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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Debris content plays an important role in controlling erosion capacity and sedimentation characteristics during outburst floods. Numerical models should incorporate sediments in hazard analyses to obtain more accurate assessments of outburst flood magnitudes and downstream behaviors. In this paper, we propose a novel water–sediment mixture flow model to reconstruct the ancient outburst floods at Xuelongnang and demonstrate the performance of this model through comparisons with field evidence. The simulated outburst flood reaches a maximum breach discharge of 10,697.35 m3/s and a peak sediment discharge of 65.29 m3/s, traveling downstream for 87 km within 5.43 h. Based on simulations of riverbed changes, inundation depth, velocity, shear stress, and Froude number, our findings suggest that topographic controls influence hydraulic patterns, which subsequently affect erosional and depositional processes and contribute to landscape evolution. During the downstream propagation of the outburst flood in narrowed valley sections, simulated sediment-simulated deposition occurs downstream while erosion occurs upstream, coinciding with the maximum inundation depths attributed to hydraulic jump phenomena. We also discuss the formation processes of the outburst deposits, identifying areas of greatest channel aggradation. Calculated bed shear stress suggests that sediment transport by the flood deposits on the riverbed decreases as the flood stage wanes, forming the rhythmite-interbedded structures observed in field investigations. This work provides a viable and promising approach to understanding hydro-sediment-morphodynamic processes in flood pathways and the erosional and depositional features left by outburst floods, supporting modern outburst flood hazard prevention and mitigation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Modelling glacial lake outburst floods (GLOFs) or 'jökulhlaups', necessarily involves the propagation of large and often stochastic uncertainties throughout the source to impact process chain. Since flood routing is primarily a function of underlying topography, communication of digital elevation model (DEM) uncertainty should accompany such modelling efforts. Here, a new stochastic first-pass assessment technique was evaluated against an existing GIS-based model and an existing 1D hydrodynamic model, using three DEMs with different spatial resolution. The analysis revealed the effect of DEM uncertainty and model choice on several flood parameters and on the prediction of socio-economic impacts. Our new model, which we call MC-LCP (Monte Carlo Least Cost Path) and which is distributed in the supplementary information, demonstrated enhanced 'stability' when compared to the two existing methods, and this 'stability' was independent of DEM choice. The MC-LCP model outputs an uncertainty continuum within its extent, from which relative socio-economic risk can be evaluated. In a comparison of all DEM and model combinations, the Shuttle Radar Topography Mission (SRTM) DEM exhibited fewer artefacts compared to those with the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM), and were comparable to those with a finer resolution Advanced Land Observing Satellite Panchromatic Remote-sensing Instrument for Stereo Mapping (ALOS PRISM) derived DEM. Overall, we contend that the variability we find between flood routing model results suggests that consideration of DEM uncertainty and pre-processing methods is important when assessing flow routing and when evaluating potential socio-economic implications of a GLOF event. Incorporation of a stochastic variable provides an illustration of uncertainty that is important when modelling and communicating assessments of an inherently complex process. [ABSTRACT FROM AUTHOR]

A well-known landslide dam that collapsed and generated a large outburst flood is used to show the importance of forensic geology analysis, which is the on-site multidisciplinary study of geohazards carries out as soon as possible after their occurrence; this study is focused on understanding the complete spectrum of all mechanisms that caused the disaster. Diagnostic elements of all natural processes fade with time, allowing for progressively divergent interpretations that may impact the appropriateness of potential mitigation actions, as we demonstrate. The multidisciplinary field control of the abrupt rupture of a natural dam on the Santa Cruz River on 12 November 2005, that released c. 37 million m3 of water and sediment, can radically change the interpretation of how this dam collapsed. In situ sedimentological, geomorphological and topographical analyses of the remains of the collapsed natural dam suggest it was built in two mass-wasting episodes instead of one, as previously interpreted, involving different slide materials. The first episode matches previous interpretations; a landslide that evolved into a rock avalanche, generating an initial dam of high stability due to its density, and observed angles of repose. This dam was not removed completely during the rupture, but rather suffered minor erosion at its top by the flood drag effect. The second episode is interpreted as a snow-dominated mixed avalanche, reaching much greater heights on the opposite side of the valley. This avalanche is estimated to be 85% snow, 8% debris and 7% ice-cemented permafrost fragments, and is evidenced by a thin residual deposit draping the valley sides, as most of this deposit melted out before any field control was undertaken. The growth of the lake level, along with the dam weight loss due to ablation, generated the hydrostatic instability that caused the floating of the central sector of this second dam and the violent evacuation of the water, similar to a jökulhlaup. This analysis explains the partial dam collapse, sudden water release and the preserved field evidence. This different interpretation suggests that the mitigation actions already taken can be improved and that monitoring systems are urgently needed. A rapid and professional assessment of any large-scale geohazard site would be the way to avoid interpretation discrepancies, and to guarantee that mitigation actions taken are adequate. Learning from this event may help decision makers to take better mitigation measures and potentially save lives. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent years, the intensified influences of global climate change and human activities have increased the frequency of large-scale debris flow disasters. As a result, main river channels often become blocked, thus forming a disaster chain of rivers dammed by debris flow followed by outburst flooding. In order to quickly and easily reveal the dynamic process of a debris flow dam breach, and quantitatively predict the outburst flood hazard, this study takes the Zhouqu "8.8" debris flow barrier dam in Western China as an example. Based on a stability assessment, China Institute of Water Resources and Hydropower Research's Dam Breach Slope (DBS-IWHR), China Institute of Water Resources and Hydropower Research's Dam Breach (DB-IWHR), and Hydrologic Engineering Center's River Analysis System (HEC-RAS) were integrated to simulate the development of dam breach, breach flood, and outburst flood evolution, respectively, under different scenarios. The simulated peak discharge flow of the actual spillway was 317.15 m3/s, which was consistent with the actual discharge of 316 m3/s. The results under different scenarios showed that, with the increased inflow of the barrier lake, the erosion rate of the dam increased, the peak discharge of the dam break flood increased, the peak arrival time shortened, and the downstream flooding area increased. These findings could provide scientific support for risk management and emergency decision-making with respect to barrier dam failure. [ABSTRACT FROM AUTHOR]

When utilizing a finite volume method to predict outburst flood evolution in real geometry, the processing of wet-dry front and dry cells is an important step. In this paper, we propose a new approach to process wet-dry front and dry cells, including four steps: (1) estimating intercell properties; (2) modifying interface elevation; (3) calculating dry cell elevations by averaging intercell elevations; and (4) changing the value of the first term of slope limiter based on geometry in dry cells. The Harten, Lax, and van Leer with the contact wave restored (HLLC) scheme was implemented to calculate the flux. By combining the MUSCL (Monotone Upstream–centred Scheme for Conservation Laws)-Hancock method with the minmod slope limiter, we achieved second-order accuracy in space and time. This approach is able to keep the conservation property (C-property) and the mass conservation of complex bed geometry. The results of numerical tests in this study are consistent with experimental data, which verifies the effectiveness of the new approach. This method could be applied to acquire wetting and drying processes during flood evolution on structured meshes. Furthermore, a new settlement introduces few modification steps, so it could be easily applied to matrix calculations. The new method proposed in this study can facilitate the simulation of flood routing in real terrain. [ABSTRACT FROM AUTHOR]

Climate change has led to the formation of numerous high-altitude lakes of glacial origin in the Himalaya. Safed Lake is one of the largest glacial lakes, located at an elevation 4882 m a.s.l. in the state of Uttarakhand, central Himalaya, India. A temporal analysis of the lake surface using satellite imagery shows that the lake has grown more than double its size from 0.10 km2 to 0.23 km2 over the past 50 years. In this study, we performed a hazard assessment of the lake using 1D and 2D hydrodynamic modeling. We identified the potential glacial lake outburst flood (GLOF) triggering factors and evaluated the impact of a moraine breach event of the lake on the nearest village located 16.2 km downstream of the lake. A series of dynamic simulations were performed for different scenario-models based on varied breach depths, breach widths and time of moraine failure. In a worst-case GLOF scenario where breach depth reached up to 60 m, hydrodynamic routing of the breach hydrograph along the given channel revealed inundation depth up to 5 m and flow velocities up to 3.2 m s−1 at Milam village. Considering the flat geometry of the frontal moraine, hazard assessment of the lake was performed by for different breach incision depths (30 and 15 m). In addition, the study incorporated a series of hydrodynamic routing to understand the sensitivity of GLOF to different model input parameters and terrain conditions. The sensitivity of the initial GLOF hydrograph to breach formation time (Tf) was evaluated by considering different hypothetical breach scenarios with a varied time of failure. Increases of 11.5% and 22% in the peak flooding were recorded when the moraine failure time was decreased by 15 and 30 min respectively. The two-dimensional sensitivity revealed flow velocity (m s−1) to be more sensitive to change in Manning's N when compared to the inundation depth (m). Changes of 10.7% and 0.5% in the mean flow velocity (in m s−1) and flow depth (in m) were recorded when dN was 0.01. The flow velocity was more sensitive to the slope and the top-width of the channel when compared to the inundation depths. A regression of flow velocity versus slope gives a correlation coefficient of 0.76. GLOF flow hydraulics are sensitive to changes in terrain elevation, where flow depth and velocity vary in a similar manner. [ABSTRACT FROM AUTHOR]

Glacial lake outburst floods (GLOF) evolve into debris flows by erosion and sediment entrainment while propagating down a valley, which highly increases peak discharge and volume and causes destructive damage downstream. This study focuses on GLOF hazard assessment in the Bhote Koshi Basin (BKB), where was highly developed glacial lakes and was intensely affected by the Gorkha earthquake. A new 2016 glacial lake inventory was established, and six unreported GLOF events were identified with geomorphic outburst evidence from GaoFen-1 satellite images and Google Earth. A new method was proposed to assess GLOF hazard, in which large numbers of landslides triggered by earthquake were considered to enter into outburst floods enlarge the discharge and volume of debris flow in the downstream. Four GLOF hazard classes were derived according to glacial lake outburst potential and a flow magnitude assessment matrix, in which 11 glacial lakes were identified to have very high hazard and 24 to have high hazard. The GLOF hazard in BKB increased after the earthquake due to landslide deposits, which increased by 216.03 × 106 m3, and provides abundant deposits for outburst floods to evolve into debris flows. We suggest that in regional GLOF hazard assessment, small glacial lakes should not be overlooked for landslide deposit entrainment along a flood route that would increase the peak discharge, especially in earthquake-affected areas where large numbers of landslides were triggered. [ABSTRACT FROM AUTHOR]

Natural dams are formed most often in narrow, steep valleys in high mountains. The outburst floods triggered by natural dam failures result in the topography and landforms successively being altered. Boulder bars are common natural structures that are selected here to quantitatively evaluate the impact of outburst floods on the topographical and landform variations in downstream channels. In this study, we selected the Sedongpu natural dam on the Yarlung Tsangpo River formed as a result of a landslide in 2018 as an example, and studied the geomorphological changes in a river reach located 173 km downstream of the Sedongpu natural dam. The sizes and shapes of the boulder bars in this area were statistically analyzed. The results show that there are three shape types of boulder bars in this area, i.e., sickle, bamboo leaf and oval. Furthermore, it found that the relationship between the lengths and widths of boulder bars is similar before and after outburst floods, as is the relationship between perimeters and lengths of boulder bars, which means these relationships are not affected by outburst floods. And the perimeters of boulder bars are almost twice their lengths. In addition, the relationship between the areas and lengths of boulder bars follows a power function. The most important finding is that the riverine morphological features conserved self-similarity due the influence of the outburst flood erosion triggered by a natural dam failure. This finding adds to the previous observations since dam failures introduce sudden and dominating impacts on river systems. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

As a result of climate change, the frequency of glacial lake outburst floods (GLOF) is increasing in Chilean Patagonia. Yet, the impacts of the flood events on the physics and biology of fjords is still unknown. Current velocities, density, in-situ zooplankton samples, and volume backscatter (Sv) derived from an acoustic profiler were used to explore the response of circulation and zooplankton abundance in a Patagonian fjord to GLOF events in 2010 and 2014. Maximum Sv was found both during the GLOFs and in late winter to early spring of 2010 and the fall and summer of 2014. The increase in Sv in late winter and spring of 2010 corresponded to multiple zooplankton species found from in-situ net sampling. In addition, diel vertical migrations were found during this seasonal increase both qualitatively and in a spectral analysis. Concurrently with zooplankton increases, wind forcing produced a deepening of the pycnocline. Zooplankton abundance peaked in the fjord when the pycnocline depth deepened due to wind forcing and throughout the entire spring season, indicating that mixing conditions could favor secondary production. These results were corroborated by the 2014 data, which indicate that weather events in the region impact both fjord physics and ecology. [ABSTRACT FROM AUTHOR]

The retreat of mountain glaciers inevitably leads to an increase in the number of outburst moraine lakes. One of the possible mechanisms of moraine dam outburst along with overflow over the crest is the formation of a filtration channel in the body of the moraine dam (piping). An algorithm for calculating the outburst flood hydrograph, describing the development of a filtration channel in the body of a moraine dam and the subsequent formation of water overflow when the soil above the channel collapses, is proposed in this paper. Verification of proposed methodology was carried out on the basis of experimental data and published data of real outbursts. Satisfactory results verifying this methodology made it possible to use the proposed methodology for the calculation of the hydrograph of the outburst of Lake Bashkara in the Elbrus region, which occurred on 1 September 2017. It is shown that the simulation results are quantitatively comparable with the estimates obtained from field data: the time of water discharge through the channel was 16 min, the period of the outburst wave passage was 40 min, and the maximum discharge was 636 m3/s. Thus, the possibility of applying the proposed methodology for calculating the destruction of natural moraine dams has been demonstrated. [ABSTRACT FROM AUTHOR]

Landslides are usually caused by rainstorms and geological processes such as earthquakes and may have a massive impact on human production and life. The hazard chain of landslide–river blockage–outburst flood is the most common hazard chain caused by landslides. A database based on existing landslide cases was established in this study to investigate the assessment formulas of the risk of river blockage, dam stability, and peak flood discharge after a dam has broken. A risk assessment model of the landslide–river blockage–breaching hazard chain was established, including the downstream vulnerability. The case of the Baige landslide verified the applicability of the model. This model can be used in a landslide-prone area to predict whether a relatively massive river blockage will form after the landslide occurs, whether the landslide dam formed by the river blockage will breach in a short time, and the impact of the outburst flood on the downstream area. [ABSTRACT FROM AUTHOR]

Remote sensing plays an increasingly important role in the investigation of natural hazards, not only by obtaining specific data related to hazards, but also by realizing targeted research by combining with other data and/or technologies. Small-scale landslide hazard chain events occur frequently in mountainous areas with fragile geological environments and have strong destructive effects, yet have been somewhat understudied. This paper analyzes the Zhoujiaba (ZJB) landslide hazard chain that occurred in Longnan City on 18 August 2020. On the basis of the comprehensive application of multi-source remote sensing data, combined with time-series InSAR technology, electrical resistivity tomography (ERT), and numerical simulations, we studied the formation mechanism, damming characteristics, and potential outburst scenarios of this event. Our research suggests that geological structure and strong natural weathering are the preconditions for landslide development, which is eventually induced by extreme rainfall. Specific topographic conditions determine the rapid sliding and accumulation of landslide materials, and ultimately result in river damming. Our simulation results showed that a flood, rather than a debris flow, will be the result of dam outburst. When the simulated upstream inflow is 1.5 times that when the landslide occurred, 68% of the downstream village area will be flooded. The artificial spillway can effectively reduce the scale of the potential outburst flood, but there remains a risk of dam failure owing to the shallow depth. Our study of the hazard chain of a small-scale landslide using a combination of methods will provide a valuable reference for the analysis and treatment of similar hazard chains. [ABSTRACT FROM AUTHOR]

We use 124 scenes of TerraSAR-X data that were acquired in 2009 and 2010 to analyse the spatial and temporal variability in surface kinematics of the debris-covered Inylchek Glacier, located in the Tien Shan mountain range in Central Asia. By applying the feature tracking method to the intensity information of the radar data and combining the results from the ascending and descending orbits, we derive the surface velocity field of the glaciated area. Analysing the seasonal variations over the upper part of the Southern Inylchek branch, we find a temperature-related increase in velocity from 25 cm/d up to 50 cm/d between spring and summer, with the peak occurring in June. Another prominent velocity peak is observable one month later in the lower part of the Southern Inylchek branch. This area shows generally little motion, with values of approximately 5-10 cm/d over the year, but yields surface kinematics of up to 25 cm/d during the peak period. Comparisons of the dates of annual glacial lake outburst floods (GLOFs) of the proglacial Lake Merzbacher suggest that this lower part is directly influenced by the drainage, leading to the observed mini-surge, which has over twice the normal displacement rate. With regard to the GLOF and the related response of Inylchek Glacier, we conclude that X-band radar systems such as TerraSAR-X have a high potential for detecting and characterising small-scale glacial surface kinematic variations and should be considered for future inter-annual glacial monitoring tasks. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In recent decades, climate change has led to global warming, glacier melting, glacial lake outbursts, sea level rising, and more extreme weather, and has seriously affected human life. Remote sensing technology has advanced quickly, and it offers effective observation techniques for studying and monitoring glaciers. In order to clarify the stage of research development, research hotspots, research frontiers, and limitations and challenges in glacier mass balance based on remote sensing technology, we used the tools of bibliometrics and data visualization to analyze 4817 works of literature related to glacier mass balance based on remote sensing technology from 1990 to 2021 in the Web of Science database. The results showed that (1) China and the United States are the major countries in the study of glacier mass balance based on remote sensing technology. (2) The Chinese Academy of Sciences is the most productive research institution. (3) Current research hotspots focus on "Climate change", "Inventory", "Dynamics", "Model", "Retreat", "Glacier mass balance", "Sea level", "Radar", "Volume change", "Surface velocity", "Glacier mapping", "Hazard", and other keywords. (4) The current research frontiers include water storage change, artificial intelligence, High Mountain Asia (HMA), photogrammetry, debris cover, geodetic method, area change, glacier volume, classification, satellite gravimetry, grounding line retreat, risk assessment, lake outburst flood, glacier elevation change, digital elevation model, geodetic mass balance, (DEM) generation, etc. According to the results of the visual analysis of the literature, we introduced the three commonly used methods of glacier mass balance based on remote sensing observation and summarized the research status and shortcomings of different methods in glacier mass balance. We considered that the future research trend is to improve the spatial and temporal resolution of data and combine a variety of methods and data to achieve high precision and long-term monitoring of glacier mass changes and improve the consistency of results. This research summarizes the study of glacier mass balance using remote sensing, which will provide valuable information for future research across this field. [ABSTRACT FROM AUTHOR]

Debris-covered glaciers have contrasting melting mechanisms and climate response patterns if compared with debris-free glaciers and thus show a unique influence on the hydrological process. Based on high-resolution satellite images and unpiloted aerial vehicle surveys, this study investigated the dynamic changes of Zhuxi Glacier, a thick debris-covered glacier in the southeastern Tibetan Plateau. Our result shows that the whole glacier can be divided into the active regime and stagnant regime along the elevation of 3400 m a.s.l. The mean surface velocity of the active regime was 13.1 m yr−1, which was five times higher than that of the stagnant regime. The surface-lowing rate of this debris-covered glacier reaches more than 1 m yr−1 and displays an accelerating trend. The majority of ice loss concentrates around ice cliffs and supraglacial ponds, the ablation hotspots. These hotspots can be roughly classified into three types, including persistent, expanding, and shrinking patterns, at different dynamic regimes on the Zhuxi Glacier. With the evolution of these hotpots and glacier dynamic changes, the supraglacial ponds showed significant change, with the total number fluctuating from 15 to 38 and the total area increasing from 1128 m2 to 95790 m2 during the past decade. The recent exponential expansion of the proglacial lake and the significant downwasting of stagnant ice inside the dammed terminus moraine possibly trigger the glacial lake outburst flood and thus threaten the security of livelihoods and infrastructure downstream. [ABSTRACT FROM AUTHOR]

Glacial lakes are a sensitive indicator of regional climate change and one of the initiators of glacier disasters. It is of great significance to understand the spatial distribution and change characteristics of glacial lakes for exploring their response patterns to climate change and assessing the glacial lake outburst flood (GLOF) susceptibility. Based on Gaofen-1/6 PMS, Sentinel-2A/2B MSI and Landsat TM/ETM+/OLI images from 2000 to 2020, we integrated geographic information technology and mathematical and statistical methods to analyze the spatial and temporal distribution of glacial lakes in Nepal and their dynamic changes, and further discriminated and evaluated the GLOF susceptibility of glacial lakes. The results show that there were 2420 glacial lakes in Nepal in 2020, mainly distributed within the 4500~5500 m, with an area of 87.21 km2 and a water storage of 1921.72 × 106 m3. The number and area of glacial lakes with each area above 0.01 km2 in Nepal showed an increasing trend from 2000 to 2020, while 499 new glacial lakes were born, 139 lakes disappeared, the area and water storage increased by 19.46 km2, 403.07 × 106 m3, respectively. Glacial lakes at altitudes <3000 m were relatively stable, while the number and area of glacial lakes at altitudes within 4500~5500 m increased rapidly. We assessed the GLOF susceptibility of 40 moraine-dammed glacial lakes with an area above 0.2 km2 in Nepal, and found that there were 8, 12, 14 and 6 glacial lakes with low, medium, high and very high susceptibility, respectively. Among glacial lakes with very high GLOF susceptibility, potential GLOF events of Tsho Rolpa glacial lake, Lower Barun glacial lake and glacial lake with code of GL87091E27797N will cause great harm to downstream regions. GLOFs in Nepal will be in an active status in the future, therefore, the dynamics of glacial lakes and their surroundings should be continuously monitored. [ABSTRACT FROM AUTHOR]

We calibrate the k- ω S S T turbulence model for free surface flows in the channel or on the slope using machine learning techniques. To calibrate the turbulence model, an experiment is carried out in an inclined rectangular research chute. In the experiment, the pressure values in the flow are measured at different distances from the bottom; after transforming data, the flow velocity profile is obtained. The k- ω S S T turbulence model is calibrated based on experimental data using the Nelder-Mead optimization algorithm. The calibrated turbulence model is then used to calculate the glacial lake Maliy Azau outburst flood on the Elbrus (Central Caucasus). [ABSTRACT FROM AUTHOR]

Glacial lakes in the Nepal Himalaya can threaten downstream communities and have large socio-economic consequences if an outburst flood occurs. This study identified 131 glacial lakes in Nepal in 2015 that are greater than 0.1 km2 and performed a first-pass hazard and risk assessment for each lake. The hazard assessment included mass entering the lake, the moraine stability, and how lake expansion will alter the lake's hazard in the next 15-30 years. A geometric flood model was used to quantify potential hydropower systems, buildings, agricultural land, and bridges that could be affected by a glacial lake outburst flood. The hazard and downstream impacts were combined to classify the risk associated with each lake. 11 lakes were classified as very high risk and 31 as high risk. The potential flood volume was also estimated and used to prioritize the glacial lakes that are the highest risk, which included Phoksundo Tal, Tsho Rolpa, Chamlang North Tsho, Chamlang South Tsho, and Lumding Tsho. These results are intended to assist stakeholders and decision makers in making well-informed decisions with respect to the glacial lakes that should be the focus of future field studies, modeling efforts, and risk-mitigation actions. [ABSTRACT FROM AUTHOR]

Outburst floods resulting from giant landslide dams can cause devastating damage to hundreds or thousands of kilometres of a river. Accurate and timely delineation of flood inundated areas is essential for disaster assessment and mitigation. There have been significant advances in flood mapping using remote sensing images in recent years, but little attention has been devoted to outburst flood mapping. The short-duration nature of these events and observation constraints from cloud cover have significantly challenged outburst flood mapping. This study used the outburst flood of the Baige landslide dam on the Jinsha River on 3 November 2018 as an example to propose a new flood mapping method that combines optical images from Sentinel-2, synthetic aperture radar (SAR) images from Sentinel-1 and a Digital Elevation Model (DEM). First, in the cloud-free region, a comparison of four spectral indexes calculated from time series of Sentinel-2 images indicated that the normalized difference vegetation index (NDVI) with the threshold of 0.15 provided the best separation flooded area. Subsequently, in the cloud-covered region, an analysis of dual-polarization RGB false color composites images and backscattering coefficient differences of Sentinel-1 SAR data were found an apparent response to ground roughness's changes caused by the flood. We carried out the flood range prediction model based on the random forest algorithm. Training samples consisted of 13 feature vectors obtained from the Hue-Saturation-Value color space, backscattering coefficient differences/ratio, DEM data, and a label set from the flood range prepared from Sentinel-2 images. Finally, a field investigation and confusion matrix tested the prediction accuracy of the end-of-flood map. The overall accuracy and Kappa coefficient were 92.3%, 0.89 respectively. The full extent of the outburst floods was successfully obtained within five days of its occurrence. The multi-source data merging framework and the massive sample preparation method with SAR images proposed in this paper, provide a practical demonstration for similar machine learning applications using remote sensing. [ABSTRACT FROM AUTHOR]

The Karakoram mountain range is prone to natural disasters such as glacial surging and glacial lake outburst flood (GLOF) events. In this study, we aimed to document and reconstruct the sequence of events caused by glacial debris flows that dammed the Immit River in the Hindu Kush Karakoram Range on 17 July 2018. We used satellite remote sensing and field data to conduct the analyses. The order of the events in the disaster chain were determined as follows: glacial meltwater from the G2 glacier (ID: G074052E36491N) transported ice and debris that dammed the meltwater at the snout of the G1 glacier (ID: G074103E36480N), then the debris flow dammed the Immit River and caused Lake Badswat to expand. We surveyed the extent of these events using remote sensing imagery. We analyzed the glaciers' responses to this event chain and found that the glacial debris flow induced G1 to exhibit accelerating ice flow in parts of the region from 25 July 2018 to 4 August 2018. According to the records from reanalysis data and data from the automatic weather station located 75 km from Lake Badswat, the occurrence of this disaster chain was related to high temperatures recorded after 15 July 2018. The chains of events caused by glacially related disasters makes such hazards more complex and dangerous. Therefore, this study is useful not only for understanding the formation of glacial disaster chains, but also for framing mitigation plans to reduce the risks for vulnerable downstream/upstream residents. [ABSTRACT FROM AUTHOR]

Glacial lakes mapping using satellite remote sensing data are important for studying the effects of climate change as well as for the mitigation and risk assessment of a Glacial Lake Outburst Flood (GLOF). The 3U cubesat constellation of Planet Labs offers the capability of imaging the whole Earth landmass everyday at 3–4 m spatial resolution. The higher spatial, as well as temporal resolution of PlanetScope imagery in comparison with Landsat-8 and Sentinel-2, makes it a valuable data source for monitoring the glacial lakes. Therefore, this paper explores the potential of the PlanetScope imagery for glacial lakes mapping with a focus on the Hindu Kush, Karakoram and Himalaya (HKKH) region. Though the revisit time of the PlanetScope imagery is short, courtesy of 130+ small satellites, this imagery contains only four bands and the imaging sensors in these small satellites exhibit varying spectral responses as well as lower dynamic range. Furthermore, the presence of cast shadows in the mountainous regions and varying spectral signature of the water pixels due to differences in composition, turbidity and depth makes it challenging to automatically and reliably extract surface water in PlanetScope imagery. Keeping in view these challenges, this work uses state of the art deep learning models for pixel-wise classification of PlanetScope imagery into the water and background pixels and compares the results with Random Forest and Support Vector Machine classifiers. The deep learning model is based on the popular U-Net architecture. We evaluate U-Net architecture similar to the original U-Net as well as a U-Net with a pre-trained EfficientNet backbone. In order to train the deep neural network, ground truth data are generated by manual digitization of the surface water in PlanetScope imagery with the aid of Very High Resolution Satellite (VHRS) imagery. The created dataset consists of more than 5000 water bodies having an area of approx. 71 km 2 in eight different sites in the HKKH region. The evaluation of the test data show that the U-Net with EfficientNet backbone achieved the highest F1 Score of 0.936. A visual comparison with the existing glacial lake inventories is then performed over the Baltoro glacier in the Karakoram range. The results show that the deep learning model detected significantly more lakes than the existing inventories, which have been derived from Landsat OLI imagery. The trained model is further evaluated on the time series PlanetScope imagery of two glacial lakes, which have resulted in an outburst flood. The output of the U-Net is also compared with the GLakeMap data. The results show that the higher spatial and temporal resolution of PlanetScope imagery is a significant advantage in the context of glacial lakes mapping and monitoring. [ABSTRACT FROM AUTHOR]

The outburst flood of the Baige landslide dam caused tremendous damage to infrastructure, unfinished hydraulic buildings, roads, and bridges that were built or under construction along the Jinsha River. Can downstream hydraulic buildings, such as high dams with flood control and discharge function, accommodate outburst floods or generate more serious losses due to wave overtopping? In this study, the unsteady flow of a one-dimensional hydraulic calculation was used to simulate natural flood discharge. Assuming a high dam (Yebatan arch dam) is constructed downstream, the flood processes were carried out in two forms of high dam interception (complete interception, comprehensive flood control of blocking and draining). Moreover, three-dimensional visualization of the inundation area was performed. Simulation results indicate that the Yebatan Hydropower Station can completely eliminate the outburst flood risk even under the most dangerous situations. This station can reduce the flood peak and delay the peak flood arrival time. Specifically, the flood peak decreased more obviously when it was closer to the upstream area, and the flood peak arrival time was more delayed when the flood spread further downstream. In addition, the downstream water depth was reduced by approximately 10 m, and the inundation area was reduced to half of the natural discharge. This phenomenon shows that hydraulic buildings such as high dams can reduce the inundation area of downstream farmlands and extend the evacuation time for downstream residents during the flood process, thus reducing the loss of life and property. [ABSTRACT FROM AUTHOR]

On 17 June 2020, a large ancient landslide over the Aniangzhai (ANZ) slope, Danba County, Sichuan Province, China, was reactivated by a series of multiple phenomena, including debris flow triggered by heavy rainfall and flooding. In this study, Synthetic Aperture Radar (SAR) images acquired by the Sentinel-1A/B satellite and optical images captured by the PlanetScope satellites were jointly used to analyze and explore the deformation characteristics and the Spatial-Temporal evolution of the ANZ landslide before and after the multi-hazard chain. Several areas of pre-failure movements were found from the multi-temporal optical images analysis before the reactivation of the ANZ landslide. The large post-failure surface deformation over the ANZ slope was also retrieved by the optical pixel offset tracking (POT) technique. A major northwest movement with the maximum horizontal deformation of up to 14.4 m was found. A time-series InSAR technique was applied to analyze the descending and ascending Sentinel-1A/B datasets spanning from March 2018 to July 2020, showing that the maximum magnitudes of the Line of Sight (LoS) displacement velocities were −70 mm/year and 45 mm/year, respectively. The Spatial-Temporal evolution over the ANZ landslide was analyzed based on the time-series results. No obvious change in acceleration (precursory deformation) was detected before the multi-hazard chain, while clear accelerated deformation can be observed over the slope after the event. This suggested that heavy rainfall was the most significant triggering factor for the generation and reactivation of the ANZ landslide. Other preparatory factors, including the deformation behavior, the undercutting and erosion of the river and the outburst flood, the local terrain conditions, and earthquakes, might also have played an important role in the generation and reactivation of the landslide. [ABSTRACT FROM AUTHOR]

Gendered vulnerability from women's point of view has gained popularity in disaster studies in recent decades especially in the Global South. The positioning of women in society during normal times gives rise to vulnerabilities that are revealed when a disaster strikes. These vulnerabilities are often deep-rooted in societal makeup, cultural and traditional norms, and the economic fabric of society. In the context of Pakistan, the role of women in disaster risk reduction programs is still an under-researched area. In this paper, the gendered vulnerability progression in one of the mountain rural communities of Hassanabad in Hunza Valley (Northern Pakistan) is analyzed post-Shishper glacier lake outburst flood (GLOF) in 2019 and 2020. The study uses empirical qualitative data. Semi-structured interviews were conducted with men and women of different age groups within Hassanabad village. A thematic gendered analysis unveiled several interlinked social, economic, and institutional vulnerabilities. The gendered transitional phase of Hassanabad society positively indicates women's involvement in different spheres of life, including disaster management and mitigation. However, the lack of gender consideration on a formal institutional level exacerbates the gendered vulnerabilities in Hassanabad village. The case study of Hassanabad demonstrated that women not only have an awareness of hazards but are also willing to participate proactively in disaster mitigation activities. Therefore, to reduce community vulnerability and yield long-term positive outcomes of disaster management and mitigation strategies, women must be involved at the formal institutional levels. [ABSTRACT FROM AUTHOR]

A glacial lake outburst flood (GLOF) is a typical glacier-related hazard in high mountain regions. In recent decades, glacial lakes in the Himalayas have expanded rapidly due to climate warming and glacial retreat. Some of these lakes are unstable, and may suddenly burst under different triggering factors, thus draining large amounts of water and impacting downstream social and economic development. Glacial lakes in the Poiqu River basin, Central Himalayas, have attracted great attention since GLOFs originating there could have a transboundary impact on both China and Nepal, as occurred during the Cirenmaco GLOF in 1981 and the Gongbatongshaco GLOF in 2016. Based on previous studies of this basin, we selected seven very high-risk moraine-dammed lakes (Gangxico, Galongco, Jialongco, Cirenmaco, Taraco, Beihu, and Cawuqudenco) to simulate GLOF propagation at different drainage percentage scenarios (i.e., 25%, 50%, 75%, and 100%), and to conduct hazard assessment. The results show that, when any glacial lake is drained completely or partly, most of the floods will enter Nepal after raging in China, and will continue to cause damage. In summary, 57.5 km of roads, 754 buildings, 3.3 km2 of farmland, and 25 bridges are at risk of damage due to GLOFs. The potentially inundated area within the Chinese part of the Poiqu River basin exceeds 45 km2. Due to the destructive impacts of GLOFs on downstream areas, appropriate and effective measures should be implemented to adapt to GLOF risk. We finally present a paradigm for conducting hazard assessment and risk management. It uses only freely available data and thus is easy to apply. [ABSTRACT FROM AUTHOR]

As an approach with great potential, the interpretation of space-borne synthetic aperture radar (SAR) images has been applied for monitoring the dynamic evolution of the glacial lakes in recent years. Considering unfavorable factors, such as inherent topography-induced effects and speckle noise in SAR images, it is challenging to accurately map and track the dynamic evolution of the glacial lakes by using multi-temporal SAR images. This paper presents an improved neighborhood-based ratio method utilizing a time series of SAR images to identify the boundaries of the glacial lakes and detect their spatiotemporal changes. The proposed method was applied to monitor the dynamic evolution of the two glacial lakes with periodic water discharge at the terminus of the Gongba Glacier in the southeastern Tibetan Plateau by utilizing 144 Sentinel-1A SAR images collected between October of 2014 and November of 2020. We first generated the reference intensity image (RII) by averaging all the SAR images collected when the water in the glacial lakes was wholly discharged, then calculated the neighborhood-based ratio between RII and each SAR intensity image, and finally identified the boundaries of the glacial lakes by a ratio threshold determined statistically. The time series of areas of the glacial lakes were estimated in this way, and the dates for water recharging and discharging were accordingly determined. The testing results showed that the water of the two glacial lakes began to be recharged in April and reached their peak in August and then remained stable dynamically until they began to shrink in October and were discharged entirely in February of the following year. We observed the expansion process with annual growth rates of 3.19% and 12.63% for these two glacial lakes, respectively, and monitored a glacial lake outburst flood event in July 2018. The validation by comparing with the results derived from Sentinel-2A/B optical images indicates that the accuracy for identifying the boundaries of the glacial lakes with Sentinel-1A SAR images can reach up to 96.49%. Generally, this contribution demonstrates the reliability and precision of SAR images to provide regular updates for the dynamic monitoring of glacial lakes. [ABSTRACT FROM AUTHOR]

In Kyrgyzstan, outburst flood disasters from glacial lakes are increasing. An example is the sudden drainage on 8 August 2019 of the Toguz-Bulak glacial lake in the Tosor river basin of the northern Tien Shan region. In this study, we used remote sensing and field surveys to examine the reasons for the outburst. We found that the lake area changed from 0.021 km² to 0.002 km2 due to the outburst, in which most of the initial 130,000 m3 of water discharged within four hours. In examining the longer-term behavior of this lake, we found that from 2010 through 2019, it appears in June and disappears in September every year. Its maximum area occurs in late July and early August. With the expansion of the lake basin between 2010 and 2019, the lake also increased greatly in size, particularly so in the three years before the outburst, linked to high summer temperatures and the resulting higher inflow of glacier meltwater, finally leading to the sudden drainage in 2019. Before this outburst, a 2-m high moraine dam retained the lake. Continuously inflowing meltwater and the related increasing pressure by the lake water mass eventually broke the moraine dam. Satellite radar interferometry revealed active displacement fringes in the lake basin and moraine dam due to the melting and subsidence of buried ice. An analysis using digital elevation models from 1964 and 2010 also confirms the surface lowering in the lake basin by up to 8.5 m and on the moraine dam by 2 m. Such lowering of the proglacial moraine complex destabilized the moraine dam. [ABSTRACT FROM AUTHOR]

In a previous study two pairs of paleo-landslides within an 8 km reach of the upper Yellow River were studied and dated back to ca. 80 ka, however the relationship between these two pairs of paleo-landslides were not explored. This study inferred that the initial pair of landslides (Dehenglong and Suozi) appearing contiguously and forming an upstream 46 km-long lake along the river may be triggered by earthquake events from nearby capable faults. Subsequently, backwater inundating the valley floor as the dammed lake formed may cause shear stress of sediments lowered on steep slopes adjacent to the River, and eventually induce the other two additional landslides (Xiazangtan and Kangyang) ~8 km upstream. This could be inferred from two optically stimulated luminescence (OSL) samples yielding ca. 80 ka also, which were collected from asymmetric folds 10 to 30 cm in amplitude within the bedding plane between lake/lakeshore sediment and landslide mass at the front lobes of the two additional landslides. We estimated the maximum volume of this dammed lake was 38 km3 and may generate an outburst flood with an estimated peak discharge of 6.1 × 105 m3/s, which may cause massive geomorphic effects and potential disasters upstream and downstream. It is important to better understand the geomorphic process of this damming event in mountainous area with respect to reflecting tectonic uplift, paleoclimatic change and forecast and mitigate hazards on the northeast Tibetan Plateau. [ABSTRACT FROM AUTHOR]

A glacial lake outburst flood (GLOF) is a phenomenon that is widely known by researchers because such an event can wreak havoc on the natural environment as well as on manmade infrastructure. Therefore, a GLOF risk assessment is necessary, especially within river basins with hydropower plants, and may lead to a tremendous amount of socioeconomic loss if not done. However, due to the subjective and objective limitations of the available GLOF risk assessment methods, we have proposed a new and easily applied method with a wider application and without the need for adaptation changes in accordance with the subject area, which also allows for the repeated use of this model. In this study, we focused our efforts on the Upper Arun Hydroelectric Project (UAHEP) in the Arun River Basin, and we (1) identified 49 glacial lakes with areas greater than 0.1 km2; (2) geographically represented and analyzed these 49 glacial lakes for the period of 1990–2018; (3) analyzed the correlation between the temperature and precipitation trends and the occurrence of recorded GLOF events in the region; (4) proposed a new method based on the documented affected lengths and volumes derived from historical GLOF events to identify 4 potentially critical lakes; and (5) evaluated the discharge profiles using widely used empirical methods and further discussed the physical properties, triggering factors, and outburst probability of the critical lakes. To achieve these objectives, a series of intensive and integrated desk studies, data collections, and GLOF simulations and analyses were performed. [ABSTRACT FROM AUTHOR]

Youtube.com has become one of the most popular places to share videos on the Internet, storing a large amount of audiovisual materials. People all over the world can upload their videos and watch videos of others. The research potential of this information source has received increasing popularity across scientific disciplines. In this contribution, we explore the top viewed videos containing selected cryospheric keywords, both general (cryosphere, glacier, ice, permafrost, snow), and specific, focusing on different types of cryospheric hazards (avalanche, blizzard and glacial lake outburst flood/jokulhlaup). Searching 100 top-viewed videos for each keyword, our database consists of 859 videos. Each video is described by several qualitative characteristics (e.g., video type, geographical focus) as well as quantitative characteristics (e.g., views per day, likes). A total of 310 videos in our database (36.1% of all) are classified as videos with factual cryospheric content. We show that the broader audience represented by YouTube users is particularly interested in videos capturing dynamic processes such as calving of glaciers. While videos found for general cryosphere keywords have attracted a generally higher attention of YouTube users (total views), videos found for specific keywords are ranked among the most liked. Further, we analyze where the videos with cryospheric content are filmed, revealing several hotspots for different keywords located in all continents except for Africa. Finally, we discuss the potentials of cryosphere videos for educational and research purposes, pointing out that videos filmed by incidental witnesses of low-frequency processes such as glacial lake outburst floods might contribute to the elucidation of their dynamics, magnitude and behavior as well as the occurrence in space and time. [ABSTRACT FROM AUTHOR]