Spatial and temporal variation of snow cover in the Himalayan and Karakorum region using MODIS data (2000-2019)

2020 ◽  
Author(s):  
Jaydeo Kumar Dharpure ◽  
Ajanta Goswami ◽  
Anil V. Kulkarni
Keyword(s):  
Snow Cover ◽  
Geographical Area ◽  
Spatial And Temporal Variation ◽  
Polar Regions ◽  
Regional Variability ◽  
Snow Cover Area ◽  
Modis Data ◽  
Slope Test ◽  
Depletion Curve ◽  
The Mean

<p>The Himalayan and Karakorum (H-K) region comprise the highest amount of snow and ice cover outside the Polar Regions. The H-K region is grouped into four-part, i.e., the Karakorum (KK), Western (WH), Central (CH), and Eastern Himalayas (EH), based on climate and geographic location. The EH and CH mainly feed by summer-monsoon snowfall, whereas the KK and WH are winters accumulated. This regional variability of climate will affect the water availability for hydropower generation, agriculture, and ecosystem. Therefore, the mapping and monitoring of snow cover change over the study area played an essential role in the context of climate change. The snow cover area (SCA) was observed using Moderate-resolution Imaging Spectroradiometer (MODIS) daily snow cover products version 6 during 2000-2019. Different cloud removal techniques (e.g., multi-sensor, temporal, spatial, regional snow line, multiday backward) are applied to reduce the cloud cover pixels over snow pixels of the MODIS data. The mean annual SCA of the H-K region is ∼26.4% of the total geographical area during the study period. The statistical trend analysis of mean monthly, seasonal, and annual SCA is examined using Mann-Kendal and Sen’s slope test. The mean yearly SCA of the H-K region shows an increasing trend during 2000-2009 and start decreasing significantly during 2009-2019. Similar results are observed in the KK, WH, CH, and EH, which shows a decreasing trend of mean annual SCA since 2009. The mean seasonal SCA shows a significant decreasing trend in summer (June to September) and winter (December to February) since 2009, suggesting a seasonal shift or change in snow cover. Overall, the winter shows an insignificant decreasing trend in comparison to the other seasons during 19 hydrological years (2000-01 to 2018-19). The mean monthly minimum SCA observed in August for the KK and WH, July for the CH, and June for the EH. However, the mean maximum SCA in February for the KK, WH, CH, and March for the EH. The snow cover depletion curve suggests that the maximum SCA in February and minimum in August of the entire region during the study period. The seasonal variation of SCA can be highly related to the influence of monsoonal patterns in the region.</p>

scholarly journals Modis Snowline Elevation Changes During Snowmelt Runoff Events in Europe

2019 ◽  
Vol 67 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Juraj Parajka ◽  
Nejc Bezak ◽  
John Burkhart ◽  
Bjarki Hauksson ◽  
Ladislav Holko ◽  
...  
Keyword(s):  
Snow Cover ◽  
Base Flow ◽  
Snowmelt Runoff ◽  
Regional Variability ◽  
Snow Cover Area ◽  
Cloud Coverage ◽  
Maximum Elevation ◽  
Elevation Changes ◽  
The Mean ◽  
Runoff Events

Abstract This study evaluates MODIS snow cover characteristics for large number of snowmelt runoff events in 145 catchments from 9 countries in Europe. The analysis is based on open discharge daily time series from the Global Runoff Data Center database and daily MODIS snow cover data. Runoff events are identified by a base flow separation approach. The MODIS snow cover characteristics are derived from Terra 500 m observations (MOD10A1 dataset, V005) in the period 2000-2015 and include snow cover area, cloud coverage, regional snowline elevation (RSLE) and its changes during the snowmelt runoff events. The snowmelt events are identified by using estimated RSLE changes during a runoff event. The results indicate that in the majority of catchments there are between 3 and 6 snowmelt runoff events per year. The mean duration between the start and peak of snowmelt runoff events is about 3 days and the proportion of snowmelt events in all runoff events tends to increase with the maximum elevation of catchments. Clouds limit the estimation of snow cover area and RSLE, particularly for dates of runoff peaks. In most of the catchments, the median of cloud coverage during runoff peaks is larger than 80%. The mean minimum RSLE, which represents the conditions at the beginning of snowmelt events, is situated approximately at the mean catchment elevation. It means that snowmelt events do not start only during maximum snow cover conditions, but also after this maximum. The mean RSLE during snowmelt peaks is on average 170 m lower than at the start of the snowmelt events, but there is a large regional variability.

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

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.

scholarly journals ESTIMATION OF SNOW DEPLETION CURVE FOR GANGOTRI BASIN USING MULTI-SOURCE REMOTE SENSING DATA

2021 ◽  
Vol V-3-2021 ◽  
pp. 197-202
Author(s):  
P. Verma ◽  
S. K. Ghosh ◽  
R. Ramsankaran
Keyword(s):  
Snow Cover ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Snowmelt Runoff ◽  
Multiple Sources ◽  
Snow Cover Area ◽  
Depletion Curve ◽  
Normalized Difference Snow Index ◽  
Runoff Model ◽  
Key Parameter

Abstract. Snow Depletion Curve derived from satellite images is a key parameter in Snowmelt Runoff Model. The fixed temporal resolution of a satellite and presence of cloud cover in Himalayas restricts accuracy of generated SDC. This study presents an effective approach of reducing temporal interval between two consecutive dates by integrating normalized Snow Cover Area estimated from multiple sources of satellite data. SCA is extracted by using Normalized Difference Snow Index for six snowmelt seasons from 2013 to 2018 for Gangotri basin situated in Indian Himalayas. This work also explores potential of recently launched Sentinel-3A for estimating SCA. Normalized SCA is utilized to eliminate the effect of difference in spatial resolution of various satellites. The result develops an important linear relation between SDC and time with a decrease in snow cover of 0.005/day that may be further refined by increasing the number of snowmelt seasons. This relationship may help scientific community in understanding hydrological response of glaciers to climate change.

scholarly journals Trends in Snow Cover Duration Across River Basins in High Mountain Asia From Daily Gap-Filled MODIS Fractional Snow Covered Area

2021 ◽  
Vol 9 ◽  
Author(s):  
Chelsea Ackroyd ◽  
S. McKenzie Skiles ◽  
Karl Rittger ◽  
Joachim Meyer
Keyword(s):  
Snow Cover ◽  
Critical Role ◽  
River Basins ◽  
High Mountain ◽  
Polar Regions ◽  
Snow Cover Area ◽  
Data Limitations ◽  
Snow Cover Duration ◽  
Spectral Mixture ◽  
Syr Darya

High Mountain Asia (HMA) has the largest expanse of snow outside of the polar regions and it plays a critical role in climate and hydrology. In situ monitoring is rare due to terrain complexity and inaccessibility, making remote sensing the most practical way to understand snow patterns in HMA despite relatively short periods of record. Here, trends in snow cover duration were assessed using MODIS between 2002 and 2017 across the headwaters of the region’s primary river basins (Amu Darya, Brahmaputra, Ganges, Indus, and Syr Darya). Data limitations, associated with traditional binary mapping and data gaps due to clouds, were addressed with a daily, spatially and temporally complete, snow cover product that maps the fraction of snow in each pixel using spectral mixture analysis. Trends in fractional snow cover duration (fSCD) were calculated at the annual and monthly scale, and across 1,000 m elevation bands, and compared to trends in binary snow cover duration (SCD). Snow cover is present, on average, for 102 days across all basin headwaters, with the longest duration in western basins and shortest in eastern basins. Broadly, snow cover is in decline, which is most pronounced in elevation bands where snow is most likely to be present and most needed to sustain glaciers. Some of the strongest negative trends in fSCD were in the Syr Darya, which has 13 fewer days between 4,000–5,000 m, and Brahmaputra, which has 31 fewer days between 5,000–6,000 m. The only increasing tendency was found in the Indus between 2,000 and 5,000 m. There were differences between fSCD and SCD trends, due to SCD overestimating snow cover area relative to fSCD.

Snow Cover Dynamics and its Spatio-Temporal Distribution in the Central Higher Himalaya of India

2021 ◽  
Vol 14 (9) ◽  
pp. 15-22
Author(s):  
Masoom Reza ◽  
Ramesh Chandra Joshi
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Geographical Area ◽  
Temporal Distribution ◽  
Melting Rate ◽  
Optical Data ◽  
Snow Cover Area ◽  
Central Himalayas ◽  
Spatio Temporal ◽  
The Impact

Retreating glaciers, changing timber line and decreasing accumulation of snow in the Himalaya are considered the indicators of climate change. In this study, an attempt is made to observe the snow cover change in the higher reaches of the Central Himalayas. Investigation of climate change through snow cover is very important to understand the impact and adaptation in an area. Landsat thematic and multi spectral optical data with a spatial resolution of 60m and 30m are considered for the estimation and extraction of snow cover. Total 3,369 Km2 snow cover area is lost since 1972 out of total geographical area i.e. 17,227 Km2. The accumulation of snow during winter is lower than the melting rate during summer. The current study identified the decrease of 19.6 % snow cover in 47 years since 1972 to 2019. Composite satellite imageries of September to December show that the major part of the study area covered with snow lies above 3600m. Overall observation indicates that in 47 years, permanent snow cover is decreasing in Central Himalayas.

scholarly journals Assimilation of MODIS snow cover area data in a distributed hydrological model

2011 ◽  
Vol 8 (1) ◽  
pp. 1329-1364 ◽  
Author(s):  
G. Thirel ◽  
P. Salamon ◽  
P. Burek ◽  
M. Kalas
Keyword(s):  
Particle Filter ◽  
Snow Cover ◽  
Hydrological Model ◽  
Snow Water Equivalent ◽  
Water Cycle ◽  
Research Centre ◽  
Distributed Hydrological Model ◽  
Joint Research ◽  
Snow Cover Area ◽  
Depletion Curve

Abstract. Snow is an important component of the water cycle and its estimation in hydrological models is of great importance concerning snow melting flood events simulations and forecasting. The LISFLOOD model is a spatially distributed hydrological model designed at the Joint Research Centre for large European river basins. It is used for a variety of applications including flood forecasting and assessing the effects of land use change and climate change. In order to improve the streamflow simulations of this model, especially with respect to snowmelt induced floods, the assimilation of Snow Cover Area (SCA) has been evaluated in this study. For this purpose daily 420 m-resolution MODIS satellital SCA data have been used, which were then converted in Snow Water Equivalent (SWE) using a Snow Depletion Curve. Tests were performed over the Morava basin, a tributary of the Danube, for a period of almost three years. Two data assimilation techniques, the Ensemble Kalman Filter (EnKF) and the particle filter, were compared, for assimilating the MODIS composites of SCA every seven days. Two approaches were tested, in which the SWE of the model was adjusted either using three altitudinal-based zones or seven sub-basins-based zones. These experiments showed the improvement of the SWE of the model when compared with MODIS-derived snow for both the EnKF and the particle filter. However, on average only the particle filter improved the discharge simulation, because the EnKF imposed too important water balance modifications, which deteriorated the simulation of the discharges during the snow melt periods.

scholarly journals Changes in seasonal snow cover in Hindu Kush-Himalayan region

2011 ◽  
Vol 5 (2) ◽  
pp. 755-777 ◽  
Author(s):  
D. R. Gurung ◽  
A. V. Kulkarni ◽  
A. Giriraj ◽  
K. S. Aung ◽  
B. Shrestha ◽  
...  
Keyword(s):  
Snow Cover ◽  
Linear Trend ◽  
Geographical Area ◽  
Western Himalaya ◽  
Seasonal Snow ◽  
Snow Covered Area ◽  
Covered Area ◽  
Depletion Curve ◽  
Hindu Kush ◽  
Seasonal Snow Cover

Abstract. The changes in seasonal snow covered area in the Hindu Kush-Himalayan (HKH) region have been examined using Moderate – resolution Imaging Spectroradiometer (MODIS) 8-day standard snow products. The average snow covered area of the HKH region based on satellite data from 2000 to 2010 is 0.76 million km2 which is 18.23% of the total geographical area of the region. The linear trend in annual snow cover from 2000 to 2010 is −1.25±1.13%. This is in consistent with earlier reported decline of the decade from 1990 to 2001. A similar trend for western, central and eastern HKH region is 8.55±1.70%, +1.66% ± 2.26% and 0.82±2.50%, respectively. The snow covered area in spring for HKH region indicates a declining trend (−1.04±0.97%). The amount of annual snowfall is correlated with annual seasonal snow cover for the western Himalaya, indicating that changes in snow cover are primarily due to interannual variations in circulation patterns. Snow cover trends over a decade were also found to vary across seasonally and the region. Snow cover trends for western HKH are positive for all seasons. In central HKH the trend is positive (+15.53±5.69%) in autumn and negative (−03.68&plusmn3.01) in winter. In eastern HKH the trend is positive in summer (+3.35±1.62%) and autumn (+7.74±5.84%). The eastern and western region of HKH has an increasing trend of 10% to 12%, while the central region has a declining trend of 12% to 14% in the decade between 2000 and 2010. Snow cover depletion curve plotted for the hydrological year 2000–2001 reveal peaks in the month of February with subsidiary peaks observed in November and December in all three regions of the HKH.

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

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).

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

2012 ◽  
Vol 127 ◽  
pp. 271-287 ◽  
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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