Search Results (57)

The glaciers in the High Mountain Asia (HMA) region are highly vulnerable to global warming, posing significant threats to downstream populations and infrastructure through glacier lake outburst floods (GLOFs). The monitoring and early warnings of these events are challenging due to sparse observations in these remote regions. To explore reproducing the evolution of GLOFs with sparse observations in situ, this study focuses on the outburst event and corresponding GLOFs in August 2018 caused by the Kyagar Glacier lake, a typical glacier lake of the HMA in the Karakoram, which is known for its frequent outburst events, using a combination of multi-satellite remote sensing data (Sentinel-1 and Sentinel-2) and the HEC-RAS hydrodynamic model. The water depth of the glacier lake and downstream was extracted from satellite data adapted by the Floodwater Depth Elevation Tool (FwDET) as a baseline to compare them with simulations. The elevation-water volume curve was obtained by extrapolation and was applied to calculate the water surface elevation (WSE). The inundation of the downstream of the lake outburst was obtained through flood modeling by incorporating a load elevation-water volume curve and the Digital Elevation Model (DEM) into the hydrodynamic model HEC-RAS. The results showed that the Kyagar glacial lake outburst was rapid and destructive, accompanied by strong currents at the end of each downstream storage ladder. A series of meteorological evaluation indicators showed that HEC-RAS reproduced the medium and low streamflow rates well. This study demonstrated the value of integrating remote sensing and hydrodynamic modeling into GLOF assessments in data-scarce regions, providing insights for disaster risk management and mitigation. Full article

The Sikkim region of the Eastern Himalayas is highly susceptible to Glacial Lake Outburst Floods (GLOFs), a risk that has increased significantly due to rapid glacial retreat driven by climate change in recent years. This study presents a comprehensive evaluation of GLOF susceptibility in Sikkim, employing Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (FAHP) models. Key factors influencing GLOF vulnerability, including lake volume, seismic activity, precipitation, slope, and proximity to rivers, were quantified to develop AHP and FAHP based susceptibility maps. These maps were validated using Receiver Operating Characteristic (ROC) curves, with the AHP method achieving an Area Under the Curve (AUC) of 0.92 and the FAHP method scoring 0.88, indicating high predictive accuracy for both models. A comparison of the two approaches revealed distinct characteristics, with FAHP providing more granular insights into moderate-risk zones, while AHP offered stronger predictive capability for high-risk areas. Our results indicated that the expansion of glacial lakes, particularly over the past three decades, has heightened the potential for GLOFs, highlighting the urgent need for continuous monitoring and adaptive risk mitigation strategies in the region. This study, in addition to enhancing our understanding of GLOF risks in Sikkim, also provides a robust framework for assessing and managing these risks in other glacial regions worldwide. Full article

Glacial Lake Outburst Flood (GLOF) events, particularly prevalent in Asia’s High Mountain regions, pose a significant threat to downstream regions. However, limited understanding of triggering mechanisms and inadequate observations pose significant barriers for early warnings of impending GLOFs. The 2018 Nyalam GLOF event in southern Tibet offers a valuable opportunity for retrospective analysis. By combining optical and radar remote sensing images, meteorological data, and seismicity catalogs, we examined the spatiotemporal evolution, triggering factors, and the outburst mechanism of this event. Our analysis reveals a progressive retreat of 400–800 m for the parent glaciers between 1991 and 2018, increasing the runoff areas at glacier termini by 167% from 2015 to 2018 and contributing abundant meltwater to the glacial lake. In contrast, the lake size shrunk, potentially due to a weakening moraine dam confirmed by SAR interferometry, which detected continuous subsidence with a maximum line-of-sight (LOS) rate of ~120 mm/a over the preceding ~2.5 years. Additionally, temperature and precipitation in 2018 exceeded the prior decade’s average. Notably, no major earthquakes preceded the event. Based on these observations, we propose a likely joint mechanism involving high temperatures, heavy precipitation, and dam instability. An elevated temperature and precipitation accelerated glacial melt, increasing lake water volume and seepage through the moraine dam. This ultimately compromised dam stability and led to its failure between 3 August 2018 and 6 August 2018. Our findings demonstrate the existence of precursory signs for impending GLOFs. By monitoring the spatiotemporal evolution of environmental factors and deformation, it is possible to evaluate glacial lake risk levels. This work contributes to a more comprehensive understanding of GLOF mechanisms and is of significant importance for future glacial lake risk assessments. Full article

On 4 October 2023, a glacier lake outburst flood (GLOF) occurred at South Lhonak Lake in the northwest of Sikkim, India, posing a severe threat to downstream lives and property. Given the serious consequences of GLOFs, understanding their triggering factors is urgent. This paper conducts a comprehensive analysis of optical imagery and InSAR deformation results to study changes in the surrounding surface of the glacial lake before and after the GLOF event. To expedite the processing of massive InSAR data, an InSAR processing system based on the SBAS-InSAR data processing flow and the AI Earth cloud platform was developed. Sentinel-1 SAR images spanning from January 2021 to March 2024 were used to calculate surface deformation velocity. The evolution of the lake area and surface variations in the landslide area were observed using optical images. The results reveal a significant deformation area within the moraine encircling the lake before the GLOF, aligning with the area where the landslide ultimately occurred. Further research suggests a certain correlation between InSAR deformation results and multiple factors, such as rainfall, lake area, and slope. We speculate that heavy rainfall triggering landslides in the moraine may have contributed to breaching the moraine dam and causing the GLOF. Although the landslide region is relatively stable overall, the presence of a crack in the toparea of landslide raises concerns about potential secondary landslides. Our study may improve GLOF risk assessment and management, thereby mitigating or preventing their hazards. Full article

Glacial lake outburst floods (GLOF) hazards in alpine areas are increasing. The effects of climate change on GLOF hazards are unclear. This study examined 37 glacial lakes and climate data from 15 meteorological stations and explored the correlation between climate variations at different temporal scales. The results indicate that 19 GLOFs hazards occurred in El Niño (warm) years, 8 GLOFs hazards occurred in La Niña (cold) years, 3 GLOFs hazards occurred in cold/warm or warm/cold transition years, and 7 GLOFs hazards occurred in normal years. The higher the fluctuations, the higher the probability of GLOF hazards. Climatic conditions can be divided into three categories: extreme temperature and precipitation, as represented by the Guangxie Co GLOF; extreme precipitation, as represented by the Poge Co GLOF; and extreme temperature, as represented by the Tsho Ga GLOF. Full article

The Vanj River Basin contains a dynamic glacier, the Medvezhiy glacier, which occasionally poses a danger to local residents due to its surging, flooding, and frequent blockages of the Abdukahor River, leading to intense glacial lake outburst floods (GLOF). This study offers a new perspective on the quantitative assessment of glacier surface velocities and associated lake changes during six surges from 1968 to 2023 by using time-series imagery (Corona, Hexagon, Landsat), SRTM elevation maps, ITS_LIVE, unmanned aerial vehicles, local climate, and glacier surface elevation changes. Six turbulent periods (1968, 1973, 1977, 1989–1990, 2001, and 2011) were investigated, each lasting three years within a 10–11-year cycle. During inactive phases, a reduction in the thickness of the glacier tongue in the ablation zone occurred. During a surge in 2011, the flow accelerated, creating an ice dam and conditions for GLOF. Using these datasets, we reconstructed the process of the Medvezhiy glacier surge with high detail and identified a clear signal of uplift in the surface above the lower glacier tongue as well as a uniform increase in velocities associated with the onset of the surge. The increased activity of the Medvezhiy glacier and seasonal fluctuations in surface runoff are closely linked to climatic factors throughout the surge phase, and recent UAV observations indicate the absence of GLOFs in the glacier’s channel. Comprehending the processes of glacier movements and related changes at a regional level is crucial for implementing more proactive measures and identifying appropriate strategies for mitigation. Full article

Over the past decades, the cryosphere has changed significantly in High Mountain Asia (HMA), leading to multiple natural hazards such as rock–ice avalanches, glacier collapse, debris flows, landslides, and glacial lake outburst floods (GLOFs). Monitoring cryosphere change and evaluating its hydrological effects are essential for studying climate change, the hydrological cycle, water resource management, and natural disaster mitigation and prevention. However, knowledge gaps, data uncertainties, and other substantial challenges limit comprehensive research in climate–cryosphere–hydrology–hazard systems. To address this, we provide an up-to-date, comprehensive, multidisciplinary review of remote sensing techniques in cryosphere studies, demonstrating primary methodologies for delineating glaciers and measuring geodetic glacier mass balance change, glacier thickness, glacier motion or ice velocity, snow extent and water equivalent, frozen ground or frozen soil, lake ice, and glacier-related hazards. The principal results and data achievements are summarized, including URL links for available products and related data platforms. We then describe the main challenges for cryosphere monitoring using satellite-based datasets. Among these challenges, the most significant limitations in accurate data inversion from remotely sensed data are attributed to the high uncertainties and inconsistent estimations due to rough terrain, the various techniques employed, data variability across the same regions (e.g., glacier mass balance change, snow depth retrieval, and the active layer thickness of frozen ground), and poor-quality optical images due to cloudy weather. The paucity of ground observations and validations with few long-term, continuous datasets also limits the utilization of satellite-based cryosphere studies and large-scale hydrological models. Lastly, we address potential breakthroughs in future studies, i.e., (1) outlining debris-covered glacier margins explicitly involving glacier areas in rough mountain shadows, (2) developing highly accurate snow depth retrieval methods by establishing a microwave emission model of snowpack in mountainous regions, (3) advancing techniques for subsurface complex freeze–thaw process observations from space, (4) filling knowledge gaps on scattering mechanisms varying with surface features (e.g., lake ice thickness and varying snow features on lake ice), and (5) improving and cross-verifying the data retrieval accuracy by combining different remote sensing techniques and physical models using machine learning methods and assimilation of multiple high-temporal-resolution datasets from multiple platforms. This comprehensive, multidisciplinary review highlights cryospheric studies incorporating spaceborne observations and hydrological models from diversified techniques/methodologies (e.g., multi-spectral optical data with thermal bands, SAR, InSAR, passive microwave, and altimetry), providing a valuable reference for what scientists have achieved in cryosphere change research and its hydrological effects on the Third Pole. Full article

Glacial lake outburst floods (GLOFs) are one of the most severe disasters in alpine regions, releasing a large amount of water and sediment that can cause fatalities and economic loss as well as substantial damage to downstream infrastructures. The risk of GLOFs in the Himalayas is exacerbated by glacier retreat caused by global warming. Critical economic corridors, such as the Rongxer Watershed, are threatened by GLOFs, but the lack of risk assessment specific to the watershed hinders hazard prevention. In this study, we propose a novel model to evaluate the risk of GLOF using a combination of remote sensing observations, GIS, and hydrological models and apply this model to the GLOF risk assessment in the Rongxer Watershed. The results show that (1) the area of glacial lakes in the Rongxer Watershed increased by 31.19% from 11.35 km² in 1990 to 14.89 km² in 2020, and (2) 18 lakes were identified as potentially dangerous glacial lakes (PDGLs) that need to be assessed for the GLOF risk, and two of them were categorized as very high risk (Niangzongmajue and Tsho Rolpa). The proposed model was robust in a GLOF risk evaluation by historical GLOFs in the Himalayas. The glacial lake data and GLOF risk assessment model of this study have the potential to be widely used in research on the relationships between glacial lakes and climate change, as well as in disaster mitigation of GLOFs. Full article

The Shishapangma region, situated in the middle of the Himalayas, is rich in glacial lakes and glaciers. Hence, glacial lake outburst floods (GLOFs) have become a top priority because of the severe threat posed by GLOFs to the downstream settlements. This study presents a comprehensive analysis of GLOF hazards using multi-source remote sensing datasets and designs a flood model considering the different breaching depths and release volumes for the Galong Co region. Based on high-resolution optical images, we derived the expanding lake area and volume of glacial lakes. We monitored deformation velocity and long-term deformation time series around the lake dam with Small BAseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR). The glacier thinning trend was obtained from the difference in the Digital Elevation Model (DEM). We identified potential avalanche sources by combining topographic slope and measurable deformation. We then carried out flood modeling under three different scenarios using the hydrodynamic model HEC-RAS for Galong Co, which is formed upstream of Nyalam. The results show that the Nyalam region is exposed to high-intensity GLOFs in all scenarios. The larger breaching depth and release volumes caused a greater flow depth and peak discharge. Overall, the multiple remote sensing approaches can be applied to other glacial lakes, and the modeling can be used as a basis for GLOF mitigation. Full article

The glacial lakes in the Southeastern Qinghai–Tibet Plateau (SEQTP) have undergone dramatic expansion in the context of global warming, leading to several glacial lake outburst floods (GLOFs) disasters. However, there is a gap and incompleteness in glacial lake inventories across this area due to the heavy cloud cover. In this study, an updated and comprehensive glacial lake inventory was produced by object-based image analysis (OBIA) and manual vectorization based on the Sentinel-1 SAR and Sentinel-2 MSI images acquired in 2022. Detailed steps regarding the OBIA were provided, and the feature set of Sentinel-1 SAR images suitable for extracting glacial lakes was also determined in this paper. We found that the mean combination of ascending-orbit and descending-orbit images is appropriate for mapping glacial lakes. VV-polarized backscattering coefficients from ascending-orbit achieved a better performance for delineating glacial lakes within the study area. Moreover, the distribution of glacial lakes was characterized in terms of four aspects: size, type, elevation, and space. There were 3731 glacial lakes with a total area of 1664.22 ± 0.06 km² in the study area; most of them were less than 0.07 km². Ice-contacted lakes were primarily located in the Palongzangbo basin (13.24 ± 0.08 km²). Nyang Qu basin had the most abundant glacial lake resources (2456 and 93.32 ± 0.18 km²). A comparison with previously published glacial lake datasets demonstrated that our dataset is more complete. This inventory is useful for evaluating water resources, studying glacier–glacial lake interactions, and assessing GLOFs’ susceptibility in the SEQTP. Full article

Lake-terminating glaciers have some peculiar behaviors compared to land-terminating glaciers, but in-depth observation is still limited regarding their formation, which is crucial for understanding the glacier–lake interaction. Here, the long-term evolutions of Tanymas Lake and the Fedchenko Glacier were investigated based on Landsat images, Google Earth imagery, KH-9 images, glacier surface elevation and velocity change datasets, and meteorological records. The results indicate that Tanymas Lake is both an ice-contact proglacial lake and an ice-dammed lake. It covered an area of 1.10 km² in September 2022, and it is one of the largest glacial lakes in Pamir and even in HMA. The initial basin of Tanymas Lake is a moraine depression in Tanymas Pass, and the blocked dam is the Tanymas-5 Glacier and its terminal moraine. Tanymas Lake was in an embryonic stage before August 2005, in a formation and expansion stage from August 2005 to September 2018, and in a new expansion stage after September 2018. In this process, the Tanymas terminus of the Fedchenko Glacier also transformed from a land terminus to a partial lake terminus, and then to a complete lake terminus. The formation of Tanymas Lake is associated with the accumulation of glacial meltwater and the blockage of drainage, while the slow expansion of Tanymas Lake is related to the cold climate and slight glacier mass loss of Central Pamir. In the coming decades, with the accelerated mass loss of the Tanymas terminus of the Fedchenko Glacier, the area, depth, and water storage of Tanymas Lake will continue to increase, accompanied by the growing GLOF risk. Full article

Glaciers experience periodic variations in flow velocity called surges, each of which influences the glacier’s characteristics and the occurrence of downstream disasters (e.g., ice-dammed lake outburst floods). The Karakoram region contains many surging glaciers, yet there are few comprehensive studies of multiple surge cycles. In this work, Landsat, topographic map, Shuttle Radar Topography Mission (SRTM), TerraSAR-X/TanDEM-X, ITS_LIVE, and Sentinel-1 glacier velocity data were used to systematically analyze the characteristics of Kyagar Glacier since the 1970s. Three surging events were identified, with active phases in 1975–1978, 1995–1997, and 2014–2016. The timing of these surges was similar, with a cycle of 19–20 years, an active phase of 3–4 years, and a quiescent phase of 16–17 years. During the quiescent phase, a large amount of ice accumulates in the lower part of the accumulation zone, and the terminal of the tongue thins significantly. According to the most recent surge event (2014–2016), glacier flow accelerated suddenly in the active phase and reached a maximum velocity of 2 ± 0.08 m d⁻¹. Then, the glacier terminal thickened sharply, the reservoir zone thinned by 12 ± 0.2 m, and the terminal receiving zone thickened by 28 ± 0.2 m. The glacier may have entered a quiescent phase after July 2016. The glacier surge causes a large amount of material to transfer from upstream to downstream, forming an ice dam and creating conditions for a glacial lake outburst flood (GLOF). At the termination of the active phase, the subglacial drainage channel became effective, triggering the GLOF. For a period of the quiescent phase, the glacier ablation intensifies and the GLOF repeats constantly. One surge caused 7–8 GLOFs, and then a continuous reduction in the ice dam elevation. Eventually, the ice dam disappeared, and the GLOF no longer continued before the next glacier-surging event. Full article

Establishing an effective real-time monitoring and early warning system for glacier lake outburst floods (GLOFs) requires a full understanding of their occurrence mechanism. However, the harsh conditions and hard-to-reach locations of these glacial lakes limit detailed fieldwork, making satellite imagery a critical tool for monitoring. Lake Mercbacher, an ice-dammed lake in the central Tian Shan mountain range, poses a significant threat downstream due to its relatively high frequency of outbursts. In this study, we first monitored the daily changes in the lake area before the 2022 Lake Mercbacher outburst. Additionally, based on historical satellite images from 2014 to 2021, we calculated the maximum lake area (MLA) and its changes before the outburst. Furthermore, we extracted the proportion of floating ice and water area during the period. The results show that the lake area of Lake Mercbacher would first increase at a relatively low speed (0.01 km²/day) for about one month, followed by a relatively high-speed increase (0.04 km²/day) until reaching the maximum, which would last for about twenty days. Then, the lake area would decrease slowly until the outburst, which would last five days and is significant for early warning. Moreover, the floating ice and water proportion provides more information about the outburst signals. In 2022, we found that the floating ice area increased rapidly during the early warning stage, especially one day before the outburst, accounting for about 50% of the total lake area. Historical evidence indicates that the MLA shows a decreasing trend, and combining it with the outburst date and climate data, we found that the outburst date shows an obvious advance trend (6 days per decade) since 1902, caused by climate warming. Earlier melting results in an earlier outburst. This study provides essential references for monitoring Lake Mercbacher GLOFs and building an effective early warning system. Full article

On 25 June 2020, a glacial lake outburst flood (GLOF) occurred in Jinwuco, Nidou Zangbo, and southeast Tibet, causing catastrophic damage to multiple infrastructures such as roads, bridges, and farmlands in the surrounding and downstream areas. Due to the lack of long-term monitoring of glacial lake and glacier changes in the region and the surrounding surface, the spatial and temporal evolutionary characteristics and triggering factors of the disaster still need to be determined. Here, we combine multi-temporal optical remote sensing image interpretation, surface deformation monitoring with synthetic aperture radar (SAR)/InSAR, meteorological observation data, and corresponding soil moisture change information to systematically analyze the spatial and temporal evolution characteristics and triggering factors of this GLOF disaster. Optical images taken between 1987 and 2020 indicate that the glacial lake’s initial area of 0.39 km² quickly grew to 0.56 km², then plummeted to 0.26 km² after the catastrophe. Meanwhile, we found obvious signs of slippage beside the lateral moraine at the junction of the glacier’s terminus and the glacial lake. The pixel offset tracking (POT) results based on SAR images acquired before and after the disaster reveal that the western lateral moraine underwent a 40 m line of sight (LOS) deformation. The small baseline subset InSAR (SBAS-InSAR) results from 2017 to 2021 show that the cumulative deformation of the slope around the lateral moraine increased in the rainy season before the disaster, with a maximum cumulative deformation of −52 mm in 120 days and gradually stabilized after the disaster. However, there are three long-term deformation areas on the slope above it, showing an increasing trend after the disaster, with cumulative deformation exceeding −30 mm during the monitoring period. The lateral moraine collapse occurred in a warm climate with continuous and intense precipitation, and the low backscatter intensity prior to the slide suggests that the soil was very moist. Intense rainfall is thought to be the catalyst for lateral moraine collapse, whereas the lateral moraine falling into the glacier lake is the direct cause of the GLOF. This study shows that the joint active–passive remote sensing technique can accurately obtain the spatial and temporal evolution characteristics and triggering factors of GLOF. It is helpful to understand the GLOF event caused by the slide of lateral moraine more comprehensively, which is essential for further work related to glacial lake hazard assessment. Full article

Against the background of the ongoing atmospheric warming, the glacial lakes that are nourished and expanded in High Mountain Asia pose growing risks of glacial lake outburst floods (GLOFs) hazards and increasing threats to the downstream areas. Effectively extracting the area and consistently monitoring the dynamics of these lakes are of great significance in predicting and preventing GLOF events. To automatically extract the lake areas, many deep learning (DL) methods capable of capturing the multi-level features of lakes have been proposed in segmentation and classification tasks. However, the portability of these supervised DL methods need to be improved in order to be directly applied to different data sources, as they require laborious effort to collect the labeled lake masks. In this work, we proposed a simple glacial lake extraction model (SimGL) via weakly-supervised contrastive learning to extend and improve the extraction performances in cases that lack the labeled lake masks. In SimGL, a Siamese network was employed to learn similar objects by maximizing the similarity between the input image and its augmentations. Then, a simple Normalized Difference Water Index (NDWI) map was provided as the location cue instead of the labeled lake masks to constrain the model to capture the representations related to the glacial lakes and the segmentations to coincide with the true lake areas. Finally, the experimental results of the glacial lake extraction on the 1540 Landsat-8 image patches showed that our approach, SimGL, offers a competitive effort with some supervised methods (such as Random Forest) and outperforms other unsupervised image segmentation methods in cases that lack true image labels. Full article