96 research outputs found

    Investigating the dynamics of Greenland's glacier-fjord systems

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    Over the past two decades, Greenland’s tidewater glaciers have dramatically retreated, thinned and accelerated, contributing significantly to sea level rise. This change in glacier behaviour is thought to have been triggered by increasing atmospheric and ocean temperatures, and mass loss from Greenland’s tidewater glaciers is predicted to continue this century. Substantial research during this period of rapid glacier change has improved our understanding of Greenland’s glacier-fjord systems. However, many of the processes operating in these systems that ultimately control the response of tidewater glaciers to changing atmospheric and oceanic conditions are poorly understood. This thesis combines modelling and remote sensing to investigate two particularly poorly-understood components of glacier-fjord systems, with the ultimate aim of improving understanding of recent glacier behaviour and constraining the stability of the ice sheet in a changing climate. The research presented in this thesis begins with an investigation into the dominant controls on the seasonal dynamics of contrasting tidewater glaciers draining the Greenland Ice Sheet. To do this, high resolution estimates of ice velocity were generated and compared with detailed observations and modelling of the principal controls on seasonal glacier flow, including terminus position, ice mĂ©lange presence or absence, ice sheet surface melting and runoff, and plume presence or absence. These data revealed characteristic seasonal and shorter-term changes in ice velocity at each of the study glaciers in more detail than was available from previous remote sensing studies. Of all the environmental controls examined, seasonal evolution of subglacial hydrology (as inferred from plume observations and modelling) was best able to explain the observed ice flow variations, despite differences in geometry and flow of the study glaciers. The inferred relationships between subglacial hydrology and ice dynamics were furthermore entirely consistent with process-understanding developed at land-terminating sectors of the ice sheet. This investigation provides a more detailed understanding of tidewater glacier subglacial hydrology and its interaction with ice dynamics than was previously available and suggests that interannual variations in meltwater supply may have limited influence on annually averaged ice velocity. The thesis then shifts its attention from the glacier part of the system into the fjords, focusing on the interaction between icebergs, fjord circulation and fjord water properties. This focus on icebergs is motivated by recent research revealing that freshwater produced by iceberg melting constitutes an important component of fjord freshwater budgets, yet the impact of this freshwater on fjords was unknown. To investigate this, a new model for iceberg-ocean interaction is developed and incorporated into an ocean circulation model. This new model is first applied to Sermilik Fjord — a large fjord in east Greenland that hosts Helheim Glacier, one of the largest tidewater glaciers draining the ice sheet — to further constrain iceberg freshwater production and to quantify the influence of iceberg melting on fjord circulation and water properties. These investigations reveal that iceberg freshwater flux increases with ice sheet runoff raised to the power ~0.1 and ranges from ~500-2500 mÂł s⁻Âč during summer, with ~40% of that produced below the pycnocline. It is also shown that icebergs substantially modify the temperature and velocity structure of Sermilik Fjord, causing 1-5°C cooling in the upper ~100 m and invigorating fjord circulation, which in turn causes a 10-40% increase in oceanic heat flux towards Helheim Glacier. This research highlights the important role of icebergs in Greenland’s iceberg congested fjords and therefore the need to include them in future studies examining ice sheet – ocean interaction. Having investigated the effect of icebergs on fjord circulation in a realistic setting, this thesis then characterises the effect of submarine iceberg melting on water properties near the ice sheet – ocean interface by applying the new model to a range of idealised scenarios. This near-glacier region is one which is crucial for constraining ocean-driven retreat of tidewater glaciers, but which is poorly-understood. The simulations show that icebergs are important modifiers of glacier-adjacent water properties, generally acting to reduce vertical variations in water temperature. The iceberg-induced temperature changes will generally increase submarine melt rates at mid-depth and decrease rates at the surface, with less pronounced effects at greater depth. This highlights another mechanism by which iceberg melting can affect ice sheet – ocean interaction and emphasises the need to account for iceberg-ocean interaction when simulating ocean-driven retreat of Greenland’s tidewater glaciers. In summary, this thesis has helped to provide a deeper understanding of two poorly-understood components of Greenland’s tidewater glacier-fjord systems: (i) interactions between subglacial hydrology and ice velocity, and; (ii) iceberg-ocean interaction. This research has enabled more precise interpretations of past glacier behaviour and can be used to inform model development that will help constrain future ice sheet mass loss in response to a changing climate."I must express my gratitude to the University of St Andrews and to the Scottish Alliance for Geoscience, Environment and Society (SAGES) for funding and supporting me as a research student."-- Fundin

    Ice Sheet and Sea Ice Ultrawideband Microwave radiometric Airborne eXperiment (ISSIUMAX) in Antarctica: first results from Terra Nova Bay

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    An airborne microwave wide-band radiometer (500–2000 MHz) was operated for the first time in Antarctica to better understand the emission properties of sea ice, outlet glaciers and the interior ice sheet from Terra Nova Bay to Dome C. The different glaciological regimes were revealed to exhibit unique spectral signatures in this portion of the microwave spectrum. Generally, the brightness temperatures over a vertically homogeneous ice sheet are warmest at the lowest frequencies, consistent with models that predict that those channels sensed the deeper, warmer parts of the ice sheet. Vertical heterogeneities in the ice property profiles can alter this basic interpretation of the signal. Spectra along the lengths of outlet glaciers were modulated by the deposition and erosion of snow, driven by strong katabatic winds. Similar to previous experiments in Greenland, the brightness temperatures across the frequency band were low in crevasse areas. Variations in brightness temperature were consistent with spatial changes in sea ice type identified in satellite imagery and in situ ground-penetrating radar data. The results contribute to a better understanding of the utility of microwave wide-band radiometry for cryospheric studies and also advance knowledge of the important physics underlying existing L-band radiometers operating in space.</p

    Using glaciers to identify, monitor and predict volcanic activity

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    Globally, ~250 Holocene active volcanoes are either glacier-clad or have glaciers in close proximity. The presence of glaciers on a volcano sometimes masks evidence of volcanic activity and therefore makes direct observations of volcanic activity more challenging if compared to an ‘ice-free’ volcano. However, it is also possible that glaciers can provide indirect information about the activity of the volcanoes on which they sit. With this in mind, the overall aim of this thesis is to assess the degree to which volcanically triggered impacts on glaciers can be observed from optical satellite imagery, and to consider whether these impacts can be used to help identify, monitor and predict volcanic activity. To achieve this, volcanically triggered changes in glacier surface morphology and glacier surface velocity are studied on ice-clad volcanoes using optical satellite images. Approximately 1400 optical satellite images are investigated from key, well-documented eruptions from 1972 to 2015 (i.e., during the satellite remote sensing era) and around the globe. To investigate volcanically triggered changes in surface velocity, glacier velocimetry is performed on Cone Glacier (Mount Veniaminof, Alaska) using 99 Sentinel-2 band 8 images (near-infrared, central wavelength: 842 nm) covering two volcanically active periods, one from September to December 2018 and one in March/April 2021. This approach includes the extraction of velocities along a profile line (following an inferred ice flowline), the generation of time-series velocities, and the calculation of velocity difference maps. The extensive analysis of optical satellite images around the globe shows that the most common observable volcanic impact on glacier morphology (for both thick and thin ice-masses) is ice cauldron and opening formation, often (but not exclusively) associated with concentric crevassing. Other observable volcanic impacts on glacier morphology include ice bulging and fracturing due to subglacial dome growth, localized crevassing due to supraglacial lava flows and widespread glacier crevassing, presumably, due to meltwater-triggered glacier acceleration and advance. Glacier velocimetry results from Cone Glacier show faster glacier surface velocities ~10 months prior to the 2018 volcanically active period and ~2 months prior to the 2021 volcanically active period. Also, an amplified seasonal cycle of faster-than-usual surface velocities in the summer and slower-than-usual surface velocities in the winter is observed during both years with an eruption. Volcanically triggered meltwater is considered as a cause of changing the subglacial drainage at Cone Glacier and is therefore argued as a potential cause of the observed surface velocity changes. The wider applicability of the results to other temperate and polythermal glaciers affected by volcanic activity is discussed. In all, this thesis works towards a deeper understanding of volcanic impacts on glacier morphology and dynamics, elaborates main limitations of using optical satellite images to study ice-clad volcanoes and provides advice for best practice for monitoring glaciers in volcanically active areas

    Development of high-precision snow mapping tools for Arctic environments

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    Le manteau neigeux varie grandement dans le temps et l’espace, il faut donc de nombreux points d’observation pour le dĂ©crire prĂ©cisĂ©ment et ponctuellement, ce qui permet de valider et d’amĂ©liorer la modĂ©lisation de la neige et les applications en tĂ©lĂ©dĂ©tection. L’analyse traditionnelle par des coupes de neige dĂ©voile des dĂ©tails pointus sur l’état de la neige Ă  un endroit et un moment prĂ©cis, mais est une mĂ©thode chronophage Ă  laquelle la distribution dans le temps et l’espace font dĂ©faut. À l’opposĂ© sur la fourchette de la prĂ©cision, on retrouve les solutions orbitales qui couvrent la surface de la Terre Ă  intervalles rĂ©guliers, mais Ă  plus faible rĂ©solution. Dans l’optique de recueillir efficacement des donnĂ©es spatiales sur la neige durant les campagnes de terrain, nous avons dĂ©veloppĂ© sur mesure un systĂšme d’aĂ©ronef tĂ©lĂ©pilotĂ© (RPAS) qui fournit des cartes d’épaisseur de neige pour quelques centaines de mĂštres carrĂ©s, selon la mĂ©thode Structure from motion (SfM). Notre RPAS peut voler dans des tempĂ©ratures extrĂȘmement froides, au contraire des autres systĂšmes sur le marchĂ©. Il atteint une rĂ©solution horizontale de 6 cm et un Ă©cart-type d’épaisseur de neige de 39 % sans vĂ©gĂ©tation (48,5 % avec vĂ©gĂ©tation). Comme la mĂ©thode SfM ne permet pas de distinguer les diffĂ©rentes couches de neige, j’ai dĂ©veloppĂ© un algorithme pour un radar Ă  onde continue Ă  modulation de frĂ©quence (FM-CW) qui permet de distinguer les deux couches principales de neige que l’on retrouve rĂ©guliĂšrement en Arctique : le givre de profondeur et la plaque Ă  vent. Les distinguer est crucial puisque les caractĂ©ristiques diffĂ©rentes des couches de neige font varier la quantitĂ© d’eau disponible pour l’écosystĂšme lors de la fonte. Selon les conditions sur place, le radar arrive Ă  estimer l’épaisseur de neige selon un Ă©cart-type entre 13 et 39 %. vii Finalement, j’ai Ă©quipĂ© le radar d’un systĂšme de gĂ©olocalisation Ă  haute prĂ©cision. Ainsi Ă©quipĂ©, le radar a une marge d’erreur de gĂ©olocalisation d’en moyenne <5 cm. À partir de la mesure radar, on peut dĂ©duire la distance entre le haut et le bas du manteau neigeux. En plus de l’épaisseur de neige, on obtient Ă©galement des points de donnĂ©es qui permettent d’interpoler un modĂšle d’élĂ©vation de la surface solide sous-jacente. J’ai utilisĂ© la mĂ©thode de structure triangulaire (TIN) pour toutes les interpolations. Le systĂšme offre beaucoup de flexibilitĂ© puisqu’il peut ĂȘtre installĂ© sur un RPAS ou une motoneige. Ces outils Ă©paulent la modĂ©lisation du couvert neigeux en fournissant des donnĂ©es sur un secteur, plutĂŽt que sur un seul point. Les donnĂ©es peuvent servir Ă  entraĂźner et Ă  valider les modĂšles. Ainsi amĂ©liorĂ©s, ils peuvent, par exemple, permettre de prĂ©dire la taille, le niveau de santĂ© et les dĂ©placements de populations d’ongulĂ©s, dont la survie dĂ©pend de la qualitĂ© de la neige. (Langlois et coll., 2017.) Au mĂȘme titre que la validation de modĂšles de neige, les outils prĂ©sentĂ©s permettent de comparer et de valider d’autres donnĂ©es de tĂ©lĂ©dĂ©tection (par ex. satellites) et d’élargir notre champ de comprĂ©hension. Finalement, les cartes ainsi crĂ©Ă©es peuvent aider les Ă©cologistes Ă  Ă©valuer l’état d’un Ă©cosystĂšme en leur donnant accĂšs Ă  une plus grande quantitĂ© d’information sur le manteau neigeux qu’avec les coupes de neige traditionnelles.Abstract: Snow is highly variable in time and space and thus many observation points are needed to describe the present state of the snowpack accurately. This description of the state of the snowpack is necessary to validate and improve snow modeling efforts and remote sensing applications. The traditional snowpit analysis delivers a highly detailed picture of the present state of the snow in a particular location but lacks the distribution in space and time as it is a time-consuming method. On the opposite end of the spatial scale are orbital solutions covering the surface of the Earth in regular intervals, but at the cost of a much lower resolution. To improve the ability to collect spatial snow data efficiently during a field campaign, we developed a custom-made, remotely piloted aircraft system (RPAS) to deliver snow depth maps over a few hundred square meters by using Structure-from-Motion (SfM). The RPAS is capable of flying in extremely low temperatures where no commercial solutions are available. The system achieves a horizontal resolution of 6 cm with snow depth RMSE of 39% without vegetation (48.5% with vegetation) As the SfM method does not distinguish between different snow layers, I developed an algorithm for a frequency modulated continuous wave (FMCW) radar that distinguishes between the two main snow layers that are found regularly in the Arctic: “Depth Hoar” and “Wind Slab”. The distinction is important as these characteristics allow to determine the amount of water stored in the snow that will be available for the ecosystem during the melt season. Depending on site conditions, the radar estimates the snow depth with an RMSE between 13% and 39%. v Finally, I equipped the radar with a high precision geolocation system. With this setup, the geolocation uncertainty of the radar on average < 5 cm. From the radar measurement, the distance to the top and the bottom of the snowpack can be extracted. In addition to snow depth, it also delivers data points to interpolate an elevation model of the underlying solid surface. I used the Triangular Irregular Network (TIN) method for any interpolation. The system can be mounted on RPAS and snowmobiles and thus delivers a lot of flexibility. These tools will assist snow modeling as they provide data from an area instead of a single point. The data can be used to force or validate the models. Improved models will help to predict the size, health, and movements of ungulate populations, as their survival depends on it (Langlois et al., 2017). Similar to the validation of snow models, the presented tools allow a comparison and validation of other remote sensing data (e.g. satellite) and improve the understanding limitations. Finally, the resulting maps can be used by ecologist to better asses the state of the ecosystem as they have a more complete picture of the snow cover on a larger scale that it could be achieved with traditional snowpits

    Review Article: Global Monitoring of Snow Water Equivalent Using High-Frequency Radar Remote Sensing

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    Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth\u27s surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth\u27s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∌ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world\u27s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth\u27s cold regions\u27 ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements

    Analysis of ice-sheet temperature profiles from low-frequency airborne remote sensing

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    Abstract Ice internal temperature and basal geothermal heat flux (GHF) are analyzed along a study line in northwestern Greenland. The temperatures were obtained from a previously reported inversion of airborne microwave brightness-temperature spectra. The temperatures vary slowly through the upper ice sheet and more rapidly near the base increasing from ~259 K near Camp Century to values near the melting point near NorthGRIP. The flow-law rate factor is computed from temperature data and analytic expressions. The rate factor increases from ~1 × 10−8 to 8 × 10−8 kPa−3 a−1 along the line. A laminar flow model combined with the depth-dependent rate factor is used to estimate horizontal velocity. The modeled surface velocities are about a factor of 10 less than interferometric synthetic aperture radar (InSAR) surface velocities. The laminar velocities are fitted to the InSAR velocities through a factor of 8 enhancement of the rate factor for the lower 25% of the column. GHF values retrieved from the brightness temperature spectra increase from ~55 to 84 mW m−2 from Camp Century to NorthGRIP. A strain heating correction improves agreement with other geophysical datasets near Camp Century and NEEM but differ by ~15 mW m−2 in the central portion of the profile

    Developing Parameter Constraints for Radar-based SWE Retrievals

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    Terrestrial snow is an important freshwater reservoir with significant influence on the climate and energy balance. It exhibits natural spatiotemporal variability which has been enhanced by climate change, thus it is important to monitor on a large scale. Active microwave, or radar remote sensing has shown frequency-dependent promise in this regard, however, interpretation remains a challenge. The aim of this thesis was to develop constraints for radar based SWE retrievals which characterize and limit uncertainty with a focus on the underlying physical processes, snowpack stratigraphy, the influence of vegetation, and effects of background scattering. The University of Waterloo Scatterometer (UWScat) was used to make measurements at 9.6 and 17.2 GHz of snow and bare ground in a series of field-based campaigns in Maryhill and Englehart, ON, Grand Mesa, CO (NASA SnowEx campaign, year 1), and Trail Valley Creek, NT. Additional measurements from Tobermory, ON, and Churchill, MB (Canadian Snow and Ice Experiment) were included. The Microwave Emission Model for Layered Snowpacks, Version 3, adapted for backscattering (MEMLS3&a) was used to explore snowpack parameterization and SWE retrieval and the Freeman-Durden three component decomposition (FD3c) was used to leverage the polarimetric response. Physical processes in the snow accumulation environment demonstrated influence on regional snowpack parameterization and constraints in a SWE retrieval context with a single-layer snowpack parameterization for Maryhill, ON and a two-layer snowpack parameterization for Englehart, ON resulting in a retrieval RMSE of 21.9 mm SWE and 24.6 mm SWE, respectively. Use of in situ snow depths improved RMSE to 12.0 mm SWE and 10.9 mm SWE, while accounting for soil scattering effects further improved RMSE by up to 6.3 mm SWE. At sites with vegetation and ice lenses, RMSE improved from 60.4 mm SWE to 21.1 mm SWE when in situ snow depths were used. These results compare favorably with the common accuracy requirement of RMSE ≀ 30 mm and underscore the importance of understanding the driving physical processes in a snow accumulation environment and the utility of their regional manifestation in a SWE retrieval context. A relationship between wind slab thickness and the double-bounce component of the FD3c in a tundra snowpack was introduced for incidence angles ≄ 46° and wind slab thickness ≄ 19 cm. Estimates of wind slab thickness and SWE resulted in an RMSE of 6.0 cm and 5.5 mm, respectively. The increased double-bounce scattering was associated with path length increase within a growing wind slab layer. Signal attenuation in a sub-canopy SWE retrieval was also explored. The volume scattering component of the FD3c yielded similar performance to forest fraction in the retrieval with several distinct advantages including a real-time description of forest condition, accounting for canopy geometry without ancillary information, and providing coincident information on forest canopy in remote locations. Overall, this work demonstrated how physical processes can manifest regional outcomes, it quantified effects of natural inclusions and background scattering on SWE retrievals, it provided a means to constrain wind slab thickness in a tundra environment, and it improved characterization of coniferous forest in a sub-canopy SWE retrieval context. Future work should focus on identifying ice and vegetation conditions prior to SWE retrieval, testing the spatiotemporal validity of the methods developed herein, and finally, improving the integration of snowpack attenuation within retrieval efforts

    Melt on Antarctic ice shelves: observing surface melt duration from microwave remote sensing and modeling the dynamical impacts of subshelf melting

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    Dissertation (Ph.D.) University of Alaska Fairbanks, 2021Melt on the surface and underside of Antarctic ice shelves are important to the mass balance and stability of the ice sheet, and therefore pose significance to global sea levels. Satellite-based passive microwave observations provide daily or near-daily coarse resolution surface observations from 1978 on, and we use this record to identify days in which melt water is present on the ice sheet and ice shelf surfaces, called melt days. There are significant differences in the results of melt detection methods however, and we evaluate four different passive microwave melt detection algorithms. There is a lack of sufficient ground truth observations, so we use Google Earth Engine to build time series of Sentinel-1 Synthetic Aperture Radar images from which we can also detect melt to serve as a comparison dataset. A melt detection method using a Kmeans clustering algorithm developed here is shown to be the most effective on ice shelves, so we further apply this method to quantify melt days across all Antarctica ice shelves for every year from 1979/80 to 2019/20. The highest sums of melt days occur on the Antarctic Peninsula at 89 melt days per year, and we find few linear trends in the annual melt days on ice shelves around the continent. The primary mode of spatial variability in the melt day dataset is closely related to the Southern Annular Mode, a climate index for the southward migration of Southern Westerly Winds, which has been increasing in recent decades. Positive Southern Annular Mode index values are associated with decreased melt days in some regions of Antarctica. We also present a novel application of passive microwave analysis to detect changes in firn structure due to unusually large melt events in some regions and we show how this method detects ice lens formation and grain growth on specific ice shelves. To study the impacts of subshelf melt we focus on the Filchner-Ronne region of Antarctica, which contains the second largest ice shelf on the continent. We performed an ensemble of ice sheet model runs for a set of ocean warming scenarios. Each ensemble used a realistic range of physical parameters to control ice dynamics and sliding, generated by a Bayesian analysis of a surrogate model and observed velocities. Increased ocean temperatures were associated with increased mass loss, and by the year 2100 this region contributed 14 mm to sea level per degree of ocean warming at depth between +0°C and +4°C of ocean potential temperature. Beyond +4°C, the rate mass loss increased substantially. This mass loss corresponded to grounding line retreat across the region.NSF Award #1543432, NASA grant #80NSSC17K056

    Monitoring Snow Cover and Snowmelt Dynamics and Assessing their Influences on Inland Water Resources

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    Snow is one of the most vital cryospheric components owing to its wide coverage as well as its unique physical characteristics. It not only affects the balance of numerous natural systems but also influences various socio-economic activities of human beings. Notably, the importance of snowmelt water to global water resources is outstanding, as millions of populations rely on snowmelt water for daily consumption and agricultural use. Nevertheless, due to the unprecedented temperature rise resulting from the deterioration of climate change, global snow cover extent (SCE) has been shrinking significantly, which endangers the sustainability and availability of inland water resources. Therefore, in order to understand cryo-hydrosphere interactions under a warming climate, (1) monitoring SCE dynamics and snowmelt conditions, (2) tracking the dynamics of snowmelt-influenced waterbodies, and (3) assessing the causal effect of snowmelt conditions on inland water resources are indispensable. However, for each point, there exist many research questions that need to be answered. Consequently, in this thesis, five objectives are proposed accordingly. Objective 1: Reviewing the characteristics of SAR and its interactions with snow, and exploring the trends, difficulties, and opportunities of existing SAR-based SCE mapping studies; Objective 2: Proposing a novel total and wet SCE mapping strategy based on freely accessible SAR imagery with all land cover classes applicability and global transferability; Objective 3: Enhancing total SCE mapping accuracy by fusing SAR- and multi-spectral sensor-based information, and providing total SCE mapping reliability map information; Objective 4: Proposing a cloud-free and illumination-independent inland waterbody dynamics tracking strategy using freely accessible datasets and services; Objective 5: Assessing the influence of snowmelt conditions on inland water resources
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