A study of decadal scale glacier changes of the Lunana glacier system in Bhutan, Himalaya, with considerations to glacial lake outburst floods (GLOFs)

This study assesses changes in glacier area, velocity, and geodetic mass balance for a selection of glaciers in the Lunana glacier system of Bhutan, Himalaya. It takes considerations to Glacial Lake Outburst Floods (GLOFs) by creating a glacial lake inventory of two important potential dangerous glacial lakes, Raphstreng Tsho and Luggye Tsho. Bhutan is located in the eastern parts of the HKH region and is known for its earlier GLOF events. The precipitation in Bhutan is driven by the Indian monsoon resulting in 60% annual precipitation, the high amount of rainfall results in rockfalls that covers large valley glacier tongues with debris. I studied the glacier area changes between 1976, 1996 and 2018 using freely available Landsat satellite imagery, SAR Sentinel 1&2, the SRTM Digital Elevation Model (DEM) and HMA DEM. The geodetic mass balance was calculated between 1976, 2000 and 2018/9 (for selected glaciers) using DEM constructed from high-resolution stereo images, Pléiades and SPOT, granted from the European Space Agency, as well as using the already accessed SRTM DEM and a Hexagon DEM courtesy of King, et al. (2019). The glacier velocity was generated using SAR TerraSAR-X data from 2016 and shows an average yearly displacement over the Lunana glacier system. The glacial lake time series for Raphstreng Tsho and Luggye Tsho where studied between 1993 and 2018 using a stack of freely available Landsat imagery. The results of this study, show a variety of decadal glacial changes over Lunana glacier system, with glaciers lowering on an average by 0.48± 0.08 m a-1 between 1976 and 2018/9 which calculates to a geodetic mass balance of -0.41 ± 0.068 m w.e. a-1. The system had a total average of 12.73% area of reduction for all glaciers, between the same time period. The Lunana glacier system consists of both debris-covered glaciers in the south and debris-free glaciers in the north, and as a result, the glacier changes vary between the two regions. Between 1976 – 2018/9 the southern region had an average surface melt of 0.76 ± 0.07 m a-1 which calculates to a geodetic mass balance of -0.65 ± 0.06 m w.e. a-1 and a 12.65% area of reduction. For the Northern region, the average surface melt was measured to be 1.26 ± 0.07 m a-1 which calculates to a geodetic mass balance of 1.07 ± 0.06 m w.e. a-1 and a 12.80% area of reduction. The glacier velocity was calculated to be at average of 3.05 ± 0.73 m a-1 over the south region and 3.78 ± 0.73 m a-1 over the north region. The Luggye glacier 1, located in the southern parts of Lunana glacier system, is the main input source for glacier meltwater to Luggye Tsho an ice-moraine dam proglacial lake which outburst in 1994 due to hydrostatic pressure. Between 1976 and 2018/9, the Luggye glacier 1 has had a considerable loss in surface elevation by 1.19 ± 0.07 m a-1 which calculates to a geodetic mass balance of 1.01 ± 0.069 m w.e. a-1. The 1994 GLOF event discharged over 18 million m3 of water, destroying infrastructure, flooding villages and houses which killed 21 humans. Today, Luggye Tsho is classified to yield over 1.41 km2 of water, an increase from its former state of 1.12 km2 in 1993, just before the event. This study cannot affirm if PDGLs such as Luggye Tsho is to outburst in the future, but it does affirm its growth in lake area and its input source from glacier melt over Luggye glacier, and that it should be monitored in case of potential outbreak. This can be done by doing repeated analysis of glacier velocity and calculation of glacier mass balance, as this would calculate the input source amount of meltwater to Luggye Tsho.Masteroppgave i geografiGEO350MASV-PHYGMASV-GEOGMPGEOGRMASV-MEH

Quantification and Change Assessment Benjamin Aubrey Robson 2016 Dissertation date: 31st October 2016 of Debris-Covered Glaciers using Remote Sensing

This thesis investigates how remote sensing data can be used to assess the changing state of debris-covered ice. The principal study areas are the Manaslu Region in Nepal (papers I and III) and the Hohe Tauern National Park, Austria (paper II). Clean glacier ice is straightforward to semi-automatically classify using multi-spectral satellite imagery owing to the strong spectral signature of clean ice in the visible and near-infrared sections of the electromagnetic spectrum. Since the ablation zones of clean ice glaciers are at the pressure melting point, a change in terminus position or glacier area can be directly linked to a change in climate. Debris-covered ice is however more complicated to map and to interpret temporal change. Supraglacial debris is spectrally indistinguishable from the surrounding paraglacial terrain, and requires auxiliary data such as a Digital Elevation Model (DEM), thermal band data, or flow data. Object-Based Image Analysis (OBIA) provides a framework for combining multiple datasets in one analysis, while additionally allowing shape, contextual, hierarchical and textural criteria to be used to classify imagery. Paper I combines optical (Landsat-8), topographic (void-filled SRTM) and SAR coherence (ALOS PALSAR) data within an OBIA workflow to semi-automatically classify both clean ice and debris-covered ice in the challenging area surrounding Mount Manaslu in Nepal. When compared with manually delineated outlines, the classification achieved an accuracy of 91% (93% for clean ice and 83% for debriscovered ice). The classification was affected by seasonal snow and shadows while the debris-covered ice mapping was influenced by the datasets being temporally inconsistent, and the mountainous topography causing inconsistencies in the SAR coherence data. The method compares well with other automated techniques for classifying debris-covered ice, but has two additional advantages: firstly, that SAR coherence data can distinguish active ice from stagnant ice based on whether motion or significant downwasting has occured, and secondly, that the method is applicable over a large study area using just space-borne data. Paper II explores the potential of using high-resolution (10 m) topographic data and an edge detection algorithm to morphologically map the extent of debris-covered ice. The method was applied in the Hohe Tauern National Park, Austria, using a 10 m DEM derived from airborne Light Detection and Radar (LiDAR) acquisitions. Additionally, the end-of-summer transient snowline (TSL) was also mapped, which approximates the annual Equilibrium Line Altitude (ELA). Our classification was applied on three Landsat satellite images from 1985, 2003 and 2013 and compared the results to the Austrian Glacier Inventories from 1969 and 1998 to derive decadal-scale glacial changes. A mean rate of glacier area reduction of 1.4 km2a-1 was calculated between 1969 and 2013 with a total reduction in area of 33%. The TSL rose by 92 m between 1985 and 2013 to an altitude of 3005 m. By comparing our results with manually delineated outlines an accuracy of 97.5% was determined. When a confusion matrix was calculated it could be seen that the results contained few false positives but some false negatives which were attributed to seasonal snow, shadows and misclassified debris. Our results correspond broadly with those found in other areas of the European Alps although a heterogeneity in glacier change is observable. We recommend that future glacier mapping investigations should utilise a combination of both SAR coherence data and high-resolution topographic data in order to delineate the extent of both active and stagnant glacier ice. Paper III investigates decadal scale changes in glacier area, velocity and volume in the previously undocumented Manaslu Region, Nepal. Between 2001 and 2013 the glacier area reduced by 8.2% (-0.68% a-1). Simultaneously, the glaciers lowered by -0.21 ± 0.08 m a-1 and had a slightly negative specific mass balance of -0.05 ± 016 m w.e a-1 although mass balances ranged -2.49 ± 2.24 to +0.27 ± 0.30 m w.e a-1 throughout the region. The geodetic mass balance for select glaciers covered by a Corona DEM between 1970 and 2013 was -0.24 ± 0.12 m w.e a-1 which became more negative (-0.51 ± 0.12 m w.e. a-1) between 2005 and 2013. Rates of surface lowering over debriscovered ice increasing by 168% between 1970 – 2000 (0.40 ± 0.18 m a-1) and 2005 – 2013 (1.07 ±0.48 m a-1). The rate of glacier melt varies due to presumed increases in debris thickness at the upper and lower boundaries of the ablation zone, while an area of enhanced glacier downwasting corresponds to the presence of supraglacial lakes and exposed ice. The glacier velocity varies across the region. Many glaciers have stagnant sections towards the glacier termini, and a trend of ongoing stagnation is observable. No relationship exists between trends in glacier area and glacier volume or velocity, although a weak relationship exists between trends in the changes of volume and velocity. The rates of glacier area and velocity change appear to be similar, although the number of glaciers that had records of area, velocity, and volume was few. Our results are comparable to studies looking at mean surface lowerings and geodetic mass balances in other areas of the Himalayas, and point towards heterogeneous yet pronounced mass losses across the Himalaya region

SNOW COVER AND GLACIER DYNAMICS STUDY USING C-AND L-BAND SAR DATASETS IN PARTS OF NORTH WEST HIMALAYA

The seasonal snow cover and permanent ice in form of Himalayan glaciers provide fresh water to many perineal rivers of Himalayas. The melt water from seasonal snow and glaciers, especially during of 15 March to 15 June acts as important source of water for drinking, hydropower and irrigation requirements of many areas in North India. This work has highlights the use of C-band Synthetic Aperture Radar (SAR) data from RISAT-1, Sentinel-1A and 1B satellites and ALOS-PALSAR-2 PolInSAR data for snow cover and glacier dynamics study for parts of North West Himalaya. Glacier velocity was derived using InSAR based method using 6 day temporal interval images from Sentinel-1 satellites and 14 day interval for PALSAR-2 satellite. High coherence was obtained for main glacier in both the data sets, which resulted accurate line of site (LOS) glacier velocity estimates for test glaciers. These InSAR data glacier velocity results are obtained after a gap of 21 years. Glacier facies was estimated using multi-temporal SAR image composition based classification. All these maps were verified by extensive ground surveys done at these sites during 2014–2017. The time series data of C-band SAR in VV/VH polarisation was also used to map snow cover in test basins of Bhagirathi and Beas River. The VV/VH data clearly shows difference between dry and wet snow, thus helping in improved snow cover mapping using SAR data. This study will help in refining algorithms to be used for such studies using upcoming NASA-ISRO SAR (NISAR) mission

Assessment of Snow Status Changes Using L-HH Temporal-Coherence Components at Mt. Dagu, China

Multitemporal Phased Array type L-band Synthetic Aperture Radar (PALSAR) horizontally transmitted and horizontally received (HH) coherence data was decomposed into temporal-coherence, spatial-coherence, and thermal noise components. The multitemporal data spanned between February and May of 2008, and consisted of two pairs of interferometric SAR (InSAR) images formed by consecutive repeat passes. With the analysis of ancillary data, a snow increase process and a snow decrease process were determined. Then, the multiple temporal-coherence components were used to study the variation of thawing and freezing statuses of snow because the components can mostly reflect the temporal change of the snow that occurred between two data acquisitions. Compared with snow mapping results derived from optical images, the outcomes from the snow increase process and the snow decrease process reached an overall accuracy of 71.3% and 79.5%, respectively. Being capable of delineating not only the areas with or without snow cover but also status changes among no-snow, wet snow, and dry snow, we have developed a critical means to assess the water resource in alpine areas

Automated Delineation of Supraglacial Debris Cover Using Deep Learning and Multisource Remote Sensing Data

Funding: S.K. acknowledges funding from the DST-India via INSPIRE fellowship scheme (DST/INSPIRE Fellowship/2017/IF170680). S.K. acknowledges funding from Deutscher Akademischer Austauschdienst (DAAD) funding ID 2021/22 (57552338).Peer reviewedPublisher PD

Remote Sensing of Snow Cover Using Spaceborne SAR: A Review

The importance of snow cover extent (SCE) has been proven to strongly link with various natural phenomenon and human activities; consequently, monitoring snow cover is one the most critical topics in studying and understanding the cryosphere. As snow cover can vary significantly within short time spans and often extends over vast areas, spaceborne remote sensing constitutes an efficient observation technique to track it continuously. However, as optical imagery is limited by cloud cover and polar darkness, synthetic aperture radar (SAR) attracted more attention for its ability to sense day-and-night under any cloud and weather condition. In addition to widely applied backscattering-based method, thanks to the advancements of spaceborne SAR sensors and image processing techniques, many new approaches based on interferometric SAR (InSAR) and polarimetric SAR (PolSAR) have been developed since the launch of ERS-1 in 1991 to monitor snow cover under both dry and wet snow conditions. Critical auxiliary data including DEM, land cover information, and local meteorological data have also been explored to aid the snow cover analysis. This review presents an overview of existing studies and discusses the advantages, constraints, and trajectories of the current developments

Remote Sensing of Mountain Glaciers and Related Hazards

Mountain glaciers are highly sensitive to temperature and precipitation fluctuations and active geomorphic agents in shaping the landforms of glaciated regions which are direct imprints of past glaciations, providing reliable evidence of the evolution of the past Cryosphere and contain important information on climatic variables. But most importantly, glaciers have aroused a lot of concern in terms of glacier area changes, thickness change, mass balance and their consequences on water resources as well as related hazards. The contribution of glacier mass loss to global sea-level rise and increasing number of glacier-related hazards are the most important and current socioeconomic concerns. Therefore, understanding the dynamics of the changes and constant monitoring of glaciers are essential for studying climate, water resource management and hydropower and also to predict and evade glacier-related hazards. The recent advances in the techniques of earth observations have proved as a boon for investigating glaciers and glacier-related hazards. Remote sensing technology enables extraction of glacier parameters such as albedo/reflectance/scattering, glacier area, glacier zones and facies, equilibrium line, glacier thickness, volume, mass balance, velocity and glacier topography. The present chapter explores the prospective of remote sensing technology for understanding and surveying glaciers formed at high, inaccessible mountains and glacier-induced hazards

One Decade of Glacier Mass Changes on the Tibetan Plateau Derived from Multisensoral Remote Sensing Data

The Tibetan Plateau (TP) with an average altitude of 4,500 meters above sea level is characterized by many glaciers and ice caps. Glaciers are a natural indicator for climate variability in this high mountain environment where meteorological stations are rare or non-existent. In addition, the melt water released from the Tibetan glaciers is feeding the headwaters of the major Asian river systems and contributes to the rising levels of endorheic lakes on the plateau. As many people directly rely on the glacier melt water a continuous glacier monitoring program is necessary in this region. In situ measurements of glaciers are important, but are spatial limited due to large logistical efforts, physical constrains and high costs. Remote sensing techniques can overcome this gap and are suitable to complement in situ measurements on a larger scale. In the last decade several remote sensing studies dealt with areal changes of glaciers on the TP. However, glacier area changes only provide a delayed signal to a changing climate and the amount of melt water released from the glaciers cannot be quantified. Therefore it is important to measure the glacier mass balance. In order to estimate glacier mass balances and their spatial differences on the TP, several remote sensing techniques and sensors were synthesized in this thesis. In a first study data from the Ice Cloud and Elevation Satellite (ICESat) mission were employed. ICESat was in orbit between 2003 and 2009 and carried a laser altimeter which recorded highly accurate surface elevation measurements. As in mid-latitudes these measurements are rather sparse glaciers on the TP were grouped into eight climatological homogeneous sub-regions in order to perform a statistical sound analysis of glacier elevation changes. To assess surface elevation changes of a single mountain glacier from ICESat data, an adequate spatial sampling of ICESat measurements need to be present. This is the case for the Grosser Aletschgletscher, located in the Swiss Alps which served as a test site in this thesis. In another study data from the current TanDEM-X satellite mission and from the Shuttle Radar Topography Mission (SRTM) conducted in February 2000 were employed to calculate glacier elevation changes. In a co-authored study, these estimates could be compared with glacier elevation changes obtained from the current French Pléiades satellite mission. In order to calculate glacier mass balances, the derived elevation changes were combined with assumptions about glacier area and ice density in all studies. In this thesis contrasting patterns of glacier mass changes were found on the TP. With an ICESat derived estimate of -15.6±10.1 Gt/a between 2003 and 2009 the average glacier mass balance on the TP was clearly negative. However, some glaciers in the central and north-western part of the TP showed a neutral mass balance or a slightly positive anomaly which was also confirmed by data from the current TanDEM-X satellite mission. A possible explanation of this anomaly in mass balance could be a compensation of the temperature driven glacier melt due to an increase in precipitation