Search Results (234)

Glacial-lake outburst floods (GLOFs) threaten more than three million residents of south-east Kazakhstan, yet quantitative data on lake growth and storage are scarce. We inventoried 154 lakes on the northern flank of the Ile-Alatau and selected four moraine-dammed basins with the greatest historical flood activity for detailed study. Annual lake outlines (2016–2023) were extracted from 3 m PlanetScope imagery with a Normalised Difference Water Index workflow, while late-ablation echo-sounder surveys (2023–2024) yielded sub-metre bathymetric grids. A regionally calibrated area–volume power law translated each shoreline to water storage, and field volumes served as an independent accuracy check. The lakes display divergent trajectories. Rapid thermokarst development led to a 37% increase in the surface area of Lake 13bis, expanding from 0.039 km² to 0.054 km² over a 5-year period. In contrast, engineering-induced drawdown resulted in a 44% reduction in the area of Lake 6, from 0.019 km² to 0.011 km². Lakes 5 and 2, which are supplied by actively retreating glaciers, exhibited surface area increases of 4.8% and 15%, expanding from 0.077 km² to 0.088 km² and from 0.061 km² to 0.070 km², respectively. The empirical model reproduces field volumes to within ±25% for four lakes, confirming its utility for rapid hazard screening, but overestimates storage in low-relief basins and underestimates artificially drained lakes. This is the first study in Ile-Alatau to fuse daily 3 m multispectral imagery with ground-truth bathymetry, delivering an 8-year, volume-resolved record of lake evolution. The results identify Lake 5 and Lake 2 as priority targets for early-warning systems and demonstrate that sustained intervention can effectively suppress GLOF risk. Incorporating these storage trajectories into regional disaster plans will sharpen evacuation mapping, optimise resource allocation, and inform transboundary water-hazard policy under accelerating climate change. Full article

The Tibetan Plateau’s lakes, serving as critical water towers for over two billion people, exhibit divergent responses to climate change that remain poorly quantified. This study develops a deep learning framework integrating Synthetic Aperture Radar (SAR) altimetry from Sentinel-3A with bias-corrected CMIP6 (Coupled Model Intercomparison Project Phase 6) climate projections under Shared Socioeconomic Pathways (SSP) scenarios (SSP2-4.5 and SSP5-8.5, adjusted via quantile mapping) to predict lake-level changes across eight Tibetan Plateau (TP) lakes. Using a Feed-Forward Neural Network (FFNN) optimized via Bayesian optimization using the Optuna framework, we achieve robust water level projections (mean validation R² = 0.861) and attribute drivers through Shapley Additive exPlanations (SHAP) analysis. Results reveal a stark north–south divergence: glacier-fed northern lakes like Migriggyangzham will rise by 13.18 ± 0.56 m under SSP5-8.5 due to meltwater inputs (temperature SHAP value = 0.41), consistent with the early (melt-dominated) phase of the IPCC’s ‘peak water’ framework. In comparison, evaporation-dominated southern lakes such as Langacuo face irreversible desiccation (−4.96 ± 0.68 m by 2100) as evaporative demand surpasses precipitation gains. Transitional western lakes exhibit “peak water” inflection points (e.g., Lumajang Dong’s 2060 maximum) signaling cryospheric buffer loss. These projections, validated through rigorous quantile mapping and rolling-window cross-validation, provide the first process-aware assessment of TP Lake vulnerabilities, informing adaptation strategies under the Sustainable Development Goals (SDGs) for water security (SDG 6) and climate action (SDG 13). The methodological framework establishes a transferable paradigm for monitoring high-altitude freshwater systems globally. Full article

The Qinghai-Tibet Plateau is a sensitive area of global climate change and an “Asian water tower” and lakes in Qinghai-Tibet Plateau changes are of great significance to the regional hydrological cycle and ecological balance. However, the existing research mostly focuses on a single lake or short-term monitoring, and lacks a systematic review of the evolution of knowledge structure and interdisciplinary dynamics. Based on 354 literatures from CNKI (China National Knowledge Infrastructure) and Web of Science, this study used CiteSpace 6.3.R1 software to construct a scientific knowledge map of lake changes in the Qinghai-Tibet Plateau under the background of climate change for the first time. By analyzing the number of publications, research hotspots, institutional cooperation networks and keyword emergence rules, the core triangle structure of ”climate change–Qinghai-Tibet Plateau–lake” was revealed, and the three stages of sedimentary reconstruction (2002–2008), glacier–lake coupling (2005–2014) and human–land system comprehensive research (2015–2025) were divided. The study found that the scientific literature written in Chinese and the scientific literature written in English focused on empirical cases and model simulations, respectively, The research frontiers focused on hot karst lakes (burst intensity 3.71), lake water level (2.97) and carbon cycle (2.13). The research force is centered on the Chinese Academy of Sciences, forming a cluster of institutions in the northwest region, but international cooperation only accounts for 12.3%. Future research needs to deepen multi-source data fusion, strengthen cross-regional comparison, and build an international cooperation network to cope with the complex challenges of plateau lake systems under climate change. This study provides a scientific basis for the paradigm shift and future direction of plateau lake research. Full article

Morphological problems for distinguishing between glacier ice, glacier ice with a debris cover (debris-covered glaciers), and rock glaciers are outlined with respect to recognising and mapping these features. Decimal latitude–longitude [dLL] values are used for geolocation. One model for rock glacier formation and flow discusses the idea that they consist of ‘mountain permafrost’. However, signs of permafrost-derived ice, such as flow features, have not been identified in these landsystems; talus slopes in the neighbourhoods of glaciers and rock glaciers. An alternative view, whereby rock glaciers are derived from glacier ice rather than permafrost, is demonstrated with examples from various locations in the mountain domain, 𝔻𝕞. A Google Earth and field examination of many rock glaciers shows glacier ice exposed below a rock debris mantle. Ice exposure sites provide ground truth for observations and interpretations stating that rock glaciers are indeed formed from glacier ice. Exposure sites include bare ice at the headwalls of cirques and above debris-covered glaciers; additionally, ice cliffs on the sides of meltwater pools are visible at various locations along the lengths of rock glaciers. Inspection using Google Earth shows that these pools can be traced downslope and their sizes can be monitored between images. Meltwater pools occur in rock glaciers that have been previously identified in inventories as being indictive of permafrost in the mountain domain. Glaciers with a thick rock debris cover exhibit ‘hidden ice’ and are shown to be geomorphological units mapped as rock glaciers. Full article

The water regime in Pakistan’s northern region has experienced significant changes regarding hydrological extremes like floods because of climate change. Coupling hydrological models with remote sensing data can be valuable for flow simulation in data-scarce regions. This study focused on simulating the snow- and glacier-melt runoff using the snowmelt runoff model (SRM) in the Gilgit and Kachura River Basins of the upper Indus basin (UIB). The SRM was applied by coupling it with in situ and improved cloud-free MODIS snow and glacier composite satellite data (MOYDGL06) to simulate the flow under current and future climate scenarios. The SRM showed significant results: the Nash–Sutcliffe coefficient (NSE) for the calibration and validation period was between 0.93 and 0.97, and the difference in volume (between the simulated and observed flow) was in the range of −1.5 to 2.8% for both catchments. The flow tends to increase by 0.3–10.8% for both regions (with a higher increase in Gilgit) under mid- and late-21st-century climate scenarios. The Gilgit Basin’s higher hydrological sensitivity to climate change, compared to the Kachura Basin, stems from its lower mean elevation, seasonal snow dominance, and greater temperature-induced melt exposure. This study concludes that the simple temperature-based models, such as the SRM, coupled with improved satellite snow cover data, are reliable in simulating the current and future flows from the data-scarce mountainous catchments of Pakistan. The outcomes are valuable and can be used to anticipate and lessen any threat of flooding to the local community and the environment under the changing climate. This study may support flood assessment and mapping models in future flood risk reduction plans. Full article

Tropical glaciers are highly sensitive to climate change, with their mass balance influenced by temperature and precipitation, which affects the accumulation area. In this study, we developed an open-source tool to map the accumulation area of glaciers in the Cordillera Blanca, Peru (1988–2023), using Landsat images, spectral indices, and the Otsu method. We analyzed trends and correlations between snow accumulation area, meteorological patterns from ERA5 data, and oscillation modes. The results were validated using field data and manual mapping. Greater discrepancies were observed in glaciers with debris cover or small clean glaciers (<1 km²). The Amazonian and Pacific sectors showed a significant trend in decreasing accumulation areas, with reductions of 8.99% and 10.24%, respectively, from 1988–1999 to 2010–2023. El Niño events showed higher correlations with snow accumulation, snowfall, and temperature during the wet season, indicating a stronger influence on the Pacific sector. The accumulation area was strongly anti-correlated with temperature and correlated with snowfall in both sectors at a 95% confidence level (α = 0.05). The highest correlations with meteorological parameters were observed during the dry season, suggesting that even minor changes in temperature or precipitation could significantly impact the accumulation area. 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

During a research expedition to the Kanchenjunga Conservation Area (KCA), eastern Nepal, in April–June 2024, local concern was expressed about the rapid development of meltwater ponds upon the terminus of the Kanchenjunga glacier since 2020, especially in terms of the possible formation of a large and potentially dangerous glacial lake. Our resultant study of the issue included informal interviews with local informants, comparison of time series satellite composite images acquired by Sentinel-2 Multispectral Instrument, and modeling of different lake development, outburst flood scenarios, and prospective downstream impacts. Assuming that the future glacial lake will be formed by the merging of present-day supraglacial ponds, filling the low-gradient area beneath the present-day glacier terminal complex, we estimated the potential volume of a Kanchenjunga proglacial lake to be 33 × 10⁶ m³. Potential mass movement-triggered outburst floods would travel downstream distances of almost 120 km even under the small magnitude scenario, and under the worst-case scenario would reach the Indo-Gangetic Plain and cross the border into India, exposing up to 90 buildings and 44 bridges. In response, we suggest that the lower Kanchenjunga glacier region be regularly monitored by both local communities and Kathmandu-based research entities over the next decade. The development of user-friendly early warning systems, hazard mapping and zoning programs, cryospheric hazards awareness building programs, and construction of locally appropriate flood mitigation measures are recommended. Finally, the continued development and refinement of the models presented here could provide governments and remote communities with a set of inexpensive and reliable tools capable of providing the basic information needed for communities to make informed decisions regarding hazard mitigation, adaptive, and/or preventive measures related to changing glaciers. Full article

Mountain regions are particularly sensitive and vulnerable to the impacts of climate change. Over the past three decades, mountain temperatures have risen significantly faster than those in lowland areas. The Hindu Kush–Karakoram–Himalaya region, often referred to as the “water tower of Asia”, is the largest freshwater source outside the polar regions. However, it is currently undergoing cryospheric degradation as a result of climatic change. In this study, the Normalized Difference Glacier Index (NDGI) was calculated using Landsat and Sentinel satellite images. The results revealed that glaciers in Chitral, located in the Eastern Hindu Kush Mountains of Pakistan, lost 816 km² (31%) of their total area between 1992 and 2022. On average, 27 km² of glacier area was lost annually, with recession accelerating between 1997 and 2002 and again after 2007. Satellite analyses also indicated a significant increase in both maximum (+7.3 °C) and minimum (+3.6 °C) land surface temperatures between 1992 and 2022. Climate data analyses using the Mann–Kendall test, Theil–Sen Slope method, and the Autoregressive Integrated Moving Average (ARIMA) model showed a clear increase in air temperatures from 1967 to 2022, particularly during the summer months (June, July, and August). This warming trend is expected to continue until at least 2042. Over the same period, annual precipitation decreased, primarily due to reduced snowfall in winter. However, rainfall may have slightly increased during the summer months, further accelerating glacial melting. Additionally, the snowmelt season began consistently earlier. While initial glacier melting may temporarily boost water resources, it also poses risks to communities and economies, particularly through more frequent and larger floods. Over time, the remaining smaller glaciers will contribute only a fraction of the former runoff, leading to potential water stress. As such, monitoring glaciers, climate change, and runoff patterns is critical for sustainable water management and strengthening resilience in the region. Full article

Understanding glacier and climate variations since pre-Industrial times is crucial for evaluating the present-day glacier response to climate change. Here, we focus on twelve small glaciers (≤2.0 km²) on both the northern and southern slopes of the Greater Caucasus to assess post-Little Ice Age glacier–climate fluctuations in this region. We reconstructed the Little Ice Age glacier extent using a manual detection method based on moraines. More recent glacier fluctuations were reconstructed using historical topographical maps and satellite imagery. Digital elevation models were used to estimate the topographic characteristics of glaciers. We also used the accumulation area ratio (AAR) method and a regional temperature lapse rate to reconstruct glacier snowlines and corresponding temperatures since the 1820s. The results show that all selected glaciers have experienced area loss, terminus retreat, and equilibrium line altitude (ELA) uplift over the last 200 years. The total area of the glaciers has decreased from 19.1 ± 0.9 km² in the 1820s to 9.7 ± 0.2 km² in 2020, representing a −49.2% loss, with an average annual reduction of −0.25%. The most dramatic reduction occurred between the 1960s and 2020, when the glacier area shrank by −35.5% or −0.59% yr⁻¹. The average terminus retreat for all selected glaciers was −1278 m (−6.4 m/yr⁻¹) during the last 200 years, while the average retreat over the past 60 years was −576 m (−9.6 m/yr⁻¹). AAR-based (0.6 ± 0.05) ELA reconstructions from all twelve glaciers suggest that the average ELA in the 1820s was about 180 m lower (3245 ± 50 m a.s.l.) than today (3425 ± 50 m a.s.l.), corresponding to surface air temperatures <1.1 ± 0.3 °C than today (2001–2020). The largest warming occurred between the 1960s and today, when snowlines rose by 105 m and air temperatures increased by <0.6 ± 0.3 °C. This study represents a first attempt at using glacier evidence to estimate climate changes in the Caucasus region since the Little Ice Age, and it can be used as a baseline for future studies. Full article

Glacial retreat is a major global challenge, particularly in arid and semi-arid regions where glaciers serve as critical water sources. This research focuses on glacial retreat and its impact on land cover and land use changes (LULC) in the Barroso Mountain range, Tacna, Peru, which is a critical area for water resources in the hyperarid Atacama Desert. Employing advanced remote sensing techniques through the Google Earth Engine (GEE) cloud computing platform, we analyzed historical trends (1985–2022) using Landsat satellite imagery. A normalized index classification was carried out to generate LULC maps for the years 1986, 2001, 2012, and 2022. Future projections until 2042 were developed using Cellular Automata–Markov (CA–Markov) modeling in QGIS, incorporating six predictive environmental variables. The resulting maps presented an overall accuracy (OA) greater than 83%. Historical analysis revealed a dramatic glacier reduction from 44.7 km² in 1986 to 7.4 km² in 2022. In contrast, wetlands expanded substantially from 5.70 km² to 12.14 km², indicating ecosystem shifts potentially driven by glacier meltwater availability. CA–Markov chain modeling projected further glacier loss to 3.07 km² by 2042, while wetlands are expected to expand to 18.8 km² and bodies of water will reach 4.63 km². These future projections (with accuracies above 84%) underline urgent implications for water management, environmental sustainability, and climate adaptation strategies, particularly with regard to downstream hydrological risks and ecosystem resilience. Full article

Glacier meltwater influences streamflow and various activities in the western US. The Wind River Range (WRR) in Wyoming, which contains the largest glacial mass in the Rocky Mountains of the conterminous US, has been retreating since the Little Ice Age. This study examines long-term changes in WRR glaciers (>0.2 km²) over 1968–2019 and investigates their relationship with climatic and topographic factors. Using USGS topographic maps, satellite imagery, DEM datasets, and GPS surveys, we analyzed glacier area and surface elevation changes. Our results show a 19.2 ± 0.9% glacier area reduction from 1972 to 2019, with a 10.6 ± 0.3% decline from 2000–2019. Glacier thinning was most pronounced between 2000 and 2019 at −0.58 ± 0.11 m y⁻¹, with lower-elevation glaciers thinning faster. Small, south-facing glaciers retreated more rapidly, while slope effects were mixed. Increasing spring temperatures and a shift toward more spring precipitation falling as rain has likely exacerbated glacier loss since 2000. Such accelerated melting has significant implications for water availability and ecosystem health if warming continues, affecting agricultural, industrial, and recreational water use. Understanding these trends is key for future water resource management and ecosystem sustainability in the region. Full article

In Antarctica, SAR interferometry has largely been used in coastal glacial areas, while in rare cases this method has been used on the Antarctic plateau. In this paper, the authors present a digital elevation and ice flow map based on SAR interferometry for an area encompassing Talos Dome (TD) and the Frontier Mountain (FM) meteorite site in North Victoria Land/Antarctica. A digital elevation model (DEM) was calculated using a double SAR interferometry method. The DEM of the region was calculated by extracting approximately 100 control points from the Reference Elevation Model of Antarctica (REMA). The two DEMs differ slightly in some areas, probably due to the penetration of the SAR-C band signal into the cold firn. The largest differences are found in the western area of TD, where the radar penetration is more pronounced and fits well with the layer structures calculated by the georadar and the snow accumulation observations. By differentiating a 70-day interferogram with the calculated DEM, a displacement interferogram was calculated that represents the ice dynamics. The resulting ice flow pattern clearly shows the catchment areas of the Priestley and Rennick Glaciers as well as the ice flow from the west towards Wilkes Basin. The ice velocity field was analysed in the area of FM. This area has become well known due to the search for meteorites. The velocity field in combination with the calculated DEM confirms the generally accepted theories about the accumulation of meteorites over the Antarctic Plateau. Full article

The Patagonia Icefield, the largest ice mass in the Southern Hemisphere outside Antarctica, has experienced significant growth and expansion of ice-contact lakes in recent decades, with lake surface water temperature (LSWT) being one of the key influencing factors. LSWT affects glacier melting at the waterline and accelerates glacier mass loss. However, the observations of ice-contact LSWT are often limited to short-term, site-based field measurements, which hinders long-term, whole-lake monitoring. This study examines LSWT for the three largest ice-contact lakes in the Patagonia Icefield—Lake Argentino, Lake Viedma, and Lake O’Higgins, each exceeding 1000 km²—and the three largest nearby non-ice-contact lakes for comparison using MODIS data between 2002 and 2022. In 2022, the mean LSWTs for Lake Argentino, Lake Viedma, and Lake O’Higgins were 7.2, 7.0, and 6.4 °C, respectively. In summer, ice-contact lakes exhibited wider LSWT ranges and more pronounced cooling near glacier termini and warming farther away compared to other seasons, demonstrating glacier melt cooling and its seasonal variability. Over the past 20 years, both Lake Viedma and Lake O’Higgins showed a warming rate of +0.20 °C dec⁻¹, p > 0.1, with slower warming near the glacier, reflecting glacier contact suppression on the LSWT trend. Conversely, Lake Argentino displayed a significant warming rate of +0.43 °C dec⁻¹ (p < 0.05), with faster rates near the glacier terminus, possibly linked to a prolonged and large (>64 km²) iceberg accumulation event from March 2010 to October 2011 in Glacier Upsala’s fjord. Iceberg mapping shows that larger events caused more pronounced short-term (24 days) LSWT cooling in Lake Argentino’s ice-proximal region. This study highlights the role of glacier–lake interactions including calving events in regulating ice-contact lake water temperature. Full article

Climate change is resulting in significant transformations in mountain areas all over the world, causing the melting of glacier ice, reduction in snow accumulation, and permafrost loss. Changes in the mountain cryosphere are not only modifying flora and fauna distributions but also affecting the stability of slopes in those regions. For all these reasons, and because of the risks these phenomena pose to the population, the dentification of dangerous areas is a crucial step in the development of risk reduction strategies. While several methods and examples exist that cover the assessment and computation of single sub-components, there is still a lack of application of risk assessment due to glacier melting over large areas in which the final result can be directly employed in the design of risk mitigation policies at regional and municipal levels. This research is focused on landslides and gravitational movements on slopes resulting from rapid glacier melting phenomena in the Valle d’Aosta region in Italy, with the aim of providing a tool that can support spatial planning in response to climate change in Alpine environments. Through the conceptualization and development of a GIS-based and multi-criteria approach, risk is then estimated by defining hazard indices that consider different aspects, combining the experience acquired from studies carried out in various disciplinary fields, to obtain a framework at the regional level. This first assessment is then deepened for the Lys River Valley, where the mapping of hazardous areas was implemented, obtaining a classification of buildings according to their hazard score to estimate the potential damage and total risk relating to possible slope instability events due to ice melt at the local scale. Full article