Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Meteorological conditions before the event
Type: text

The intensity, duration, and frequency of precipitation, as well as temperature rise, can affect the timing and magnitude of glacier movements and GLOF events. To further understand the meteorological conditions before the 2020 event, we processed daily precipitation, monthly precipitation, and air temperature data. Figure 7 shows the meteorological conditions at Jinweng Co. The monthly precipitation fluctuates seasonally, with the rainy season lasting from February to July and very little precipitation during the intervening winter months. The highest monthly rainfall of up to 240 mm occurred during June 2020, and the heaviest daily rainfall reached 45 mm on June 21, 2020. This was approximately 4 days before the GLOF event. Moreover, air temperature changed periodically, with the hottest period of the year from late May to mid-August. Extreme rainfall and temperature conditions are important driving factors that increased discharge into the lake and led to the lake outburst (see discussion later).

It can be seen that the June 25, 2020, outburst occurred at the highest monthly/daily precipitation. The unusually heavy rainfall combined with the warmer summer temperature provides a plausible explanation for the Jinweng Co outburst for two reasons.

First, heavy rainfall increased water inflow to Jinweng Co and thus increased discharge. Second, the heavy rainfall on June 21 may have also acted as an indirect trigger of the outburst when this precipitation provoked slope movement into the lake.

The Jinweng Co outburst chain provides a strong example of the role of extreme precipitation and temperature change in a GLOF-related disaster. According to the meteorological reports, the weather has been warming at a rate of 0.5 °C per decade over the last 40 years (You et al. 2016). This suggests that the warming trend constantly persists over Tibet. Based on the results of the glacier movement and lake change, it is certain that climate warming has caused glacier tongue recede, thinning, and lake expansion.


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Slope movement and ice collapse before the GLOF event
Type: text

To understand the factors associated with the June 2020 outburst, we used time series SAR intensity images and two-pass InSAR (e.g., Lu et al. 2003). Figure 8a-e show the time series SAR intensity images from May 28 to July 15 and reveal several changes. The lake expanded from May 28 to June 9, as indicated by the yellow arrows in Fig. 8a, b. In Fig. 8c-e, we found a section at the western lateral moraine moved downslope into the lake on or after June 21, and the deposit from the landslide can be

Fig. 7 Daily and monthly precipitation and air temperature records over the Jinweng Co area. Daily precipitation is shown as blue bars, monthly rainfall in black smoothed curve, and air temperature in purple dots

data/('triggering factors of glacial lake_SAR_optical_image', '.pdf')_extraction.md


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Slope movement and ice collapse before the GLOF event
Type: figure
Figure

Image /page/5/Figure/12 description: A combination chart displaying climate data from late 2016 to mid-2020. The x-axis represents the date in yyyy/mm/d format, starting from 2016/12/1 and extending past 2020/6/1. There are two y-axes. The left y-axis, labeled in blue, represents daily precipitation in millimeters (mm) and ranges from 0 to 50. The right y-axis has two scales: one in magenta for Temperature in degrees Celsius (°C) ranging from -20 to 20, and another in black for Monthly precipitation (mm) ranging from 0 to 300. The chart displays three data series: Daily precipitation is shown as blue vertical bars, Monthly precipitation is a black line graph, and Temperature is represented by magenta dots. All three data series show a clear seasonal pattern, with peaks in the summer months and troughs in the winter months. A specific event labeled "Outburst" in red text is marked with a red dashed vertical line around May 2020, coinciding with a high peak in daily precipitation.


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Slope movement and ice collapse before the GLOF event
Type: figure
Figure

Image /page/6/Figure/0 description: A scientific figure composed of ten panels arranged in two rows and five columns, labeled (a) through (j). The top row, panels (a) to (e), displays a time series of grayscale images of a rugged terrain, dated 2020/5/28, 2020/6/9, 2020/6/21, 2020/7/3, and 2020/7/15 respectively. The bottom row, panels (f) to (j), shows colorful images of the same terrain over different time periods: (f) 2017/5/20-2017/7/31, (g) 2017/6/1-2017/8/24, (h) 2018/6/20-2018/8/7, (i) 2019/7/21-2019/8/26, and (j) 2020/8/8-2020/8/20. Each panel includes a circular magnified inset showing a detailed view of a specific area. Panel (a) contains a north arrow and a scale bar indicating 0, 0.5, and 1 Km. At the bottom right, a color scale bar for the colorful images ranges from 0 to 2.83 cm.


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Slope movement and ice collapse before the GLOF event
Type: text

**Fig. 8** Map of the landslide activity. **a–e** Sentinel-1 intensity images of the Jinweng Co and its surroundings representing the situation on May 28, June 9, June 21, July 3, and July 15. SAR backscattering images over the landslide are enlarged in the inset to improve visibil-

ity. **f-j** Deformation interferograms of Jinweng Co and surroundings for several periods during 2017–2020. Each fringe (a complete cycle of color variations) represents a 2.83 cm range change in the radar look direction

seen in Fig. 8d, e. We used InSAR to study possible long-term deformation in the area around the landslide for several periods in 2017–2020 (Fig. 8f-j). Since interferometric coherence for C-band Sentinel-1 images are low in the Jinweng Co surroundings (where the surface is covered with snow in winter), we analyzed interferograms with high coherence acquired in summer (Fig. 8f-j). The baselines between the image pairs were less than 60 m, so the interferograms were insensitive to DEM errors. The deformation maps formed from independent image pairs with

very different atmospheric situations show essentially the same patterns at a section of the lateral moraine. This means that the fringes are a real deformation. Therefore, this section of the lateral moraine was experiencing long-term deformation and likely finally collapsed into the lake due to heavy rainfall on June 21, 2020. Therefore, the rainfall-triggered landslide that occurred on or after June 21, 2020, exerted an important effect on this lake outburst event because the water waves may have overflowed the dam and/or directly caused the rupture of the dam.


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Slope movement and ice collapse before the GLOF event
Type: figure
Figure

Image /page/6/Figure/5 description: A scientific figure presented in a grid format, comparing two grayscale images of a rugged, mountainous terrain. The figure is divided into two main columns. The left column contains two rectangular images labeled (a) and (b). Image (a) at the top left shows the terrain with a north arrow in the upper left corner, a scale bar labeled '0 0.5 1 Km' in the lower left, and three white circles numbered 1, 2, and 3 highlighting specific areas. Image (b) below it shows a similar view of the terrain without any annotations. The right column consists of a 2x3 grid of six circular, magnified images. The top row is labeled (a1), (a2), and (a3), and these correspond to the magnified views of the areas marked 1, 2, and 3 in image (a), respectively. The bottom row is labeled (b1), (b2), and (b3), which are the corresponding magnified views from image (b). Each pair of vertical images, such as (a1) and (b1), shows the same feature, allowing for a direct comparison between the two source images (a) and (b).


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Discussions > Slope movement and ice collapse before the GLOF event
Type: text

**Fig. 9** (a) Average Sentinel-1 intensity image based on SAR images of May 28 and June 9 2020. (b) Average Sentinel-1 intensity image based on SAR images of June 21, July 3, July 15, and July 27, 2020.

The changes in the glacier tongue, the landslide, and the southern end of the lake are shown by (a1) (b1), (a2) (b2), and (a3) (b3), respectively


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Recent Landslides
Type: figure
Figure

Image /page/7/Picture/1 description: A diagram illustrating the causes of recent landslides. The image shows a body of water labeled "Jinweng Co" surrounded by brown land labeled "Lateral moraine". On the left, a light blue "Glacier" is shown melting into the lake, indicated by a red arrow and the word "Melting". Above the scene, grey clouds are causing "Extreme rainfall". The combination of melting and rainfall leads to "Water rising", indicated by a yellow arrow pointing up from the water's surface. A green mass of earth, labeled "Landslide", is shown sliding from the moraine into the lake. On the far right, the lake has an "Outlet" where water flows out.


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Recent Landslides
Type: text

**Fig. 10** Schematic diagrams illustrating the triggering factors and final mechanism of dam failure

The time series SAR intensity images also indicate that significant changes occurred before the landslide on the southern end of the lake between June 9 and 21. We compared the average intensity images before and after June 9 (Fig. 9) to investigate this phenomenon. Figure 9 shows a clear difference in the glacier tongue (Fig. 9a1, b1). We suggest that the change in the lake surface on June 21 (Fig. 9, b3) resulted from the collapse of ice on a steep portion of the glacier tongue (Fig. 9(a1), (b1)). Such collapse and runout could also have trapped moraine on the path into the lake. Hence, between June 9 and 21, the ice collapsed under the steep topography and transported the iceberg and moraine into the front of the lake. This caused the obvious variation seen in the June 21 SAR image (Fig. 9). Moreover, the landslide that occurred in the western lateral moraine can be observed through Fig. 9a2, b2. The distinct sliding boundary further demonstrates that the landslide might cause harm to the lake by striking the lake body and may be one of the primary GLOF triggering factors.


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Recent Landslides > Outburst mechanism of Jinweng Co
Type: text

Based on the displacement features of the parent glacier, the lake changes with SAR intensity, optical images, inventory data, and extreme meteorological conditions, there is evidence that the slope of the western lateral moraine was unstable due to glacier recede. The extremely high precipitation in June 2020 facilitated the erosion of the pre-weakening slope, finally inducing landslide activity. The sketch map in Fig. 10 shows the triggering factors and outburst mechanism of Jinweng Co. First, the hydrologically controlled glacier movement and melting generated masses of destabilizing sediments. Second, due to geomorphic conditions, the steep slopes above the lake produced huge kinetic energy when ice masses slid into the lake. Third, the daily precipitation about 4 days before the GLOF event was the largest in the past 3 years. Anomalous rain events or seasonal changes in the dynamics of the surrounding glaciers might be key triggering factors causing sudden hydro-fracturing and outburst floods in summer. Increased water inflow to the lake caused increased discharge from the morainedammed lake, which may have provoked increased erosion and incision

of the outflow channel into the dam body. More importantly, the landslide activity that occurred from the western lateral moraine on or after June 21 played a key role in the GLOF event because the fast slope movement into the lake is capable of producing water waves. This may have caused direct dam rupture. Overall, the causal chain for triggering the June 2020 outburst is a hydraulic connection established from a possible collapse of the glacial ice, a landslide, heavy precipitation, and warm temperature.

Recent Landslides
Outburst mechanism of Jinweng Co


Document: Analyzing the triggering factors of glacial lake outburst floods with SAR and optical images: a case study in Jinweng Co, Tibet, China
Section: Conclusions
Type: text

Multi-source remote sensing datasets and processing methods combined with meteorological observations were used in this study for GLOF investigation. These were then applied to comprehend the recent movement of parent glaciers and reveal the mechanisms leading to the outburst flood. Offset tracking of multi-track Sentinel-1 images was combined to retrieve the long-term time series displacement and 3D glacier flow velocity field. Optical Sentinel-2 and Landsat-8 images and inventory data were interpreted to reconstruct the long-term changes in the glacial lake. SAR intensity images and interferograms were analyzed to characterize changes in the glacier tongue and lateral moraine collapse.

In this study, to analyze lake outburst factors, we identified two important critical stages for the Jinweng Co outburst. First, ice collapse occurred in the parent glacier from June 9 to 21, and this transported ice and moraine into the front of the lake. Second, a landslide originating from the western lateral moraine occurred forcefully from June 21 to 25 and placed additional deposits into the lake body. The water level increased due to the unusually heavy rainfall on June 21, 2020; when combined with meltwater from glaciers, it provoked anomalous water importation. Due to the availability of pre-weakening lateral moraine combined with heavy rainfall on June 21, landslide activity was a serious factor for triggering dam failure by producing displacement waves. Hence, the main mechanism may be that the landslide mobilized and entered the lake between June 21 and 25, which caused the surface waves, triggered overtopping, and finally caused dam rupture.

The kinetic movement and outburst mechanism factors of Jinweng Co revealed in this study can be used to assess the potential risks of other glacier lakes in the region. Further, with the rise in extreme precipitation and the rapid melting of glaciers that lead to the destabilization of glacial lakes, moraine instabilities under changing climate conditions could become more likely. Therefore, process chains such as Jinweng Co will become increasingly significant in the future.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Type: text

Check for updates

Liye Yang1,2, Zhong Lu³ ⊠, Chaoying Zhao⁴ ⊠, Qin Zhang⁴, Xie Hu⁵ & Baohang Wang6

The frequency and intensity of glacial lake outburst floods (GLOFs) are increasing with rapid glacier retreat under a warming climate, yet the processes linking triggers and downstream responses remain poorly understood. Here, we investigate the 2013 GLOF at Ranzerio lake in southeastern Tibet using multi-source remote sensing, field observations, and hydrodynamic modeling. A glacier tongue collapse, with an estimated volume of  $3.8 \times 10^6 \, \text{m}^3$ , was identified as the primary trigger of the moraine dam breach. Flood routing simulations with the HEC-RAS 2D model reproduced a peak discharge of  $7930 \pm 18 \, \text{m}^3/\text{s}$  about  $25 \pm 5 \, \text{min}$  after the outburst, capturing flood propagation and geomorphic impacts downstream. The results reveal the multistage process chain of the outburst and highlight the importance of monitoring lake evolution, glacier movement, terrain change, and meteorological conditions for early warning and risk management in glacierized mountain regions.

High Mountain Asia (HMA) is experiencing rapid warming at a rate of 0.32 °C per decade, driving widespread glacier retreat and the expansion of glacial lakes1. These changes are contributing to an increased frequency and magnitude of glacial lake outburst floods (GLOFs), which pose significant threats to downstream communities and infrastructure2–5. GLOFs can be triggered by both short-term dynamic processes, such as avalanches, landslides, or extreme rainfall, and long-term destabilization mechanisms, including permafrost degradation, dam weakening, and buried ice melt6,7.

In the Himalayas, displacement waves from ice or rock avalanches are responsible for nearly half of all moraine-dam failures. Under ongoing climate warming, processes such as the rapid expansion of glacial lakes, accelerated glacier retreat, and growing instability of ice- and permafrost-affected slopes are expected to heighten the likelihood of moraine dam failure, thereby increasing both the frequency and potential magnitude of GLOF hazards6-8.

Despite increasing concern among scientists and hazard management authorities about the growing frequency and potential impacts of GLOFs, many events in remote high-altitude regions remain insufficiently documented owing to limited monitoring and poor accessibility7,9. These events often involve complex, cascading processes—such as mass movement initiation, wave generation, dam overtopping and erosion, and downstream flooding—whose timing and dynamics depend on the trigger type4,10. For example, GLOFs triggered by sudden ice or rock avalanches typically evolve over seconds to minutes, whereas those induced by extreme rainfall may


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Type: text

Despite increasing concern among scientists and hazard management authorities about the growing frequency and potential impacts of GLOFs , many events in remote high - altitude regions remain insufficiently documented owing to limited monitoring and poor accessibility  7 , 9  . These events often involve complex , cascading processes — such as mass movement initiation , wave generation , dam overtopping and erosion , and downstream flooding — whose timing and dynamics depend on the trigger type  4 , 10  . For example , GLOFs triggered by sudden ice or rock avalanches typically evolve over seconds to minutes , whereas those induced by extreme rainfall may

develop over several hours or days. In this study, we specifically focus on GLOFs triggered by sudden events. By contrast, GLOFs associated with ice-dammed lake drainage can occur over much longer timescales, ranging from days to months, but these are not considered here.

Advancements in remote sensing now allow for the near-continuous monitoring of glacier and lake dynamics, providing valuable information for hazard assessment. Synthetic Aperture Radar (SAR) and optical offset tracking enable the quantification of multi-dimensional glacier motion, offering insights into surge and avalanche precursors11–14. Interferometric Synthetic Aperture Radar (InSAR) techniques have been widely applied to detect slope deformation linked to permafrost thaw and ground ice creep15,16. Combined with hydrodynamic models such as HEC-RAS, these datasets can help reconstruct flood processes and assess downstream impacts17–19. However, the reliability of model outputs is contingent on the quality and resolution of input parameters, highlighting the importance of integrated, multi-source observations.

On 5 July 2013, a GLOF from Ranzerio lake (30.47°N, 93.53°E) in southeastern Tibet caused severe damage to downstream infrastructure and communities. Several studies have investigated this event, with optical imagery, terrain data, and field observations suggesting that a glacier avalanche was the likely trigger20–22. However, a comprehensive assessment that combines high-resolution remote sensing and dynamic modeling to fully characterize the flood mechanism, evolution, and post-event glacier response remains lacking. A more comprehensive approach is needed to

1College of Civil Engineering, Xiangtan University, Xiangtan, China. 2Hunan Provincial Key Laboratory of Geomechanics and Engineering Safety, Xiangtan University, Xiangtan, China. 3Roy M. Huffington Department of Earth Sciences, Southern Methodist University, Dallas, TX, USA. 4College of Geological Engineering and Geomatics, Chang'an University, Xi'an, China. 5College of Urban and Environmental Sciences, Peking University, Beijing, China. 6College of Geography and Oceanography, Minjiang University, Fuzhou, China. ⊠e-mail: zhonglu@mail.smu.edu; cyzhao@chd.edu.cn

capture the interactions between glacier dynamics and dam failure processes. Addressing this gap is critical for improving process-based understanding of GLOF initiation and propagation in paraglacial environments.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Type: text

 4  College of Geological Engineering and Geomatics , Chang ' an University , Xi ' an , China .  5  College of Urban and Environmental Sciences , Peking University , Beijing , China .  6  College of Geography and Oceanography , Minjiang University , Fuzhou , China . ⊠ e - mail : zhonglu @ mail . smu . edu ; cyzhao @ chd . edu . cn capture the interactions between glacier dynamics and dam failure processes . Addressing this gap is critical for improving process - based understanding of GLOF initiation and propagation in paraglacial environments .

This study addresses these knowledge gaps by integrating multi-source satellite remote sensing, high-resolution terrain data, and physically based hydrodynamic modeling to investigate the 2013 Ranzerio GLOF. Specifically, we: (1) quantified temporal changes in glacial lake extent and parent glacier velocity between 2010 and 2021; (2) identified the primary trigger of the lake outburst; (3) reconstructed the flood hydrograph and downstream routing using the HEC-RAS 2D model; and (4) synthesized the GLOF process chain by combining geomorphic, glaciological, and meteorological datasets. This integrated framework enhances understanding of the multistage processes driving GLOFs in paraglacial environments and provides a transferable approach to support hazard assessment and early-warning efforts in High Mountain Asia.

Ranzerio lake is located in Zhongyu Township, Jiali County, south-eastern Tibet, situated above the Nidu Zangpo River (Fig. 1). The study area spans elevations from approximately 4500 m to 6386 m above sea level. It lies within a semi-humid monsoon climate zone, with a mean annual temperature of  $-0.4\,^{\circ}\text{C}$  and approximately 83% of annual precipitation occurring between May and September, largely driven by monsoonal circulation20. The region is characterized by a dense distribution of glaciers and glacial lakes. Due to ongoing climate warming, the Qinghai–Tibet Plateau (QTP) has undergone widespread permafrost degradation in recent decades. According to the permafrost distribution map by Zou et al.23, the study area is underlain by permafrost (Fig. 1a).


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Type: text

a mean annual temperature of $ - 0 . 4 \ , ^ { \ circ } \ text { C } $ and approximately 83 % of annual precipitation occurring between May and September , largely driven by monsoonal circulation  20  . The region is characterized by a dense distribution of glaciers and glacial lakes . Due to ongoing climate warming , the Qinghai – Tibet Plateau ( QTP ) has undergone widespread permafrost degradation in recent decades . According to the permafrost distribution map by Zou et al .  23  , the study area is underlain by permafrost ( Fig . 1a ) .

Before the outburst, Ranzerio lake was one of the largest morainedammed glacial lakes in southeastern Tibet, with a surface area of approximately 0.58 km2, and measuring about 1.4 km in length and 0.5 km in width21. Both the lake and its parent glacier were aligned along a north-south axis. Following the GLOF, two new dammed lakes formed in the Yibu and Luoqiong valleys, with surface areas of approximately 0.13 km2 and 0.33 km2, respectively20,21. These lakes were impounded in tributary valleys where GLOF-deposited debris from the main valley blocked the natural drainage pathways, effectively damming the tributary streams. High-resolution satellite imagery reveals substantial geomorphic changes on the valley slopes surrounding Ranzerio lake. Figure 1a shows the spatial coverage of Sentinel-1 SAR data and RapidEye optical imagery used in this study. Figure 1b, c illustrates lake and glacier changes before and after the outburst. In 2010, the glacier and lake areas were 5.28 km2 and 0.58 km2, respectively, and a well-defined drainage channel was visible (Fig. 1b). By 12 September 2013, following the outburst, the glacier area had slightly decreased to 5.13 km2, while the lake area had been reduced by 54%, shrinking to 0.25 km2 (Fig. 1c). Inset panels show detailed views of the incised moraine dam and downstream impoundments, as captured by RapidEye imagery and confirmed through field surveys8.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > Long-term development of the glacier and Ranzerio lake
Type: text

Long-term changes in Ranzerio lake area and glacier tongue length were quantified from 2010 to 2021. Figure 2 presents the temporal evolution of these features over the study period. Between 2010 and 2012, the lake area expanded modestly from approximately 0.54 km² to 0.58 km². However, following the outburst flood event in July 2013, the lake area decreased sharply to about 0.27 km² by September 2013, indicating a substantial alteration of the glacier-lake system.

Subsequently, the lake area gradually increased, reaching roughly  $0.29\,\mathrm{km^2}$  by 29 October 2021 (Fig. 2b). Concurrently, the glacier tongue exhibited continuous retreat. Prior to the outburst, the tongue length had diminished to 317 m by 2012 and further to 300 m by July 2013. After the event, retreat accelerated, with the glacier tongue length reducing to approximately 128 m by October 2021, corresponding to an average retreat rate of ~22 m/yr (Fig. 2c).


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > Triggering factors of Ranzerio lake outburst
Type: text

Glacier surface velocities were derived using high-resolution RapidEye imagery and the offset tracking method. Annual horizontal glacier velocities from 2010 to 2013 are shown in Fig. 3. In these maps, vector arrows depict flow direction, while color gradients indicate velocity magnitude.

Between 30 October 2010 and 24 October 2011 (Fig. 3a), horizontal glacier velocity was relatively modest. During the subsequent period (24 October 2011 to 5 September 2012; Fig. 3b), a distinct shift in flow pattern occurred. In particular, the glacier tongue on the steep slope exhibited intensified southward motion, with velocities reaching approximately 30 m/yr. From 5 September 2012 to 12 September 2013 (Fig. 3c), the glacier tongue accelerated further, advancing toward the lake at a velocity of ~40 m/yr. Although the observed acceleration of glacier flow could have increased stress at the glacier–lake interface and potentially affected the stability of the proglacial moraine, direct evidence from ice-core stratigraphy or internal deformation measurements is lacking for the 2013 event. Therefore, while glacier velocity may have contributed to moraine destabilization, DEM-derived elevation changes provide the most robust geomorphic evidence for the onset of the GLOF.

RapidEye optical imagery revealed the development of a crevasse between October 2010 and September 2013. In the upper portion of the step icefall, transverse crevasses were consistently observed (Fig. 4), indicating increasing internal glacier stress. Accumulated glacier ice was observed flowing downslope toward the lake basin, cascading over steep sections of the glacier front and partially reaching the lake margin, rather than floating on the lake surface. By September 2012, imagery clearly showed glacier ice resting directly on the lake surface (Fig. 4c). Continued glacier retreat, combined with the progressive enlargement of crevasses, culminated in ice collapse from the tongue into the lake between September 2012 and September 2013. These dynamic instabilities—such as sudden mass movements or ice collapse—are considered triggers for the lake outburst event, potentially generating displacement waves that rapidly increase lake levels and erode the lake dam.

Further, we analyzed terrain changes using high-resolution 5 m TanDEM-X DEMs acquired on 22 April 2013 and 16 September 2013, representing pre- and post-GLOF conditions. Figure 5 illustrates the topographic evolution over this period. Before the outburst, the glacier tongue exhibited steep slopes averaging 39.6° and was characterized by well-developed transverse crevasses (Fig. 5a). Following the GLOF, substantial surface lowering was observed on the glacier tongue and within the lake basin (Fig. 5b). The differential DEM (Fig. 5c) revealed surface elevation losses of up to  $\sim\!50$  m in the steepest portions of the glacier tongue, indicating significant ice collapse. The estimated volume of collapsed glacier ice was approximately  $3.8\times10^6\,\mathrm{m}^3$  based on elevation differences and DEM resolution.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > Triggering factors of Ranzerio lake outburst
Type: text

tongue exhibited steep slopes averaging 39 . 6 ° and was characterized by well - developed transverse crevasses ( Fig . 5a ) . Following the GLOF , substantial surface lowering was observed on the glacier tongue and within the lake basin ( Fig . 5b ) . The differential DEM ( Fig . 5c ) revealed surface elevation losses of up to $ \ sim \ ! 50 $ m in the steepest portions of the glacier tongue , indicating significant ice collapse . The estimated volume of collapsed glacier ice was approximately $ 3 . 8 \ times10 ^ 6 \ , \ mathrm { m } ^ 3 $ based on elevation differences and DEM resolution .

Additionally, the lake surface elevation dropped by approximately 45 m (inset map in Fig. 5c), indicating deep incision of the moraine spillway as a result of rapid drainage. The breach depth was therefore estimated at ~45 m, consistent with previous field assessments21. Together, these observations support the hypothesis that an ice collapse from the steep glacier tongue generated displacement waves, which induced a rapid and transient rise in lake level, thereby eroding the moraine dam and ultimately triggering its failure.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: text

We reconstructed the 2013 GLOF event at Ranzerio lake to quantify flood depth, flow velocity, and discharge at downstream settlements. Figure 6 illustrates the modeled maximum flow depth and velocity. The hydrograph inset in Fig. 6a shows that the peak discharge at the dam breach ( $\sim$ 7930  $\pm$  18 m³/s) occurred approximately 25  $\pm$  5 min after the breach initiation.

To assess downstream impacts, we analyzed modeled flow parameters at four villages: Rongqingcun (Village 1), Zhaixongcun (Village 2), Bengdacun (Village 3), and Lingngucai (Village 4), located ~26, 28, 35, and 40 km from Ranzerio lake, respectively (Figs. 1 and 7). The modeled flood


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: figure
Figure

Image /page/2/Figure/2 description: A scientific figure composed of three panels, labeled (a), (b), and (c), illustrating changes in a glacial landscape using remote sensing data.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: text

Panel (a) is a regional map centered around Jiali, with coordinates from 93°20'E to 93°40'E and 30°20'N to 30°40'N. It shows a main river with several numbered villages along its banks, and distinguishes between areas of "Seasonally frozen ground" and "Permafrost." The map outlines the coverage areas for "Sentinel-1" (black), "RapidEye" (orange), and the "Study area" (red). A red star marks the "Lake site." An inset map in the top right corner shows the location of the study area on an elevation map of the Tibetan Plateau.

Panel (b) is a satellite image showing a close-up of the study area before a change event. It features a "Glacier" outlined in purple, a "Lake" outlined in blue at the glacier's terminus, and a "Drainage channel" outlined in orange extending from the lake.

Panel (c) is a satellite image of the same area as (b), showing the landscape after the change event. It highlights a newly formed "Dam" (yellow line), a resulting "Flooding area" (reddish-brown outline), and a "New lake" that has formed downstream. Two inset images provide zoomed-in views of the "Dam" and the "New lake."

A comprehensive legend at the bottom defines all the symbols and outlines used across the panels.

Fig. 1 | Spatial coverage of multi-source remote sensing datasets and changes in the glacier and Ranzerio lake (created using ArcGIS 10.4 by the authors).

a Footprints of remote sensing imagery: black rectangle indicates Sentinel-1 SAR

a Footprints of remote sensing imagery: black rectangle indicates Sentinel-1 SAR coverage, orange indicates RapidEye optical imagery, and the red box delineates the study area. Locations of downstream villages are also shown: Rongqingcun (Village

1), Zhaixongcun (Village 2), Bengdacun (Village 3), and Lingngucai (Village 4).  $\bf b$  Pre-GLOF (30 October 2010) and  $\bf c$  post-GLOF (12 September 2013) RapidEye images, illustrating the landscape changes triggered by the 2013 Ranzerio lake GLOF event.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: figure
Figure

Image /page/3/Figure/2 description: A scientific figure illustrating the changes in Ranzerio lake and its associated glacier tongue from 2010 to 2021, divided into three parts: (a), (b), and (c).


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: text

Part (a) displays a series of nine satellite images of the lake. The top row, labeled "Before," shows images from 2010/10/30, 2011/10/24, and 2012/9/5, where the lake is large. The next two rows, labeled "After," show images from 2013/9/12, 2016/12/13, 2017/8/24, 2019/9/26, 2020/8/25, and 2021/10/29. The 2013 image shows a significantly smaller lake with ice debris, corresponding to a major event. Subsequent images show the lake slowly recovering but not reaching its pre-2013 size.

Part (b) is a line graph plotting "Lake area (km²)" against "Year" from 2010 to 2022. The lake area increases from about 0.53 km² in 2010 to a peak of about 0.59 km² in 2012. A sharp drop, labeled "2013 event," occurs in 2013, with the area decreasing to about 0.27 km². After 2013, the lake area shows a slight, gradual increase, reaching about 0.30 km² by 2022.

Part (c) is a line graph plotting "Glacier tongue (m)" against "Year" from 2010 to 2022. The graph shows a consistent decrease in the length of the glacier tongue over the period. It starts at over 600 m in 2010 and drops to approximately 120 m by 2022. A label "2013 event" is placed near the data points for 2012 and 2013, indicating a continued retreat during that time.

Fig. 2 | Time series of Ranzerio lake and the glacier tongue from 2010 to 2021 (created using ArcGIS 10.4 and Origin 2021 by the authors). a Spatiotemporal evolution of the glacier tongue and lake extent. b Temporal changes in lake area. c Temporal changes in glacier tongue length.

hydrographs and flow depths at these sites are shown in Fig. 7 and summarized in Table 1.

Results indicate a progressive attenuation of both peak discharge and maximum flow depth with increasing downstream distance. At village 1, the peak discharge was  $\sim 2623 \pm 7 \text{ m}^3/\text{s}$ , arriving  $89 \pm 7 \text{ min}$

after the breach, with a flow depth of  $\sim$ 7.7  $\pm$  0.6 m. At village 2, the peak discharge decreased to  $\sim$ 2485  $\pm$  14 m³/s, occurring at 101  $\pm$  6 min postbreach, with a depth of  $\sim$ 5.5  $\pm$  0.1 m. At village 3, the discharge further declined to  $\sim$ 1056  $\pm$  5 m³/s, reaching the site at 177  $\pm$  7 min, with a depth of  $\sim$ 4.3  $\pm$  0.1 m. At village 4, the peak discharge was  $\sim$ 242  $\pm$  2 m³/s,


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: figure
Figure

Image /page/4/Figure/2 description: A four-panel figure illustrating glacier horizontal velocity from 2010 to 2013. The three main panels, labeled (a), (b), and (c), show 3D topographical maps of a glacier and the adjacent Razerio Lake during different time periods. The glacier's surface is covered with colored vectors indicating the direction and speed of ice flow. The fourth panel provides a legend. Panel (a) covers the period 2010/10/30-2011/10/24. Panel (b) covers 2011/10/24-2012/9/5. Panel (c) covers 2012/9/5-2013/9/12. The legend in the bottom right indicates that a reference red vector represents a velocity of 60 meters per year (m/yr). Below this, a color bar for 'Horizontal Velocity (m/yr)' shows a scale from 0 (blue) to 60 (red), with labeled increments of 10.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > GLOF reconstruction and downstream impact assessment
Type: text

Fig. 3 | Glacier horizontal velocities from 2010 to 2013 (created using Origin 2021 by the authors). a 30 October 2010 to 24 October 2011. b 24 October 2011 to 5 September 2012. c 5 September 2012 to 12 September 2013. Vector arrows indicate flow direction, and color shading represents the magnitude of horizontal velocity.

arriving  $332 \pm 9$  min after the event, with a maximum modeled depth of  $\sim 2.2 \pm 0.2$  m.

These results demonstrate the rapid onset and high magnitude of the initial flood wave, followed by progressive attenuation downstream. Such dynamics underscore the need for rapid detection of upstream triggers, such as ice collapse, and for coordinated early warning systems coupled with targeted risk-reduction measures. Practical applications include continuous remote sensing of glacier and lake conditions, real-time hydrological monitoring, and automated alert systems to inform downstream communities and guide emergency response planning.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > Deposition estimation and uncertainty in flood simulation
Type: text

Due to the absence of direct post-event water depth measurements, the simulated GLOF inundation extent was validated against observations from high-resolution RapidEye imagery. The flood extent was delineated from two 5 m resolution RapidEye scenes acquired on 12 September 2013 (Fig. 8a). Comparison shows that the observed inundation area was 3.67 km², while the simulated extent covered 3.89 km², representing a relative difference of ~6.0%. Likewise, the modeled new lake area (0.339 km²) closely matched field-derived measurements (0.330 km²)8,20, with a deviation of only ~2.7%. These small differences fall within the expected uncertainty range and indicate that the hydraulic model is capable of reliably reproducing the spatial extent of flooding.

Owing to the limited spatial coverage of the available DEM datasets, deposition and erosion were analyzed only within the overlapping areas (Fig. 8b). The DEM difference analysis revealed a total sediment deposition of  $48.06 \pm 0.004 \, \text{Mm}^3$  and a total erosion of  $25.54 \pm 0.005 \, \text{Mm}^3$ , resulting in a net volumetric change of  $22.52 \, \text{Mm}^3$  within the analyzed area. It should be noted that these estimates here are limited to the DEM coverage and do not represent the total downstream sediment caused by the flood.

Flow dynamics during GLOF events are often complex, involving transitions from clear-water to sediment-laden or debris flows with possible

non-Newtonian rheologies5,24. Due to the absence of detailed sediment data for this event, we adopted a clear-water hydraulic model following established approaches5,18,25. While this simplification may underestimate sediment-transport effects, it provides credible estimates of inundation extent, flooding discharge, and timing given the available dataset.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > Glacier movement after the lake outburst
Type: text

To investigate the post-outburst dynamics of the parent glacier, we derived glacier displacement time series using the PO-MSBAS method applied to Sentinel-1 SAR imagery acquired between 2017 and 2021. Azimuth displacements, representing motion along the satellite flight path, were used to approximate north-south glacier movement, consistent with the glacier's primary orientation 12,26.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Results > Glacier movement after the lake outburst
Type: figure
Figure: Figure 9 presents the azimuth displacement time series, revealing a persistent southward glacier motion with an average velocity of $\sim$ 6 m/yr in the accumulation zone. At point G (Fig. 9i), the cumulative LOS displacement reached $\sim$ 7 m, while the total azimuth displacement over the 4-year period amounted to $\sim$ 20 m, indicating sustained glacier flow following the outburst event.

Figure 9 presents the azimuth displacement time series, revealing a persistent southward glacier motion with an average velocity of  $\sim$ 6 m/yr in the accumulation zone. At point G (Fig. 9i), the cumulative LOS displacement reached  $\sim$ 7 m, while the total azimuth displacement over the 4-year period amounted to  $\sim$ 20 m, indicating sustained glacier flow following the outburst event.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

The 2013 Ranzerio lake outburst can be understood within the broader framework of moraine-dammed GLOF triggering mechanisms27–31. Such events are commonly initiated by external disturbances—such as ice or rock collapse, mass movements, or displacement waves—that erode the dam and trigger its failure. Our evidence indicates that the Ranzerio outburst was most likely driven by a sudden ice collapse and the subsequent generation of high-energy displacement waves.

High-resolution glacier velocity mapping revealed sustained acceleration of the glacier tongue, from ~30 m/yr in 2011–2012 to ~40 m/yr in 2012–2013, accompanied by crevasse expansion and downslope extension toward the lake margin. By late 2012, the glacier


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: figure
Figure

Image /page/5/Figure/2 description: A four-panel figure displaying satellite images of a glacier tongue from 2010 to 2013, illustrating changes over time. Each panel is labeled with a letter and a date.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

- Panel (a), dated 2010/10/30, shows the glacier with a red flag pointing to a feature labeled "crevasse". A white dashed line indicates the glacier's edge, labeled "Glacier retreat".
- Panel (b), dated 2011/10/24, shows the same area a year later, with the "crevasse" still marked and the glacier's edge having retreated further back.
- Panel (c), dated 2012/9/5, is a false-color image highlighting the "crevasse" with a red flag.
- Panel (d), dated 2013/9/12, shows a significant "break" in the glacier, indicated by red text and four red arrows pointing to the fractures.

All panels are marked with coordinates 30°29' and 93°32' and include a scale bar for 0.05 km. A partial caption at the bottom reads: "glacier crevasse on its tongue from 2010 to 2013 (created using ArcGIS September 2013. Note: The zoomed-in sections may appear less sharp du...".

Fig. 4 | Glacier crevasse on its tongue from 2010 to 2013 (created using ArcGIS 10.4 by the authors). a RapidEye image on 30 October 2010. b RapidEye image on 24 October 2011. c RapidEye image on 5 September 2012. d RapidEye image on 12

September 2013. Note: The zoomed-in sections may appear less sharp due to the original PlanetScope spatial resolution and local magnification used to highlight details.

front was in direct contact with the lake surface. Similar pre-failure acceleration patterns have been observed in other ice-avalanche-induced GLOFs32-34, where progressive destabilization often precedes catastrophic collapse. DEM differencing between April and September

2013 revealed surface lowering of up to ~50 m on the steep glacier tongue, corresponding to an estimated ice loss volume of ~3.8  $\times$  10  $^6$  m³. This sudden collapse likely generated displacement waves capable of overtopping the moraine dam  $^{35\text{--}37}$ .


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: figure
Figure

Image /page/6/Figure/2 description: A figure composed of three maps and one line graph, illustrating the topographical changes before and after a Glacial Lake Outburst Flood (GLOF). The maps are located at approximately 93°32' E longitude and between 30°28' and 30°29' N latitude. Map (a), labeled "Pre-GLOF", shows a grayscale topographical view with a "Steep Region" and "Crevasses" indicated. A large, textured area is outlined in blue. Map (b), labeled "Post-GLOF", shows the same region after the event, with the previously blue-outlined area now outlined in pink and appearing smoother. Map (c) displays the "Elevation change (m)" using a color scale. The area of change is highlighted, showing a significant loss of elevation (colored yellow, orange, and red), with a total volume change of 3.8x10^6 m^3 noted. The legend for elevation change ranges from -50 to >50 meters. A "Breach Dam" is indicated at the lower end of the affected area. Below the maps, a line graph plots "Dam breach depth (m)" on the y-axis versus "Distance (km)" on the x-axis. The y-axis ranges from 0 to 45 m, and the x-axis from 0.00 to 0.25 km. The blue line on the graph shows the depth profile of the breach, starting at 0, rising to a peak of approximately 43 meters at a distance of about 0.12 km, and then decreasing sharply.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

Fig. 5 | Terrain changes of the glacier tongue and Ranzerio lake before and after the GLOF, derived from TanDEM-X datasets (created using ArcGIS 10.4 and Origin 2021 by the authors). a Pre-GLOF terrain on 22 April 2013. b Post-GLOF terrain on 16 September 2013. c Elevation difference map showing terrain changes

before and after the event, highlighting the ice collapse that occurred from the lower glacier tongue and the incision of the moraine dam. The inset map illustrates the dam breach, with an incision depth of  $\sim\!45$  m.

Meteorological analysis based on ERA5 reanalysis data further highlighted anomalous conditions in early July 2013, as shown in Fig. 10. Mean daily June–July temperatures over 2004–2013 ranged from 4.19–6.54 °C and 6.20–8.52 °C, respectively. Corresponding mean daily precipitation also fluctuated notably, with June averages between ~4.50 mm and 7.28 mm, and July averages between 4.94 mm and 8.48 mm. Cumulative June–July totals varied from ~293.5 mm to 481.2 mm, with the 2013 value (423.6 mm) exceeding the median but remaining below the decadal maximum. Using the 2004–2012 baseline, the 95th percentile thresholds for daily precipitation and temperature were 11.68 mm and 8.83 °C, respectively 38. Importantly, the days immediately preceding the GLOF outburst included both an extreme high-temperature event (5 July 2013) and an extreme precipitation event (3 July 2013), each surpassing these thresholds. These conditions likely enhanced meltwater input and hydrological loading on the proglacial lake, thereby exacerbating dam instability 29,39,40.

Integrating the geomorphological, glaciological, and meteorological evidence, we propose a multi-stage process chain, as shown in Fig. 11: (1) long-term glacier retreat and steepening of the ice front above the lake increased susceptibility to collapse; (2) short-term metrological anomalies in early July 2013 accelerated destabilization; (3) a sudden ice collapse generated displacement waves, rapidly elevating lake levels and imposing erosion on the moraine dam; and (4) overtopping and subsequent erosion breached the dam to a depth of ~45 m, releasing the lake volume as a high-magnitude flood that caused downstream geomorphic change and sediment redistribution.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

glaciological , and meteorological evidence , we propose a multi - stage process chain , as shown in Fig . 11 : ( 1 ) long - term glacier retreat and steepening of the ice front above the lake increased susceptibility to collapse ; ( 2 ) short - term metrological anomalies in early July 2013 accelerated destabilization ; ( 3 ) a sudden ice collapse generated displacement waves , rapidly elevating lake levels and imposing erosion on the moraine dam ; and ( 4 ) overtopping and subsequent erosion breached the dam to a depth of ~ 45 m , releasing the lake volume as a high - magnitude flood that caused downstream geomorphic change and sediment redistribution .

This study provides a comprehensive reconstruction of the 2013 Ranzerio GLOF by integrating geomorphic, glaciological, and meteorological datasets with high-resolution remote sensing and physically based hydrodynamic modeling. Differential DEM analysis revealed pronounced surface lowering of up to  $\sim\!50$  m on the steep glacier tongue, corresponding to an ice-collapse volume of  $\sim\!3.8\times10^6\,\mathrm{m}^3$ . This ice collapse acted as the primary trigger, generating displacement waves that abruptly raised lake levels and imposed extreme erosion on the moraine dam. Hydrodynamic simulations constrained by field-derived breach geometry successfully reproduced the outburst process, estimating a peak discharge of  $7930\pm18\,\mathrm{m}^3/\mathrm{s}$ , a breach depth of  $\sim\!45\,\mathrm{m}$ , and an inundation extent closely matching RapidEye observations (relative difference  $\sim\!6\%$ ). These quantitative results validate the reliability of our reconstruction.

By explicitly linking the multistage process chain—from accelerated glacier flow and tongue destabilization, through ice collapse and displacement wave generation, to moraine-dam breach and downstream flooding—this study identifies specific indicators that can be monitored for early warning. Observables such as ice-front acceleration, sudden ice mass movement, and dam erosion provide actionable signals for hazard detection. Furthermore, the reconstruction of erosion and deposition volumes along the flood path offers quantitative input for hazard mapping and risk assessment, allowing identification of areas most susceptible to inundation and sediment impact.

Beyond the event-specific insights, the integrated methodological framework—combining optical and SAR remote sensing, DEM


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: figure
Figure

Image /page/7/Figure/2 description: A figure with two maps, labeled (a) and (b), and an inset graph, illustrating the characteristics of the Ranzerio lake outburst flooding.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

Map (a) displays the 'Maximum Flow depth (m)' in a river valley. The flood path is colored on a scale from light blue (0-4 m) to dark pink (36-40 m). The map includes latitude and longitude coordinates, with four numbered green circles (1, 2, 3, 4) marking locations along the river downstream from Ranzerio lake.

Map (b) shows the 'Maximum Flow velocity (m/s)' for the same event and location. The flow velocity is represented by a color scale from dark red (0-2 m/s) to dark blue (18-20 m/s).

An inset graph plots 'Discharge (m³/s)' on the y-axis against 'Time (min)' on the x-axis. A red line shows the discharge hydrograph, which peaks sharply. An annotation indicates the peak discharge is 7930 m³/s at 25 minutes. Both maps include a scale bar showing 0, 2, and 4 km.

Fig. 6 | The maximum flowing depth and velocity of Ranzerio lake outburst flooding (created using ArcGIS 10.4 and Origin 2021 by the authors). a The maximum flooding depth. b The maximum flow velocity.

differencing, ERA5-based meteorological reanalysis, and hydraulic modeling—provides a transferable approach for high-mountain regions. This framework supports the development of early warning systems, targeted hazard mapping, and quantitative risk assessment, contributing to climate adaptation planning in other rapidly changing cryospheric environments.

Several limitations in this study should be acknowledged. First, due to the absence of direct post-event field measurements—such as wash limits or downstream water surface elevation profiles—it was not possible to validate modeled water surface profiles against observed data. This constrains our ability to comprehensively evaluate model performance in reproducing

downstream flow dynamics beyond the inundation extent10. To partially address this limitation, we compared the modeled inundation area with high-resolution satellite imagery, which provided reliable spatial delineation of the flood extent. Future post-event field campaigns should therefore prioritize the collection of wash limits, water surface elevations, and sediment deposition profiles to enhance model calibration and to better constrain flood dynamics in similar GLOF events.

Second, the sediment erosion and deposition analysis derived from DEM differencing provided only a partial estimate of geomorphic change associated with the 2013 Ranzerio GLOF. However, these estimates capture


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: figure
Figure

Image /page/8/Figure/2 description: A figure containing four line graphs, labeled (a) Village1, (b) Village2, (c) Village3, and (d) Village4. Each graph plots Flow depth (m) on the left y-axis and Discharge (m³/s) on the right y-axis against Time (min) on the x-axis, which ranges from 0 to 1000. The legend indicates that a blue line with a shaded uncertainty band represents Flow depth, and a red line with circle markers represents Discharge. In graph (a) Village1, both flow depth and discharge show a sharp, immediate peak, with flow depth reaching about 8.5 m and discharge reaching about 2700 m³/s, before gradually decreasing. In graph (b) Village2, the pattern is similar, with flow depth peaking around 5.5 m and discharge peaking around 2700 m³/s. In graph (c) Village3, the peaks are lower and occur slightly later, with flow depth reaching about 4.5 m and discharge about 1100 m³/s. In graph (d) Village4, the rise is much more gradual, with flow depth peaking around 2.5 m and discharge around 600 m³/s at approximately 300 minutes.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

Fig. 7 | Flooding discharge and depth of Ranzerio lake at four downstream villages (created using ArcGIS 10.4 and Origin 2021 by the authors). a–d Flow depth and discharge at four downstream villages, respectively.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: table
Table: Table 1 | GLOF peak discharges and flow depths at four downstream villages

| Routing location | Time (min) | Maximum discharge (m³/s) | Maximum flow depth(m) |
|------------------|------------|--------------------------|-----------------------|
| Village1         | $89 1 7$  | $2623 1 7$              | $7.7 1 0.6$          |
| Village2         | $101 1 6$ | $2485 1 14$             | $5.5 1 0.1$          |
| Village3         | $177 1 7$ | $1056 1 5$              | $4.3 1 0.1$          |
| Village4         | $332 1 9$ | $242 1 2$               | $2.2 1 0.2$          |

Routing location
Time (min)
Maximum discharge (m³/s)
Maximum flow depth(m)


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Discussion
Type: text

only a fraction of the total sediment budget, as extensive downstream reaches were not covered by the available DEMs. A more complete understanding of GLOF sediment budgets and flow dynamics therefore, requires extending DEM differencing to wider downstream areas. Moreover, coupling such geomorphic analyses with detailed sedimentological investigations of flood deposits will be essential for constraining flow rheology, sediment transport mechanisms, and depositional patterns2,41. This integration will provide critical insights into the physical processes governing GLOFs and improve the predictive capability of hazard assessments in high-mountain environments.

Finally, while this study focused on the triggering mechanisms and flooding processes of the 2013 Ranzerio GLOF, future research should also examine hillslope dynamics surrounding proglacial lake basins. The valley slopes around Ranzerio lake are underlain by permafrost, and ongoing regional permafrost degradation driven by climatic warming may exacerbate slope instability and surface deformation5. Remote sensing techniques, particularly InSAR, offer effective means to monitor

and quantify such ground movements in remote, data-scarce high-mountain environments 18,42,43. Characterizing the temporal and spatial evolution of hillslope deformation could improve assessments of potential hazards threatening moraine dam stability or triggering future outburst floods. Integrating hillslope monitoring with hydrological and glaciological datasets, therefore, represents a promising approach for enhancing early warning systems and advancing comprehensive hazard evaluations in glacierized regions under climate change.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods
Type: text

To investigate the 2013 Ranzerio lake GLOF event, we developed an integrated processing workflow combining multi-source satellite remote sensing data with physically based hydrodynamic modeling. The datasets used are summarized in Table 2.

Four high-resolution RapidEye optical images (5 m spatial resolution) acquired between 2010 and 2013 were used to delineate lake boundaries and estimate horizontal glacier surface velocities prior to the outburst. An additional five RapidEye images (2016–2021) were analyzed to track postevent changes in glacier extent and lake area. Sentinel-1 SAR imagery (2017–2021) was further used to monitor glacier motion after the event. To quantify terrain changes and evaluate potential triggering mechanisms, we employed two TanDEM-X digital elevation models (5 m resolution) acquired on 22 April and 16 September 2013. Elevation differencing between the two DEMs enabled the identification of pre- and post-GLOF surface changes.

Meteorological forcing was characterized using daily precipitation and temperature data from the ERA5 reanalysis44. Specifically, we used the post-processed daily statistics from 1940 to the present, available from the


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods
Type: figure
Figure

Image /page/9/Figure/2 description: A multi-panel figure comparing flooded areas and downstream elevation changes in a mountainous, snow-covered region. The figure is composed of four main panels labeled (a), (a1), (a2), and (b).


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods
Type: text

Panel (a) is an overview map showing a river valley. A legend indicates three types of areas: "Lake area" (light purple), "Mapped inundation area" (magenta dashed line), and "Simulated inundation area" (blue dashed line). The mapped and simulated areas follow the path of a flood down the valley. The map includes latitude and longitude coordinates and a 1 km scale bar.

Panel (a1) is a zoomed-in view of the upper part of the flood path, showing the "Maximum Flow depth (m)". A color scale indicates depths from 0-4 m (light blue) to 24-28 m (dark purple).

Panel (a2) is a zoomed-in view of the lower part of the flood path, also showing the maximum flow depth. A specific area is highlighted with a dashed box and labeled "0.339 km²". A further magnified view of this area shows a lake-like feature labeled "0.330 km²".

Panel (b) shows the "Elevation change (m)" along the same flood path. A color scale ranges from red (-50 to -40 m) to blue (90 to 100 m), representing erosion and deposition, respectively. The upper reaches of the path are shown in red, orange, and yellow, while the lower, wider area is shown in green and blue.

Fig. 8 | Comparison of flooded areas and downstream elevation changes (created using ArcGIS 10.4 by the authors). a Flood inundation area between simulated and mapped results. b Elevation changes occur at the downstream due to limited DEM coverage.

Copernicus Climate Data Store (https://cds.climate.copernicus.eu/datasets/derived-era5-single-levels-daily-statistics). This globally consistent dataset assimilates a wide range of observations into a state-of-the-art atmospheric model, providing ~0.25° (~28 km) spatial resolution and daily temporal resolution. For this study, daily total precipitation and air temperature from June to July 2004–2013 were extracted for the study area to characterize meteorological conditions leading up to the GLOF.

In the absence of pre-event SAR acquisitions, glacier surface velocities for 2010–2013 were estimated using optical image correlation applied to the RapidEye dataset. Ice collapse volume was quantified from TanDEM-X elevation changes and subsequently used to inform the GLOF process reconstruction. The outburst flood was simulated using the HEC-RAS 2D hydrodynamic model, incorporating breach parameters derived from DEM differencing and previous field studies. HEC-RAS was selected for its proven capability in dam-break and flood routing simulations, as well as its ability to represent unsteady flow dynamics in complex terrain 5.18,19.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Lake mapping using optical imagery
Type: text

To map the temporal evolution of the Ranzerio lake and minimize classification uncertainties, we employed high-resolution RapidEye multispectral imagery from 2010 to 2021. To ensure that seasonal

hydrological fluctuations did not confound interannual changes in lake area, imagery was deliberately selected from the same season each year. This seasonal consistency is a widely recognized strategy in glacial lake monitoring, as it reduces the influence of transient factors such as snowmelt or seasonal ice cover, thereby improving the comparability of multi-year measurements 45,46.

Lake boundaries were delineated using a semi-automated approach based on the Normalized Difference Water Index (NDWI). For images acquired under conditions of low solar illumination or partial snow/ice cover, manual editing was conducted to correct misclassified pixels, guided by careful visual inspection. The final lake polygons were further cross-checked against historical optical imagery and existing glacier lake inventories for the Tibetan Plateau 16,47 to ensure both spatial accuracy and temporal consistency. This integrated approach provided a robust time series of glacial lake outlines, suitable for quantifying area changes across the study period.

Methods
Lake mapping using optical imagery


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Glacier velocity using optical and SAR images
Type: text

To quantify glacier surface displacement before and after the 2013 Ranzerio lake outburst, we applied offset tracking techniques to both optical and SAR datasets. Annual glacier velocities from 2010 to 2013


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Glacier velocity using optical and SAR images
Type: figure
Figure

Image /page/10/Figure/2 description: A figure composed of nine panels, labeled (a) through (i), illustrating glacier displacement from 2017 to 2020. Panels (a) through (h) are a time series of 3D topographic maps showing the cumulative displacement of a glacier near Razerio Lake. The dates for the maps are: (a) 2017/03/21, (b) 2018/07/02, (c) 2018/12/29, (d) 2019/07/09, (e) 2019/12/24, (f) 2020/04/22, (g) 2020/07/15, and (h) 2020/10/31. A color scale at the bottom indicates cumulative displacement in meters (m), ranging from -15 (purple) to +15 (red), with 0 being green. Over time, the glacier area on the maps changes from green to blue and purple, indicating increasing negative displacement. Panel (i) is a scatter plot titled 'Glacier displacement (m)' versus 'Year'. The y-axis ranges from -20 to 0 m, and the x-axis ranges from 2017 to 2021. The plot shows two data series: AZI (red dots) and LOS (blue dots). Both series show a downward trend over time. The AZI displacement starts near 0 in 2017 and decreases to approximately -15 m by late 2020. The LOS displacement also starts near 0 in 2017 and decreases to about -7 m by late 2020.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Glacier velocity using optical and SAR images
Type: text

Fig. 9 | Glacier displacement time series from 2017 to 2020 (created using ArcGIS 10.4 and Origin 2021 by the authors). a-h Displacement on 21 March 2017, 2 July 2018, 29 December 2018, 9 July 2019, 24 December 2019, 22 April 2020, 15 July 2020,

31 October 2020, respectively. The colors represent the cumulative displacement. i The two-dimensional displacement time series on point G.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Glacier velocity using optical and SAR images
Type: figure
Figure

Image /page/10/Figure/5 description: Fig. 10 | Daily temperature, daily precipitation, and cumulative precipitation at Ranzerio site between June and July from 2004 to 2014 (created using Python 3.12 by the authors). Daily temperature is shown in blue solid lines, daily precipitation is shown in gray bars, and cumulative precipitation is shown in gray dashed lines.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Glacier velocity using optical and SAR images
Type: figure
Figure

Image /page/10/Figure/6 description: A multi-axis graph plots meteorological data from January 1, 2004, to January 1, 2014. The x-axis represents the date. The primary y-axis on the left, labeled 'Daily Precipitation (mm)', ranges from 0 to 25. The secondary y-axis on the right has two scales: 'Temperature (°C)' from -5 to 15, and 'Cumulative Precipitation (mm)' from 0 to over 5000. The graph displays four data series as indicated by the legend: a red dashed line for 'Event: 2013-07-5', gray bars for 'Daily Precipitation (mm)', a solid blue line for 'Temperature (°C)', and a dashed black line for 'Cumulative Precipitation (mm)'. The daily precipitation is shown as dense vertical bars, exhibiting an annual pattern. The temperature follows a cyclical annual pattern, peaking in the middle of each year. The cumulative precipitation shows a sawtooth pattern, resetting to zero at the beginning of each year and increasing throughout the year. A specific event on July 5, 2013, is marked with a vertical red dashed line, corresponding to a high daily precipitation event shown as a red bar.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Glacier velocity using optical and SAR images
Type: text

were derived using four high-resolution (5 m) ortho-rectified RapidEye images. Displacements were estimated using the phase correlation-based image matching algorithm implemented in the COSI-Corr software package, a robust method for large-scale glacier motion analysis48–51.

The image pairs were processed by computing phase differences in the Fourier domain to detect sub-pixel offsets. Matching window sizes ranging from 32 to 256 pixels and a step size of 2 pixels were tested to optimize correlation quality. A signal-to-noise ratio (SNR) threshold of 0.9 was used to filter out low-confidence matches. Displacement fields in the east–west

and north–south directions were produced, followed by noise suppression using gross error removal, non-local means filtering, and polynomial surface fitting (deramping). Horizontal surface velocities were obtained by combining the displacement components and normalizing by the acquisition interval. Given the 5 m pixel resolution, the expected measurement precision was approximately 0.25–0.5 m48.

For the post-outburst period (2017–2021), glacier motion was estimated using Sentinel-1 SAR data processed with the GAMMA software. Pixel Offset tracking was performed using a matching window of  $128 \times 128$  pixels in range and azimuth directions, and a search step of  $4 \times 1$  pixels. A normalized cross-correlation threshold of 0.3 was applied to exclude unreliable offset vectors12. The offset time series were then integrated using the Multi-dimensional Small Baseline Subset (MSBAS) method  $^{11,12}$ . Then, we used the Pixel Offset tracking MSBAS (PO-MSBAS) method to retrieve glacier displacement time series in both azimuth and line-of-sight (LOS) directions by singular value decomposition (SVD).


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Terrain change using TanDEM-X data
Type: text

To assess terrain changes associated with the Ranzerio lake outburst, we employed two TanDEM-X digital elevation models (DEMs) with a spatial resolution of 5 m, acquired on 22 April 2013 and 16 September 2013. DEM differencing is a widely used approach for quantifying surface elevation changes over time52,53. However, accurate estimation of elevation change requires prior co-registration of the DEMs to eliminate horizontal and vertical misalignments that can introduce systematic biases.

We adopted the gradient-based co-registration method proposed by Ye et al.54. In this approach, pixel-wise oriented gradients were extracted from the reference DEM (April 2013) and compared to the target DEM (September 2013) using the fast Fourier transform (FFT) to compute a similarity metric in the frequency domain. Control points (CPs) were identified through this similarity analysis, and a transformation was applied to align the target DEM to the reference. The co-registered DEMs were then differenced to produce an elevation change map.

Methods
Terrain change using TanDEM-X data


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Terrain change using TanDEM-X data
Type: figure
Figure

Image /page/11/Picture/7 description: A diagram illustrates the process of a glacial lake outburst flood. On the left, a large piece of ice, labeled "Ice collapse ~3.8x10^6 m^3", is shown breaking off from a "Glacier" and falling into a "Lake" below. The impact creates "Displacement waves" in the lake. These waves travel across the lake and wash over a natural dam, an event labeled "Dam overtopping". The water that spills over the dam flows down the other side, resulting in "Flooding". A sun is depicted in the upper right corner of the diagram.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > Terrain change using TanDEM-X data
Type: text

**Fig. 11** | Schematic diagrams showing the likely mechanisms of the disaster chains of the GLOF event for Ranzerio lake (created using Python 3.12 by the authors).

The elevation difference dataset was used to detect geomorphic changes in the glacier and surrounding slopes, supporting the analysis of surface deformation patterns. GLOF triggering zones were delineated where elevation loss exceeded 5 m and local slope gradients were steeper than 30°, following established approaches10,55. These elevation changes also served as input for assessing the dam breach parameters, supporting downstream hydrodynamic modeling of the outburst event. Moreover, to evaluate geomorphic changes caused by the 2013 Ranzerio GLOF, we performed DEM differencing between pre- and post-event high-resolution DEMs within their common overlapping spatial extent41. We calculated sediment volumes by multiplying pixel area by elevation change values and summing over deposition and erosion zones separately. Due to the limited spatial coverage of DEM data, these volume estimates represent only a partial sediment budget of the GLOF pathway and do not capture all downstream effects.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: text

The hydrodynamic simulation of the 2013 Ranzerio lake outburst was performed using HEC-RAS, a widely used two-dimensional hydraulic modeling software developed by the U.S. Army Corps of Engineers. The 2D flow module in HEC-RAS solves the shallow water equations, which are commonly applied for simulating unsteady surface water flows17–19. Key model inputs include digital elevation data, lake volume before the outburst, dam breach parameters, Manning's roughness coefficients, and upstream/downstream boundary conditions.

To ensure accurate representation of pre-flood topography, we employed 5 m resolution TanDEM-X data acquired on 22 April 2013, reflecting terrain conditions prior to the outburst event. The pre-event lake area and volume were derived from high-resolution RapidEye imagery and previously published field observations21,22. Before the outburst, the lake covered approximately 0.58 km² with an estimated volume of  $\sim 11.7 \times 10^6$  m³ by Peng et al. 22. To estimate dam breach parameters, we applied Froehlich's empirical equations 56, which are widely used in outburst flood modeling due to their relatively low uncertainty. The equation provides estimates of dam failure time ( $T_f$  in hours) and peak discharge ( $Q_p$  in  $m^3/s$ ):

$$\begin{cases}
T_f = 0.00254(V_w)^{0.53}(h_b)^{-0.9} \\
Q_p = 0.607(V_w)^{0.295}(h_w)^{1.24}
\end{cases}$$
(1)

where  $h_b$  is the dam breach depth (in m),  $V_w$  is the lake volume above  $h_b$  (in m³),  $h_w$  is the depth of water above the breach dam (in m).

The released flood volume was calculated by comparing the lake volume before and after the outburst event. Post-outburst lake depths were obtained from bathymetric measurements collected by an uncrewed automated sampling and monitoring vessel8. Lake volume after the GLOF was calculated by summing the product of lake depth and pixel area across the lake extent, as expressed in Eq. (2):

$$V = D_i \times R_i^2 \tag{2}$$

where  $D_i$  represents the depth for each individual pixel,  $R_i$  represents the corresponded pixel size of 5 m.

Methods
GLOF simulation using HEC-RAS model


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: table
Table: Table 2 | Summary of multi-source data used in the study

| Data             | RapidEye                                                                                | TanDEM-X                         | Sentinel-1       | Precipitation                                         | Temperature |
|------------------|------------------------------------------------------------------------------------------------------------|----------------------------------|------------------|-------------------------------------------------------|-------------|
| Used bands       | Red/Green/Blue/Near infrared                                                                               | X                                | C                | -                                                     | -           |
| Pixel spacing    | 5 m                                                                                | 5 m                              | 2.3 m × 14.0 m   | 0.25°                                                 | 0.25°       |
| Numbers          | 9                                                                                | 2                                | 115              | -                                                     | -           |
| Acquisition date | 2010/10/30;2011/10/24; 2012/09/05;2013/09/12; 2016/12/ 13;2017/08/24; 2019/09/26;2020/08/25; 2021/10/29 | 2013/04/22; 2013/09/16           | 2017–2021        | 2004–2013                                             |             |
| Purpose          | Glacier velocity before the lake outburst; Area changes before and after the lake outburst                 | Elevation changes; GLOF modeling | Glacier velocity | Meteorological factors analysis for the lake outburst |             |

Data RapidEye TanDEM-X Sentinel-1 Precipitation Temperature


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: text

Fig. 12 | Lake depth of Ranzerio lake after the outburst event (created using ArcGIS 10.4 and Origin 2021 by the authors). a The distribution of lake depth. b The lake depth along the profile.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: figure
Figure

Image /page/12/Figure/3 description: The image consists of two parts, labeled (a) and (b), illustrating the bathymetry of a lake.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: text

Part (a) is a bathymetric map of the lake. The map uses a color scale to represent lake depth, ranging from blue for 0 meters to red for 40 meters. Blue contour lines are drawn at 5-meter intervals. A dashed black line labeled "Profile" runs longitudinally through the lake. The map includes coordinates 30°28'30" and 93°32", a north arrow, and a scale bar indicating 0.2 km.

Part (b) is a line graph showing the depth profile along the dashed line from part (a). The x-axis represents "Distance (km)" from approximately 1.2 to 0, and the y-axis represents "Depth (m)" from 0 to 40, with depth increasing downwards. The blue line shows that the lake depth starts at 0 m, increases sharply, fluctuates in the deepest section between approximately 28 m and 35 m, and then gradually becomes shallower, reaching a depth of about 5 m at a distance of 1.2 km.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: figure
Figure: Figure 12 shows the spatial distribution of lake depth after the outburst and depth variations along a selected profile. The maximum lake depth reached approximately 36 m, with depths exceeding 20 m mainly occurring between 0.05 km and 0.15 km along the profile. Using this approach, the post-outburst lake volume was estimated at $\sim\!3.8\times10^6$ m³. By subtracting this from the pre-outburst volume, the total released flood volume was calculated to be approximately 7.9 $\times$ 10 $^6$ m³. We did not explicitly include the additional water volume potentially contributed by mass movements in the simulation because reliable knowledge of collapse dynamics is limited. Moreover, it is difficult to assess how well the lake model can represent the complex interaction between the collapse and the lake $^{77,58}$ . As a result, our estimates of flood volume and peak discharge should be regarded as conservative values.

Figure 12 shows the spatial distribution of lake depth after the outburst and depth variations along a selected profile. The maximum lake depth reached approximately 36 m, with depths exceeding 20 m mainly occurring between 0.05 km and 0.15 km along the profile. Using this approach, the post-outburst lake volume was estimated at  $\sim\!3.8\times10^6$  m³. By subtracting this from the pre-outburst volume, the total released flood volume was calculated to be approximately 7.9  $\times$  10  $^6$  m³. We did not explicitly include the additional water volume potentially contributed by mass movements in the simulation because reliable knowledge of collapse dynamics is limited. Moreover, it is difficult to assess how well the lake model can represent the complex interaction between the collapse and the lake  $^{77,58}$ . As a result, our estimates of flood volume and peak discharge should be regarded as conservative values.


Document: Triggering factors and flooding processes of glacial lake outburst flood at Ranzerio lake
Section: Methods > GLOF simulation using HEC-RAS model
Type: text

In the GLOF simulations, Manning's roughness coefficients were assigned according to land cover and vegetation types, with typical values ranging from 0.025 to 0.033 and an average value of 0.035,17. Accordingly, a roughness coefficient of 0.03 was applied to the unvegetated downstream channel. The model employed the full momentum equations to simulate two-dimensional, unsteady flow, using a time step of 1 s and a total simulation duration of 24 h. Upstream boundary conditions were derived from the estimated dam breach hydrographs, while downstream boundary conditions were specified as a normal water depth gradient of 0.01 m/m17,19. Thus, the 2013 Ranzerio lake outburst GLOF was reconstructed using observed breach parameters and released lake volume to ensure realistic simulation results. Additionally, uncertainties in the simulation parameters, lake bathymetry, model parameters, and flow transitions inevitably propagate into flood outputs5. Given the challenges in directly constraining

these parameters, we assessed the uncertainty in the hydraulic reconstruction by quantifying the spatial variability of modeled peak discharge and flow depth. Specifically, we calculated the standard deviations of these variables across neighboring grid cells surrounding downstream villages59. This approach yields a representative range of discharge and depth, reflecting the robustness and sensitivity of the hydraulic reconstruction. Furthermore, the simulated inundation extent was compared against flood mapping derived from RapidEye imagery to evaluate model uncertainty.


Document: veh-et-al-hazard-from-himalayan-glacier-lake-outburst-floods
Type: text

Sustained glacier melt in the Himalayas has gradually spawned more than 5,000 glacier lakes that are dammed by potentially unstable moraines. When such dams break, glacier lake outburst floods (GLOFs) can cause catastrophic societal and geomorphic impacts. We present a robust probabilistic estimate of average GLOFs return periods in the Himalayan region, drawing on 5.4 billion simulations. We find that the 100-y outburst flood has an average volume of  $33.5^{+3.7}/_{-3.7} \times 10^6 \text{ m}^3$  (posterior mean and 95% highest density interval [HDI]) with a peak discharge of  $15,600^{+\bar{2},000}/_{-1,800}~m^{\bar{3}}\cdot s^{-1}.$  Our estimated GLOF hazard is tied to the rate of historic lake outbursts and the number of present lakes, which both are highest in the Eastern Himalayas. There, the estimated 100-y GLOF discharge (~14,500 m3·s-1) is more than 3 times that of the adjacent Nyainqentanglha Mountains, and at least an order of magnitude higher than in the Hindu Kush, Karakoram, and Western Himalayas. The GLOF hazard may increase in these regions that currently have large glaciers, but few lakes, if future projected ice loss generates more unstable moraine-dammed lakes than we recognize today. Flood peaks from GLOFs mostly attenuate within Himalayan headwaters, but can rival monsoon-fed discharges in major rivers hundreds to thousands of kilometers downstream. Projections of future hazard from meteorological floods need to account for the extreme runoffs during lake outbursts, given the increasing trends in population, infrastructure, and hydropower projects in Himalayan headwaters.

atmospheric warming  $\mid$  meltwater lakes  $\mid$  GLOF  $\mid$  extreme-value statistics  $\mid$  Bayesian modeling


Document: veh-et-al-hazard-from-himalayan-glacier-lake-outburst-floods
Type: text

may increase in these regions that currently have large glaciers , but few lakes , if future projected ice loss generates more unstable moraine - dammed lakes than we recognize today . Flood peaks from GLOFs mostly attenuate within Himalayan headwaters , but can rival monsoon - fed discharges in major rivers hundreds to thousands of kilometers downstream . Projections of future hazard from meteorological floods need to account for the extreme runoffs during lake outbursts , given the increasing trends in population , infrastructure , and hydropower projects in Himalayan headwaters . atmospheric warming $ \ mid $ meltwater lakes $ \ mid $ GLOF $ \ mid $ extreme - value statistics $ \ mid $ Bayesian modeling

onsoonal floods are among the most destructive natural nonsonial moots are among the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater Himalayan region and the adjacent hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater hazards in the greater haz mountain ranges of the Hindu Kush, Karakoram, Nyainqentanglha, and Hengduan Shan (Fig. 1). Regional projections for the lower Indus, Ganges, and Brahmaputra rivers hold that flood frequencies will rise noticeably in the 21st century (1, 2), putting the livelihoods of 220 million people at risk (3). In Himalayan headwaters, such prognoses have disregarded episodic, but potentially destructive, floods from the sudden emptying of morainedammed lakes. Such glacier lake outburst floods (GLOFs) occur largely independently of hydrometeorological floods, but can surpass their peak discharges by orders of magnitude in the upper river reaches (4-6). Glacier lakes dammed by abandoned moraines are susceptible to outburst, triggered by ice or debris falls, strong earthquake shaking, internal piping, or overtopping waves that exceed the shear resistance of the dam (7–9). These triggers mostly happen unrecorded in remote terrain, eroding the impounding barriers within minutes to hours, and releasing sediment-laden floods that may travel >100 km downstream (7). With little to no warning, communities and infrastructure downstream have often been caught unprepared, suffering loss of human lives and livestock, and damage to roads, buildings, and hydropower facilities (10-12). An objective and reproducible hazard assessment of such dam-break floods is key to human safety and sustainable development, and is repeatedly emphasized in research and media coverage of atmospheric warming, dwindling glaciers, and growing meltwater lakes (3, 13, 14).


Document: veh-et-al-hazard-from-himalayan-glacier-lake-outburst-floods
Type: text

unrecorded in remote terrain , eroding the impounding barriers within minutes to hours , and releasing sediment - laden floods that may travel > 100 km downstream ( 7 ) . With little to no warning , communities and infrastructure downstream have often been caught unprepared , suffering loss of human lives and livestock , and damage to roads , buildings , and hydropower facilities ( 10 - 12 ) . An objective and reproducible hazard assessment of such dam - break floods is key to human safety and sustainable development , and is repeatedly emphasized in research and media coverage of atmospheric warming , dwindling glaciers , and growing meltwater lakes ( 3 , 13 , 14 ) .

GLOFs have gained growing attention in the Himalayas (15, 16), where these disasters have had the highest death toll worldwide

(17). While the distribution and dynamics of moraine-dammed lakes have been mapped extensively in recent years (12, 18–21), objectively appraising the current Himalayan GLOF hazard has remained challenging. The high-alpine conditions limit detailed fieldwork, leading researchers to extract proxies of hazard from increasingly detailed digital topographic data and satellite imagery. These data allow for readily measuring or estimating the geometry of ice and moraine dams, the possibility of avalanches or landslides entering a lake, or the water volumes released by outbursts (9, 18, 20). Ranking these diagnostics in GLOF hazard appraisals has mostly relied on expert judgment (18, 22), because triggers and conditioning factors are largely unknown for most historic GLOFs (23).

Guided by studies on earthquakes, landslides, wildfires, and floods, we use the magnitude and frequency of GLOFs in a given area and period as an objective metric of hazard. GLOFs have occurred at an average rate of  $\sim 1.3 \text{ y}^{-1}$  in the Himalayas in the past 3 decades (23), although of differing size, which is conventionally described by the released flood volume  $V_0$  or the associated peak discharge  $Q_p$ . These parameters are difficult to measure during dam failure but can be estimated eventually from the surface areas of glacier lakes. We thus scaled the manually mapped areas of all 5,184 Himalayan moraine-dammed lakes (>0.01 km2) to volumes using a Bayesian robust regression of maximum lake depth versus area from 24 bathymetrically surveyed lakes (Materials and Methods and SI Appendix, Fig. S2 and Table S1). Our approach assumes that all lakes are equally susceptible to outburst and that any incision depth is possible, which is consistent with data from Himalayan dam breaks (SI Appendix, Fig. S3). We used a Bayesian variant of a physical dam-break model (24, 25) to predict peak discharge  $Q_p$  from the product of  $V_0$  and the breach erosion rate k (Materials and Methods and SI Appendix, Figs. S4 and


Document: Significance
Section: Significance
Type: text

Glacier lake outburst floods (GLOFs) have become emblematic of a changing mountain cryosphere. The Himalayas suffered the highest losses from these sudden pulses of meltwater but lack a quantitative appraisal of GLOF hazard. We express the hazard from Himalayan glacier lakes by the peak discharge for a given return period. The 100-y GLOF has a mean discharge of ~15,600 m³·s⁻¹, comparable to monsoonal river discharges hundreds of kilometers downstream. The Eastern Himalayas are a hotspot of GLOF hazard that is 3 times higher than in any other Himalayan region. The size of growing glacier lakes and the frequency of lake outbursts determine GLOF hazard, which needs to be acknowledged better in flood hazard studies.

Author contributions: G.V. and O.K. designed research; G.V. and O.K. performed research; G.V. and O.K. analyzed data; and G.V., O.K., and A.W. wrote the paper.

The authors declare no competing interest.

This article is a PNAS Direct Submission.

Published under the PNAS license.

Data deposition: All input data are available at Zenodo (http://doi.org/10.5281/zenodo. 3523213), and model codes are available at GitHub (https://github.com/geveh/GLOFhazard).

1To whom correspondence may be addressed. Email: georg.veh@uni-potsdam.de.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/doi:10.1073/pnas.1914898117/-/DCSupplemental.

First published December 30, 2019.

Downloaded from https://www.pnas.org by IIT MUMBAI on August 8, 2025 from IP address 103.21.125.81


Document: Significance
Section: Significance
Type: figure
Figure

Image /page/1/Figure/1 description: A figure with three panels (A, B, C) illustrating the distribution and characteristics of moraine-dammed glacial lakes in the Himalayas. Panel A is the main map showing the study region, which includes the Hindu Kush, Karakoram, Western Himalaya, Central Himalaya, Eastern Himalaya, Nyainqen-tanglha, and Hengduan Shan mountain ranges. The map displays major rivers like the Indus, Ganges, Brahmaputra, and Yangtze, and cities such as Kabul, Islamabad, New Delhi, and Kathmandu. The distribution of lakes is shown using circles, where the size of the circle indicates the total lake area (with a key showing sizes for <3, 6, 12, 24, and 36 km²) and the color indicates the lake quantity (from 1 in light gray to 330 in dark blue). Yellow triangles mark the locations of Glacial Lake Outburst Floods (GLOFs) that occurred between 1935 and 2017. Panel B is an inset map showing the location of the study area within Asia, covering parts of India and China. Panel C is a histogram showing the frequency distribution of lake sizes. The x-axis represents lake size in square meters on a logarithmic scale (10^4, 10^5, 10^6), and the y-axis represents frequency, ranging from 0 to 500. The histogram shows that smaller lakes are most frequent, with the highest frequency (over 500) occurring for lakes around 10^4 to 2x10^4 m², and the frequency decreases as lake size increases.


Document: Significance
Section: Significance
Type: text

Fig. 1. Moraine-dammed glacier lakes in the Himalayas. (A) Distribution of moraine-dammed lakes in our study region in 1° × 1° bins. Bubbles are scaled to the total lake area, and color-coded to abundance. Reported GLOFs (yellow triangles) have occurred most frequently in the past 8 decades in regions where glacier lakes are largest (23). (B) Location of the Himalayas between the Indian subcontinent and the Tibetan Plateau. (C) Histogram of glacier lake areas.

S5). In summary, we obtained  $4.6 \times 10^8$  and  $4.9 \times 10^9$  scenarios of  $V_0$  and  $Q_p$ , respectively, for all moraine-dammed lakes in the Himalayas. These numbers ensure that we have sufficiently explored the physically plausible space for fitting an extreme-value distribution to these key flood diagnostics. We further stacked our simulations, accounting for contemporary mean annual GLOF rates between 0.03 and 0.71 y<sup>-1</sup> in 7 subregions of the Himalayas, and estimated GLOF return periods in terms of the 100-y flood volume  $V_{100}$  and discharge  $Q_{p100}$  (Materials and Methods) (26, 27).