Search Results (21)

The increasing threat of Glacial Lake Outburst Floods (GLOFs), intensified by climate change, underscores the urgency for developing advanced early warning systems. The near-annual, cyclical outbursts of Lake Merzbacher in the Tien Shan mountains present a severe downstream threat, yet its remote location and lack of instrumentation pose a significant challenge to traditional monitoring. To bridge this gap, we develop and validate a dynamic risk assessment framework driven entirely by remote sensing data. Methodologically, the framework introduces an innovative Ice-Water Composite Index (IWCI) to resolve the challenge of lake area extraction under mixed ice-water conditions. This is coupled with a high-fidelity 5 m resolution Digital Elevation Model (DEM) of the lake basin, autonomously generated from GF-7 Dual-Line Camera (DLC) imagery, which enables accurate daily volume retrieval. Through systematic feature engineering, nine key hydro-thermal drivers are quantified from MODIS and other products to train a Random Forest (RF) machine learning model, establishing the non-linear relationship between catchment processes and lake volume. The model demonstrates robust predictive performance on an independent validation set (2023–2024) (R² = 0.80, RMSE = 5.15 × 10⁶ m³), accurately captures the complete lake-filling cycle from initiation to near-peak stage. Furthermore, feature importance analysis quantitatively confirms that Positive Accumulated Temperature (PAT) is the dominant physical mechanism governing the lake’s storage dynamics. This end-to-end framework offers a transferable paradigm for GLOF hazard management, enabling a critical shift from static, regional assessments to dynamic, site-specific early warning in data-scarce alpine regions. Full article

Mountain glaciers are sensitive indicators of climate variability, and their retreat since the end of the Little Ice Age (LIA) has strongly reshaped alpine environments worldwide. In the Greater Caucasus, glacier shrinkage has accelerated over the past century, yet detailed multi-temporal reconstructions remain limited for many glaciers. Here, we reconstruct the post-LIA evolution of Tsaneri–Nageba Glacier, one of largest ice bodies in the Georgian Caucasus, and document the development of its newly formed proglacial lake. Using a combination of geomorphological mapping, historical maps, multi-temporal satellite imagery, Uncrewed Aerial Vehicle (UAV) photogrammetry, and sonar bathymetry, we quantify glacier change from ~1820 to 2025 and provide the first direct measurements of a proglacial lake in the Tsaneri–Nageba system—and indeed in the Georgian Caucasus as a whole. Our results reveal that Tsaneri–Nageba Glacier has shrunk from ~48 km² at its LIA maximum to ~30.6 km² in 2025, a loss of −43.5% (or −0.21% yr⁻¹). The pace of shrinkage intensified after 2000, with the steepest losses recorded between 2014 and 2025. Terminus positions shifted up-valley by nearly 3.9 km (Tsaneri) and 4.3 km (Nageba), accompanied by fragmentation of the former compound valley glacier into smaller ice bodies. Long-term meteorological records confirm strong climatic forcing, with pronounced summer warming since the 1990s and declining winter precipitation. A proglacial lake started to form in mid-summer 2015, which by 03/09/15 had a surface area of ~14,366 m², expanding to ~106,945 m² by 10/07/2025. The lake is in contact with glacier ice and is thus prone to calving. It is dammed by unconsolidated moraines and bounded by steep, active slopes, making it susceptible to generating a glacial lake outburst flood (GLOF). By providing the first quantitative measurements of a proglacial lake in the region, this study establishes a baseline for future monitoring and risk assessment. The findings highlight the urgency of integrating glaciological, geomorphological, and hazard studies to support community safety and water resource planning in the Caucasus. Full article

Glacial lake outburst floods (GLOFs) represent increasingly common and high-magnitude geohazards across the cryosphere of the Tibetan Plateau, particularly under ongoing climate warming and glacier retreat. This study combines multi-temporal remote sensing imagery and detailed Flo-2D hydrodynamic modeling to investigate the erosive dynamics of the 2020 Jinwuco GLOF in Southeastern Tibetan Plateau. Key conclusions include: (1) The 2.35 km-long flood routing channel exhibits pronounced non-uniformity in horizontal curvature, channel width, and cross-sectional shape, significantly influencing flood propagation; five representative cross-sections divide the channel into six distinct segments. (2) Prominent lateral erosion occurred proximally to the dam, attributable to extreme erosive forces and high sediment transport capacity during peak discharge, with horizontal channel curvature further amplifying local impact and erosion. (3) Erosion rates were highest near the dam and in downstream narrow segments, while mid-reach sections with greater width experienced lower erosion. (4) Maximum flow depths reached 28.12 m in topographically confined reaches, whereas peak velocities occurred in upstream and downstream curved sections. (5) The apparent critical erosive shear stress of bank material is controlled not only by soil strength but also by flood dynamics and pre-existing channel morphology, indicating strong feedback between flow dynamics, channel morphology, and critical erosive shear stress of bank material. This study provides a generalized and transferable framework for analyzing GLOF-related erosion in data-scarce high-altitude regions, offering critical insights for hazard assessment, regional planning, and risk mitigation strategies. Full article

With ongoing global warming, glacier lake outburst floods (GLOFs) and associated debris flows pose increasing threats to downstream communities and infrastructure. Glacial lakes differ in their triggering factors and breach mechanisms, necessitating event-specific analysis. This study investigates the GLOF risk of Jiongpuco Lake, located in the southeastern part of the Tibetan Plateau, using an integrated approach combining remote sensing, field surveys, and numerical modeling. Results show that the lake has expanded significantly—from 2.08 km² in 1990 to 5.43 km² in 2021—with the most rapid increase observed between 2015 and 2016. InSAR data and optical imagery indicate that surrounding moraine deposits remain generally stable. However, ice avalanches from the glacier terminus are identified as the primary trigger for lake outburst via wave-induced overtopping. Mechanical and geomorphological analyses suggest that the moraine dam is resistant to downcutting erosion, reinforcing overtopping as the dominant failure mode. To assess potential impacts, three numerical simulation scenarios were conducted based on different avalanche volumes. Under the extreme scenario involving a 5-million m³ ice avalanche, the modeled peak discharge at the dam site reaches approximately 19,000 m³/s. Despite the high flood magnitude, the broad and gently sloped downstream terrain facilitates rapid attenuation of flood peaks, resulting in limited impact on downstream settlements. These findings offer critical insights for GLOF hazard assessment, disaster preparedness, and risk mitigation under a changing climate. Full article

Glacial Lake Outburst Floods (GLOFs) have emerged as a critical threat to high-mountain communities and ecosystems, driven by accelerated glacier retreat and lake expansion under climate change. This review synthesizes advancements in remote sensing technologies and methodologies for GLOF monitoring, risk assessment, and mitigation. Through a Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA)-guided systematic literature review and bibliometric analysis of studies from 2010 to 2025, we evaluate the transformative role of remote sensing in overcoming traditional field-based limitations. Central to this review is the exploration of multi-sensor data fusion for high-resolution lake dynamics mapping, machine learning algorithms for predictive risk modelling, and hydrodynamic simulations for flood propagation analysis. This review underscores the importance of these technologies in improving GLOF risk assessments and supporting early warning systems, which are crucial for safeguarding vulnerable high-mountain communities. It addresses existing challenges, such as data integration and model calibration, and advocates for collaborative efforts between scientists, policymakers, and local stakeholders to translate technological advancements into effective mitigation strategies, ensuring the sustainability of these at-risk regions. Full article

This study assesses the risks of glacial lake outburst floods (GLOFs) from moraine sediment dams around Gurudongmar Lake in the Northern Sikkim Himalayas at an elevation of 17,800 feet. It focuses on three moraine sediment dams, analysing the implications of slope failure on the upstream side and the downstream stability under steady seepage conditions, as well as the risks posed by permafrost thawing. Using a comprehensive methodology that includes geotechnical evaluations, remote sensing, and digital elevation models (DEMs), the research employs finite element analysis via PLAXIS2D for the stability assessment. The main findings indicate a stratification of sediment types: the upper layers are loose silty sand, while the lower layers are dense silty sand, with significant variations in shear strength, permeability, and other geotechnical properties. Observations of solifluctions suggest that current permafrost conditions enhance the dams’ stability and reduce seepage. However, temperature trends show a warming climate, with the average days below 0 °C decreasing from 314 (2004–2013) to 305 (2014–2023), indicating potential permafrost thawing. This thawing could increase seepage and destabilise the dams, raising the risk of GLOFs. Numerical simulations reveal that scenarios involving water level rises of 5 and 10 m could lead to significant deformation and reduced safety factors on both the upstream lateral dams and downstream front dams. The study emphasises the urgent need for ongoing monitoring and risk assessment to address the potential hazards associated with GLOFs. Full article

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 (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

One of the main glacier-related natural hazards that are common to alpine locations is the occurrence of glacial lake outburst floods (GLOFs), which can seriously harm downstream towns and infrastructure. GLOFs have increased in frequency in the central Himalayas in recent years as a result of global warming, and careful management of glacial lakes is a crucial step in catastrophe prevention. In this study, field surveys were conducted on 28 August 2020 and 1 August 2021 with the help of an unmanned aerial vehicle (UAV) and a boat bathymetric system on an unmanned surface vessel (USV), combined with 22 years of Landsat series imagery and Sentinel-2 MSI imagery data. Spatial analysis was then used to investigate changes in lake surface conditions, dam stability, and surrounding topography before and after an integrated project of the Jialong Co lake. The results show that: (1) from 2000 to 2020 (before engineering management), the area of the Jialong Co glacial lake increased from 0.2148 ± 0.0176 km² to 0.5921 ± 0.0003 km². The glacial lake expansion rate from 2000 to 2010 (0.0145 km²/a) was greater than the rate from 2011 to 2020 (6.92 $\times$ 10⁻⁶ km²/a). In 2021 (after engineering treatment), the glacial lake perimeter, area, and volume decreased by 0.6014 km, 0.1136 km², and 1.90 × 10⁷ m³, respectively. The amount of excavation during the project treatment was 8.13 million square meters, and the amount of filling was 1.24 million square meters. According to the results of the unmanned surface vessel (USV), the elevation of the lake surface dropped from 4331 m to 4281 m, and the water level dropped by 50 m (the designed safe water level line dropped by 30 m). (2) The results of the UAV topographic survey and geomorphological analysis showed that the engineered reinforcement of the outlet channel and surrounding dam effectively mitigated severe scouring of the foot of the final moraine at the outlet of the spillway, as well as the likelihood of glacial lake outbursts caused by ice avalanches and landslides. (3) The comprehensive engineering treatment of this typical glacial lake effectively lowered the water level and improved the stability of the moraine ridge and lake dam, providing a scientific foundation for other glacial lake outburst risk assessments and disaster mitigation and management measures. Thus, it is critical to evaluate the impact of comprehensive engineering management of key glacial lakes to support glacial lake management. Full article

Climate warming-induced glacier recession has resulted in the development and rapid expansion of glacial lakes in the Himalayan region. The increased melting has enhanced the susceptibility for Glacial Lake Outburst Floods (GLOFs) in the region. The catastrophic failure of potentially dangerous glacial lakes could be detrimental to human life and infrastructure in the adjacent low-lying areas. This study attempts to assess the GLOF hazard of Gangabal lake, located in the Upper Jhelum basin of Kashmir Himalaya, using the combined approaches of remote sensing, GIS, and dam break modeling. The parameters, such as area change, ice thickness, mass balance, and surface velocity of the Harmukh glacier, which feeds Gangabal lake, were also assessed using multitemporal satellite data, GlabTop-2, and the Cosi–Corr model. In the worst-case scenario, 100% volume (73 × 10⁶ m³) of water was considered to be released from the lake with a breach formation time (bf) of 40 min, breach width (bw) of 60 m, and producing peak discharge of 16,601.03 m³/s. Our results reveal that the lake area has increased from 1.42 km² in 1972 to 1.46 km² in 1981, 1.58 km² in 1992, 1.61 km² in 2001, 1.64 km² in 2010, and 1.66 km² in 2020. The lake area experienced 17 ± 2% growth from 1972 to 2020 at an annual rate of 0.005 km². The feeding glacier (Harmukh) contrarily indicated a significant area loss of 0.7 ± 0.03 km² from 1990 (3.36 km²) to 2020 (2.9 km²). The glacier has a maximum, minimum, and average depth of 85, 7.3, and 23.46 m, respectively. In contrast, the average velocity was estimated to be 3.2 m/yr with a maximum of 7 m/yr. The results obtained from DEM differencing show an average ice thickness loss of 11.04 ± 4.8 m for Harmukh glacier at the rate of 0.92 ± 0.40 m/yr between 2000 and 2012. Assessment of GLOF propagation in the worst-case scenario (scenario-1) revealed that the maximum flood depth varies between 3.87 and 68 m, the maximum flow velocity between 4 and 75 m/s, and the maximum water surface elevation varies between 1548 and 3536 m. The resultant flood wave in the worst-case scenario will reach the nearest location (Naranaag temple) within 90 min after breach initiation with a maximum discharge of 12,896.52 m³ s⁻¹ and maximum flood depth and velocity of 10.54 m and 10.05 m/s, respectively. After evaluation of GLOF impacts on surrounding areas, the area under each inundated landuse class was estimated through the LULC map generated for both scenarios 1 and 2. In scenario 1, the total potentially inundated area was estimated as 5.3 km², which is somewhat larger than 3.46 km² in scenario 2. We suggest a location-specific comprehensive investigation of Gangbal lake and Harmukh glacier by applying the advanced hazard and risk assessment models/methods for better predicting a probable future GLOF event. Full article

The frequency of glacier lake outbursts floods (GLOFs) is likely to increase with the ongoing glacier retreat, which produces new glacial lakes and enlarges existing ones. Here, we simulate the outburst of a potentially dangerous glacial lake in Bhutan by applying hydrodynamic modelling. Although the lake volume is known, several parameters connected to the dam breach and the routing of the flood are rough estimates or assumptions, which introduce uncertainties in the results. For this reason, we create an ensemble of nine outburst scenarios. The simulation of magnitude and timing of possible inundation depths is an important asset to prepare emergency action plans. For our case study in the Mo Chu River Basin, the results show that, even under the worst case scenario, little damage to residential buildings can be expected. However, such an outburst flood would probably destroy infrastructure and farmland and might even affect the operation of a hydroelectric powerplant more than 120 km downstream the lake. Our simulation efforts revealed that, by using a 30-m elevation model instead of a 5-m raster, flood magnitude and inundation areas are overestimated significantly, which highly suggests the use of high-resolution terrain data. These results may be a valuable input for risk mitigation efforts. Full article

Glacial lake outburst flood (GLOF) is one of the major natural disasters in the Qinghai-Tibetan Plateau (QTP). On 25 June 2020, the outburst of the Jiwenco Glacial Lake (JGL) in the upper reaches of Nidu river in Jiari County of the QTP reached the downstream Niwu Township on 26 June, causing damage to many bridges, roads, houses, and other infrastructure, and disrupting telecommunications for several days. Based on radar and optical image data, the evolution of the JGL before and after the outburst was analyzed. The results showed that the area and storage capacity of the JGL were 0.58 square kilometers and 0.071 cubic kilometers, respectively, before the outburst (29 May), and only 0.26 square kilometers and 0.017 cubic kilometers remained after the outburst (27 July). The outburst reservoir capacity was as high as 5.4 million cubic meters. The main cause of the JGL outburst was the heavy precipitation process before outburst and the ice/snow/landslides entering the lake was the direct inducement. The outburst flood/debris flow disaster also led to many sections of the river and buildings in Niwu Township at high risk. Therefore, it is urgent to pay more attention to glacial lake outburst floods and other low-probability disasters, and early real-time engineering measures should be taken to minimize their potential impacts. Full article