Glacier Change, Supraglacial Debris Expansion and Glacial Lake Evolution in the Gyirong River Basin, Central Himalayas, between 1988 and 2015

Remote Sensing of Surface Water Dynamics in the Context of Global Change—A Review

Inland surface water is often the most accessible freshwater source. As opposed to groundwater, surface water is replenished in a comparatively quick cycle, which makes this vital resource—if not overexploited—sustainable. From a global perspective, freshwater is plentiful. Still, depending on the region, surface water availability is severely limited. Additionally, climate change and human interventions act as large-scale drivers and cause dramatic changes in established surface water dynamics. Actions have to be taken to secure sustainable water availability and usage. This requires informed decision making based on reliable environmental data. Monitoring inland surface water dynamics is therefore more important than ever. Remote sensing is able to delineate surface water in a number of ways by using optical as well as active and passive microwave sensors. In this review, we look at the proceedings within this discipline by reviewing 233 scientific works. We provide an extensive overview of used sensors, the spatial and temporal resolution of studies, their thematic foci, and their spatial distribution. We observe that a wide array of available sensors and datasets, along with increasing computing capacities, have shaped the field over the last years. Multiple global analysis-ready products are available for investigating surface water area dynamics, but so far none offer high spatial and temporal resolution.

Glacial Lake Area Changes in High Mountain Asia during 1990-2020 Using Satellite Remote Sensing

Changes in a large-scale glacial lake area directly reflect the regional glacier status and climate changes. However, long time series of glacial lake dataset and comprehensive investigation of the spatiotemporal changes in the glacial lake area in the whole High Mountain Asia (HMA) region remained elusive. Satellite remote sensing provides an indispensable way for dynamic monitoring of glacial lakes over large regions. But glacial lakes are quite small and discretely distributed, and the extraction of glacial lakes is usually influenced by clouds, snow/ice cover, and terrain shadows; thus, there is a lack of an automatic method to continuously monitor the dynamic changes of glacial lakes in a large scale. In this paper, we developed a per-pixel composited method named the "multitemporal mean NDWI composite" to automatically extract the glacial lake area in HMA from 1990 to 2020 using time-series Landsat data. There were 19,294 glacial lakes covering a total area of 1471.85 ± 366.42 km² in 1990, and 22,646 glacial lakes with an area of 1729.08 ± 461.31 km² in 2020. It is noted that the glacial lake area in the whole HMA region expanded by 0.58 ± 0.21%/a over the past three decades, with high spatiotemporal heterogeneity. The glacial lake area increased at a consistent speed over time. The fastest expansion was in East Kun Lun at an average rate of 2.01 ± 0.54%/a, while in the Pamir and Hengduan Shan, they show slow increases with rates of 0.33 ± 0.08%/a and 0.39 ± 0.01%/a, respectively, during 1990-2020. The greatest increase in lake area occurred at 5000-5200 m a.s.l., which increased by about 45 km² (~25%). We conclude that the temperature rise and glacier thinning are the leading factors of glacial lake expansion in HMA, and precipitation is the main source of lake water increase in West Kun Lun. Using the proposed method, a large amount of Landsat images from successive years of melting seasons can be fully utilized to obtain a pixel-level composited cloud-free and solid snow/ice-free glacial lake map. The uncertainties from supraglacial ponds and glacial meltwater were also estimated to improve the reliability and comparability of glacial lake area changes among different regions. This study provides important technical and data support for regional climate changes, glacier hydrology, and disaster analysis.

Recent Changes of Glacial Lakes in the High Mountain Asia and Its Potential Controlling Factors Analysis

The current glacial lake datasets in the High Mountain Asia (HMA) region still need to be improved because their boundary divisions in the land–water transition zone are not precisely delineate, and also some very small glacial lakes have been lost due to their mixed reflectance with backgrounds. In addition, most studies have only focused on the changes in the area of a glacial lake as a whole, but do not involve the actual changes of per pixel on its boundary and the potential controlling factors. In this research, we produced more accurate and complete maps of glacial lake extent in the HMA in 2008, 2012, and 2016 with consistent time intervals using Landsat satellite images and the Google Earth Engine (GEE) cloud computing platform, and further studied the formation, distribution, and dynamics of the glacial lakes. In total, 17,016 and 21,249 glacial lakes were detected in 2008 and 2016, respectively, covering an area of 1420.15 ± 232.76 km2 and 1577.38 ± 288.82 km2; the lakes were mainly located at altitudes between 4400 m and 5600 m. The annual areal expansion rate was approximately 1.38% from 2008 to 2016. To explore the cause of the rapid expansion of individual glacial lakes, we investigated their long-term expansion rates by measuring changes in shoreline positions. The results show that glacial lakes are expanding rapidly in areas close to glaciers and had a high expansion rate of larger than 20 m/yr from 2008 to 2016. Glacial lakes in the Himalayas showed the highest expansion rate of more than 2 m/yr, followed by the Karakoram Mountains (1.61 m/yr) and the Tianshan Mountains (1.52 m/yr). The accelerating rate of glacier ice and snow melting caused by global warming is the primary contributor to glacial lake growth. These results may provide information that will help in the understanding of detailed lake dynamics and the mechanism, and also facilitate the scientific recognition of the potential hazards associated with glacial lakes in this region.

Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018

Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the GST variability at Hailuogou glacier, a temperate glacier located in Southeastern Tibetan Plateau, from 1990 to 2018. We utilized a modified mono-window algorithm to calculate the GST using the Landsat 8 thermal infrared sensor (TIRS) band 10 data and Landsat 5 thematic mapper (TM) band 6 data. Three essential parameters, including the emissivity of ice and snow, atmospheric transmittance, and effective mean atmospheric temperature, were employed in the GST algorithm. The remotely-sensed temperatures were compared with two other single-channel algorithms to validate GST algorithm’s accuracy. Results from different algorithms showed a good agreement, with a mean difference of about 0.6 ℃. Our results showed that the GST of the Hailuogou glacier, both in the upper debris-free part and the lower debris-covered tongue, has experienced a slightly increasing trend at a rate of 0.054 ℃ a−1 during the past decades. Atmospheric warming, expanding debris cover in the lower part, and a darkening debris-free accumulation area are the main causes of the warming of the glacier surface.

Examining the glacial lake dynamics in a warming climate and GLOF modelling in parts of Chandra basin, Himachal Pradesh, India

The presented study reports applicability of Lake Detection Algorithm (LDA) for an automated extraction of glacial lakes over a large geographical region and dynamics of Samudra Tapu and Gepang Gath glacial lakes. The areal extent of lake boundary extracted through LDA and areal extent of manually interpreted lake boundary exhibit a remarkable agreement (R²~0.99). Glacial lake dynamics is assessed in terms of areal and volumetric expansion for two selected glacial lakes from 1979 to 2017, i.e. Samudra Tapu (0.95 km²), and Gepang Gath (0.67 km²). They show volumetric expansion from 8.52 × 10⁶ m³ (1979) to 80.34 × 10⁶ m³ (2017) and 2.04 × 10⁶ m³ (1979) to 32.44 × 10⁶ m³ (2017) respectively. Statistical analysis (Mann-Kendall and Sen's slope) of climate data indicates rise in mean annual temperature (0.021 °C yr^-1; 1961-2015) and fall in annual precipitation (-2.74 mm yr^-1; 1951-2015) at different confidence intervals. Further Glacial Lake Outburst Flood (GLOF) is modelled using empirical relationship and Simplified Dam Breach Model (SMPDBK). The SMPDBK demonstrates discharge of 3866.52 and 2100.90 m³ s^-1 reaching Chhatru and Sissu village posing threat to life and property. The study also exhibits that glacial shrinkage under the influence of climate change causes expansion of glacial lakes. This expansion is expected to intensify catastrophic GLOF and resultant fatalities and destruction in the downstream region.

Glacial Lake Inventory and Lake Outburst Flood/Debris Flow Hazard Assessment after the Gorkha Earthquake in the Bhote Koshi Basin

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.

Hydrodynamic moraine-breach modeling and outburst flood routing - A hazard assessment of the South Lhonak lake, Sikkim

The presence of glacial lakes in the Himalaya makes it a potential mountain hazard, as catastrophic failure of such waterbodies may lead to high-magnitude glacial lake outburst flood (GLOF) events that can cause significant damage to the low-lying areas. The present study evaluates the hazard potential of the South Lhonak lake located in the state of Sikkim, using both one and two-dimensional hydrodynamic modeling approaches. Different breach parameters were calculated based on the lake bathymetry and moraine dimensions. The worst-case GLOF scenario is revealed during an overtopping failure of the moraine, producing a peak flood of 6064.6 m³ s^-1 and releasing a total water volume of 25.7 × 10⁶ m³. The GLOF hydrograph is routed to calculate peak flood (m³ s^-1), inundation depth (m) and flow velocity (ms^-1) along the main flow channel. The interaction of the flood wave with a major topographic obstruction located 15.6 km downstream of the lake, shows a significant reduction of the flow energy leading to a minimization of the South Lhonak GLOF impact. The flood wave reaches the nearest town Lachen, located at a distance of 46 km downstream from the lake, at 3 h 38 min after the initiation of the breach, with a peak flood of 3928.16 m³ s^-1 and a maximum flow velocity of 13.6 ms^-1. At Chungthang town, located at a distance of 62.35 km from South Lhonak lake, the flood wave potentially inundates settlements along the bank of the flow channel, where a peak flood of 3828.08 m³ s^-1 is reached after 4 h of the initial dam breach event. The study also incorporates modeling of a framework to propose a potential flood remediation measure of the South Lhonak lake GLOF by demonstrating the effect of a lateral inline structure along the flow channel, to check the flow of the potential flood wave.

Development of Supraglacial Ponds in the Everest Region, Nepal, between 1989 and 2018

Several supraglacial ponds are developing and increasing in size and number in the Himalayan region. They are the precursors of large glacial lakes and may become potential for glacial lake outburst floods (GLOFs). Recently, GLOF events originating from supraglacial ponds were recorded; however, the spatial, temporal, and seasonal distributions of these ponds are not well documented. We chose 23 debris-covered glaciers in the Everest region, Nepal, to study the development of supraglacial ponds. We used historical Landsat images (30-m resolution) from 1989 to 2017, and Sentinel-2 (10-m resolution) images from 2016 to 2018 to understand the long-term development and seasonal variations of these ponds. We also used fine-resolution (0.5–2 m) WorldView and GeoEye imageries to reveal the high-resolution inventory of these features and these images were also used as references for accuracy assessments. We observed a continuous increase in the area and number of ponds from 1989–2017, with minor fluctuations. Similarly, seasonal variations were observed at the highest ponded area in the pre- and postmonsoon seasons, and lowest ponded area in the winter season. Substantial variations of the ponds were also observed among glaciers corresponding to their size, slope, width, moraine height, and elevation. The persistency and densities of the ponds with sizes >0.005 km2 were found near the glacier terminuses. Furthermore, spillway lakes on the Ngozompa, Bhote Koshi, Khumbu, and Lumsamba glaciers were expanding at a faster rate, indicating a trajectory towards large lake development. Our analysis also found that Sentinel-2 (10-m resolution) has good potential to study the seasonal changes of supraglacial ponds, while fine-resolution (<2 m) imagery is able to map the supraglacial ponds with high accuracy and can help in understanding the surrounding morphology of the glacier.

Glacial Lakes in the Nepal Himalaya: Inventory and Decadal Dynamics (1977–2017)

Himalayan glaciers, in general, are shrinking and glacial lakes are evolving and growing rapidly in number and size as a result of climate change. This study presents the latest remote sensing-based inventory (2017) of glacial lakes (size ≥0.0036 km2) across the Nepal Himalaya using optical satellite data. Furthermore, this study traces the decadal glacial lake dynamics from 1977 to 2017 in the Nepal Himalaya. The decadal mapping of glacial lakes (both glacial-fed and nonglacial-fed) across the Nepal Himalaya reveals an increase in the number and area of lakes from 1977 to 2017, with 606 (55.53 ± 16.52 km2), 1137 (64.56 ± 11.64 km2), 1228 (68.87 ± 12.18 km2), 1489 (74.2 ± 14.22 km2), and 1541 (80.95 ± 15.25 km2) glacial lakes being mapped in 1977, 1987, 1997, 2007, and 2017, respectively. Glacial lakes show heterogeneous rates of expansion in different river basins and elevation zones of Nepal, with apparent decadal emergences and disappearances. Overall, the glacial lakes exhibited ~25% expansion of surface areas from 1987 to 2017. For the period from 1987 to 2017, proglacial lakes with ice contact, among others, exhibited the highest incremental changes in terms of number (181%) and surface area (82%). The continuous amplified mass loss of glaciers, as reported in Central Himalaya, is expected to accompany glacial lake expansion in the future, increasing the risk of glacial lake outburst floods (GLOFs). We emphasize that the rapidly increasing glacial lakes in the Nepal Himalaya can pose potential GLOF threats to downstream population and infrastructure.