Susceptibility Assessment of Moraine-Dammed Glacial Lakes in the Eastern Himalaya: A Geospatial Approach

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The global warming has contributed to the continuing expansion of the glacial lakes. These topographic depressions, confined by ice, bedrock, moraine, or a combination of these, accumulate the melt water annually, and often the poor structural integrity of moraine dam fails to withstand the pressure exerted by the volume of accumulated water, leading to occurrence of a glacial lake outburst flood (GLOF). Since, GLOFs are mostly an instantaneous phenomenon and have the potential to cause severe damage to the property and loss of lives, a comprehensive analysis of GLOFs is necessary. The present study focuses on Sikkim and Arunachal Pradesh (Indian Eastern Himalaya) to create an inventory of glacial lakes with area > 0.01 km 2 and assess their hazard potential. 340 and 1529 lakes in Sikkim and Arunachal Himalaya were manually identified from the 50 cm high resolution combined product of Worldview-8 and Geo-Eye true Ortho-rectified Satellite Imageries, out of which 27 in Sikkim and 6 in Arunachal Himalaya were identified as moraine dammed lakes. A detailed inventory of these lakes in GIS environment incorporated 14 parameters including 11 crucial controls on outburst susceptibility using AHP. The susceptibility map is classified into 4 classes, namely very high (4 lakes), high (12 lakes), medium (13 lakes) and low (4 lakes). Validation of the susceptibility classes was validated with 3 known GLOF events from the Himalaya. This novel study highlights the need to monitor and assess possible GLOFs in future while providing a high precision base inventory to open further research in this direction. Indian Eastern Himalayas Glacial Lake Outburst Flood (GLOF) Moraine Dammed Glacial Lake AHP Outburst Susceptibility Level Figures Figure 1 Figure 2 Figure 3 Figure 4 1 Introduction Global warming is a major cause of glacier retreat across the world. It is estimated that the global glacial mass reduction could be as high as 18% by the year 2100 relative to 2015. The polar caps and high mountains will be the most extensively affected regions. (Pachauri and Reisinger, 2007 ). High Asian Mountains demonstrate global warming at an average rate of 0.3 ± 0.2°C per decade, thereby, overtaking the average global warming rate of 0.2 ± 0.1°C per decade (Hoegh-Guldberg et al., 2018 ). Climatologists estimate an increase of 2.1°C to 2.6°C in temperature by 2050 and around 3.3°C to 3.8°C by 2080 over the Indian region, which is already experiencing climate change (Verma 2021 ). The rapid increase in global mean temperatures is intensifying glacial melting, which in turn elevates the hazard of glacial lake outburst floods by destabilizing moraine-dammed lakes due to the increased accumulation of meltwater. The Himalaya is one of the largest sources of glacial mass outside the polar region with an estimated glacier coverage of 60,000 km 2 (Islam and Patel 2022). It works as a fresh water tower to millions of lives in downstream region (A. Aggarwal et al. 2016 ). Himalayan glaciers have undergone drastic changes in the last two decades, characterized by significant retreat and mass loss, with glacier mass loss rates doubling between 2000 and 2016 compared to the period from 1975 to 2000 (Bolch et al. 2008 , Maurer et al. 2019 ). The Himalayan glaciers are presently losing an average of about 0.4% of their mass per year (Chand et al. 2017 ) due to an estimated temperature increase between 1°C and 6°C in the region from 1970 to 2005 (Pachauri and Reisinger 2007 ). As the average mean temperature rises around the globe due to human interferences, these glaciers melt and produce a large number of glacial lakes in high altitude areas (Yu, He, and Liu 2022; Liu et al. 2019 ; Shrestha et al. 2010 ; Nie et al. 2020). Due to continuously increasing number of glacial lakes in the Himalaya, the risk of glacial lake outburst flood (GLOF) is also intensifying (Mohanty and Maiti 2021; Yu, He, and Liu 2022; S. Wang, Qin, and Xiao 2015; Yao et al. 2018 ). Pertaining to GLOF, the glacial lakes in the Himalaya mainly classified into 3 categories: (1) ice-dammed; (2) moraine-dammed, and (3) bedrock-dammed (Vilímek et al. 2014 ). Previous studies have demonstrated that the moraine dammed lakes exhibit high susceptibility to breaching, primarily due to composition of their moraines, which are usually the poorly sorted unconsolidated rock fragments plucked from valley floor and carried by glaciers. This type of material is inadequate for securely containing the substantial volumes of water that typically accumulate within these lakes (Veh 2019 ; Fan et al. 2019 ; Hegglin and Huggel 2008; Prakash and Nagarajan 2017 ; S. Aggarwal et al. 2017). Moraine-dammed Lake can further be categorized as End-moraine dammed lake, Lateral moraine dammed lake, Ice-capped Lateral moraine dammed lake and others. However, the end-moraine dammed lakes are the most hazardous lakes, which are responsible for most of the GLOF events (ICIMOD 2011). An unexpected breach of these kind of lakes is a threat to infrastructure and life in downstream areas (Prakash and Nagarajan 2017 ). The Eastern Himalayan region has gained significant attention in the recent years due to its vulnerability to GLOFs. While the western and central parts of the Indian Himalaya have been well-documented in terms of glacial mass and area changes, the eastern region remains relatively understudied (Tiwari et al. 2021 , Islam and Patel 2022, Mohanty, Maiti, and Dixit 2023). As the Eastern Himalayan region is highly prone to the GLOF events, mapping of glacial lakes in this region is crucial for hazard analysis and risk assessment. Therefore, a comprehensive inventory of glacial lakes in the Sikkim and Arunachal Pradesh Himalaya has been created in the present study by mapping the lakes from a high-resolution data at the scale of 1:2000 and below. The geomorphic parameters and dam characteristics have also been included in the dataset with appropriate weightage applied to each parameter to identify the most vulnerable glacial lakes and subsequently assess susceptibility of the lakes to dam failure or an outburst using analytic hierarchy process (AHP). The study utilizes high resolution optical imagery data (50cm spatial resolution) in conjunction with DEM (5m spatial resolution) to create highly accurate inventory of glacial lakes, while also highlighting the need for more research in understanding associated risks and implementing mitigation strategies in the region. 2 Regional setting The Indian Eastern Himalayan landscape is host to rich bio resources, which fulfil miscellaneous needs of the communities living in it (Theengh et al. 2023 ). The Indian summer is responsible for annual precipitation for the Indian sub-continent (Dimri et al. 2016 ). The study area experiences a good amount of precipitation in monsoonal season from June to September. Figure 1 . (a) State boundary map of India showing study area (Sikkim and Arunachal Pradesh) highlighted. (b) District map of Sikkim (c) District map of Arunachal Pradesh 2.1 Sikkim Sikkim is situated in the Himalayan foothills, encompassing an area of 7906 km 2 . The state comprises 28 mountain peaks, over 80 glaciers, 227 high-altitude lakes, 5 major hot springs, and more than 100 rivers and streams. Sikkim is characterized by mountainous terrain with an elevation ranging from 280 m in the south at the border with West Bengal to 8586 m in the northern peak near Nepal and Tibet. Sikkim is bounded in the west by the north-south limb of the Great Himalayan Range, which includes the world's third-highest peak, Khangchendzonga. In the east, it is bounded by the Chola range, and to its south lies the Singalila ridge. The major river of the state is the Teesta, which originates from Chho Lhamo lake in the north and is further augmented by numerous tributaries and rivers, of which Tholung, Lachung, Great Rangeet, and Rangpo are significant drainages. The majority of inhabited regions in Sikkim experience a temperate climate, with temperatures rarely exceeding 28° C during summer months. While most of northern Sikkim experiences severe, arid winters, the southern region remains comparatively less cold. Peak temperatures are typically recorded in July and August, with the lowest temperatures occurring in December and January. During the monsoon season, which extends from May to early October, heavy precipitation increases the likelihood of landslides triggered by localized monsoon activity ( https://www.indiawris.gov.in ). The state of Sikkim is predominantly mountainous, characterized by a lack of any extensive alluvial plains. The alluvium along river channels, which is the youngest geological unit in the region is dated to the Quaternary period. In contrast, the primary rock types that characterize the area are composed of Pre-Cambrian formations, which include phyllites, slates, quartzites, and schists. These lithologies belong to five major geological units i.e. Kanchenjunga gneiss, Darjeeling gneiss, Chungthang schists and gneiss, Lingtse granite gneiss and Daling group. The region exhibits significant geological deformation resulting from tectonic activity and the presence of major thrusts, including the Main Boundary Thrust (MBT), the Main Central Thrust (MCT), and various suture zones. These processes have caused the rock formations to undergo extensive folding, warping, and faulting, which in turn has facilitated the development of numerous lineaments throughout the area. 2.2 Arunachal Pradesh Arunachal Pradesh, situated within the foothills of the Himalaya, is the largest state in northeastern India covering an area of 83,743 km² approximately. The relief of the mountains in the region ranges from over 7000 m to approximately 300 m elevation amsl. The topography of Arunachal Pradesh shows mountainous to sub-mountainous ranges gradually sloping downwards into the alluvial plains of Assam. This geomorphologically diverse landscape plays an important factor in controlling the hydrological processes, influencing local climate and also protecting the state’s unique ecological system. It is divided into valleys by the rivers Kameng, Subansiri, Siang, Lohit and Tirap. India’s Largest River Brahmaputra enters the state from Tibet and flows into Assam where it goes down to Bangladesh and fall into Bay of Bengal. River system of Arunachal Pradesh includes rivers coming from higher Himalayas, Patkoi and Arakan Ranges, finally drain in the Brahmaputra River ( https://www.indiawris.gov.in ). The climate of Arunachal Pradesh varies according to the altitude of the region from temperate to subtropical. At the highest altitude, the state experiences an alpine climate and the lower part experiences hot and humid climatic conditions with a max temperature around 40°C (https://www.indiawris.gov.i n). Arunachal Pradesh experiences heavy rainfall during May to September, average recorded rainfall in the state is 300 centimeters that varies between 80 to 450 centimeters. In the monsoons, the temperature ranges from 22° C to 30° C. In the winter months, the temperature ranges from 15° C to 20° C. The rainfall of the Arunachal Pradesh is heaviest in the country which makes the state landslide prone. Figure 2 . Northeast Region summer rainfall: 1871–2016. (Trend-mm/year) and significance at 10%, 5% and 1% level, rainfall data for the period 1871–2013 based on 306 stations and 2014–2016 based on IMD subdivision rainfall (ESSO/IITM/STCVP/SR/02(2017)/189). 3 Materials and methods The district boundaries of Sikkim and Arunachal Pradesh were demarcated from Survey of India topographic maps at 1: 250,000 scale. Ortho-rectified natural color imagery with a spatial resolution of 50 cm, derived from the WorldView-8 and GeoEye satellite platforms, was employed to precisely delineate the boundaries of glacial lakes. A DEM was generated through the integration of data from both sensors, achieving a spatial resolution of 5 m. The high-resolution imagery and detailed elevation data facilitated extraction of various parameters pertinent to the geometry of the moraine dams and characteristics of glacial lakes. Annual precipitation and mean temperature data were obtained from the Indian Meteorological Department and its state branches, based on recently published reports. Additionally, glacial lake evolution data from the National Disaster Management Authority (NDMA) was utilized to assess changes in these lakes. Maps of seismic activity from the Bureau of Indian Standards (BIS) and mass movement maps from the Department of Science and Technology (DST) were also incorporated into the analysis of glacial lakes. In the present work, all the glacial lakes were mapped and a threshold area of 0.01 km 2 was chosen to distinguish the glacial lakes from ponds and waterlogged areas. The process was followed by identification and sorting of moraine dammed glacial lakes based on 14 characteristic parameters including geometric, local relationship of the feature with surrounding structures, and stability controlling building material properties. The regional seismicity, mass movement, and climatic conditions, which could be effective in contributing to or triggering a dam breach were also considered. AHP (Analytical hierarchy Process) method was adopted for evaluating the parameters which can trigger a moraine dammed glacial lake. At last, glacial lake outburst susceptibility level was introduced for GLOF assessment. The datasets used along with their specifications and their role in the study elaborated in the Table 1 . Table 1 Details of data sources used Dataset Date Resolution Source Use Worldview-8 and Geo-Eye true Ortho-rectified Satellite Imagery 2018 50cm VRICON Glacial lake mapping DEM 2018 5m VRICON Elevation, slope and dam geometry measurements Terra Explorer 3D - - Terra Explorer Lake characteristics, Dam Geometry, and surrounding conditions Measurement Topographic map 2002 1:50000 Survey Of India (OSM) State Boundary Delineation Mass movement maps 2009 DST (Department of Science and Technology), Govt. of India National Disaster Management Authority, NDMA Outburst susceptibility assessment Seismic zone map 1893–2002 Bureau of Indian Standard Outburst susceptibility assessment Meteorological data 2009–2018 1871–2016 - Hydrome Division, India Meteorological Department, New Delhi Indian Institute of Tropical Meteorology (IITM) Earth System Science Organization (ESSO) Ministry of Earth Sciences (MoES) PUNE, INDIA Outburst susceptibility assessment Lake evolution data 2011–2018 National Disaster Management Authority, NDMA Outburst susceptibility assessment 3.1 Identification of potentially dangerous moraine dammed glacial lakes and selection of their outburst susceptibility parameters A moraine dam is a natural barrier composed of often unsorted sediments ranging from sand to boulders, and ice, confining the meltwater from glaciers. It forms when a glacier retreats and leaves behind a pile of debris (Jain, Ahmed, and Lohani 2023). A moraine dam can block the flow of meltwater from the glacier and create a glacial lake, which could be found in frozen state also (Khadka, Zhang, and Chen 2019). Identification of such lakes can contribute to segregate potentially hazardous lakes and mitigate outburst floods in mountainous region. The resultant glacial lakes were further imported in the 3D software Terra Explorer. Properly blocked and large flowing moraine dammed lakes were visually identified and demarcated in the glacier region. Previous studies have defined the predominant geometric and geomorphic parameters to classify the glacial lake outburst susceptibility level towards breaching and outburst (Islam and Patel 2022; McKillop and Clague 2007; S. Aggarwal et al. 2017; Prakash and Nagarajan 2017 ). In the present study, 14 parameters were selected to generate glacial lake inventory and to categorize the moraine dam glacial lake’s stability. These parameters were extracted using high resolution satellite imagery, DEM, and lake evolution data. 3.1.1 Moraine dam geometrical parameters The geometry of the moraine dam is an important factor in defining the stability of the dam which governs the susceptibility to breaching. These parameters are: Moraine Height: A higher moraine dam can hold more water in glacial lake, but it can also increase the stress on the dam and make it more prone to breaching which can also lead to bigger flooding events (Yu, He, and Liu 2022). Width of Crest: A wider dam crest permits more water to pass through, resulting in a higher peak discharge and a larger flood volume (Prakash and Nagarajan 2017 ). Slant Height: The slant height of the moraine dam can influence the pressure exerted by the water on the moraine dam, as well as the volume of water that can be released in case of a breakdown (Ahmed et al. 2021 ). Bottom Width: It influences the amount of water that can flow under or through the dam in case of a breach or a seepage (Begam and Sen 2019). Moraine Width to Height Ratio: Width to height ratio impacts the hydraulic gradient which leads to piping within the moraine dam and slope failure. Piping can weaken the strength of internal structure of dam and resulting in full or partial failure of a dam (Huggel et al. 2004 ). Distal Face Slope: It shows the probability of slope failure and the erodibility of a moraine dam which may trigger a GLOF event (Xin- et al. 2008). Geometrical factors of moraine dam were calculated with the help of 3D rendering of satellite images and with tools available for marking and measuring within 3D software. Firstly, the high resolution 2D satellite imagery was ingested in Tera Explorer 3D software. then, parameters of already identified moraine dammed glacial lakes were measured and calculated in 3D environment. 3.1.2 Glacial lake characteristics Lake Area: Glacial lakes which are larger in size are more prone to GLOF as they usually contain more water and exposed to potential mass movement (Prakash and Nagarajan 2017 ; Khadka, Zhang, and Chen 2019; Senese et al. 2018 ). Distance between Glacier Lake: Smaller the distance between lake and parent glacier, it is more prone to associated dynamics (Xin- et al. 2008). Freeboard: It indicates whether a dam will fail due to overtopping of a displacement wave. Overtopping waves have potential to erode the dam which leads to dam failure (Islam and Patel 2022). Slope Between Lake and Glacier: A higher slope difference between the glacier snout and lake outlet would be more likely to bring the lake to overflow its bounds (S. Wang, Qin, and Xiao 2015). Percentage increase in lake Area: An increase in lake area resulting in an increased volume of water in lake if it is in direct contact with glacier (Prakash and Nagarajan 2017 ). Area of lake was calculated semi-automatically with the help of geospatial tools, changes in lake area of moraine dammed glacial lakes were calculated with data provided by NDMA (National Disaster Management Authority) from 2011 to 2017, the distance, freeboard, snout steepness and slope between lake and its adjacent glacier was calculated and measured with Terra Explorer 3D software. 3.1.3 Moraine dam material characteristics Moraine-dammed glacial lakes are prone to breaching due to the unconsolidated material that constitutes the dam and the steepness of surroundings (Prakash and Nagarajan 2017 ; McKillop and Clague 2007). Material properties of moraine dam can be determined only through field investigation, which was carried out at two moraine dammed glacial lakes in Sikkim. These lakes were included in high outburst susceptibility level and low susceptibility. 3.1.4 Surrounding topographic and climatic conditions Precipitation/Rainfall: Rainfall is one of the key factors to cause the outburst flood. It induces GLOF by different mechanisms such as sudden increase in volume of the water in the lake increases outward pressure on the dam walls leading to a subsequent breach. It may also trigger landslides or avalanches during the monsoon season, which indirectly may initiate a GLOF event. Periodic rainfalls occurring at regular intervals weaken the moraine dam by erosion and saturate the dam material, eventually becoming a cause of displacement waves or overtopping of the moraine dam. The rainfall may also cause melting of the ice cores, leading to the collapse of the moraine dam and the release of a large volume of water . Seismicity: Sikkim and Arunachal Pradesh are situated in the high-risk seismic zone IV, V of the Indian seismic zone map, respectively. Sikkim state is spread out on the Himalayan Mountain range with two main thrust faults, the Main Boundary Thrust (MBT) and Main Central Thrust (MCT) crossing the state. These faults are responsible for the generation of earthquakes in this region. Arunachal Pradesh is situated on the eastern Himalayan Mountain range, where two major tectonic plates, the Indian plate and the Eurasian plate, collide and generate earthquakes. Seismic activity like mass movements, which can either rupture the moraine dam or the debris released can increase water level resulting in overtopping of the lake. Mass Movement: The accumulation of debris or steep scarps around a lake is essential to its hazard status, since mass movements into a lake can led it to overflow (Huggel et al. 2004 ; Allen et al. 2016 ). Mass wasting associated with landslides, avalanches, or rockfalls, can destabilize the moraine dam or increase the water level and pressure in the lake, and cause a large-scale natural hazard event facilitated by the GLOF. Precipitation data of lakes were obtained from different sources including monthly or yearly rainfall data from Indian Meteorological Department (IMD) state branches, Indian Institute of Tropical Meteorology (IITM), Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), and published reports. Seismic data were collected from BIS (Bureau of Indian Standard) and readily available seismic zone maps. The information regarding sites and size of mass movement was derived from interpretation of steep slopes around the lake from 3D visualization of high-resolution satellite image, published literatures, Department of Science and Technology (DST), and National Disaster Management Authority (NDMA). 3.2 Moraine dammed glacial lake outburst susceptibility analysis and assessment The historical data of GLOF events in the Himalayan region were collected from the literature surveys and published reports to analyze and evaluate the contribution of the selected parameters for moraine dam breaching (Jain and Lohani 2012). Mass movement is considered a major cause of dam failure as it has triggered 22 outbursts out of 41 GLOF events in the Himalayan region (Prakash and Nagarajan 2017 ). Avalanche and landslides caused by the earthquake have been registered in the past events in the Himalayan region which is a causative factor in the moraine dam failure. The self-destruction of the dam is caused by high hydrostatic pressure, snowmelt, moraine slope failure and degradation of dam over the period, resulting in 15 outburst events out of 41 in the Himalayan region (Prakash and Nagarajan 2017 ). Out of 14 parameters used to make glacial lake inventory, 11 crucial parameters were selected for outburst susceptibility analysis which summarized in the table below. Table 2 Index values of parameters with their sub-criteria S. No. Factors Classes Probability of Outburst Index value (Ci) Reference 1 Lake Area > 0.10 sq. Km 0.05–0.10 sq. Km 0.01–0.05 sq. Km High Medium Low 1.00 0.50 0.25 (Bolch et al., 2011; Prakash* and Nagarajan 2017) 2 Increase in lake Area > 100% 50–100% < 50% High Medium Low 1.00 0.50 0.25 (Bolch et al., 2011, Prakash* and Nagarajan 2017) 3 Glacier lake Distance In contact 500 m High Medium Low 1.00 0.50 0.25 (Prakash* and Nagarajan 2017; Wang et al., 2011) 4 Slope b/w lake and Glacier > 21° < 12° − 21° < 12° High Medium Low 1.00 0.50 0.25 (Prakash* and Nagarajan 2017, Wang et al., 2011) 5 Moraine Width to Height Ratio 0.5 High Medium Low 1.00 0.50 0.25 (Huggel et al., 2004 , Prakash* and Nagarajan 2017) 6 Width of Crest 60 m High Medium Low 1.00 0.50 0.25 (Prakash* and Nagarajan 2017) 7 Distal face Slope > 20° 12°- 20° < 12° High Medium Low 1.00 0.50 0.25 (Prakash* and Nagarajan 2017; Wang et al., 2011) 8 Freeboard 0 (Surface Drainage) 5m High Medium Low 1.00 0.50 0.25 ( Prakash* and Nagarajan 2017) 9 Mass Movement Impact Susceptibility High Medium Low High Medium Low 1.00 0.50 0.25 (Bolch et al., 2011; Huggel et al., 2004 , Prakash* and Nagarajan 2017) 10 Extreme Rainfall events Frequent Sporadic Unlikely High Medium Low 1.00 0.50 0.25 (Huggel et al., 2004 , Prakash* and Nagarajan 2017) 11 Seismic Zone Zone 5 Zone 4 Zone 3 High Medium Low 1.00 0.50 0.25 (Prakash* and Nagarajan 2017) Each parameter was further divided into three classes according to the potential of the parameter to cause an outburst. Index values were assigned to these three classes with respect to their potential based on the conditions and controls described by various researchers and experts.1 was assigned as highest, 0.5 as medium and 0.25 as lowest index value (Ci). All the parameters were then analyzed and calculated to estimate the relative significance based on the knowledge and information gained from literature survey, published reports, field data, past GLOF events etc. Eventually all the parameters were ranked and weighed using AHP. This multi criteria technique (AHP) incorporates the elusive aspects associated with the glacial lake factor using pairwise comparison matrix (given below in Table 3 ). A pairwise comparison matrix was created by allocating a value of 1 to 9 to each pairwise comparison (Rass et al. 2020 ; Drieniková et al. 2010 ). Value 1 in the pairwise comparison matrix denoted both factors are equally important, 3 as moderate importance, 5 as strong importance, 7 as very strong importance over, and 9 represented one of the parameters was extremely important (Ndalianis et al. 1995; Eldrandaly 2013 ; Nadja and Karlheinz 2004). Table 3 Pairwise comparison matrix of parameters computed using the AHP S. No. Factors 1 2 3 4 5 6 7 8 9 10 11 1 Lake Area 1 0.5 0.5 0.5 0.5 2 1 0.33 0.25 1 2 2 Increase in lake Area 3 1 2 3 2 2 2 1 0.33 2 3 3 Glacier lake Distance 2 0.5 1 1 2 3 2 0.5 0.25 1 2 4 Slope b/w lake and Glacier 2 0.33 1 1 0.5 2 1 0.5 0.25 1 2 5 Moraine Width to Height Ratio 2 0.5 1 2 1 2 1 0.5 0.25 0.5 2 6 Width of Crest 0.5 0.5 0.33 0.5 0.5 1 0.5 0.5 0.25 0.5 1 7 Distal face Slope 1 0.5 0.5 1 1 2 1 0.5 0.33 1 1 8 Freeboard 3 1 2 2 2 2 2 1 0.33 2 2 9 Mass Movement Impact Susceptibility 4 3 4 4 4 4 3 3 1 3 3 10 Extreme Rainfall events 1 0.5 1 1 2 2 1 0.5 0.33 1 2 11 Seismic Zone 0.5 0.33 0.5 0.5 0.5 1 1 0.5 0.33 0.5 1 The concept of consistency is one of the characteristics that distinguishes AHP from the other multi criteria techniques and gives coherence to the method (Herath and Prato 2017; Aguarón et al. 2019; Kulakowski 2020 ). The consistency of the matrix of order n is evaluated. Comparisons made by this method are subjective and the AHP tolerates inconsistency through the amount of redundancy in the approach (J. Wang, Chakraborty, and Ouyang 2011). If this consistency index fails to reach a required level, then answers to comparisons may be re-examined. The consistency index, CI, is calculated as CI = (ƛ max - n)/ (n − 1) where ƛ max is the maximum eigenvalue of the judgement matrix. This CI can be compared with that of a random matrix, RI (Saaty,1980). The ratio derived; CR (= CI/RI) is termed the consistency ratio. Saaty suggests the value of CR should be less than 0.1. A CR with a value higher than 0.10 requires re-evaluation of the judgments in the original matrix of pairwise comparisons (Drobne and Lisec 2009; Selçuk 2013 ). The AHP produces weight values for each alternative based on the judged importance of one alternative over another with respect to a common criterion (Vargas 2011 ; Hendrikx, Murphy, and Onslow 2014; Nadja and Karlheinz 2004). Based on the history of past GLOF (Table 6 ) occurrences, a pairwise comparison matrix had generated for the parameters by assigning higher values to those parameters whose occurrence is more frequent associated with the GLOF events. Weights (Wi) were calculated for each parameter. The final weights were calculated of each parameter by multiplying the Wi factor weight with the Ci class index value. The outburst susceptibility score for each lake was completed by adding the final weights of all the parameters (Prakash and Nagarajan 2017 ). 4 Results 4.1 Glacial lake mapping Primary focus of this study was to prepare an inventory of moraine dammed glacial lakes and their physical characteristics, also assessing their vulnerability for breaching phenomena. A total of 766 lakes were found in Sikkim with 340 lakes having area of 0.01 Km 2 and above. Out of these, 27 glacial lakes having area 8.3379 km 2 were found to be moraine dammed in nature from its total area7096 Km 2 . Similarly, total 2834 lakes were found in Arunachal Pradesh with 1529 lakes having area of 0.01 Km 2 and above. Among these, 6 moraine dammed lakes were found with area acquired 0.77 Km 2 from its total area 82115 Km 2 . 4.2 Inventory of moraine dammed glacial lakes Inventories of vulnerable moraine dammed glacial lakes using 14 parameters were prepared for Sikkim and Arunachal Pradesh (given in Table 4 and 5 ) including parameters of moraine dammed lakes such as moraine height, width, slant height, bottom width, and freeboard; lake characteristics (lake proximity to glacier, slope between lake and glacier, lake Area) were extracted using 3D visualization and analysis through software Terra Explorer. Surrounding conditions (Seismicity, mass movement, climatic conditions) were assessed with previous published maps and reports. Changes in moraine dammed lakes were also observed with the data provided by NDMA for the period of 2011 to 2018 for observing changing trend of lake per year. Table 4 Moraine Dammed Glacial Lake Inventory of Sikkim with Lake ID and other important measured parameters Sr. No. Lake ID Area (Km 2 ) Glacier lake Distance (m) Freeboard (m) Width of Crest (m) Slant height(m) Moraine Height (m) Bottom Width (m) Moraine Width/Height Ratio Slope Between Lake and Glacier (°) % increase in Lake Area Distal Face Slope (°) Precipitation Seismicity Mass Movement 1 L1 0.0151 842 6.00 27.43 33.20 5.83 32.68 4.70 12.04° Low 30.95° Normal IV low 2 L2 0.2630 0 45.60 32.57 83.72 20.92 81.06 1.5 14.23° Low 32.92° Normal IV low 3 L3 0.1222 1249 8.00 28.56 24.77 6.14 24.00 4.65 4.58° Low 16.42° Normal IV low 4 L4 0.5714 0 23.25 5.00 30.70 11.140 28.61 0.44 18.62° Low 31.8° Normal IV high 5 L5 1.1758 0 4.00 4.68 95.10 12.73 94.24 0.36 4.73° Low 26.69° Normal IV high 6 L6 0.0627 0 3.00 17.58 77.51 15.26 75.99 1.15 19.61° Low 17.95° Normal IV low 7 L7 0.0355 870 2.00 5.78 11.70 0.15 11.70 38.53 2.82° Low 26.36° Normal IV low 8 L8 0.0266 364 6.63 7.26 15.48 2.19 15.32 3.31 10.31° Low 29.09° Normal IV high 9 L9 0.0192 0 0.00 6.21 22.23 1.23 22.20 5.04 10.26° Low 43.49° Normal IV high 10 L10 0.1053 0 20.01 11.19 129.26 2.69 129.23 4.16 13.75° Low 23.45° Normal IV High 11 L11 0.1286 0 11.03 2.87 91.09 8.18 90.72 0.35 18.42° Low 34.02° Normal IV medium 12 L12 0.1089 528 0.00 1.00 25.26 5.92 24.56 0.16 3.57° Low 20.41° Normal IV medium 13 L13 0.0388 625 4.00 2.56 38.83 2.77 38.73 0.92 7.21° Low 29.51° Normal IV high 14 L14 0.1784 0 4.00 29.43 34.04 2.51 33.95 11.72 17.94° Low 10.62° Normal IV medium 15 L15 0.0419 0 5.23 3.72 13.96 2.20 13.79 1.69 23.6° Low 27.42° Normal IV low 16 L16 0.0263 0 5.63 4.69 16.10 0.51 16.09 9.19 24.76° Low 27.91° Normal IV medium 17 L17 0.0874 0 23.82 38.04 46.77 5.17 46.48 7.35 23.75° Low 32.56° Normal IV low 18 L18 0.3161 0 7.66 7.67 47.95 2.26 47.90 3.39 9.2° Low 20.02° Normal IV medium 19 L19 0.9716 0 2.66 6.19 163.17 2.91 163.14 2.12 10.41° Low 18.69° Normal IV Low 20 L20 0.4313 0 9.92 89.950 136.88 23.25 134.89 3.86 17.01° Low 21.14° Normal IV Low 21 L21 0.3153 0 9.13 438.03 433.24 43.48 431.05 10.07 6.53° Low 20.37° Normal IV medium 22 L22 1.2236 0 0.00 293.16 329.07 25.63 328.07 11.43 6.08° Low 29.24° Normal IV Low 23 L23 0.3516 0 31.27 150.02 175.18 30.95 172.42 4.84 28.97° Low 14.17° Normal IV Medium 24 L24 0.3040 1516 0.00 206.70 32.90 6.44 32.26 32.09 4.44° Low 12.01° Normal IV Low 25 L25 0.6766 0 0.00 242.59 455.59 14.76 455.35 16.43 4° Low 30.95° Normal IV Low 26 L26 0.6605 0 13.20 23.470 44.48 3.25 44.36 7.22 43.28° Low 19.25° Normal IV medium 27 L27 0.0803 224 85.63 14.450 116.65 46.09 107.16 0.31 17.67° Low 19.81° Normal IV medium Table 5 Moraine Dammed Glacial Lake Inventory of Arunachal Pradesh with Lake ID and other important measured parameters Sr. No. Lake ID Area (Km 2 ) Glacier lake Distance (m) Freeboard (m) Width of Crest (m) Slant height(m) Moraine Height (m) Bottom Width (m) Moraine Width/Height Ratio Slope Between Lake and Glacier (°) % increase in Lake Area Distal Face Slope (°) Precipitation Seismicity Mass Movement 1 L1 0.165 0 1.04 7.02 111.05 28.52 107.32 0.123 45.92° Low 14.88° Deficient V Low 2 L2 0.134 0 1.11 12.3 0 0 146.53 0 24.69° Low 21.67° Deficient V Low 3 L3 0.071 0 0.5 8.38 142.51 35.23 138.08 0.118 17.42° Low 14.31° Deficient V Low 4 L4 0.371 0 0.5 63.5 275.6 38.01 272.96 0.835 7.24° Low 7.93° Deficient V Low 5 L5 0.027 486.46 5.48 13.2 323.68 130.16 296.35 0.050 18.27° Low 23.71° Deficient V Low 6 L6 0.022 0 1.14 24.44 68.09 1.56 74.10 7.833 26.42° Low 27.04° Deficient V Low Table 6 Data, characteristics and outburst susceptibility scores of past three events in Himalayan regions computed using the AHP Area (Km 2 ) % increase in Lake Area Glacier lake Distance (m) Slope Between Lake and Glacier (°) Width of Crest (m) Moraine Width/Height Ratio Freeboard (m) Distal Face Slope (°) Precipitation Seismicity Mass Movement Weight References Dig Tso Eastern Nepal 04-Aug1985 0.5 Medium 0 10 > 5 30–35 Medium High High 0.70 (Lamsal et al., 2016; Osti et al., 2011; Osti and Egashira, 2009) Chorabari Kedarnath India 17-Jun2013 0.025 Low No Glacier NA 5 35–40 High High High 0.63 (Allen et al., 2015; Das et al., 2015) 4.3 GLOF outburst susceptibility assessment Out of 14 parameters calculated for every moraine dammed lake, 11 parameters (refer Table 2 ) were analyzed for outburst susceptibility assessment. Slant height, Moraine height and bottom width) were not considered for outburst assessment because these 3 parameters were subordinate of moraine width to height ratio which was one of crucial parameter in outburst analysis. Out of total 1869 lakes; 33 moraine dammed lakes were used for outburst susceptibility analysis based on 11 important parameters. Moraine dam geometry, lake characteristics, rainfall events, mass movement and seismicity were examined and computed. Eventually, lake outburst susceptibility score for each moraine dammed glacial lake was calculated using AHP technique. The outburst susceptibility level of moraine dammed lakes was divided into four classes, low, medium, high and very high based on susceptibility score. AHP technique was applied to the 3 lakes in the Himalayan region (given in Table 6 ) which have suffered from outburst in past for verification (Prakash* and Nagarajan 2017). Two lakes had the outburst susceptibility score > 0.7, and the other one had the score 0.63. therefore, a score of 0.65 was used as a threshold for classifying lakes with very high outburst susceptibility, 0.55 representing high and 0.45 as medium susceptibility. Out of the 27 lakes in Sikkim, 24 lakes are situated in North Sikkim district and the remaining 3 lakes are in West Sikkim district. In North Sikkim, 2 lakes are very highly susceptible having weight scores (L11 having score 0.7225 and L1 having core 0.735) respectively, 8 lakes falling under high outburst susceptibility score, 10 lakes are falling in medium danger level and 4 moraine dammed lakes were falling under low outburst susceptibility level. There are 3 moraine dammed lakes in West Sikkim, out of which 2 lakes have very high susceptibility score and 1 lake has high susceptibility score. Out of 27 moraine dammed lakes in Sikkim (Table 7 ), 4 were classified as very high and 9 as highly susceptible, whereas 10 lakes came under medium and 4 lakes have low outburst susceptibility score (Fig. 3 ). The 13 moraine dammed lakes which were falling within the high to very high outburst susceptibility range should be further studied and monitored for detailed hazard assessment. Table 7 Moraine dammed Glacial Lakes of Sikkim with their outburst susceptibility weights Sr.No. Lake_ID Area (Km 2 ) Latitude Longitude Weights 1 L1 1.175335 28° 0' 19.932" N 88° 42' 47.740" E 0.735 2 L2 0.316116 27° 32' 0.101" N 88° 5' 8.552" E 0.5625 3 L3 1.223572 27° 54' 45.977" N 88° 11' 48.547" E 0.515 4 L4 0.67658 27° 49' 18.103" N 88° 14' 55.693" E 0.56 5 L5 0.062723 27° 56' 34.019" N 88° 16' 19.644" E 0.4725 6 L6 0.014535 27° 51' 28.086" N 88° 13' 58.079" E 0.375 7 L7 0.304046 27° 51' 6.539" N 88° 14' 26.045" E 0.4475 8 L8 0.035631 27° 57' 53.354" N 88° 22' 8.584" E 0.485 9 L9 0.315266 27° 58' 53.534" N 88° 30' 30.991" E 0.5325 10 L10 0.080269 28° 0' 0.916" N 88° 32' 53.367" E 0.4775 11 L11 0.571389 27° 58' 30.038" N 88° 36' 58.225" E 0.7225 12 L12 0.085966 27° 52' 23.304" N 88° 38' 16.295" E 0.5075 13 L13 0.660525 27° 59' 33.207" N 88° 32' 45.090" E 0.565 14 L14 0.019722 27° 33' 57.970" N 88° 7' 0.457" E 0.74 15 L15 0.105257 27° 33' 45.581" N 88° 7' 23.367" E 0.685 16 L16 0.181697 27° 58' 7.235" N 88° 47' 49.269" E 0.545 17 L17 0.025311 27° 57' 3.617" N 88° 42' 16.003" E 0.605 18 L18 0.027547 27° 51' 37.166" N 88° 51' 53.759" E 0.5775 19 L19 0.045292 27° 51' 3.933" N 88° 52' 32.442" E 0.515 20 L20 0.104255 27° 52' 23.580" N 88° 47' 21.676" E 0.6025 21 L21 0.03745 27° 51' 50.996" N 88° 48' 9.478" E 0.6125 22 L22 0.118736 27° 43' 22.274" N 88° 41' 25.567" E 0.5975 23 L23 0.351627 27° 56' 55.360" N 88° 18' 19.002" E 0.585 24 L24 0.431334 28° 0' 21.314" N 88° 29' 35.213" E 0.4875 25 L25 0.260014 28° 0' 52.126" N 88° 33' 42.028" E 0.4975 26 L26 0.123446 28° 0' 52.028" N 88° 39' 8.097" E 0.3825 27 L27 0.971621 28° 0' 24.844" N 88° 41' 53.173" E 0.5 Arunachal Pradesh has 6 moraine dammed lakes in Tawang and West kameng districts. All lakes are located in Kangto Glacier region which is the highest point in Arunachal Pradesh (details given in Table 8 ). The area in which Kangto Glacier is located lies in the Lada circle of East Kameng district of the state. East side of Tawang district where kangto glacier falls has 4 moraine dammed glacial lakes. from which 2 lakes were highly susceptible and 3 lakes have medium outburst susceptibility level (Fig. 4 ). West Kameng has 1 moraine dammed glacial lake with high outburst vulnerability level. Table 8 Moraine dammed glacial lakes of Arunachal Pradesh with their outburst susceptibility weights Sr.No. Lake_ID Area (Km 2 ) Latitude Longitude Weights 1 L1 0.070938 27° 44' 0.191" N 92° 22' 25.167" E 0.59 2 L2 0.024471 27° 45' 39.101" N 92° 24' 12.775" E 0.4875 3 L3 0.023577 27° 45' 21.202" N 92° 23' 39.420" E 0.545 4 L4 0.132661 27° 45' 21.063" N 92° 24' 3.796" E 0.635 5 L5 0.132257 27° 43' 39.450" N 92° 26' 6.144" E 0.59 6 L6 0.353295 27° 46' 12.492" N 92° 25' 57.475" E 0.535 The field investigation was carried out at two moraine dammed glacial lakes in Sikkim which were identified with the help of geospatial techniques and falling under high outburst susceptibility level and low susceptibility level with ID number (L13, L10 shown in Table 7 ) having area 0.6605 Km 2 , 0.0803 Km 2 respectively via Café 15000 at (27° 59' 33.207" N, 88° 32' 45.090" E), (28° 0' 0.916" N, 88° 32' 53.367" E) at 16000 ft was scheduled from 29.11.2019 to 08.12.2019. At the time of visit, L13 moraine dammed glacial lake’s water level was at 5 to 15 m from surface level. Height was variable with general trend of decreasing elevation from source towards the outlet. It showed the typical moraine dam characteristics such as unconsolidated rock fragments (regolith) ranging from boulders to pebbles with lack of any prominent sorting in sediment size. Apparently, the outlet was clearly marked by arrangement of subrounded rock fragments in a channel forming downslope from the mouth of the glacier, suggesting an annual discharge of glacial melt water. The second glacial lake was situated adjacent on the upslope implies the origin of the lake from a retreating glacier and having same material composition like lake13. 5 Discussion 5.1 Glacial Lake dynamics Every single lake or pond in study area was demarcated with the help of high-resolution data which could be used for monitoring of lake evolution in future. Moraine dammed glacial lake identification and parameters calculation was also executed on 5m spatial resolution DEM and Ortho-rectified natural color imagery of 50cm spatial resolution which improved glacial lake parameter visualization and demarcation for every single moraine dammed lake over medium resolution used in various studies (Prakash and Nagarajan 2017 ; S. Aggarwal et al. 2017; Islam and Patel 2022). 3D Software (Terra explorer) was considered over internet-based services because these services did not provide orthorectified data which could make incorrect feature calculation. MDGL evolution data (refer section 3 ) provided by NDMA (National Disaster Management Authority) exhibited an average increasing trend less than 50% which displayed low outburst susceptibility of lakes in study area (Table 2 ). Heavy rainfall/precipitation was a possible factor for incidence of GLOF event in (Uttarakhand and Sikkim) Indian Himalaya occurred in the 2013 and 2023 respectively, which caused widespread devastation and loss of lives. Therefore, it is important to monitor the hydrological and meteorological conditions of glacial lakes to assess and mitigate the risk of GLOFs. 5.2 Outburst Susceptibility Assessment The present study found new potentially dangerous lakes in the study area (refer Table 7 and 8 ) with the help of high-resolution data which could be further used for flood simulation modelling in downstream regions. Landslide and precipitation were found to be the main dominant parameters in this region which cause outburst by overtopping and displacement wave mechanism, weakening the moraine dam of a glacial lake. The AHP based methodology for outburst susceptibility assessment built on behalf of past studies which uses similar quantitative and qualitative approaches (Xin- et al. 2008; S. Aggarwal et al. 2017; Islam and Patel 2022; Prakash and Nagarajan 2017 ). AHP method was used despite other multi criteria techniques or other present methodologies, because it suited best for the present article for outburst susceptibility assessment. Although the AHP method is simple and systematic it suffers from certain limitations, such as involving various experts to ensure consistency of judgments, time-consuming data acquisition and a long process. The Threshold accomplished for classification of outburst level was also based on past GLOF events in the Himalaya. Thus, first-order of proposed AHP based method was used to identify and prioritize potentially hazardous lakes in the study area. 6 Conclusions Present Study included mapping of all glacial lakes in Sikkim and Arunachal Pradesh with high resolution satellite imagery and Digital Elevation Model. Moraine dammed Glacial Lake inventories have prepared with the computation of 14 parameters playing major role in triggering Glacial Lake Outburst Hazard in the downstream areas. It was difficult to obtain and measure the moraine dam parameters, dam material properties, lake depth measurements, drainage conditions and the presence of ice in moraines manually and using medium-resolution satellite data as various studies have done till now. hence, we have attempted to extract GLOF triggering parameters with the help of availability of very high-resolution data. It may be possible to identify and prevent potential GLOF events by measuring and monitoring of moraine dams. As result concluded that 4 lakes in Sikkim have very high outburst susceptibility level and 9 lakes as high likewise in Arunachal Pradesh 3 lakes are highly susceptible to outburst. Mitigation of these lakes is crucial for hazard assessment. These lakes should be regularly monitored with the help of different available technologies like drone/aerial survey etc. These techniques can be used for artificial triggering of a moraine dam of glacial lake at high elevation areas and can prevent devastating impacts of outburst hazard in downstream areas. Declarations Disclosure Statement No potential conflict of interest was reported by the authors Funding NA Ethics Declaration NA Author Contribution All three authors conducted the research work.Sangeeta Pohal and Munmun Baisantry wrote the manuscript. Chitesh Sharma reviewed the manuscript. References Aggarwal, Arpit, Sanjay K. Jain, Anil K. 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Veh, Georg. 2019. “Outburst Floods from Moraine-Dammed Lakes in the Himalayas,” 134. Verma, Omkar. 2021. “Climate Change and Its Impacts with Special Reference to India.” In. https://doi.org/10.1007/978-3-030-67932-3_3 . Vilímek, Vít, Adam Emmer, Christian Huggel, Yvonne Schaub, and Sara Würmli. 2014. “Database of Glacial Lake Outburst Floods (GLOFs)-IPL Project No. 179.” Landslides 11 (1): 161–65. https://doi.org/10.1007/s10346-013-0448-7 . Wang, John, Chandana Chakraborty, and Huanyu Ouyang. 2011. “The Analytic Hierarchy Process.” Encyclopedia of Decision Making and Decision Support Technologies. https://doi.org/10.4018/9781599048437.ch003 . Wang, Shijin, Dahe Qin, and Cunde Xiao. 2015. “Moraine-Dammed Lake Distribution and Outburst Flood Risk in the Chinese Himalaya.” Journal of Glaciology 61 (225): 115–26. https://doi.org/10.3189/2015JoG14J097 . Xin-, Wang, Shiyin Liu, Wanqin Guo, and Junil Xu. 2008. “Assessment and Simulation of Glacier Lake Outburst Floods for Longbasaba and Pida Lakes, China.” Mountain Research and Development 28 (3–4): 310–17. https://doi.org/10.1659/mrd.0894 . Yao, Xiaojun, Shiyin Liu, Lei Han, Meiping Sun, and Linlin Zhao. 2018. “Definition and Classification System of Glacial Lake for Inventory and Hazards Study.” Journal of Geographical Sciences 28 (2): 193–205. https://doi.org/10.1007/s11442-018-1467-z . Yu, Bin, Yuanxun He, and Yang Liu. 2022. “Quantitative Susceptibility Assessment of Breach of Moraine-Dammed Lakes.” Diqiu Kexue - Zhongguo Dizhi Daxue Xuebao/Earth Science - Journal of China University of Geosciences 47 (6). https://doi.org/10.3799/dqkx.2021.161 . Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5394608","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":384671597,"identity":"0c26b9fb-d3f6-4823-a76e-e06d82041d8a","order_by":0,"name":"Sangeeta Pohal","email":"","orcid":"","institution":"Defence Geoinformatics Research Organisation, DRDO","correspondingAuthor":false,"prefix":"","firstName":"Sangeeta","middleName":"","lastName":"Pohal","suffix":""},{"id":384671598,"identity":"bb0f8b79-5685-4450-b4b6-c4aa92e818df","order_by":1,"name":"Chitesh Kumar Sharma","email":"","orcid":"","institution":"Defence Geoinformatics Research Organisation, DRDO","correspondingAuthor":false,"prefix":"","firstName":"Chitesh","middleName":"Kumar","lastName":"Sharma","suffix":""},{"id":384671599,"identity":"d644de89-f80c-4ffd-ada1-459c5817c090","order_by":2,"name":"Munmun Baisantry","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYPCCAwxsUJYcmPuAaC0HGBiMwXQCMVpgVGIDiIFPi+6M3KObeXfckefjP/zs8cc9h9Pnhx1+CLTFTk63AbsWsxt5abd5zzwzbJNIMzc48Oxw7sbbaQZALcnGZgdwackxu83bdpixTYLBTOLAAaCW2QkgLQcStxHQYt/Gf/wbSEu64ez0D0RpSWxjyAHbkiAvnUPAljNvzG7ObXuW3CaRUyZx5kC64QbpnIIDCQZ4/HI8x+zG27Y7tvP7j2+TqDhgLS8/O33zhw8VdnK4tKCDZgYDsEoD4pSDQB2DfAPxqkfBKBgFo2BkAACSuWyWWwLthAAAAABJRU5ErkJggg==","orcid":"","institution":"Defence Geoinformatics Research Organisation, DRDO","correspondingAuthor":true,"prefix":"","firstName":"Munmun","middleName":"","lastName":"Baisantry","suffix":""}],"badges":[],"createdAt":"2024-11-05 10:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5394608/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5394608/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":70481090,"identity":"fe0ad776-a180-4047-9cb7-5f750793ffc9","added_by":"auto","created_at":"2024-12-03 14:55:52","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":161960,"visible":true,"origin":"","legend":"\u003cp\u003e(a) State boundary map of India showing study area (Sikkim and Arunachal Pradesh) highlighted. (b) District map of Sikkim (c) District map of Arunachal Pradesh\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5394608/v1/410826a145bb3877c6d6b0ba.jpeg"},{"id":70479675,"identity":"8b881d43-a4ef-49f2-b96a-b18218686146","added_by":"auto","created_at":"2024-12-03 14:47:52","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":162821,"visible":true,"origin":"","legend":"\u003cp\u003eNortheast Region summer rainfall: 1871-2016. (Trend-mm/year) and significance at 10%, 5% and 1% level, rainfall data for the period 1871-2013 based on 306 stations and 2014-2016 based on IMD subdivision rainfall (ESSO/IITM/STCVP/SR/02(2017)/189).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-5394608/v1/12e296ef3b26d4a680dd38fe.png"},{"id":70481535,"identity":"8e07dd95-86d5-487b-915d-4c3d1c9fc650","added_by":"auto","created_at":"2024-12-03 15:03:52","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":477142,"visible":true,"origin":"","legend":"\u003cp\u003eMoraine dammed Glacial Lake Outburst susceptibility map of Sikkim showing total number of moraine dammed lakes and individual lake with their level of outburst susceptibility\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5394608/v1/f76636b08eb06c0e6d051ba7.jpeg"},{"id":70479676,"identity":"3ac210ea-c4c2-4a6b-901a-3a1f6f2f8780","added_by":"auto","created_at":"2024-12-03 14:47:52","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":792463,"visible":true,"origin":"","legend":"\u003cp\u003eMoraine dammed Glacial Lake Outburst Susceptibility Map of Arunachal Pradesh showing total number of moraine dammed lakes and individual lake with their level of outburst susceptibility\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-5394608/v1/1948496e2a734afda70dd7c2.jpeg"},{"id":73776592,"identity":"ded10763-ad8b-4f15-b10e-efb34d5416b1","added_by":"auto","created_at":"2025-01-14 14:32:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3313371,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5394608/v1/b33b31c0-db74-4dcd-be93-e39dae525233.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Susceptibility Assessment of Moraine-Dammed Glacial Lakes in the Eastern Himalaya: A Geospatial Approach","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eGlobal warming is a major cause of glacier retreat across the world. It is estimated that the global glacial mass reduction could be as high as 18% by the year 2100 relative to 2015. The polar caps and high mountains will be the most extensively affected regions. (Pachauri and Reisinger, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). High Asian Mountains demonstrate global warming at an average rate of 0.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.2\u0026deg;C per decade, thereby, overtaking the average global warming rate of 0.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u0026deg;C per decade (Hoegh-Guldberg et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Climatologists estimate an increase of 2.1\u0026deg;C to 2.6\u0026deg;C in temperature by 2050 and around 3.3\u0026deg;C to 3.8\u0026deg;C by 2080 over the Indian region, which is already experiencing climate change (Verma \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The rapid increase in global mean temperatures is intensifying glacial melting, which in turn elevates the hazard of glacial lake outburst floods by destabilizing moraine-dammed lakes due to the increased accumulation of meltwater.\u003c/p\u003e \u003cp\u003eThe Himalaya is one of the largest sources of glacial mass outside the polar region with an estimated glacier coverage of 60,000 km\u003csup\u003e2\u003c/sup\u003e (Islam and Patel 2022). It works as a fresh water tower to millions of lives in downstream region (A. Aggarwal et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Himalayan glaciers have undergone drastic changes in the last two decades, characterized by significant retreat and mass loss, with glacier mass loss rates doubling between 2000 and 2016 compared to the period from 1975 to 2000 (Bolch et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, Maurer et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The Himalayan glaciers are presently losing an average of about 0.4% of their mass per year (Chand et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) due to an estimated temperature increase between 1\u0026deg;C and 6\u0026deg;C in the region from 1970 to 2005 (Pachauri and Reisinger \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). As the average mean temperature rises around the globe due to human interferences, these glaciers melt and produce a large number of glacial lakes in high altitude areas (Yu, He, and Liu 2022; Liu et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Shrestha et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Nie et al. 2020). Due to continuously increasing number of glacial lakes in the Himalaya, the risk of glacial lake outburst flood (GLOF) is also intensifying (Mohanty and Maiti 2021; Yu, He, and Liu 2022; S. Wang, Qin, and Xiao 2015; Yao et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePertaining to GLOF, the glacial lakes in the Himalaya mainly classified into 3 categories: (1) ice-dammed; (2) moraine-dammed, and (3) bedrock-dammed (Vil\u0026iacute;mek et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Previous studies have demonstrated that the moraine dammed lakes exhibit high susceptibility to breaching, primarily due to composition of their moraines, which are usually the poorly sorted unconsolidated rock fragments plucked from valley floor and carried by glaciers. This type of material is inadequate for securely containing the substantial volumes of water that typically accumulate within these lakes (Veh \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Fan et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Hegglin and Huggel 2008; Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; S. Aggarwal et al. 2017). Moraine-dammed Lake can further be categorized as End-moraine dammed lake, Lateral moraine dammed lake, Ice-capped Lateral moraine dammed lake and others. However, the end-moraine dammed lakes are the most hazardous lakes, which are responsible for most of the GLOF events (ICIMOD 2011). An unexpected breach of these kind of lakes is a threat to infrastructure and life in downstream areas (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe Eastern Himalayan region has gained significant attention in the recent years due to its vulnerability to GLOFs. While the western and central parts of the Indian Himalaya have been well-documented in terms of glacial mass and area changes, the eastern region remains relatively understudied (Tiwari et al. \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Islam and Patel 2022, Mohanty, Maiti, and Dixit 2023). As the Eastern Himalayan region is highly prone to the GLOF events, mapping of glacial lakes in this region is crucial for hazard analysis and risk assessment. Therefore, a comprehensive inventory of glacial lakes in the Sikkim and Arunachal Pradesh Himalaya has been created in the present study by mapping the lakes from a high-resolution data at the scale of 1:2000 and below. The geomorphic parameters and dam characteristics have also been included in the dataset with appropriate weightage applied to each parameter to identify the most vulnerable glacial lakes and subsequently assess susceptibility of the lakes to dam failure or an outburst using analytic hierarchy process (AHP). The study utilizes high resolution optical imagery data (50cm spatial resolution) in conjunction with DEM (5m spatial resolution) to create highly accurate inventory of glacial lakes, while also highlighting the need for more research in understanding associated risks and implementing mitigation strategies in the region.\u003c/p\u003e"},{"header":"2 Regional setting","content":"\u003cp\u003eThe Indian Eastern Himalayan landscape is host to rich bio resources, which fulfil miscellaneous needs of the communities living in it (Theengh et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The Indian summer is responsible for annual precipitation for the Indian sub-continent (Dimri et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The study area experiences a good amount of precipitation in monsoonal season from June to September.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;1\u003c/b\u003e. (a) State boundary map of India showing study area (Sikkim and Arunachal Pradesh) highlighted. (b) District map of Sikkim (c) District map of Arunachal Pradesh\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Sikkim\u003c/h2\u003e \u003cp\u003eSikkim is situated in the Himalayan foothills, encompassing an area of 7906 km\u003csup\u003e2\u003c/sup\u003e. The state comprises 28 mountain peaks, over 80 glaciers, 227 high-altitude lakes, 5 major hot springs, and more than 100 rivers and streams. Sikkim is characterized by mountainous terrain with an elevation ranging from 280 m in the south at the border with West Bengal to 8586 m in the northern peak near Nepal and Tibet. Sikkim is bounded in the west by the north-south limb of the Great Himalayan Range, which includes the world's third-highest peak, Khangchendzonga. In the east, it is bounded by the Chola range, and to its south lies the Singalila ridge. The major river of the state is the Teesta, which originates from Chho Lhamo lake in the north and is further augmented by numerous tributaries and rivers, of which Tholung, Lachung, Great Rangeet, and Rangpo are significant drainages. The majority of inhabited regions in Sikkim experience a temperate climate, with temperatures rarely exceeding 28\u0026deg; C during summer months. While most of northern Sikkim experiences severe, arid winters, the southern region remains comparatively less cold. Peak temperatures are typically recorded in July and August, with the lowest temperatures occurring in December and January. During the monsoon season, which extends from May to early October, heavy precipitation increases the likelihood of landslides triggered by localized monsoon activity (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.indiawris.gov.in\u003c/span\u003e\u003cspan address=\"https://www.indiawris.gov.in\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe state of Sikkim is predominantly mountainous, characterized by a lack of any extensive alluvial plains. The alluvium along river channels, which is the youngest geological unit in the region is dated to the Quaternary period. In contrast, the primary rock types that characterize the area are composed of Pre-Cambrian formations, which include phyllites, slates, quartzites, and schists. These lithologies belong to five major geological units i.e. Kanchenjunga gneiss, Darjeeling gneiss, Chungthang schists and gneiss, Lingtse granite gneiss and Daling group. The region exhibits significant geological deformation resulting from tectonic activity and the presence of major thrusts, including the Main Boundary Thrust (MBT), the Main Central Thrust (MCT), and various suture zones. These processes have caused the rock formations to undergo extensive folding, warping, and faulting, which in turn has facilitated the development of numerous lineaments throughout the area.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Arunachal Pradesh\u003c/h2\u003e \u003cp\u003eArunachal Pradesh, situated within the foothills of the Himalaya, is the largest state in northeastern India covering an area of 83,743 km\u0026sup2; approximately. The relief of the mountains in the region ranges from over 7000 m to approximately 300 m elevation amsl. The topography of Arunachal Pradesh shows mountainous to sub-mountainous ranges gradually sloping downwards into the alluvial plains of Assam. This geomorphologically diverse landscape plays an important factor in controlling the hydrological processes, influencing local climate and also protecting the state\u0026rsquo;s unique ecological system. It is divided into valleys by the rivers Kameng, Subansiri, Siang, Lohit and Tirap. India\u0026rsquo;s Largest River Brahmaputra enters the state from Tibet and flows into Assam where it goes down to Bangladesh and fall into Bay of Bengal. River system of Arunachal Pradesh includes rivers coming from higher Himalayas, Patkoi and Arakan Ranges, finally drain in the Brahmaputra River (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.indiawris.gov.in\u003c/span\u003e\u003cspan address=\"https://www.indiawris.gov.in\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e The climate of Arunachal Pradesh varies according to the altitude of the region from temperate to subtropical. At the highest altitude, the state experiences an alpine climate and the lower part experiences hot and humid climatic conditions with a max temperature around 40\u0026deg;C \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e(https://www.indiawris.gov.i\u003c/span\u003e\u003cspan address=\"http://(https://www.indiawris.gov.i\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003en). Arunachal Pradesh experiences heavy rainfall during May to September, average recorded rainfall in the state is 300 centimeters that varies between 80 to 450 centimeters. In the monsoons, the temperature ranges from 22\u0026deg; C to 30\u0026deg; C. In the winter months, the temperature ranges from 15\u0026deg; C to 20\u0026deg; C. The rainfall of the Arunachal Pradesh is heaviest in the country which makes the state landslide prone.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure\u0026nbsp;2\u003c/b\u003e. Northeast Region summer rainfall: 1871\u0026ndash;2016. (Trend-mm/year) and significance at 10%, 5% and 1% level, rainfall data for the period 1871\u0026ndash;2013 based on 306 stations and 2014\u0026ndash;2016 based on IMD subdivision rainfall (ESSO/IITM/STCVP/SR/02(2017)/189).\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Materials and methods","content":"\u003cp\u003eThe district boundaries of Sikkim and Arunachal Pradesh were demarcated from Survey of India topographic maps at 1: 250,000 scale. Ortho-rectified natural color imagery with a spatial resolution of 50 cm, derived from the WorldView-8 and GeoEye satellite platforms, was employed to precisely delineate the boundaries of glacial lakes. A DEM was generated through the integration of data from both sensors, achieving a spatial resolution of 5 m. The high-resolution imagery and detailed elevation data facilitated extraction of various parameters pertinent to the geometry of the moraine dams and characteristics of glacial lakes.\u003c/p\u003e \u003cp\u003eAnnual precipitation and mean temperature data were obtained from the Indian Meteorological Department and its state branches, based on recently published reports. Additionally, glacial lake evolution data from the National Disaster Management Authority (NDMA) was utilized to assess changes in these lakes. Maps of seismic activity from the Bureau of Indian Standards (BIS) and mass movement maps from the Department of Science and Technology (DST) were also incorporated into the analysis of glacial lakes.\u003c/p\u003e \u003cp\u003eIn the present work, all the glacial lakes were mapped and a threshold area of 0.01 km\u003csup\u003e2\u003c/sup\u003e was chosen to distinguish the glacial lakes from ponds and waterlogged areas. The process was followed by identification and sorting of moraine dammed glacial lakes based on 14 characteristic parameters including geometric, local relationship of the feature with surrounding structures, and stability controlling building material properties. The regional seismicity, mass movement, and climatic conditions, which could be effective in contributing to or triggering a dam breach were also considered. AHP (Analytical hierarchy Process) method was adopted for evaluating the parameters which can trigger a moraine dammed glacial lake. At last, glacial lake outburst susceptibility level was introduced for GLOF assessment.\u003c/p\u003e \u003cp\u003eThe datasets used along with their specifications and their role in the study elaborated in the Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetails of data sources used\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDataset\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eResolution\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSource\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUse\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWorldview-8 and Geo-Eye true Ortho-rectified Satellite Imagery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVRICON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGlacial lake mapping\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDEM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eVRICON\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eElevation, slope and dam geometry measurements\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTerra Explorer 3D\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTerra Explorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLake characteristics, Dam Geometry, and surrounding conditions Measurement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopographic map\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1:50000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSurvey Of India (OSM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eState Boundary Delineation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMass movement maps\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eDST (Department of Science and Technology), Govt. of India\u003c/p\u003e \u003cp\u003eNational Disaster Management Authority, NDMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOutburst susceptibility assessment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeismic zone map\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1893\u0026ndash;2002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBureau of Indian Standard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOutburst susceptibility assessment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeteorological data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2009\u0026ndash;2018\u003c/p\u003e \u003cp\u003e1871\u0026ndash;2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHydrome Division, India Meteorological Department, New Delhi\u003c/p\u003e \u003cp\u003eIndian Institute of Tropical Meteorology (IITM) Earth System Science Organization (ESSO) Ministry of Earth Sciences (MoES) PUNE, INDIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOutburst susceptibility assessment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLake evolution data\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2011\u0026ndash;2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNational Disaster Management Authority, NDMA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOutburst susceptibility assessment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Identification of potentially dangerous moraine dammed glacial lakes and selection of their outburst susceptibility parameters\u003c/h2\u003e \u003cp\u003eA moraine dam is a natural barrier composed of often unsorted sediments ranging from sand to boulders, and ice, confining the meltwater from glaciers. It forms when a glacier retreats and leaves behind a pile of debris (Jain, Ahmed, and Lohani 2023). A moraine dam can block the flow of meltwater from the glacier and create a glacial lake, which could be found in frozen state also (Khadka, Zhang, and Chen 2019). Identification of such lakes can contribute to segregate potentially hazardous lakes and mitigate outburst floods in mountainous region. The resultant glacial lakes were further imported in the 3D software Terra Explorer. Properly blocked and large flowing moraine dammed lakes were visually identified and demarcated in the glacier region.\u003c/p\u003e \u003cp\u003ePrevious studies have defined the predominant geometric and geomorphic parameters to classify the glacial lake outburst susceptibility level towards breaching and outburst (Islam and Patel 2022; McKillop and Clague 2007; S. Aggarwal et al. 2017; Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the present study, 14 parameters were selected to generate glacial lake inventory and to categorize the moraine dam glacial lake\u0026rsquo;s stability. These parameters were extracted using high resolution satellite imagery, DEM, and lake evolution data.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1 Moraine dam geometrical parameters\u003c/h2\u003e \u003cp\u003eThe geometry of the moraine dam is an important factor in defining the stability of the dam which governs the susceptibility to breaching. These parameters are:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMoraine Height: A higher moraine dam can hold more water in glacial lake, but it can also increase the stress on the dam and make it more prone to breaching which can also lead to bigger flooding events (Yu, He, and Liu 2022).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eWidth of Crest: A wider dam crest permits more water to pass through, resulting in a higher peak discharge and a larger flood volume (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSlant Height: The slant height of the moraine dam can influence the pressure exerted by the water on the moraine dam, as well as the volume of water that can be released in case of a breakdown (Ahmed et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBottom Width: It influences the amount of water that can flow under or through the dam in case of a breach or a seepage (Begam and Sen 2019).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMoraine Width to Height Ratio: Width to height ratio impacts the hydraulic gradient which leads to piping within the moraine dam and slope failure. Piping can weaken the strength of internal structure of dam and resulting in full or partial failure of a dam (Huggel et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDistal Face Slope: It shows the probability of slope failure and the erodibility of a moraine dam which may trigger a GLOF event (Xin- et al. 2008).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eGeometrical factors of moraine dam were calculated with the help of 3D rendering of satellite images and with tools available for marking and measuring within 3D software. Firstly, the high resolution 2D satellite imagery was ingested in Tera Explorer 3D software. then, parameters of already identified moraine dammed glacial lakes were measured and calculated in 3D environment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Glacial lake characteristics\u003c/h2\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eLake Area: Glacial lakes which are larger in size are more prone to GLOF as they usually contain more water and exposed to potential mass movement (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Khadka, Zhang, and Chen 2019; Senese et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eDistance between Glacier Lake: Smaller the distance between lake and parent glacier, it is more prone to associated dynamics (Xin- et al. 2008).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFreeboard: It indicates whether a dam will fail due to overtopping of a displacement wave. Overtopping waves have potential to erode the dam which leads to dam failure (Islam and Patel 2022).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSlope Between Lake and Glacier: A higher slope difference between the glacier snout and lake outlet would be more likely to bring the lake to overflow its bounds (S. Wang, Qin, and Xiao 2015).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePercentage increase in lake Area: An increase in lake area resulting in an increased volume of water in lake if it is in direct contact with glacier (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eArea of lake was calculated semi-automatically with the help of geospatial tools, changes in lake area of moraine dammed glacial lakes were calculated with data provided by NDMA (National Disaster Management Authority) from 2011 to 2017, the distance, freeboard, snout steepness and slope between lake and its adjacent glacier was calculated and measured with Terra Explorer 3D software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Moraine dam material characteristics\u003c/h2\u003e \u003cp\u003eMoraine-dammed glacial lakes are prone to breaching due to the unconsolidated material that constitutes the dam and the steepness of surroundings (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; McKillop and Clague 2007). Material properties of moraine dam can be determined only through field investigation, which was carried out at two moraine dammed glacial lakes in Sikkim. These lakes were included in high outburst susceptibility level and low susceptibility.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e3.1.4 Surrounding topographic and climatic conditions\u003c/h2\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePrecipitation/Rainfall: Rainfall is one of the key factors to cause the outburst flood. It induces GLOF by different mechanisms such as sudden increase in volume of the water in the lake increases outward pressure on the dam walls leading to a subsequent breach. It may also trigger landslides or avalanches during the monsoon season, which indirectly may initiate a GLOF event. Periodic rainfalls occurring at regular intervals weaken the moraine dam by erosion and saturate the dam material, eventually becoming a cause of displacement waves or overtopping of the moraine dam. The rainfall may also cause melting of the ice cores, leading to the collapse of the moraine dam and the release of a large volume of water .\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSeismicity: Sikkim and Arunachal Pradesh are situated in the high-risk seismic zone IV, V of the Indian seismic zone map, respectively. Sikkim state is spread out on the Himalayan Mountain range with two main thrust faults, the Main Boundary Thrust (MBT) and Main Central Thrust (MCT) crossing the state. These faults are responsible for the generation of earthquakes in this region. Arunachal Pradesh is situated on the eastern Himalayan Mountain range, where two major tectonic plates, the Indian plate and the Eurasian plate, collide and generate earthquakes. Seismic activity like mass movements, which can either rupture the moraine dam or the debris released can increase water level resulting in overtopping of the lake.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eMass Movement: The accumulation of debris or steep scarps around a lake is essential to its hazard status, since mass movements into a lake can led it to overflow (Huggel et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Allen et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Mass wasting associated with landslides, avalanches, or rockfalls, can destabilize the moraine dam or increase the water level and pressure in the lake, and cause a large-scale natural hazard event facilitated by the GLOF.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003ePrecipitation data of lakes were obtained from different sources including monthly or yearly rainfall data from Indian Meteorological Department (IMD) state branches, Indian Institute of Tropical Meteorology (IITM), Earth System Science Organization (ESSO), Ministry of Earth Sciences (MoES), and published reports. Seismic data were collected from BIS (Bureau of Indian Standard) and readily available seismic zone maps. The information regarding sites and size of mass movement was derived from interpretation of steep slopes around the lake from 3D visualization of high-resolution satellite image, published literatures, Department of Science and Technology (DST), and National Disaster Management Authority (NDMA).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Moraine dammed glacial lake outburst susceptibility analysis and assessment\u003c/h2\u003e \u003cp\u003eThe historical data of GLOF events in the Himalayan region were collected from the literature surveys and published reports to analyze and evaluate the contribution of the selected parameters for moraine dam breaching (Jain and Lohani 2012). Mass movement is considered a major cause of dam failure as it has triggered 22 outbursts out of 41 GLOF events in the Himalayan region (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Avalanche and landslides caused by the earthquake have been registered in the past events in the Himalayan region which is a causative factor in the moraine dam failure. The self-destruction of the dam is caused by high hydrostatic pressure, snowmelt, moraine slope failure and degradation of dam over the period, resulting in 15 outburst events out of 41 in the Himalayan region (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOut of 14 parameters used to make glacial lake inventory, 11 crucial parameters were selected for outburst susceptibility analysis which summarized in the table below.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIndex values of parameters with their sub-criteria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eClasses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eProbability of Outburst\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIndex value (Ci)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLake Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.10 sq. Km\u003c/p\u003e \u003cp\u003e0.05\u0026ndash;0.10 sq. Km\u003c/p\u003e \u003cp\u003e0.01\u0026ndash;0.05 sq. Km\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Bolch et al., 2011; Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncrease in lake Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;100%\u003c/p\u003e \u003cp\u003e50\u0026ndash;100%\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Bolch et al., 2011, Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlacier lake Distance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIn contact\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;500 m\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;500 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Prakash* and Nagarajan 2017; Wang et al., 2011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSlope b/w lake and Glacier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;21\u0026deg;\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;12\u0026deg; \u0026minus;\u0026thinsp;21\u0026deg;\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;12\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Prakash* and Nagarajan 2017, Wang et al., 2011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMoraine Width to Height Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.1\u003c/p\u003e \u003cp\u003e0.1 \u0026ndash; 0.5\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Huggel et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidth of Crest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 m\u003c/p\u003e \u003cp\u003e10\u0026ndash;60 m\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;60 m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistal face Slope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;20\u0026deg;\u003c/p\u003e \u003cp\u003e12\u0026deg;- 20\u0026deg;\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;12\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Prakash* and Nagarajan 2017; Wang et al., 2011)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreeboard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (Surface Drainage)\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;5 m\u003c/p\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5m\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e( Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMass Movement Impact Susceptibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Bolch et al., 2011; Huggel et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtreme Rainfall events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequent\u003c/p\u003e \u003cp\u003eSporadic\u003c/p\u003e \u003cp\u003eUnlikely\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Huggel et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2004\u003c/span\u003e, Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeismic Zone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eZone 5\u003c/p\u003e \u003cp\u003eZone 4\u003c/p\u003e \u003cp\u003eZone 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003cp\u003eMedium\u003c/p\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.50\u003c/p\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(Prakash* and Nagarajan 2017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eEach parameter was further divided into three classes according to the potential of the parameter to cause an outburst. Index values were assigned to these three classes with respect to their potential based on the conditions and controls described by various researchers and experts.1 was assigned as highest, 0.5 as medium and 0.25 as lowest index value (Ci). All the parameters were then analyzed and calculated to estimate the relative significance based on the knowledge and information gained from literature survey, published reports, field data, past GLOF events etc. Eventually all the parameters were ranked and weighed using AHP.\u003c/p\u003e \u003cp\u003eThis multi criteria technique (AHP) incorporates the elusive aspects associated with the glacial lake factor using pairwise comparison matrix (given below in Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). A pairwise comparison matrix was created by allocating a value of 1 to 9 to each pairwise comparison (Rass et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Drienikov\u0026aacute; et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Value 1 in the pairwise comparison matrix denoted both factors are equally important, 3 as moderate importance, 5 as strong importance, 7 as very strong importance over, and 9 represented one of the parameters was extremely important (Ndalianis et al. 1995; Eldrandaly \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Nadja and Karlheinz 2004).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePairwise comparison matrix of parameters computed using the AHP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eS. No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 2 3 4 5 6 7 8 9 10 11\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLake Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 0.5 0.5 0.5 0.5 2 1 0.33 0.25 1 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIncrease in lake Area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 1 2 3 2 2 2 1 0.33 2 3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGlacier lake Distance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 0.5 1 1 2 3 2 0.5 0.25 1 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSlope b/w lake and Glacier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 0.33 1 1 0.5 2 1 0.5 0.25 1 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMoraine Width to Height Ratio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 0.5 1 2 1 2 1 0.5 0.25 0.5 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidth of Crest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 0.5 0.33 0.5 0.5 1 0.5 0.5 0.25 0.5 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistal face Slope\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 0.5 0.5 1 1 2 1 0.5 0.33 1 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFreeboard\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 1 2 2 2 2 2 1 0.33 2 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMass Movement Impact Susceptibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 3 4 4 4 4 3 3 1 3 3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eExtreme Rainfall events\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 0.5 1 1 2 2 1 0.5 0.33 1 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSeismic Zone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5 0.33 0.5 0.5 0.5 1 1 0.5 0.33 0.5 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe concept of consistency is one of the characteristics that distinguishes AHP from the other multi criteria techniques and gives coherence to the method (Herath and Prato 2017; Aguar\u0026oacute;n et al. 2019; Kulakowski \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The consistency of the matrix of order n is evaluated. Comparisons made by this method are subjective and the AHP tolerates inconsistency through the amount of redundancy in the approach (J. Wang, Chakraborty, and Ouyang 2011). If this consistency index fails to reach a required level, then answers to comparisons may be re-examined. The consistency index, CI, is calculated as\u003c/p\u003e \u003cp\u003e \u003cb\u003eCI = (ƛ\u003c/b\u003e \u003csub\u003e \u003cb\u003emax\u003c/b\u003e \u003c/sub\u003e \u003cb\u003e- n)/ (n \u0026minus;\u0026thinsp;1)\u003c/b\u003e\u003c/p\u003e \u003cp\u003ewhere ƛ\u003csub\u003emax\u003c/sub\u003e is the maximum eigenvalue of the judgement matrix. This CI can be compared with that of a random matrix, RI (Saaty,1980). The ratio derived; CR (=\u0026thinsp;CI/RI) is termed the consistency ratio. Saaty suggests the value of CR should be less than 0.1. A CR with a value higher than 0.10 requires re-evaluation of the judgments in the original matrix of pairwise comparisons (Drobne and Lisec 2009; Sel\u0026ccedil;uk \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The AHP produces weight values for each alternative based on the judged importance of one alternative over another with respect to a common criterion (Vargas \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Hendrikx, Murphy, and Onslow 2014; Nadja and Karlheinz 2004).\u003c/p\u003e \u003cp\u003eBased on the history of past GLOF (Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) occurrences, a pairwise comparison matrix had generated for the parameters by assigning higher values to those parameters whose occurrence is more frequent associated with the GLOF events. Weights (Wi) were calculated for each parameter. The final weights were calculated of each parameter by multiplying the Wi factor weight with the Ci class index value. The outburst susceptibility score for each lake was completed by adding the final weights of all the parameters (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Glacial lake mapping\u003c/h2\u003e \u003cp\u003ePrimary focus of this study was to prepare an inventory of moraine dammed glacial lakes and their physical characteristics, also assessing their vulnerability for breaching phenomena. A total of 766 lakes were found in Sikkim with 340 lakes having area of 0.01 Km\u003csup\u003e2\u003c/sup\u003e and above. Out of these, 27 glacial lakes having area 8.3379 km\u003csup\u003e2\u003c/sup\u003e were found to be moraine dammed in nature from its total area7096 Km\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSimilarly, total 2834 lakes were found in Arunachal Pradesh with 1529 lakes having area of 0.01 Km\u003csup\u003e2\u003c/sup\u003e and above. Among these, 6 moraine dammed lakes were found with area acquired 0.77 Km\u003csup\u003e2\u003c/sup\u003e from its total area 82115 Km\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Inventory of moraine dammed glacial lakes\u003c/h2\u003e \u003cp\u003eInventories of vulnerable moraine dammed glacial lakes using 14 parameters were prepared for Sikkim and Arunachal Pradesh (given in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) including parameters of moraine dammed lakes such as moraine height, width, slant height, bottom width, and freeboard; lake characteristics (lake proximity to glacier, slope between lake and glacier, lake Area) were extracted using 3D visualization and analysis through software Terra Explorer. Surrounding conditions (Seismicity, mass movement, climatic conditions) were assessed with previous published maps and reports. Changes in moraine dammed lakes were also observed with the data provided by NDMA for the period of 2011 to 2018 for observing changing trend of lake per year.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMoraine Dammed Glacial Lake Inventory of Sikkim with Lake ID and other important measured parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSr.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eNo.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eLake ID\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eArea\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(Km\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eGlacier lake Distance\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eFreeboard\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eWidth of Crest\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSlant height(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eMoraine Height\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eBottom\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eWidth\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eMoraine\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eWidth/Height Ratio\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eSlope Between Lake and Glacier (\u0026deg;)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003e% increase in Lake Area\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eDistal Face Slope (\u0026deg;)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003ePrecipitation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003eSeismicity\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003eMass Movement\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e842\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e27.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e32.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e12.04\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e30.95\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.2630\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e45.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e32.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e83.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e20.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e81.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e14.23\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e32.92\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e28.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e24.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e24.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.58\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e16.42\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.5714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e30.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e11.140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e28.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e18.62\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e31.8\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.1758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e95.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e12.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e94.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.73\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e26.69\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e17.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e15.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e75.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e19.61\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e17.95\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e11.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e38.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2.82\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e26.36\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e15.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e15.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.31\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e29.09\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0192\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e22.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e5.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.26\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e43.49\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e20.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e11.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e129.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e129.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e13.75\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e23.45\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1286\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e91.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e8.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e90.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e18.42\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e34.02\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1089\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e25.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e24.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e3.57\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e20.41\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e38.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e7.21\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e29.51\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003ehigh\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.1784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e33.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17.94\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e10.62\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e13.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e13.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e1.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.6\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e27.42\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0263\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e16.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e16.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e9.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e24.76\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e27.91\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e38.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e46.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e23.75\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e32.56\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003elow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e47.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e47.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e9.2\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e20.02\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.9716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e163.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e163.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e10.41\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e18.69\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.4313\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e89.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e136.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e23.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e134.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17.01\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e21.14\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e9.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e438.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e433.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e43.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e431.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e10.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.53\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e20.37\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.2236\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e293.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e329.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e25.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e328.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e11.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e6.08\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e29.24\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e31.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e150.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e175.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e30.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e172.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e28.97\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e14.17\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.3040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e206.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e6.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e32.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e32.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4.44\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e12.01\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e242.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e455.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e14.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e455.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e16.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e4\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e30.95\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.6605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e13.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e23.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e44.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e44.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e43.28\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e19.25\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.0803\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e85.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e14.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e116.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e46.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e107.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e17.67\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e19.81\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003emedium\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMoraine Dammed Glacial Lake Inventory of Arunachal Pradesh with Lake ID and other important measured parameters\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"16\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c16\" colnum=\"16\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSr.\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eNo.\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eLake ID\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eArea\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(Km\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eGlacier lake Distance\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eFreeboard\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eWidth of Crest\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eSlant height(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eMoraine Height\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eBottom\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eWidth\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003eMoraine\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eWidth/Height Ratio\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eSlope Between Lake and Glacier (\u0026deg;)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003e% increase in Lake Area\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eDistal Face Slope (\u0026deg;)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003ePrecipitation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c15\"\u003e \u003cp\u003e\u003cem\u003eSeismicity\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c16\"\u003e \u003cp\u003e\u003cem\u003eMass Movement\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e111.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e28.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e107.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e45.92\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e14.88\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eDeficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e146.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e24.69\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e21.67\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eDeficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e142.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e35.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e138.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e17.42\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e14.31\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eDeficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e63.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e275.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e38.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e272.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.835\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e7.24\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e7.93\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eDeficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e486.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e323.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e130.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e296.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e18.27\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e23.71\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eDeficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e24.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e68.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e74.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e7.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e26.42\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e27.04\u0026deg;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003eDeficient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c15\"\u003e \u003cp\u003eV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c16\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eData, characteristics and outburst susceptibility scores of past three events in Himalayan regions computed using the AHP\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"14\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c14\" colnum=\"14\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eArea\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(Km\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u003cem\u003e)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e% increase in Lake Area\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eGlacier lake Distance\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eSlope Between Lake and Glacier (\u0026deg;)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eWidth of Crest\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eMoraine\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eWidth/Height Ratio\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eFreeboard\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003e(m)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cem\u003eDistal Face Slope (\u0026deg;)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003ePrecipitation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eSeismicity\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003eMass Movement\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c13\"\u003e \u003cp\u003e\u003cem\u003eWeight\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c14\"\u003e \u003cp\u003e\u003cem\u003eReferences\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDig Tso Eastern Nepal 04-Aug1985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e25\u0026ndash;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(Daniel Vuichard et al., 1987\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTam Pokhari Eastern Nepal 03-Sep1998\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e30\u0026ndash;35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(Lamsal et al., 2016; Osti et al., 2011; Osti and Egashira, 2009)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChorabari Kedarnath India 17-Jun2013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo Glacier\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.1\u0026ndash;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e35\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c13\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c14\"\u003e \u003cp\u003e(Allen et al., 2015; Das et al., 2015)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3 GLOF outburst susceptibility assessment\u003c/h2\u003e \u003cp\u003eOut of 14 parameters calculated for every moraine dammed lake, 11 parameters (refer Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) were analyzed for outburst susceptibility assessment. Slant height, Moraine height and bottom width) were not considered for outburst assessment because these 3 parameters were subordinate of moraine width to height ratio which was one of crucial parameter in outburst analysis. Out of total 1869 lakes; 33 moraine dammed lakes were used for outburst susceptibility analysis based on 11 important parameters. Moraine dam geometry, lake characteristics, rainfall events, mass movement and seismicity were examined and computed. Eventually, lake outburst susceptibility score for each moraine dammed glacial lake was calculated using AHP technique. The outburst susceptibility level of moraine dammed lakes was divided into four classes, low, medium, high and very high based on susceptibility score. AHP technique was applied to the 3 lakes in the Himalayan region (given in Table \u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) which have suffered from outburst in past for verification (Prakash* and Nagarajan 2017). Two lakes had the outburst susceptibility score\u0026thinsp;\u0026gt;\u0026thinsp;0.7, and the other one had the score 0.63. therefore, a score of 0.65 was used as a threshold for classifying lakes with very high outburst susceptibility, 0.55 representing high and 0.45 as medium susceptibility.\u003c/p\u003e \u003cp\u003eOut of the 27 lakes in Sikkim, 24 lakes are situated in North Sikkim district and the remaining 3 lakes are in West Sikkim district. In North Sikkim, 2 lakes are very highly susceptible having weight scores (L11 having score 0.7225 and L1 having core 0.735) respectively, 8 lakes falling under high outburst susceptibility score, 10 lakes are falling in medium danger level and 4 moraine dammed lakes were falling under low outburst susceptibility level. There are 3 moraine dammed lakes in West Sikkim, out of which 2 lakes have very high susceptibility score and 1 lake has high susceptibility score. Out of 27 moraine dammed lakes in Sikkim (Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e), 4 were classified as very high and 9 as highly susceptible, whereas 10 lakes came under medium and 4 lakes have low outburst susceptibility score (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The 13 moraine dammed lakes which were falling within the high to very high outburst susceptibility range should be further studied and monitored for detailed hazard assessment.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMoraine dammed Glacial Lakes of Sikkim with their outburst susceptibility weights\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSr.No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLake_ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArea (Km\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWeights\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.175335\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026deg; 0' 19.932\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 42' 47.740\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.735\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.316116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 32' 0.101\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 5' 8.552\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5625\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.223572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 54' 45.977\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 11' 48.547\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 49' 18.103\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 14' 55.693\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.062723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 56' 34.019\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 16' 19.644\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4725\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.014535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 51' 28.086\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 13' 58.079\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.375\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.304046\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 51' 6.539\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 14' 26.045\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4475\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.035631\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 57' 53.354\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 22' 8.584\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.485\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.315266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 58' 53.534\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 30' 30.991\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.080269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026deg; 0' 0.916\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 32' 53.367\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.571389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 58' 30.038\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 36' 58.225\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.7225\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.085966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 52' 23.304\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 38' 16.295\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5075\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.660525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 59' 33.207\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 32' 45.090\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 33' 57.970\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 7' 0.457\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.105257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 33' 45.581\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 7' 23.367\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.181697\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 58' 7.235\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 47' 49.269\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.025311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 57' 3.617\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 42' 16.003\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.027547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 51' 37.166\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 51' 53.759\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.045292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 51' 3.933\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 52' 32.442\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.515\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.104255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 52' 23.580\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 47' 21.676\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6025\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.03745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 51' 50.996\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 48' 9.478\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.6125\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.118736\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 43' 22.274\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 41' 25.567\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.351627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 56' 55.360\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 18' 19.002\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.585\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.431334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026deg; 0' 21.314\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 29' 35.213\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.260014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026deg; 0' 52.126\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 33' 42.028\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4975\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.123446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026deg; 0' 52.028\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 39' 8.097\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.3825\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.971621\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u0026deg; 0' 24.844\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u0026deg; 41' 53.173\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eArunachal Pradesh has 6 moraine dammed lakes in Tawang and West kameng districts. All lakes are located in Kangto Glacier region which is the highest point in Arunachal Pradesh (details given in Table \u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The area in which Kangto Glacier is located lies in the Lada circle of East Kameng district of the state. East side of Tawang district where kangto glacier falls has 4 moraine dammed glacial lakes. from which 2 lakes were highly susceptible and 3 lakes have medium outburst susceptibility level (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e4\u003c/span\u003e). West Kameng has 1 moraine dammed glacial lake with high outburst vulnerability level.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMoraine dammed glacial lakes of Arunachal Pradesh with their outburst susceptibility weights\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSr.No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLake_ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eArea (Km\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eLatitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLongitude\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWeights\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.070938\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 44' 0.191\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u0026deg; 22' 25.167\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.024471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 45' 39.101\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u0026deg; 24' 12.775\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.4875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.023577\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 45' 21.202\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u0026deg; 23' 39.420\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.545\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.132661\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 45' 21.063\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u0026deg; 24' 3.796\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.635\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.132257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 43' 39.450\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u0026deg; 26' 6.144\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eL6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.353295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u0026deg; 46' 12.492\" N\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92\u0026deg; 25' 57.475\" E\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe field investigation was carried out at two moraine dammed glacial lakes in Sikkim which were identified with the help of geospatial techniques and falling under high outburst susceptibility level and low susceptibility level with ID number (L13, L10 shown in Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e) having area 0.6605 Km\u003csup\u003e2\u003c/sup\u003e, 0.0803 Km\u003csup\u003e2\u003c/sup\u003e respectively via Caf\u0026eacute; 15000 at (27\u0026deg; 59' 33.207\" N, 88\u0026deg; 32' 45.090\" E), (28\u0026deg; 0' 0.916\" N, 88\u0026deg; 32' 53.367\" E) at 16000 ft was scheduled from 29.11.2019 to 08.12.2019. At the time of visit, L13 moraine dammed glacial lake\u0026rsquo;s water level was at 5 to 15 m from surface level. Height was variable with general trend of decreasing elevation from source towards the outlet. It showed the typical moraine dam characteristics such as unconsolidated rock fragments (regolith) ranging from boulders to pebbles with lack of any prominent sorting in sediment size. Apparently, the outlet was clearly marked by arrangement of subrounded rock fragments in a channel forming downslope from the mouth of the glacier, suggesting an annual discharge of glacial melt water. The second glacial lake was situated adjacent on the upslope implies the origin of the lake from a retreating glacier and having same material composition like lake13.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e5.1 Glacial Lake dynamics\u003c/h2\u003e \u003cp\u003eEvery single lake or pond in study area was demarcated with the help of high-resolution data which could be used for monitoring of lake evolution in future. Moraine dammed glacial lake identification and parameters calculation was also executed on 5m spatial resolution DEM and Ortho-rectified natural color imagery of 50cm spatial resolution which improved glacial lake parameter visualization and demarcation for every single moraine dammed lake over medium resolution used in various studies (Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; S. Aggarwal et al. 2017; Islam and Patel 2022). 3D Software (Terra explorer) was considered over internet-based services because these services did not provide orthorectified data which could make incorrect feature calculation. MDGL evolution data (refer section \u003cspan refid=\"Sec5\" class=\"InternalRef\"\u003e3\u003c/span\u003e) provided by NDMA (National Disaster Management Authority) exhibited an average increasing trend less than 50% which displayed low outburst susceptibility of lakes in study area (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Heavy rainfall/precipitation was a possible factor for incidence of GLOF event in (Uttarakhand and Sikkim) Indian Himalaya occurred in the 2013 and 2023 respectively, which caused widespread devastation and loss of lives. Therefore, it is important to monitor the hydrological and meteorological conditions of glacial lakes to assess and mitigate the risk of GLOFs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e5.2 Outburst Susceptibility Assessment\u003c/h2\u003e \u003cp\u003eThe present study found new potentially dangerous lakes in the study area (refer Table \u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e and \u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) with the help of high-resolution data which could be further used for flood simulation modelling in downstream regions. Landslide and precipitation were found to be the main dominant parameters in this region which cause outburst by overtopping and displacement wave mechanism, weakening the moraine dam of a glacial lake. The AHP based methodology for outburst susceptibility assessment built on behalf of past studies which uses similar quantitative and qualitative approaches (Xin- et al. 2008; S. Aggarwal et al. 2017; Islam and Patel 2022; Prakash and Nagarajan \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). AHP method was used despite other multi criteria techniques or other present methodologies, because it suited best for the present article for outburst susceptibility assessment. Although the AHP method is simple and systematic it suffers from certain limitations, such as involving various experts to ensure consistency of judgments, time-consuming data acquisition and a long process. The Threshold accomplished for classification of outburst level was also based on past GLOF events in the Himalaya. Thus, first-order of proposed AHP based method was used to identify and prioritize potentially hazardous lakes in the study area.\u003c/p\u003e \u003c/div\u003e"},{"header":"6 Conclusions","content":"\u003cp\u003ePresent Study included mapping of all glacial lakes in Sikkim and Arunachal Pradesh with high resolution satellite imagery and Digital Elevation Model. Moraine dammed Glacial Lake inventories have prepared with the computation of 14 parameters playing major role in triggering Glacial Lake Outburst Hazard in the downstream areas. It was difficult to obtain and measure the moraine dam parameters, dam material properties, lake depth measurements, drainage conditions and the presence of ice in moraines manually and using medium-resolution satellite data as various studies have done till now. hence, we have attempted to extract GLOF triggering parameters with the help of availability of very high-resolution data. It may be possible to identify and prevent potential GLOF events by measuring and monitoring of moraine dams. As result concluded that 4 lakes in Sikkim have very high outburst susceptibility level and 9 lakes as high likewise in Arunachal Pradesh 3 lakes are highly susceptible to outburst. Mitigation of these lakes is crucial for hazard assessment. These lakes should be regularly monitored with the help of different available technologies like drone/aerial survey etc. These techniques can be used for artificial triggering of a moraine dam of glacial lake at high elevation areas and can prevent devastating impacts of outburst hazard in downstream areas.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDisclosure Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo potential conflict of interest was reported by the authors\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNA\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNA\u003c/strong\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll three authors conducted the research work.Sangeeta Pohal and Munmun Baisantry wrote the manuscript. 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Journal of Geographical Sciences 28 (2): 193\u0026ndash;205. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11442-018-1467-z\u003c/span\u003e\u003cspan address=\"10.1007/s11442-018-1467-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYu, Bin, Yuanxun He, and Yang Liu. 2022. \u0026ldquo;Quantitative Susceptibility Assessment of Breach of Moraine-Dammed Lakes.\u0026rdquo; Diqiu Kexue - Zhongguo Dizhi Daxue Xuebao/Earth Science - Journal of China University of Geosciences 47 (6). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3799/dqkx.2021.161\u003c/span\u003e\u003cspan address=\"10.3799/dqkx.2021.161\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Indian Eastern Himalayas, Glacial Lake Outburst Flood (GLOF), Moraine Dammed Glacial Lake, AHP, Outburst Susceptibility Level","lastPublishedDoi":"10.21203/rs.3.rs-5394608/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5394608/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe glaciers in the Himalayan region are some of the fastest retreating glaciers in the world with an annual rate of retreat of 16\u0026ndash;35 m/yr. leading to creation of a large number of glacial lakes in the Himalaya. The global warming has contributed to the continuing expansion of the glacial lakes. These topographic depressions, confined by ice, bedrock, moraine, or a combination of these, accumulate the melt water annually, and often the poor structural integrity of moraine dam fails to withstand the pressure exerted by the volume of accumulated water, leading to occurrence of a glacial lake outburst flood (GLOF). Since, GLOFs are mostly an instantaneous phenomenon and have the potential to cause severe damage to the property and loss of lives, a comprehensive analysis of GLOFs is necessary. The present study focuses on Sikkim and Arunachal Pradesh (Indian Eastern Himalaya) to create an inventory of glacial lakes with area\u0026thinsp;\u0026gt;\u0026thinsp;0.01 km\u003csup\u003e2\u003c/sup\u003e and assess their hazard potential. 340 and 1529 lakes in Sikkim and Arunachal Himalaya were manually identified from the 50 cm high resolution combined product of Worldview-8 and Geo-Eye true Ortho-rectified Satellite Imageries, out of which 27 in Sikkim and 6 in Arunachal Himalaya were identified as moraine dammed lakes. A detailed inventory of these lakes in GIS environment incorporated 14 parameters including 11 crucial controls on outburst susceptibility using AHP. The susceptibility map is classified into 4 classes, namely very high (4 lakes), high (12 lakes), medium (13 lakes) and low (4 lakes). Validation of the susceptibility classes was validated with 3 known GLOF events from the Himalaya. This novel study highlights the need to monitor and assess possible GLOFs in future while providing a high precision base inventory to open further research in this direction.\u003c/p\u003e","manuscriptTitle":"Susceptibility Assessment of Moraine-Dammed Glacial Lakes in the Eastern Himalaya: A Geospatial Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-03 14:47:47","doi":"10.21203/rs.3.rs-5394608/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11afcecd-455f-4e65-b4b5-05a7de5d884d","owner":[],"postedDate":"December 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-14T14:23:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-12-03 14:47:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5394608","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5394608","identity":"rs-5394608","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}