summer Landsat images, spanning 1974–2002, were analyzed to determine long-term variations. Interannual area changes are 10–30%; however, the MODIS data revealed that the exposed blue-ice area can be sharply reduced for up to 2 weeks after a snowfall event; and in the 2001/02 season, patchy snow cover persisted for the entire summer. The combination of MODIS seasonal and Landsat interannual data indicates that blue-ice areas can be climate-sensitive. The strong feedback between snow cover and surface energy balance implies that blue-ice areas could rapidly decrease due to climate-related increases in snowfall or reduced ablation.

A Study on Flood Forecasting in the Upper Indus Basin Considering Snow and Glacier Meltwater

2017 ◽  
Vol 12 (4) ◽  
pp. 793-805 ◽  
Author(s):  
Tong Liu ◽  
Morimasa Tsuda ◽  
Yoichi Iwami ◽  
◽  
Keyword(s):  
Snow Cover ◽  
Monsoon Season ◽  
Indus Basin ◽  
Maximum Magnitude ◽  
Upper Indus Basin ◽  
Moderate Resolution ◽  
Daily Discharge ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Tarbela Dam

This study considered glacier and snow meltwater by using the degree–day method with ground-based air temperature and fractional glacier/snow cover to simulate discharge at Skardu, Partab Bridge (P. Bridge), and Tarbela Dam in the Upper Indus Basin during the monsoon season, from the middle of June to the end of September. The optimum parameter set was determined and validated in 2010 and 2012. The simulated discharge with glaciermelt and snowmelt could capture the variations of the observed discharge in terms of peak volume and timing, particularly in the early monsoon season. The Moderate Resolution Imaging Spectroradiometer (MODIS) daily and eight-day snow cover products were applied and recommended with proper settings for application. This study also investigated the simulations with snow packs instead of daily snow cover, which was found to approach the maximum magnitude of observed discharge even from the uppermost station, Skardu.This study estimated the glacier and snow meltwater contribution at Skardu, Partab Bridge, and Tarbela as 43.2–65.2%, 22.0–29.3%, and 6.3–19.9% of average daily discharge during the monsoon season, respectively. In addition, this study evaluated the main source of simulation discrepancies and concluded that the methodology proposed in the study worked well with proper precipitation.

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