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Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 15 December 2024 | Viewed by 20539

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Special Issue Editors

Prof. Dr. Yong Nie

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Guest Editor

Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
Interests: glacier; glacial lakes and GLOFs; remote sensing

Prof. Dr. Qiao Liu

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Guest Editor

Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610299, China
Interests: glaciology; debris-covered glaciers; glacier-related hazards; glacial drainage system; remote sensing in glaciology

Prof. Dr. Guoqing Zhang

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Guest Editor

Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
Interests: lake change; remote sensing; glacial lake; GLOF
Special Issues, Collections and Topics in MDPI journals

Prof. Dr. Xin Wang

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Guest Editor

School of Earth Science and Geo-Spatial Information Engineering, Hunan University of Science and Technology, Xiangtan 411100, China
Interests: remote sensing; glacier dynamics; glacier-related hazards; glacial lake mapping

Special Issue Information

Dear Colleagues,

Glacial lakes, as water resources and also sensitive indicators for climate change, are widely distributed in High-Mountain Asia (HMA). In the case of dam failures, glacial lakes can release massive amounts of water abruptly and cause catastrophic damage to local downstream regions, also called glacial lake outburst floods (GLOFs). Remote sensing is the most feasible technique to investigate the regional distributions and changes in glacial lakes, to build GLOF datasets, and reconstruct typical GLOF events, providing fundamental data for water resource and GLOF risk evaluation. Detecting the location of potentially dangerous glacial lakes and predicting their possible socio-economic impact has a critical role in GLOF prevention and mitigation.

This Special Issue will report on recent progress in this area, with studies covering the application of remote sensing technology in glacial lake research, novel mapping approaches, monitoring techniques, and integrated assessment models towards sustainable development.

We encourage submissions of both regular research papers and reviews on topics related to the application of remote sensing in HMA glacial lakes and their related hazards, including, but not limited to, the following:

Novel glacial lake mapping approaches and applications at local to regional scales, including optical, SAR, unmanned aerial vehicle (UAV) observations, or a mixture of these techniques;
Glacial lake changes, drivers, interactions between glaciers and climate change, and associated hydrological implications;
Inventory and reconstruction of typical GLOF events to reveal the mechanisms and processes of GLOFs;
New frameworks and methods for GLOF hazard risk evaluations, as well as their application in key regions/zones/corridors of HMA, e.g., Sichuan–Tibet railway, China–Pakistan economic corridor, China–Nepal economic corridor, the Tien Shan, the Himalayas, and Karakoram;
Impact of GLOFs on downstream communities and infrastructure;
Remote sensing-based monitoring and early warnings.

Prof. Dr. Yong Nie
Prof. Dr. Qiao Liu
Prof. Dr. Guoqing Zhang
Prof. Dr. Xin Wang
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

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Keywords

novel lake mapping approaches/algorithms of remote sensing
glacial lake mapping and change
glacier and lake interactions
glacial lake outburst floods
reconstruct historical GLOFs
cascading geohazard related to glacial lake dynamics
GLOF risk assessment
social–economic impact of GLOFs
optical SAR-UAV-based monitoring

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Published Papers (9 papers)

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18 pages, 9425 KiB

Open AccessArticle

Two-Decadal Glacier Changes in the Astak, a Tributary Catchment of the Upper Indus River in Northern Pakistan

by Muzaffar Ali, Qiao Liu and Wajid Hassan

Remote Sens. 2024, 16(9), 1558; https://doi.org/10.3390/rs16091558 - 27 Apr 2024

Viewed by 1403

Abstract

Snow and ice melting in the Upper Indus Basin (UIB) is crucial for regional water availability for mountainous communities. We analyzed glacier changes in the Astak catchment, UIB, from 2000 to 2020 using remote sensing techniques based on optical satellite images from Landsat and ASTER digital elevation models. We used a surface feature-tracking technique to estimate glacier velocity. To assess the impact of climate variations, we examined temperature and precipitation anomalies using ERA5 Land climate data. Over the past two decades, the Astak catchment experienced a slight decrease in glacier area (−1.8 km²) and the overall specific mass balance was −0.02 ± 0.1 m w.e. a⁻¹. The most negative mass balance of −0.09 ± 0.06 m w.e. a⁻¹ occurred at elevations between 2810 to 3220 m a.s.l., with a lesser rate of −0.015 ± 0.12 m w.e. a⁻¹ above 5500 m a.s.l. This variation in glacier mass balance can be attributed to temperature and precipitation gradients, as well as debris cover. Recent glacier mass loss can be linked to seasonal temperature anomalies at higher elevations during winter and autumn. Given the reliance of mountain populations on glacier melt, seasonal temperature trends can disturb water security and the well-being of dependent communities. Full article

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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19 pages, 35735 KiB

Open AccessArticle

Glacial Lake Changes and Risk Assessment in Rongxer Watershed of China–Nepal Economic Corridor

by Sihui Zhang, Yong Nie and Huayu Zhang

Remote Sens. 2024, 16(4), 725; https://doi.org/10.3390/rs16040725 - 19 Feb 2024

Cited by 1 | Viewed by 1551

Abstract

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

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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19 pages, 5401 KiB

Open AccessArticle

Glacial Lake Outburst Flood Monitoring and Modeling through Integrating Multiple Remote Sensing Methods and HEC-RAS

by Liye Yang, Zhong Lu, Chaojun Ouyang, Chaoying Zhao, Xie Hu and Qin Zhang

Remote Sens. 2023, 15(22), 5327; https://doi.org/10.3390/rs15225327 - 12 Nov 2023

Cited by 4 | Viewed by 3948

Abstract

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

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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20 pages, 9852 KiB

Open AccessArticle

Inventory of Glacial Lake in the Southeastern Qinghai-Tibet Plateau Derived from Sentinel-1 SAR Image and Sentinel-2 MSI Image

by Yuan Zhang, Jun Zhao, Xiaojun Yao, Hongyu Duan, Jianxia Yang and Wenlong Pang

Remote Sens. 2023, 15(21), 5142; https://doi.org/10.3390/rs15215142 - 27 Oct 2023

Viewed by 1284

Abstract

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

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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21 pages, 11246 KiB

Open AccessArticle

Characterization of Three Surges of the Kyagar Glacier, Karakoram

by Zhen Zhang, Jinbiao Zhao, Shiyin Liu, Qibing Zhang, Zongli Jiang, Yangyang Xu and Haoran Su

Remote Sens. 2023, 15(8), 2113; https://doi.org/10.3390/rs15082113 - 17 Apr 2023

Cited by 6 | Viewed by 1846

Abstract

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

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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17 pages, 4542 KiB

Open AccessArticle

Exploring Contrastive Representation for Weakly-Supervised Glacial Lake Extraction

by Hang Zhao, Shuang Wang, Xuebin Liu and Fang Chen

Remote Sens. 2023, 15(5), 1456; https://doi.org/10.3390/rs15051456 - 5 Mar 2023

Cited by 3 | Viewed by 2160

Abstract

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

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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17 pages, 6359 KiB

Open AccessArticle

Characteristics of Glaciers Surging in the Western Pamirs

by Zhenfeng Wang, Zongli Jiang, Kunpeng Wu, Shiyin Liu, Yong Zhang, Xin Wang, Zhen Zhang and Junfeng Wei

Remote Sens. 2023, 15(5), 1319; https://doi.org/10.3390/rs15051319 - 27 Feb 2023

Cited by 2 | Viewed by 1958

Abstract

The regional surge patterns and control mechanisms for glaciers in the western Pamirs are unclear. Using remote sensing, more surge-type glaciers have been discovered in the western Pamirs. This provides an opportunity to obtain the integral characteristics of glacier surging. Using Sentinel-1A, TSX/TDX and Landsat remote sensing data, the changes in surface velocity, surface elevation and surface features of five glaciers that have recently surged in the western Pamirs are obtained. The results show that (1) all glacier surges initiate gradually for several years and most form a surge front in the upper region of the glacier. (2) For most glaciers, the active phase of the surge is more than 2 years, except for one that is within several months. (3) The peak velocity mostly occurs in summer and autumn, and the maximum velocity is less than 8 m d⁻¹. (4) There is sharp deceleration, such as the hydrologic controlled surge at the end of the surge. However, the surface flow of the transverse profiles shows no features of base sliding. Based on the comparison of surge patterns with other regions in High Mountain Asia, we conclude that the surging glaciers in the western Pamirs are triggered by thermal mechanisms under the control of sub-hydrological modulation. Full article

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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17 pages, 4500 KiB

Open AccessArticle

Variability of Glacier Velocity and the Influencing Factors in the Muztag-Kongur Mountains, Eastern Pamir Plateau

by Danni Huang, Zhen Zhang, Ling Jiang, Rui Zhang, Yijie Lu, AmirReza Shahtahmassebi and Xiaoli Huang

Remote Sens. 2023, 15(3), 620; https://doi.org/10.3390/rs15030620 - 20 Jan 2023

Cited by 5 | Viewed by 2602

Abstract

Glacier velocity is the key to understanding the nature of glaciers. Its variation plays an important role in glacier dynamics, mass balance, and climate change. The Muztag-Kongur Mountains are an important glacier region in the Eastern Pamir Plateau. Under the background of global warming, the glacier velocity variation has been widely considered, but details of the inter-annual and intra-annual changes have not been clear. In this study, we explored the inter-annual and intra-annual variations in the glacier velocity from 1990 to 2021, and the influencing factors, based on Landsat images, Inter-Mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE), and Karakoram Highway (KKH) data product analysis. The results showed the following: (1) the glacier velocity has increased since 1990, and significant growth occurred in 1995–1996. (2) A transverse profile of two typical glaciers was used to analyze the monthly variation in glacier velocity during the year. The peaks of monthly velocity occurred in May and August. (3) Since 1990, the inter-annual precipitation has increased, and the temperature increase slowed down from 2000 to 2013. The trend of inter-annual glacier velocity variation was consistent with that of the precipitation. The glacier velocity peaked in 1996/1997 due to increased precipitation in 1995. The glacier velocity over the year was consistent with the monthly precipitation trends, which indicates that precipitation has a significant influence on the change in glacier velocity. (4) In addition to temperature and precipitation, the glacier velocity variation was moderately correlated with the glacier size (length and area) and weakly correlated with the slope. The spatial distribution of glaciers shows that the spatial heterogeneity of glaciers in the Muztag-Kongur Mountains is affected by the westerly circulation. The long-term glacier velocity variation research of the Muztag-Kongur Mountains will contribute to a better understanding of glacier dynamics within the context of climatic warming, and the different influencing factors were analyzed to further explain the glacier velocity variation. Full article

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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14 pages, 5821 KiB

Open AccessTechnical Note

A Comparative Study of a Typical Glacial Lake in the Himalayas before and after Engineering Management

by Zhaoye Zhou, Xiaoqiang Cheng, Donghui Shangguan, Wangping Li, Da Li, Beibei He, Meixia Wang, Qing Ling, Xiuxia Zhang, Xiaoxian Wang, Lu Chen, Yadong Liu and Wei Chen

Remote Sens. 2023, 15(1), 214; https://doi.org/10.3390/rs15010214 - 30 Dec 2022

Cited by 5 | Viewed by 2205

Abstract

One of the main glacier-related natural hazards that are common to alpine locations is the occurrence of glacial lake outburst floods (GLOFs), which can seriously harm downstream towns and infrastructure. GLOFs have increased in frequency in the central Himalayas in recent years as a result of global warming, and careful management of glacial lakes is a crucial step in catastrophe prevention. In this study, field surveys were conducted on 28 August 2020 and 1 August 2021 with the help of an unmanned aerial vehicle (UAV) and a boat bathymetric system on an unmanned surface vessel (USV), combined with 22 years of Landsat series imagery and Sentinel-2 MSI imagery data. Spatial analysis was then used to investigate changes in lake surface conditions, dam stability, and surrounding topography before and after an integrated project of the Jialong Co lake. The results show that: (1) from 2000 to 2020 (before engineering management), the area of the Jialong Co glacial lake increased from 0.2148 ± 0.0176 km² to 0.5921 ± 0.0003 km². The glacial lake expansion rate from 2000 to 2010 (0.0145 km²/a) was greater than the rate from 2011 to 2020 (6.92

\times

10⁻⁶ km²/a). In 2021 (after engineering treatment), the glacial lake perimeter, area, and volume decreased by 0.6014 km, 0.1136 km², and 1.90 × 10⁷ m³, respectively. The amount of excavation during the project treatment was 8.13 million square meters, and the amount of filling was 1.24 million square meters. According to the results of the unmanned surface vessel (USV), the elevation of the lake surface dropped from 4331 m to 4281 m, and the water level dropped by 50 m (the designed safe water level line dropped by 30 m). (2) The results of the UAV topographic survey and geomorphological analysis showed that the engineered reinforcement of the outlet channel and surrounding dam effectively mitigated severe scouring of the foot of the final moraine at the outlet of the spillway, as well as the likelihood of glacial lake outbursts caused by ice avalanches and landslides. (3) The comprehensive engineering treatment of this typical glacial lake effectively lowered the water level and improved the stability of the moraine ridge and lake dam, providing a scientific foundation for other glacial lake outburst risk assessments and disaster mitigation and management measures. Thus, it is critical to evaluate the impact of comprehensive engineering management of key glacial lakes to support glacial lake management. Full article

(This article belongs to the Special Issue Glacial Lakes and Related Hazards: Mapping, Monitoring, and Risk Assessment)

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