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Punatsangchu basin hosts the two largest hydroelectric power projects, PHP-I (1200 MW) and PHP-II (1020 MW), both of which are at the advanced stage of construction (MOEA, 2021). With a cost estimate of 1.74 (Nu. 133.20) billion USD for PHP-I and 0.95 (Nu. 72.9) billion USD for PHP-II; these two projects are record-high investment projects in Bhutan. In the latest inventory, Punatsangchu headwaters have a total of 180 glacial lakes of larger than 0.05 km2 (Rinzin et al., 2021). The glacial lakes present an imminent threat of outburst flood to these two hydroelectric projects. Potential GLOFs can impact these hydroelectric power projects and lead to significant economic loss and potentially endanger human lives. While the potential impact of GLOFs on the hydroelectric project has been undertaken at a large scale (Schwanghart et al., 2016), this study presents a pilot-based detailed assessment of the dangerous glacial lakes and their impacts on hydropower projects in Bhutan. Except for GLOFs from the Bechung Tsho, all potential GLOFs intercept the hydroelectric projects and may present a significant risk in the future, e.g., at PHP-II, the peak ranges from 870 m3/s (Raphstreng small magnitude) to 19000 m3/s (Thorthormi large magnitude). These hydroelectric power projects are inevitably exposed to GLOFs from the lakes in the Lunana glacier complex. However, their risk will depend on the design standard of the dams. The feasibility assessment done before the commencement of these projects by the Japan International Cooperation Agency (2001) has considered peak flow up to 2176 m3/s. So, a high flood magnitude (>20,000 m3/s) from Thorthormi Tsho is an order of magnitude higher than the design flood of the hydropower projects. A flood of such magnitude may therefore cause severe damage to the reservoir and dam, causing overtopping, excessive sedimentation, outages, equipment damage, and cascading impacts on the low-lying settlements. The high concentration of sediment in the Punatsangchu river from the 1994 GLOF event of Lugge Tsho is said to have persisted up to a


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peak flow up to 2176 m < sup > 3 < / sup > / s . So , a high flood magnitude ( > 20 , 000 m < sup > 3 < / sup > / s ) from Thorthormi Tsho is an order of magnitude higher than the design flood of the hydropower projects . A flood of such magnitude may therefore cause severe damage to the reservoir and dam , causing overtopping , excessive sedimentation , outages , equipment damage , and cascading impacts on the low - lying settlements . The high concentration of sediment in the Punatsangchu river from the 1994 GLOF event of Lugge Tsho is said to have persisted up to a

month after the event (Watanbe and Daniel, 1996). The massive landslide-induced flood cascade in 2003 from the Tsatichhu river, a north-easterly flowing tributary of the Kurichu river in eastern Bhutan, resulted in an estimated loss of 1.1 million USD due to the disruption of the 60 MW Kurichu hydroelectric power plant (Dunning et al., 2006). The disruption of PHP-I and PHP-II due to GLOFs from the Lunana glacier complex could result in greater financial implications since their installed capacity is about 2-order magnitudes greater than the Kurichu hydroelectric power plant. Several past GLOF events in the Himalaya have caused implacable damage to the hydroelectric power downstream, including GLOFs that occurred in the neighbouring regions. For example, the 1985 GLOF of Dig Tsho in eastern Nepal (Vuichard and Zimmermann, 1987) and the 1981 GLOF of Cirenma Co (Wang et al., 2015), and the 2016 Gongbatongsha GLOF (Sattar et al., 2022) in the Poiqu River basin of the central Himalaya. All these experiences from the neighbouring Himalaya and Bhutan suggest that GLOFs from the lakes in the Lunana glacier complex may also cause potential damage to PHP-I and PHP-II.


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The input dam breach parameters are the essential initial condition determining the magnitude of flood hydraulics and the translated hazard and risk maps (Sattar et al., 2021a; Wahl, 2004). Previous studies have found outflow hydraulics like peak discharge are highly sensitive to breach formation time ( $T_f$ ) (Basheer et al., 2017; Sattar et al., 2021a). While there are no models to predict the uncertainty of GLOF breach parameters, previous studies (Sattar et al., 2021a; Somos-Valenzuela et al., 2015) have used embankment dam-based equations (Wahl, 2004) to predict uncertainty ranges of moraine dam breach parameters. When Wahl (2004) is used here, the value of upper bound uncertainty dam breach width for the Thorthormi Tsho is more than double (704.5 m) the actual calculated value (293.7 m), while the lower bound decreases to less than half (116.7 m). There is an extensive range of uncertainty in other breach parameters like  $T_f$  (see supplementary Table 2 for detail). Also, due to the lack of a clear historical record, scenario definition for GLOFs cannot typically depend on the site-specific frequency-magnitude relationship, commonly used in other natural hazards scenario definitions (Frey et al., 2018; GAPHAZ, 2017). As a result, the scenario definition is another primary source of uncertainty in GLOF modelling. Here we accounted for these uncertainties by considering multiple potential GLOF scenarios with varying magnitudes (3 from each lake) following the established trend in the existing literature (Frey et al., 2018; Sattar et al., 2021a; Sattar et al., 2021b). This allowed us to define 12 unique scenarios (3 for each lake), all flowing along the same trajectory. However, for disaster risk reduction worst-case GLOFs scenarios can be considered, although it could be argued that an inability to mitigate against the highest magnitude events should not remove the focus from smaller events that could, and should have mitigation schemes.

The overtopping breach failure mode in the HEC-RAS dam breach model is a gradually progressive process of dam erosion due to an overflow of water, which contrasts with overtopping resulting from a large displacement wave induced by a rapid mass movement into the lake. These differences could have underestimated the peak discharge and flood arrival time in the current study (Allen et al. 2022). Here we do not model the process chain or the trigger processes, however, we assume breach scenarios of varied dimensions to assess the downstream impact. Moreover, GLOF is a highly complex process, involving several cascading events, usually initiated by mass movement and wave overtopping, followed by debris flow, hyper-concentrated flow, and secondary debris flow (GAPHAZ, 2017; Schneider et al., 2014; Worni et al., 2014). However, these complex modelling approaches are usually applied in the context where run-out distance is relatively short (Frey et al., 2018), which is not the case in Bhutan, especially in the Punatsangchu basin. Here, most simulated floods (8/12) can reach up to 150


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assess the downstream impact . Moreover , GLOF is a highly complex process , involving several cascading events , usually initiated by mass movement and wave overtopping , followed by debris flow , hyper - concentrated flow , and secondary debris flow ( GAPHAZ , 2017 ; Schneider et al . , 2014 ; Worni et al . , 2014 ) . However , these complex modelling approaches are usually applied in the context where run - out distance is relatively short ( Frey et al . , 2018 ) , which is not the case in Bhutan , especially in the Punatsangchu basin . Here , most simulated floods ( 8 / 12 ) can reach up to 150

km downstream. The complex process chain modelling covering such a long flood reach distance is theoretically possible, it is highly challenging to model multiple scenarios using existing codes like r.avaflow (Mergili et al., 2017) due to high computation costs and numerical instabilities (Frey et al., 2018; Schneider et al., 2014). Therefore, since we modelled multiple scenarios over a very long run-out distance coupled with robust downstream risk assessment, the HEC-RAS 2D model is a reasonable alternative, especially for the first-order evaluation in this study. Nonetheless, through Google Earth high-resolution imagery, we observed that the Phochu river channel first starts with a relatively broad plain, especially in the Thanza area of Lunana, followed by a long stretch of deep valleys and gorges (20-30 km), and flood plains become wide as the river reaches the downstream site where settlements are most concentrated. This channel characteristic relates well to a typical feature that will allow erosion and entrainment of the enormous amount of debris from the upstream area that would multiply flood magnitude and thus damage caused to the lives and properties, as occurred during the 2016 GLOF event from Gongbatongsha Co in the central Himalaya (Sattar et al., 2022). Future studies addressing the critical challenges of GLOF modelling like long-runout distance, complex process chain, and high computational cost issues should be the priority.


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valleys and gorges ( 20 - 30 km ) , and flood plains become wide as the river reaches the downstream site where settlements are most concentrated . This channel characteristic relates well to a typical feature that will allow erosion and entrainment of the enormous amount of debris from the upstream area that would multiply flood magnitude and thus damage caused to the lives and properties , as occurred during the 2016 GLOF event from Gongbatongsha Co in the central Himalaya ( Sattar et al . , 2022 ) . Future studies addressing the critical challenges of GLOF modelling like long - runout distance , complex process chain , and high computational cost issues should be the priority .

Because of their high discharge and entrainment capacity, GLOFs are typically known for carrying large boulders and mobilizing large amounts of sediment which can greatly modify channel morphology (Cook et al., 2018; Nativ et al., 2022)\*\*. For example, the 2016 GLOF from Gongbatongsha Co in central Himalaya, with a discharge volume about of  $1.1 \times 10^5$  m3, changed channel morphology up to 40 km downstream and widened channel width up to 12 m at some cross sections (Cook et al., 2018, Chen et al. 2023). Likewise, the 1994 Lugge Tsho GLOF also changed channel morphology for up to 25 km downstream (Maurer et al., 2020), while debris deposits were evident as far as 200 km downstream (Watanbe and Daniel, 1996). Huber et al. (2020) suggest that numerous present-day boulders along the river channels in the Himalaya have likely been transported by historical GLOFs and estimate that GLOFs of discharge  $10^3$ – $10^5$  m3 are capable of transporting boulders of ca. 10 m diameter or more. Here, the majority of the modelled GLOF scenarios (8/12) exceed peak discharges of 103 m3/s indicating their potential to transport sediments of different grades including boulders. This implies that if future GLOF are of the same magnitude as the modelled scenarios, the impact might be far more than what we projected with our clear water flood rheology. Therefore, future studies should focus on assessing the impact of GLOF through a complex debris flow model or those allowing phase changes.


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capable of transporting boulders of ca . 10 m diameter or more . Here , the majority of the modelled GLOF scenarios ( 8 / 12 ) exceed peak discharges of 10  3  m  3  / s indicating their potential to transport sediments of different grades including boulders . This implies that if future GLOF are of the same magnitude as the modelled scenarios , the impact might be far more than what we projected with our clear water flood rheology . Therefore , future studies should focus on assessing the impact of GLOF through a complex debris flow model or those allowing phase changes .

Population and infrastructures are very dynamic in Bhutan as it is a rapidly developing country. According to ICIMOD's land cover and land use data, the built-up area within our 2D model domain has increased by ~194 % over the period from 2000 to 2020 with an annual rate of  $\sim$ 0.36 km2/yr. The agricultural land has increased from  $\sim$ 16.0 km2 in 2000 to  $\sim$ 19.5 km2 in 2015, but has dropped to  $\sim$ 17.5 km2 in 2020, although the latter might be due to the conversion of farmland into builtup areas (Supplementary Fig. S4). Similarly, according to the Bhutan population and housing census 2017, the population in the Wangdue Phodrang and Punakha, the two districts most exposed to GLOF, have increased from 48,850 to 70,926 (+45 %) between 2005 and 2017 (NSB, 2018). This increasing downstream population and built-up area coupled with an increase in glacial lake area since the 1990s indicates that downstream GLOF risk would have also increased over the period. Most importantly, increasing GLOF risk in the downstream communities in the future means that continuous monitoring of GLOF in Punatsangchu basin is highly recommended.


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This study draws upon multiple data sources, including traditional declassified Corona KH-4 and Hexagon KH-9, Landsat (TM, ETM, and OLI), DEM, LULC, OpenStreetMap, population and housing census data.

Using these data and hydrodynamic modelling, we comprehensively assessed glacial lake outburst susceptibility, downstream exposure, hazard, vulnerability, and risk in the Bhutan Himalaya. The results showed that, although all the lakes in the Lunana glacier complex have one or more unfavourable GLOF susceptibility factors, Thorthormi Tsho and Lugge Tsho are relatively more susceptible to GLOF. A detailed hazard assessment for the potential GLOFs indicated that two hydropower projects and over 16,000 people dwelling along the Phochu and Punatsangchu banks in addition to numerous structures and agricultural land are exposed to these events. Our comprehensive GLOF risk assessment revealed 1 (Lunana) subdistrict block in the very high GLOF risk zone, 9 in the high-risk zone (mainly in Punakha and Wangdue Phodrang areas), 3 in medium, and 1 in a low-risk zone. The other 3 had zero GLOF risk under current conditions.

We recommend continuous monitoring of the glacial lakes in the Lunana glacier complex (through field investigation and high-resolution satellite imagery) with a particular focus on Thorthormi Tsho and Lugge Tsho. Second, as for the downstream GLOF disaster management, we recommend that Lunana should be given the highest priority, followed by subdistrict blocks concentrated in the Wangdue Phodrang and Punakha districts like Guma and Thedtsho. The study highlights the importance of multi-source data in improving the knowledge of downstream GLOF risk and serves as a base for improving the GLOF risk reduction strategies in the region.


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The Himalayas are home to many high-risk glacial lakes. Effective prevention of glacial lake outburst floods (GLOFs) in this region has recently become an urgent priority. As a major element of an integrated risk management strategy, the GLOF early warning system is a viable and promising tool for mitigating climate change-related risks. It prevents loss of life and reduces the economic and societal impacts of disasters. Within the framework of the Second Tibetan Plateau Scientific Expedition and Research program, we developed and implemented a monitoring and early warning system (EWS) for Cirenmaco, a transboundary high-risk glacial lake located in the central Himalayas. The EWS consists of monitoring lake-level change, end-moraine displacement, ice collapse, and downstream runoff. The monitoring data can be transmitted via the Beidou and Inmarsat satellites and a mobile network to the data center. The in-situ and real-time monitoring guarantee captures the precursors of ice collapse and glacial lake outburst and raises alarms in advance for downstream communities. In terms of data transmission, monitoring elements, and warning thresholds, the Cirenmaco EWS scheme is one of the most advanced among all similar GLOF early warning systems. Implementing an early warning system is the most practical strategy for mitigating potential threats to Himalayan high-risk glacial lakes. The EWS system is less expensive than lake dam immobilization and artificial drainage projects, and it provides more valuable environmental monitoring data in high mountain areas. The Cirenmaco EWS serves an effective demonstration for the construction of similar projects to prevent and mitigate GLOFs in the Himalayas.


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Due to climate warming and ongoing glacier recession, glacial lakes in the Tibetan Plateau and its surroundings (TPS) are in a state of rapid expansion [1–3], and numerous potential glacial lakes buried within the glacier beds are projected to be exposed in the future [4-7]. Over the past few decades, the number and area of glacial lakes on the plateau have increased by  $\sim$ 10.7% and  $\sim$ 15.2%, respectively [2]. The Himalayas have the highest concentration of contemporary glacial lakes among all subregions of the TPS [8]. Because of its longitudinal length, over 2000 km from east to west, and an altitude difference of up to 5000 m, great spatial heterogeneity is manifested across many aspects, such as climate composition, geographic resources, and ecological environment [9,10], prompting it to become one of the main study areas in cryospheric science, geology, and social humanities. To date, research on glacial

https://doi.org/10.1016/j.ijdrr.2022.102914

<sup>b College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, 730000, China

\* Corresponding author.

Corresponding author. Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, 100101, China. E-mail addresses: weicaiwang@itpcas.ac.cn (W. Wang), zhangtg16@lzu.edu.cn (T. Zhang).

lakes has focused on the distribution characteristics of contemporary or potential glacial lakes, and their accompanying hazards and/or risks [4,11–15], inventory of regional glacial lake outburst floods (GLOFs) [16–20], reconstruction of previous GLOFs and projection of GLOFs from high outburst potential lakes [21–26]. However, research on prevention and mitigation measures for GLOFs from high-hazard/risk glacial lakes remains lacking [27–29].

Previous studies on identifying potentially dangerous glacial lakes selected the central Himalayas as subjects, including a large number of high-hazard/risk glacial lakes, over the other subregions of the TPS [12,15,30,31]. Zheng et al. [7] conducted a risk assessment for glacial lakes in the TPS, and another study focused on future changes in glacial lakes, as well as the accompanying enhanced hazards and risks. The results revealed that approximately 3200 potential glacial lakes are buried in the Himalayan glacier beds, accounting for 23.4% of the total number across the TPS. Approximately 32.1% of the Himalayan potential glacial lakes will be exposed by 2050 and 54.4% by 2100, at RCP8.5 scenario. The results of the risk assessment indicated that future GLOF susceptibility in this region will be at least 10 times higher than the current level. There have been several studies on glacial lake hazard/risk assessment for the entire Himalayan area, and some typical regional areas [32–35]. It is noteworthy that, although the evaluation schemes are varied among different studies, assessments of high-hazard/risk glacial lakes have comparatively high consistency and consensus [15]. Therefore, an in-depth understanding of glacial lakes with high outburst potential in this region provides a reliable basis for further studies.


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at RCP8 . 5 scenario . The results of the risk assessment indicated that future GLOF susceptibility in this region will be at least 10 times higher than the current level . There have been several studies on glacial lake hazard / risk assessment for the entire Himalayan area , and some typical regional areas [ 32 – 35 ] . It is noteworthy that , although the evaluation schemes are varied among different studies , assessments of high - hazard / risk glacial lakes have comparatively high consistency and consensus [ 15 ] . Therefore , an in - depth understanding of glacial lakes with high outburst potential in this region provides a reliable basis for further studies .

TPS regions have seen more than 100 GLOFs originating from glacial lakes (Fig. 1a) [18–20,36–38]. The Himalayas are a global hotspot of GLOFs in the TPS. Since the 1980s, the GLOF frequency has been  $\sim$ 1.3 times per year [39], and there remains a distinctively steady trend of outbursts compared to other glaciered areas of the world where the GLOF frequency is decreasing or remain constant [40]. Recent studies have suggested that the frequency of future GLOFs in some areas will not increase. One such area is the Peruvian Andes. These tropical glaciers have already retreated quite close to steep headwalls [41,42], and numerous posterior bedrock-dammed lakes have become exposed. A decrease in GLOF susceptibility has been observed, the potential for future glacial lake development is not high, as lakes will become progressively distant from their mother glacier, which is the main source of triggers. Additionally, several remedial studies have been conducted to prevent GLOFs.

Unexpected Himalayan glacial lake outburst floods have caused thousands of deaths and enormous socio-economic losses [16]. For


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Figure

Image /page/1/Figure/6 description: A figure composed of four panels, labeled a, b, c, and d, illustrating the location and characteristics of the Cirenmaco glacial lake.


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Panel a is a map of a large mountainous region, showing the distribution of glacial lakes (blue), moraine-dammed GLOFs (yellow dots), and ice-dammed GLOFs (orange dots). Red stars indicate early warning systems. The location of Cirenmaco is marked. The map covers latitudes from 25°N to 45°N and longitudes from 70°E to 100°E.

Panel b is a detailed topographic map of a specific area, showing the Poiqu River and its tributary, Zhangzangbo. Glaciers are highlighted in light blue with dashed outlines. The map's coordinates range from 28°2'N to 28°6'N and 86°0'E to 86°5'E.

Panel c is a satellite image showing the Cirenmaco glacial lake, which is a distinct turquoise color, set within a rocky, mountainous landscape. The coordinates for this view are approximately 28°3'30"N to 28°4'30"N and 86°3'E to 86°5'E.

Panel d consists of two bar charts showing changes in area over time from 1990 to 2020. The top chart, labeled 'Glacier', shows a general decrease in area from approximately 1.8 km² in 1990 to about 1.5 km² in 2020. The bottom chart, labeled 'Glacial lake', shows a general increase in area from about 0.12 km² in 1990 to a peak of over 0.3 km² in 2010, settling at around 0.28 km² in 2020.

Fig. 1. Location of Cirenmaco in the TPS. (a) Since the 1980s, there have been many GLOFs originating from moraine and ice-dammed lakes in the TPS. Meanwhile, several EWS have been established in this region. (b, c) Cirenmaco is located in the Zhangzangbo Valley, central Himalaya. (d) The area changes of the lake and its parent glacier from 1988 to 2020.

instance, a catastrophic GLOF originating from Luggye Tsho, Eastern Himalaya, on October 7, 1994, was triggered by the melting of buried ice beneath the moraine dam, and the resulting flood killed 21 people and destroyed local infrastructure [43,44]. The largest GLOF event recorded in the region occurred on June 16, 2013. Chorabari, a moraine-dammed lake in the central Himalayas, suddenly drained, and the outburst flood, accompanied by rainfall floods, washed away settlements downstream, causing more than 6000 deaths [45,46]. Therefore, determining how to prevent and mitigate these outburst flood disasters is urgent. It is necessary to assess potential GLOF hazards and risks and simulate possible outburst floods. Moreover, it is crucial to meaningfully implement a variety of remedial works, such as lake dam immobilization, artificial drainage, and construction of monitoring and early warning systems (EWS).


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GLOF event recorded in the region occurred on June 16 , 2013 . Chorabari , a moraine - dammed lake in the central Himalayas , suddenly drained , and the outburst flood , accompanied by rainfall floods , washed away settlements downstream , causing more than 6000 deaths [ 45 , 46 ] . Therefore , determining how to prevent and mitigate these outburst flood disasters is urgent . It is necessary to assess potential GLOF hazards and risks and simulate possible outburst floods . Moreover , it is crucial to meaningfully implement a variety of remedial works , such as lake dam immobilization , artificial drainage , and construction of monitoring and early warning systems ( EWS ) .

Such engineering measures have been applied sporadically worldwide, even though numerous high-risk glacial lakes have been identified. The danger, high-altitude, and inaccessibility of high mountain areas make engineering measures several times more expensive than in densely populated plains. In the Himalayas, there are currently fewer than 10 engineering measures in place at present. For instance, Jialongco (Table 1), a moraine-dammed lake in the Himalayas, drained in 2002, resulting in severe downstream damage. Considering the serious threat posed, the local government artificially strengthened the moraine dam in 2020. In contrast, in the Peruvian Andes, at least 38 glacial lakes have been used for various remedial works, including 38 lakes that were artificially drained by open-cut excavation, tunnels, or siphon measures, 15 lake dams that were strengthened; and one lake that established an EWS [27,47]. These measures were taken mainly because many villages, towns, and cities are situated downstream of the high-risk glacial lakes in the surrounding region. An EWS generally consists of monitoring the glacial lake, its parent glaciers, and/or the downstream river, formulating a disaster mitigation plan, and training for evacuation. The latter two are non-engineering measures. However, they should be conducted based on an in-depth understanding of the original GLOF hazards. The difficulty lies in fostering strong support from local governments and residents [21,28].

It is vital for the implementation of remedial work that high-risk glacial lakes, adequate economic and engineering reserves, and long-term development plans are prepared in advance. Cirenmaco is located in the Poiqu River Basin, central Himalaya, close to the China–Nepal border (Fig. 1a and b). Three GLOFs from this lake have occurred in 1964, 1981, and 1983, respectively. In the past few decades, the high outburst susceptibility of Cirenmaco and the accompanied transboundary threat of its GLOF have plagued residents in both regions [7,12,48,49]. An EWS was installed near Zhangmu Port in 2001 unilaterally by the Nepalese government, to protect downstream hydropower projects [50]. However, the absence of a glacial lake monitoring system caused the EWS to lose a considerable part of its effective functions, as the upper Poiqu River Basin is home to many high-risk glacial lakes located in China. Therefore, supported by the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program, we have establish an EWS for Cirenmaco to monitor dynamic changes in the lake and its parent glacier, lake and downstream river water-level, meteorology, etc., to provide a timely warning signal to the downstream area.


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Port in 2001 unilaterally by the Nepalese government , to protect downstream hydropower projects [ 50 ] . However , the absence of a glacial lake monitoring system caused the EWS to lose a considerable part of its effective functions , as the upper Poiqu River Basin is home to many high - risk glacial lakes located in China . Therefore , supported by the Second Tibetan Plateau Scientific Expedition and Research ( STEP ) Program , we have establish an EWS for Cirenmaco to monitor dynamic changes in the lake and its parent glacier , lake and downstream river water - level , meteorology , etc . , to provide a timely warning signal to the downstream area .

The categories of remedial work for glacial lakes with high risk, and corresponding measures. A typical case is given for the specific measure.


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Table: Table 1

| Remedial works                         | Measures                             | Typical cases                  |                                             |                                                                                | Reference     |
|----------------------------------------|--------------------------------------|--------------------------------|---------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------|
|                                        |                                      | Location                       | Name                                        | Explanation                                                                                |               |
| Artificial drainage                    | Open cut                             | Cordillera Blanca, Peru     | Palcacocha                                  | This moraine-dammed lake failed in 1941, and then an open cut was excavated in 1974, lowering the lake to a level of 3 m.                                                                                | [27]          |
|                                        | Tunnel                               | Cordillera Blanca, Peru     | Parón                                       | The tunnel became functional in 1984 and the lake level could be lowered by 52 m.                                                                                | [27]          |
|                                        | Siphon                               | Cordillera Blanca, Peru     | Lake 513                                    | This bedrock-dammed lake failed in 1991 and 2010, but a siphon was already installed in 1989, lowering the lake level of 8 m. Subsequently, a combination of tunnels was used to lower the lake level by 20 m in 1993. | [51]          |
| Lake dam immobilization             | Earth dam                            | Central Himalaya            | Jialongco                                   | This moraine-dammed lake had been drained in 2002 causing severe damage downstream, the lake is still a high risk. Thus, in 2020 the local government immobilized its dam.                                             | This study |
|                                        | Arch dam                             | Alps, Swiss                    | Trift glacier lake                          | The dam, built primarily to generate electricity, was completed by 2007, but undoubtedly reduced the incidence of glacier-related hazards.                                                                                | [52]          |
| Monitoring and Early warning system | Monitoring and/ or warning system | Central Caucasus, Russia | Bashkara Glacier lakes                   | The two sister lakes failed in 1958 and 1959. To protect the infrastructure and settlements downstream, an early warning and monitoring system was installed in 2008.                                                     | [53]          |
|                                        | Disaster mitigation plan          | Cordillera Blanca, Peru     | Lake 513                                    | When information of the GLOF arrived, alarm will be issued to evacuate. At the same time, sirens were installed in all important communities and major transportation routes.                                          | [28]          |
|                                        | Evacuation drills                    | Cordillera Blanca, Peru     | Palcacocha, Tullparaju, Cuchillacocha | Detailed evacuation plans and evacuation briefs were developed by relevant staff to protect the downstream city of Huaraz, and were given extensive publicity.                                                            | [21]          |

Remedial works
Measures
Typical cases
Reference


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Cirenmaco ( $86^{\circ}03'56''E$ ,  $28^{\circ}04'02''N$ ) glacial lake is located at 4612 m above sea level. Since the 1990s, the region in which it is situated (south slope of the central Himalayas) has been designated as a region of intensively developed of glacial lakes [2,8]. Cirenmaco's perennial mean annual precipitation can be estimated at ~1000 mm and the relevant mean annual temperature at approximately 0 °C by interpolating the nearest meteorological stations [24]. The lake, which was drained in 1981, had reached a disastrous and alarming level. Based on a post-disaster investigation conducted by Xu [54], approximately  $19 \times 10^6$  m³ of water was released, with a peak discharge of 15,920 m³/s at the breach and a total flood duration of 1 h. Because of the GLOF, substantial erosion was observed throughout the downstream valley, transporting approximately  $4 \times 10^6$  m³ of solid material. There was a possibility of debris flow within the flood spreading in the Zhangzangbo Valley. The GLOF, which moved over 50 km along the downstream Poi-qu/Sun Koshi River, destroyed two bridges (at the mouth of Zhangzangbo Valley and Zhangmu Port), 6 km of China-Nepal roads and buildings on both sides, and one hydropower facility, resulting in 200 fatalities [48,54].


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s at the breach and a total flood duration of 1 h . Because of the GLOF , substantial erosion was observed throughout the downstream valley , transporting approximately $ 4 \ times 10 ^ 6 $ m³ of solid material . There was a possibility of debris flow within the flood spreading in the Zhangzangbo Valley . The GLOF , which moved over 50 km along the downstream Poi - qu / Sun Koshi River , destroyed two bridges ( at the mouth of Zhangzangbo Valley and Zhangmu Port ) , 6 km of China - Nepal roads and buildings on both sides , and one hydropower facility , resulting in 200 fatalities [ 48 , 54 ] .

Cirenmaco has been identified as a high-hazard/risk glacial lake in recent studies [12,15,55] due to its steep surroundings, buried ice in the moraine dam, and the high exposure of downstream communities and infrastructure. Although the area of Cirenmaco underwent a rapid increase from 0.11 to 0.33 km2 beginning in the 1980s, a stable trend in lake area has been maintained since 2010 (Fig. 1c and d). On the surface, the development potential of this lake has reached its limits. However, the dead ice in the lake bottom may continuously melt to increase the lake volume, and the buried ice melting in the moraine dam may continuously affect dam stability and trigger outburst floods [24]. A bathymetric survey of Cirenmaco was conducted in 2012. The results showed that approximately  $18 \times 10^6$  m3 of water was held by this lake, with a maximum depth of 115 m [24]. Subsequently, Zhang et al. [25] simulated outburst floods at different drainage percentages and assessed the hazards and potential impacts of Cirenmaco GLOFs (Fig. 2a-c). Although their scheme for the outburst flood hydrograph as an input for the HEC-RAS model was proposed using an ideal drainage curve process, it has been demonstrated to be feasible in many other studies also [56,57]. In contrast, predicted GLOF propagation is transported entirely within a narrow valley. Because of DEM accuracy and simulation uncertainties, precisely identifying potentially damaged buildings, roads, etc., in such gullies is difficult. Therefore, prior simulation results for the Cirenmaco GLOF depth, velocity, and arrival time provide suitable reference points. The distance between Cirenmaco and the Zhangmu ports were found to be 23 km. The estimated travel time of the flood indicated that, if Cirenmaco released 100% of its volume, the GLOF would have at least 50 min to reach Zhangmu Port [25]. Moreover, studies of the 1981 GLOF reconstruction revealed that the flood time was more than an hour when it crossed this route [24]. However, we deduced that the actual flood migration time for this period may be


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Figure

Image /page/3/Figure/5 description: A multi-panel figure illustrating the simulation of a Glacial Lake Outburst Flood (GLOF). The figure is divided into four panels labeled a, b, c, and d.


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Panel (a) is a large topographic map showing a river valley in a mountainous region, spanning the border between China and Nepal. The Poiqu River flows from north to south through the valley. Several locations are marked with red dots, including Jialongco, Nyalam, Zhangzangbo Bridge, and Zhangmu Port. The map includes latitude and longitude grids, a scale bar from 0 to 4 km, and a north arrow. There are two circular insets with photographs. The top-left inset, pointing from Jialongco, shows a turquoise glacial lake surrounded by a rocky moraine. The bottom-right inset, pointing from an area near Zhangzangbo Bridge, shows a dry, rocky landscape.

Panels (b), (c), and (d) are smaller maps showing the results of a flood simulation in a specific area downstream.
- Panel (b) displays the 'Flood depth (m)', with a color scale ranging from 0.001 (blue) to 56.7 (magenta).
- Panel (c) shows the 'Flood velocity (m/s)', with a color scale from 0.1 (light blue) to 22.3 (red).
- Panel (d) presents a 'Hazard' map with a legend indicating four levels: Low (dark green), Medium (light green), High (yellow), and Very high (red).

Fig. 2. Simulation of the Circhmaco GLOF. (a) The outburst floods will cross the Zhangzangbo Bridge to Zhangmu Port and then enter Nepal at the largest drainage scenario (100%). (b) The Circhmaco GLOF depth and (c) velocity are used to composite the (d) hazard map. All data in this figure were provided by Zhang et al. [25]. The picture in the circle on the left shows the strengthened moraine dam of Jialongcuo, and on the right shows the melting of buried ice in the moraine dam of Circhmaco.


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Figure

Image /page/4/Figure/2 description: A composite image of five photographs, labeled a, b, c, d, and e, each showing a different scientific monitoring station in a remote, natural environment. Image 'a' displays a complex weather station on a rocky mountainside with a person in a red jacket nearby and solar panels on the ground. Image 'b' shows a station with a large solar panel and colorful prayer flags, set against a backdrop of green hills. Image 'c' features a station on the shore of a turquoise lake with snow-capped mountains in the background and a person standing next to it. Image 'd' depicts a station with a solar panel next to a rushing river. Image 'e' shows a simpler station on a steep, rocky slope.


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Fig. 3. Early warning system installed at Cirenmaco. A total of nine different services are contained in this project. These include (a) monitoring of the lake and its parent glacier, (b) monitoring of the environment of the downstream river, (c) water level monitoring of the glacial lake, (d) water level monitoring of the downstream river and (e) moraine dam dynamic monitoring.


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Figure

Image /page/4/Figure/4 description: A multi-panel figure displaying real-time monitoring data from a glacial valley. Panel (a) is a map of the area, showing the locations of various sensors including GNSS, cameras, meteorological stations, and water level sensors along a river and near a lake. The map includes latitude and longitude coordinates and a scale bar. Panels (b) through (j) are a series of photographs taken over time. Panels (b-d) show a glacier terminating in a turquoise lake. Panels (e-g) show the surface of the turquoise lake. Panels (h-j) show a river flowing through a rocky channel. The bottom section contains four graphs labeled (k), (l), (m), and (n), all plotted against dates from 2021/10/3 to 2021/10/19. Graph (k) shows a water level decreasing from approximately 1.8 m to 0.5 m. Graph (l) shows a water level that is stable around 0.5 m before spiking to a peak of about 0.85 m around 2021/10/19. Graph (m) shows temperature fluctuating daily between approximately -1°C and 5°C, with precipitation events shown as blue bars, including a significant event around 2021/10/18. Graph (n) shows temperature fluctuating between approximately 4°C and 12°C, also with a significant precipitation event around 2021/10/18.


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Fig. 4. Real-time monitoring data transmission via satellite and mobile networks. (a) Distribution of the main monitoring points in the Zhangzangbo Valley, and the monitoring data currently available, such as photographs taken by three visible light cameras, which are aligned (b–d) with the Cirenmaco inlet area and the snout of its parent glacier and (e–g) its outlet area, and (h–j) the terminus of the Zhangzangbo Valley. (k, l) Water level data and (m, n) meteorological data from the glacial lake and the mouth of the valley.

~40 min, according to the observed average flow velocity (9.8 m/s) of the 1981 GLOF in Nepal [54]. These data suggest that approximately 40–60 min may be required to send a warning signal.

In addition, the hazard map was composited by flood depth and velocity and translated into four intensity levels: low, medium, high, and very high (Fig. 2d). In the future, more refined and accurate simulation results can be relied upon to establish this hazard map, which has implications for determining evacuation locations in downstream areas, constructing GLOF prevention and mitigation facilities, and implementation of economic development measures. These studies provide an understanding of the possible flood damage from Cirenmaco and are the basis of this EWS construction [21,28,58].


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Section: 2. Previous studies on Cirenmaco
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Figure

Image /page/5/Figure/2 description: A topographical map displaying water depth measurements of a lake situated in a mountainous region. The map is oriented with North at the top, as indicated by a north arrow. The y-axis shows latitude from 28°3'45"N to 28°4'15"N, and the x-axis shows longitude from 86°3'45"E to 86°4'15"E. A winding path of colored dots across the dark green lake surface represents the water depth. A legend in the bottom left corner, titled "Water depth (m)", explains the color scale. The depth ranges from 6.2 meters, represented by blue, to 115.3 meters, represented by red, with green, yellow, and orange indicating intermediate depths. The deepest area, shown in red, is located in the central part of the survey path. A scale bar indicates a length of 0.2 kilometers.


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Fig. 5. In 2012. Wang et al. [24] measured the water depth and estimated the volume of Circumaco using an unmanned boat.


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Section: 2. Previous studies on Cirenmaco
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Figure

Image /page/5/Figure/4 description: A schematic diagram illustrates the major components of an early warning system (EWS) for a glacial environment. The diagram shows a mountainous landscape with a glacier labeled "Glacier ice" on a slope of bedrock. The glacier feeds into a large glacial lake, which is held in place by a moraine dam. Below the dam, there is buried ice and a downstream river system. Various monitoring systems are in place, indicated by labels and icons. On the glacier, there is "Glacier dynamic monitoring." Near the lake, there is "Meteorological monitoring" (with precipitation shown as snowflakes falling from clouds) and "Topographic mapping" (indicated by a drone). Within the lake, there is "GLacial lake dynamic monitoring" and a "Bathymetric survey." At the lake's edge, "Water level monitoring" is shown. On the moraine dam and downstream area, there is "GNSS displacement monitoring" and "Downstream river dynamic monitoring." Data from all these monitoring points is sent via blue lines to a central "Data transmission" tower. This tower transmits the data to a satellite, which then relays it to a "Data center." The data center sends information to "Observers," who can then issue an "Early warning," represented by a red icon with sound waves.


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Section: 2. Previous studies on Cirenmaco
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Fig. 6. Schematic diagram illustrating major components of the Cirenmaco EWS, including the lake and its parent glacier monitoring, downstream river monitoring, water-level monitoring, moraine dam dynamic monitoring, meteorological monitoring, bathymetric survey, topographic mapping, data transmission, and transferring the early warning signal.


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Section: 3. Characteristics of EWS > 3.1. A typical case: an EWS established for 513 Lake, Cordillera Blanca, Peru, in 2012
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Two drainage events occurred in the Peruvian glacial Lake 513, in 1994 and 2010. An ice avalanche triggered the 1994 GLOF. However, because of the prior artificial drainage of the lake, the GLOF magnitude was comparatively low, so no damage was caused to the downstream area [51,59]. The 2010 GLOF was a catastrophic event, also triggered by an ice avalanche, that severely damaged the downstream city of Carhuaz, destroying 22 buildings and 100 km of roads, and causing 100 casualties [59]. In response to the serious threat posed by Lake 513, the local government implemented an EWS in 2011–2012 to prevent potential disaster [28]. Notably, the

EWS of Lake 513 is the first glacial lake early warning system worldwide with a fully functional service system. It includes risk knowledge (hazard and risk assessment), monitoring and warning services (monitoring and warning of hazard occurrence), dissemination and communication (dissemination of warning signals), and response capability (disaster mitigation plans and evacuation drills) [60].

Risk knowledge requires field investigation and analytical work to make a hazard and risk assessment of glacial lakes to clarify lake outburst probability and downstream exposure within the GLOF path. Monitoring and warning services consist of five components [28, 61]. The first is a glacier and lake monitoring station at the lake shore, which consists of four geophones and two cameras that record ground shaking during ice avalanches and flooding, as well as glacier–glacial lake dynamics. The second component is a hydrometeorological monitoring station, which is installed downstream of the lake outlet. The third component is the repeater station, whose main function is to transmit the monitored data to the data center. The fourth component is the data center in the city of Carhuaz, which is responsible for data evaluation and storage. The fifth component is the warning station, which is primarily responsible for the warning signal. The functionality of the dissemination and communication components, as well as the response capability, largely depends on active coordination with local authorities and residents to maximize the full functionality of the EWS and reduce potential losses. The EWS of Lake 513 provides a good reference for the construction of an EWS for Cirenmaco.


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Section: 3. Characteristics of EWS > 3.2. EWSs on the TPS
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The early warning system essentially differs in predicting GLOFs versus rainfall-type floods. The EWS for GLOFs focuses on monitoring various elements and issuing timely warnings rather than providing specific flood features. This is due to GLOFs' high magnitude, short duration, and destructive properties. Forecasting rainfall-type floods, on the other hand, concentrates primarily on real-time hydrological processes based on dynamic courses of flow regime, streambed roughness, fluid density, etc., to establish effective standard curves to predict and warn of floods downstream with metrics generally on peak discharge, maximum water level, and arrival time [62].

Five EWSs have been established over the past few decades in the TPS region, to prevent GLOFs (Fig. 1a, Table 2). EWSs can be divided into two categories, based on their technical structures. The first is a semi-automatic system that relies on staff assistance. For example, a manual EWS in Bhutan was installed, with six water-level sensors and two automatic weather stations, and included a control room with two workers in a village downstream of the glacial lakes. The workers are equipped with satellite phones for information transmission [63,64]. The second was a fully automatic EWS. These services generally consist of real-time monitoring of the glacial lake and its parent glacier, hydrometeorological monitoring, data transmission and storage, and early warning [28,61]. For example, in 2014, an EWS was installed in Kyagar, an ice-dammed lake in Karakoram, China. It consists of three observation stations situated the lakeshore, estuary, and far downstream. The parameters, including the water-level of the lake and river, monitored by automatic sensors and photographs of the lake and riverbed taken by automatic time-lapse cameras, are all transferred through a satellite link to a data center [29]. If a GLOF was identified, warning signals were sent to authorities. In addition, fully automatic EWSs require an indispensable threshold to determine GLOFs, which may be real-time dynamic warning indicators such as lake and river water levels, deformation of the lake and glacier, or meteorological data [65]. The water-level threshold is frequently used in EWSs [28]. The main difference between a semi-automatic EWS and a fully automatic EWS is data transmission. Due to the remote and inaccessible environment in high-altitude mountainous regions, data transmission is very difficult and expensive. However, long-term observations using satellite for data transmission incur high costs. The frequency and cost of equipment maintenance are also higher than those of semi-automatic systems.

Overall, the quality of the current EWS applied to high-risk glacial lakes varies greatly around the world. In theory, a simple prediction scheme would require only the installation of water-level sensors for real-time analysis. Some activities in the Hindu Kush-Karakorum range rely on primitive beaconing methods to provide early warning [66]. If the purpose is not to investigate the mechanism of GLOF, but rather to provide early warning, it is a success as long as the effective alarm signal can reduce downstream exposure damage. Due to the limited data transmission scheme, fully automated and multidimensional monitoring of EWS is rare. Under the

 The GLOF early warning systems widely established in the TPS region, including the Tian Shan Mountains, Karakoram, and Himalayas.

3. Characteristics of EWS
3.2. EWSs on the TPS


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Table: Table 2

| ID | Lake name                                                          | Lake type          | Location                       | Longitude° | Latitude° | Explanation                                                                                | References |
|----|--------------------------------------------------------------------|--------------------|--------------------------------|------------|-----------|-------------------------------------------------------------------------------------------------------------------------------------|------------|
| 1  | Teztor lake                                                        | Moraine- dammed | Tien Shan, Kyrgyzstan       | 42.54      | 74.43     | The EWS was installed in 2011, and successfully predicted the Teztor lake GLOF in 2012.                                             | [67]       |
| 2  | Kyagar lake                                                        | Ice- dammed     | Karakoram, China            | 35.71      | 77.01     | The EWS combined three automatic terrestrial observation stations, and successfully predicted Kyagar GLOFs from 2015 to 2018.       | [29,38]    |
| 3  | Ropal Tsho                                                         | Moraine- dammed | Central Himalaya, Nepal  | 27.86      | 86.47     | A manual EWS was set up in 1997, and evolved into a fully automatic system in 1998.                                                 | [50]       |
| 4  | Imja Tsho                                                          | Moraine- dammed | Central Himalaya, Nepal  | 27.9       | 86.93     | The EWS combined two monitoring stations and two relay stations.                                                                    | [63]       |
| 5  | Raphstreng Tsho; Luggye Tsho; Thorthormi Tsho; Besta lake | Moraine- dammed | Eastern Himalaya, Bhutan | 27.88      | 89.74     | The EWS was installed with six water level sensors and two weather stations, and successfully predicted Lemthang Tsho GLOF in 2015. | [63,64]    |

ID
Lake name
Lake type
Location
Longitude°
Latitude°
Explanation
References


Document: 1-s2.0-S2212420922001339-main
Section: 3. Characteristics of EWS > 3.2. EWSs on the TPS
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premise of ensuring effective early warning efforts, a comprehensive monitoring system is crucial and valuable for understanding the GLOF generation mechanism, propagation process, and flow regime transformation. This is particularly true regarding the action of photo or video monitoring of glaciers and glacial lakes, which not only eliminates many false alarm signals but also motivates us to understand the potential glacier–glacial lake–moraine dam linkage process when GLOF occurs.


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Section: 4. Construction of the Cirenmaco EWS
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The Cirenmaco EWS project, which was established in 2020 and validated in 2021, is the first use of a comprehensive EWS application in a moraine-dammed lake in China. It is a fully automatic system that applies several new technologies and methods. The entire system complies with the current two basic mechanisms of moraine-dammed lake outbursts: overtopping and piping. Both mechanisms are likely to emerge in Cirenmaco drainage. Overtopping triggers mainly consist of the ice avalanche from its mother glacier, which has been detecting by photo and video monitoring and satellite remote sensing image analysis. A water-level sensor located at Cirenmaco Lake will record the potential wave displacement. This is the main surface dynamic process that we considered, because the Cirenmaco GLOF generated in 1981 was determined to have been caused by an ice avalanche based on field investigations. Piping is generally induced by the melting of buried ice; thus, surface displacement monitoring was employed to record the activity status of the Cirenmaco moraine dam. We also deployed three water-level sensors and two meteorological stations along the flood route in Zhangzangbo Valley to observe the response of the lake and river after the GLOF occurred, as well as the meteorological context of the disaster (see Table 3). We elaborates on this advanced EWS in terms of four major categories and 10 specific components.


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Section: 4. Construction of the Cirenmaco EWS > 4.1. Monitoring system
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- (i). Glacial lake, related parent glacier, and downstream river monitoring. A 6 m observation tower was built on the right bank of the lake to equip various apparatuses (Fig. 3a). Three 360° rotatable high-definition dome cameras were mounted on the tower, to capture daytime video surveillance and high-frequency timing photographs (Fig. 4a). The first camera was pointed at the lake's inlet area and the snout of its parent glacier (filming every hour from 8 a.m. to 8 p.m.) (Fig. 4b–d). The second camera was pointed at the middle of Cirenmaco Lake (filming every 3 h from 8 a.m. to 8 p.m.), and the third was pointed at the outlet area of Cirenmaco (filming every 3 h from 8 a.m. to 8 p.m.) (Fig. 4e–g) and also monitors the status of the moraine dam. A thermal imaging dome camera (infrared night vision device) was installed at the same angle as the first camera to monitor the lake and glacier (filming every hour from 8 p.m. to 8 a.m.). The thermal camera has low power consumption and a fog-penetration function and can provide video and timed photos under nighttime or foggy conditions. We also installed a group of infrared and visible light cameras at the intersection of Zhangzangbo Valley and the Poiqu River to record the state of the downstream river environment (Figs. 3b and 4h–j). The filming frequency of both cameras was one frame per hour. - (ii). Water-level monitoring of glacial lakes and downstream rivers. This service consisted of three automatic water-level sensors that also monitored additional parameters, including water temperature and pressure. One was installed on the lake shore of Cirenmaco (Fig. 3c), recording the possible wave displacement induced by an ice avalanche. One was installed at the lake outlet, and the other was installed at the terminal of the Zhangzangbo Valley (Fig. 3d), near the location of the cameras. The recordings of these sensors were collected every 30 s (Fig. 4k and l). - (iii). Dynamic monitoring of moraine dam. This element includes thickness, displacement, and temperature monitoring of the moraine dam. The Cirenmaco moraine dam has accumulated an enormous quantity of rocks, debris, and buried dead ice (Fig. 2a). The stability of the moraine dam impacts the frequency and magnitude of outburst floods. Two global navigation satellite systems (GNSS) were used to detect the elements of the moraine dam (Fig. 3e). This technology was applied here for the first time to observe the moraine dam in a glacial lake. The main potential variations were the settlement of the moraine dam caused by the melting of buried ice, and the movement effect of the moraine dam when the GLOF occurred. Ground penetrating radar was used to detect the moraine dam and analyze its thickness. - (iv). Meteorological monitoring. Meteorological stations measured more than a dozen meteorological parameters, including wind speed, wind direction, precipitation, air temperature, air humidity, radiation, soil temperature, soil moisture, and atmospheric pressure (Figs. 3a and 4m–n). We selected three automatic meteorological stations at different altitudes in Zhangzangbo Valley.

4. Construction of the Cirenmaco EWS
4.1. Monitoring system


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Section: 4. Construction of the Cirenmaco EWS > 4.1. Monitoring system
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dam in a glacial lake . The main potential variations were the settlement of the moraine dam caused by the melting of buried ice , and the movement effect of the moraine dam when the GLOF occurred . Ground penetrating radar was used to detect the moraine dam and analyze its thickness . - ( iv ) . Meteorological monitoring . Meteorological stations measured more than a dozen meteorological parameters , including wind speed , wind direction , precipitation , air temperature , air humidity , radiation , soil temperature , soil moisture , and atmospheric pressure ( Figs . 3a and 4m – n ) . We selected three automatic meteorological stations at different altitudes in Zhangzangbo Valley .

These were located at the lake shore of Cirenmaco, the middle altitude of the valley, and the intersection of the valley and the Poiqu River to monitor the three-dimensional and horizontal meteorological background of disasters within the study area. The total elevation difference between the three automatic meteorological stations was nearly 2500 m. - (v). Satellite Remote Sensing Image Monitoring. To trace the historical state of the entire sequence of Cirenmaco disasters, a series of satellite images, such as Landsat, Sentinel, and SPOT, were selected to illustrate the lake–glacier dynamics. Useful information such as glacier boundary, glacier velocity, and ice crevasse development should be extracted as much as possible. Regular updates and database maintenance are required to provide a broad contextual awareness for high-frequency water-level, meteorology, and displacement monitoring. - (vi). Bathymetric survey for the lake and topographic mapping for the lake and its surroundings. Lake volume is a critical metric in identifying potentially dangerous glacial lakes. Following the Cirenmaco bathymetric survey in 2012 (Fig. 5) [24], we conducted a more detailed bathymetric survey in 2020 to understand the lake's evolution. We also utilized drone images to create high-resolution topographic mapping around the lake.


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Table: Table 3 Primary equipment for the early warning system of Cirenmaco, as well as the involved monitoring elements, data acquisition intervals and accuracy.

| Equipment                              | Number | Locations                                    | Primarily monitored elements                                                                                | Accuracy                                                                 | Acquisition interval |
|----------------------------------------|--------|----------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------|----------------------|
| Pressure type water level sensor    | 3      | lake, downstream river                    | Water-level                                                                                | 0.1%FS                                                                   | 30 s                 |
| Automatic meteorological station | 3      | lake, Zhangzangbo Valley                  | air temperature; precipitation; wind speed and direction; air humidity; radiation; soil temperature; soil moisture; atmospheric pressure | ±0.2 °C; ±0.4 mm; ±0.3 m/s; ±5°; ±3%; ±5 W/m2; ±0.5 °C; ±3%; ±0.3 hPa | 30 min               |
| Camera                                 | 6      | glacier, glacial lake, moraine dam, river | dynamic processes                                                                                | /                                                                        | 1–3 h                |
| GNSS                                   | 2      | moraine dam                                  | surface displacement                                                                                | <1 m                                                                     | 0.25 s               |

Equipment
Number
Locations
Primarily monitored elements
Accuracy
Acquisition interval


Document: 1-s2.0-S2212420922001339-main
Section: 4. Construction of the Cirenmaco EWS > 4.2. Data-processing system
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- (vii). Data transmission. The data measured in this ESW were transmitted via the Beidou and Inmarsat satellites and a mobile network to a data center (Fig. 6). The devices situated around Cirenmaco need to employ satellites to transmit data due to the lack of mobile signal coverage. The water-level and meteorological and imaging data at the mouth (middle) of Zhangzangbo Valley can be transmitted through the mobile network. Furthermore, all these devices are powered by solar panels.
- (viii). Data Center. It is located at the Institute of Tibetan Plateau Research Chinese Academy of Sciences, China. The center is responsible mainly for data storage, real-time surveillance, and transferring early warning signals. All data were moved or directly transferred to the Tibet Autonomous Region Disaster Cloud Platform (http://holo-earth.cn:9022/), established by the Institute of Tibetan Plateau Research, Chinese Academy of Sciences. There is a delay of approximately 2 min when data transmitted via satellite and mobile networks are loaded into the platform. Subsequently, the data can be immediately used for real-time alarm analysis. In addition, all the data measured from this EWS will be shared with Nepalese authorities, which is an important measure to increase cooperation and protect lives, livelihoods, and property on both sides downstream.

4. Construction of the Cirenmaco EWS
4.2. Data-processing system


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(ix). Warning system. In this study, a compound warning threshold was used. Those already successfully operated included the water-level and meteorological thresholds. In subsequent field investigations and indoor technical implementation studies, the deformation of the lake and glacier, moraine dam displacement threshold, and seismic threshold will be incorporated. It should be emphasized that we still lack experience with alarm techniques, and many novel strategies and thresholds are constantly being investigated and developed. The water-level threshold is a critical component of our early warning system, and the three water-level sensors scattered around Zhangzangbo Valley will be integrated. The warning level was separated into three grades, with the first level being the highest and the third being the lowest. The difference between the most recent measurement and the lowest value of the water-level over the past 10 min was used to calculate water-level variation. Eventually, three water levels with thresholds of 30, 25, and 20 cm were selected (Table 4), obtained based on the analysis of our monthly acquired monitoring data. The meteorological thresholds have an auxiliary role in this system and are simply intended to remind the observer to keep a closer eye on the Cirenmaco condition over time. A warning signal was automatically issued to the observer whenever the monitoring element exceeded a specified threshold. Subsequently, the observer checks the real time photos or video of the glacial lake and its parent glacier to determine the lake situation and informs the decision makers and authorities. Since the travel time of a GLOF from Circumaco to the cross-border is ~40 min, it was very important to make the warning process easy and efficient. Despite the EWS with a time delay of ~2 min for monitoring data transmitted to the data center, the data can be used for real-time warning analysis at the platform. This could benefit our valuable basic warning time.

4. Construction of the Cirenmaco EWS
4.3. Early warning system


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Section: 4. Construction of the Cirenmaco EWS > 4.4. Response capacity development
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Disaster mitigation plans and evacuation drills for GLOFs are also critical in ensuring that potentially influenced people can be evacuated to a safe area and that their belongings are secured in a timely manner. This study examines the ability of authorities, who require a considerable degree of general awareness of the present and future challenges facing high mountain regions, specific knowledge of GLOF susceptibility, risks, and warning time, as well as considerable vigor and foresight. Prior to the establishment of the

4. Construction of the Cirenmaco EWS
4.4. Response capacity development


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Section: 4. Construction of the Cirenmaco EWS > 4.4. Response capacity development
Type: table
Table: Table 4 Constructed and in-process designs of early warning indicators and their threshold settings.

| Equipment                           | Thresholds                         | Status      |
|-------------------------------------|------------------------------------|-------------|
| Water level sensor at lake shore    | I:30 cm; II:25 cm; III: 20 cm      | Run         |
| Water level sensor at lake outlet   | I:30 cm; II:25 cm; III: 20 cm      | Run         |
| Water level sensor at valley mouth  | I:30 cm; II:25 cm; III: 20 cm      | Run         |
| Precipitation at lake shore         | I:16 mm/h; II:10 mm/h; III: 8 mm/h | Run         |
| Deformation of the lake and glacier |                                    | To be built |
| Moraine dam displacement            |                                    | To be built |
| Seismic                             |                                    | To be built |


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Section: 4. Construction of the Cirenmaco EWS > 4.4. Response capacity development
Type: text

Cirenmaco EWS, the relevant glacial lake research group, made up of researchers, had been working continuously in the area for five years and had played a key role in improving the knowledge of the local population and government regarding the glacial lake and its accompanying hazard/risk. Therefore, when the EWS was ready to be established, we gained strong support from the local government. This also facilitated many of our communication efforts for specific actions of GLOF prevention, and later maintenance of the EWS devices, and avoided some of the human damage caused by differences in perceptions, such as religious beliefs.

Formulating disaster mitigation plans, implementing relief measures, and reserving relief supplies in advance are critical steps for minimizing casualties and losses [59]. Disseminating disaster prevention knowledge to residents, and allowing them to participate fully are also necessary. At present, relevant functionaries have been cooperating with the Disaster Emergency Management Department of the Tibet Autonomous Region and Nepal to fully utilize its function and help it become an effective, timeless, and representative EWS.


Document: 1-s2.0-S2212420922001339-main
Section: 5. Summary and perspectives
Type: text

In the Himalayas, where numerous high-risk glacial lakes are distributed, the ability to prevent and mitigate GLOFs remains insufficient, especially for transboundary threats. There are no reports that mention methods to effectively solve this problem. The construction cost of the Cirenmaco EWS was kept under 0.5 million dollars, which is much less than the cost used to strengthen the moraine dam of Jialongco (>\$10 million) in the same basin. Therefore, the EWS is relatively inexpensive to establish compared to other engineering measures on glacial lakes, and the availability of valuable field observations is important for furthering scientific research and development, making it suitable for large-scale replication in the Himalayas. The cost of the satellite transmission is also affordable. The pros and cons of each scenario must be weighed by the staff of each party, and any plan put in place must match the strength of regional social and economic development.

The Cirenmaco EWS is advanced and applies many new technologies such as real-time video transmission. One of the main objectives of applying this feature is to record the entire process of a glacial lake outburst, from the initial triggering event to the flood breaking through the dam and causing damage downstream; as the dynamics of a GLOF, as it occurs, are yet directly observed. We describe in detail the Cirenmaco EWS implemented in our project in four main categories: monitoring systems, data-processing systems, early warning systems, and response capacity development. All monitoring data have been successfully transmitted in real-time, and the EWS has been functional since October 2021. Both China and Nepal could benefit from the EWS project. Our study is of great significance in adapting to the increasing disaster risks in high-altitude mountainous areas and in providing a demonstration for the prevention and mitigation of GLOFs in the Himalayas and TPS.


Document: A glacial lake outburst flood risk assessment for the Phochhu river basin
Type: text

Abstract. The melting of glaciers has led to an unprecedented increase in the number and size of glacial lakes, particularly in the Himalayan region. A glacial lake outburst flood (GLOF) is a natural hazard in which water from a glacial or glacier-fed lake is swiftly discharged. GLOFs can significantly harm life, infrastructure, and settlements located downstream and can have considerable ecological, economic, and social impacts. Based on a dam breach model, BREACH, and a hydrodynamic model, HEC-RAS (Hydrologic Engineering Centre's River Analysis System), we examined the potential consequences of a GLOF originating from the Thorthomi glacial lake, located within the Phochhu river basin, one of Bhutan's largest and rapidly expanding glacial lakes. Our analysis revealed that following a breach the Thorthomi glacial lake will likely discharge a peak flow of 16360 m3 s-1 within 4h. Such a discharge could potentially cause considerable damage, with an estimated 245 ha of agricultural land and over 1277 buildings at risk of inundation. To mitigate ecological, economic, and social impacts on downstream areas, our results emphasise an urgent need for understanding and preparing for the potential consequences of a GLOF from Thorthomi lake. Our findings provide valuable insights for policymakers and stakeholders involved in disaster management and preparedness.

data/('A glacial lake outburst flood risk assessment for the Phochhu river basin', '.pdf')_extraction.md


Document: 1 Introduction
Section: 1 Introduction > 1.1 Glacial lakes and outburst floods
Type: text

Floods are one of the most common natural disasters worldwide and can cause extensive socio-economic damage. Globally, over the last 2 decades, floods have affected approximately 2.3 billion people and have caused an estimated USD 622 billion in damage (UNISDR, 2015). Glacial lake outburst floods (GLOFs) are floods caused by sudden water release from glacial or glacier-fed lakes and cause a rapid rise in water level over a short time in downstream areas, resulting in devastating consequences (Gurung et al., 2017; Komori et al., 2012; Taylor et al., 2023). GLOFs are infrequent but highly destructive natural disasters that are difficult to predict. Prior to their occurrence, the extent of damage is also difficult to predict. Over the past few decades, the acceleration of glacier melt and recession, primarily driven by climate change, has led to a significant increase in the number of moraine-dammed (natural dams formed by glacial processes) glacial lakes (Sattar et al., 2021; Westoby et al., 2014; Worni et al., 2014). Taylor et al. (2023) estimated that approximately 15 million people are exposed to risks associated with potential GLOFs and that most of these populations are concentrated within High Mountain Asian (HMA) areas. Due to climate warming (Gardelle et al., 2011), the eastern Himalayan area, in particular, has seen a significant increase in the number and area of glacial lakes, thereby increasing the vulnerability of nearby communities to potential GLOF impacts (Hagg et al., 2021).

Although GLOF research and studies have gained global momentum in recent years, only a few studies have been per-formed in Bhutan. Numerous studies conducted in Nepal and

<sup>1National Center for Hydrology and Meteorology, Thimphu, Bhutan

<sup>2Department of Civil and Environmental Engineering, Nagoya University, Nagoya 464-8603, Aichi, Japan

China have simulated and assessed GLOF risks, although detailed studies on Bhutan's exposure to GLOF-related hazards are scarce. Such scarcity can be attributed to a lack of required field data, as well as to Bhutan's limited exposure to the global scientific community.

1 Introduction
1.1 Glacial lakes and outburst floods


Document: 1 Introduction
Section: 1 Introduction > 1.2 Past GLOF events in Bhutan
Type: text

In the past, Bhutan has faced several GLOF events; however, many of these events were either not reported or not documented. One of the most catastrophic GLOFs took place on 6 October 1994, when the moraine dam of Luggye lake partially collapsed, leading to the release of a massive amount of water and debris downstream, destruction to infrastructure and farmland, and the death of 21 people (Watanabe and Rothacher, 1996; Leber et al., 2000). Another significant GLOF occurred in 2009, when an outburst from Tshojo lake, located at the headwaters of the Phochhu river, caused downstream flooding. Based on satellite imagery and a sedimentological and geomorphological analysis, Komori et al. (2012) attributed an outburst from the supraglacial lake on the Tshojo glacier to the event. The most recent GLOF, the Lemthang Tsho outburst, took place on 28 July 2015. Gurung et al. (2017) reported that heavy rainfall triggered the event and that  $0.37 \times 10^6 \,\mathrm{m}^3$  of water was discharged.

1 Introduction
1.2 Past GLOF events in Bhutan


Document: 1 Introduction
Section: 1 Introduction > 1.3 Potentially dangerous glacial lakes in Bhutan
Type: text

Based on the latest report from the National Center for Hydrology and Meteorology (NCHM) in Bhutan, 567 glacial lakes in the country span an area of 55.04 km2, accounting for 19.03% of total water bodies (NCHM, 2021). In 2001, the Department of Geology and Mines (DGM) in Bhutan and the International Centre for Integrated Mountain Development (ICIMOD) performed the first-ever inventory of glaciers, glacial lakes, and potentially dangerous glacial lakes (PDGLs), and they identified 24 glacial lakes that fit this category (Mool et al., 2001). However, in 2019, using field-verified data and the latest Sentinel-2 satellite images, NCHM reassessed the number of PDGLs and revised the number to 25, with eight lakes now considered to be safe based on lake morphology, surrounding features, bathymetry conditions, and associated feeding glaciers (NCHM, 2019). Figure 1 provides a map of rivers and the river basin system within Bhutan, together with the distribution of glaciers and glacial lakes. The Punatsangchhu river basin contains 11 PDGLs, which is the largest number of PDGLs per basin the in the country. The Phochhu sub-basin contains nine PDGLs, making it a hotspot for GLOFs and glacially related disasters.

Warming climate exacerbates the hazards of GLOFs, so a comprehensive GLOF assessment is urgently needed since these risks will increase in the coming years. As such, a study assessing hazards associated with glacial lakes and GLOFs is crucial for understanding hazards, as well as their subsequent impacts on hydrological and socio-economic aspects within the Punatsangchhu river basin.


Document: 1 Introduction
Section: 1 Introduction > 1.4 Increasing concern regarding a Thorthomi GLOF
Type: text

Thorthomi lake is the largest of nine PDGLs within the Phochhu basin. Due to the significant potential risk posed to downstream settlements resulting from a GLOF, the Thorthomi glacial lake has become a serious concern due to the following factors: (1) rapid expansion of the Thorthomi supraglacial lake, (2) the size of glaciers and probable future lake size, (3) the weakened left lateral moraine of the lake due to the 1994 Luggye GLOF, (4) active sliding on the moraine wall separating the Thorthomi and Rapstreng lakes, (5) seepage from the lake, and (6) rock and snow avalanches, as summarised by Karma (2013). To address these factors, the government of Bhutan initiated a highpriority project, referred to as the National Adaptation Plan of Action (NAPA), under the United Nations Framework Convention on Climate Change (UNFCCC) funding scheme in 2006. The project sought to reduce the GLOF risk potential from Thorthomi lake and involved lowering the lake's water level over 4 years, resulting in a reduction of 3.68 m. However, due to challenging working conditions and health issues, the project fell 1.32 m short of its target, although approximately  $17 \times 10^6$  m3 of lake water was artificially released. The project additionally included setting up a GLOF early warning system along the Punakha-Wangdue valley for alerting residents in the event of a GLOF.


Document: 1 Introduction
Section: 1 Introduction > 1.5 The focus of our study
Type: text

To contribute to risk management efforts, we evaluated the potential risk of a GLOF from Thorthomi lake. The physically based mathematical dam breach model, BREACH, was used to simulate a glacial lake dam breach and was coupled with the Hydrologic Engineering Centre's River Analysis System (HEC-RAS) to route the flood wave propagating downstream. We sought to simulate both the spatial extent and the lead time of flood wave arrival at several locations along the river. Prior to predicting Thorthomi GLOF hazards and potential risks, we reconstructed the 1994 Luggye GLOF event to validate the dam breach model and the flood wave routing model, which includes river topography and roughness

Our study is one of a few studies that has simulated probable floods from Thorthomi lake and that has estimated inundation extent and flood arrival times within a scientific setting. Such studies form an essential basis for flood risk assessments, early warning system installation, economic planning, countermeasure planning, design, and stakeholder education and awareness programmes.

The main components of our study are as follows:

1 Introduction
1.5 The focus of our study


Document: 1 Introduction
Section: 1 Introduction > 1.5 The focus of our study
Type: figure
Figure

Image /page/2/Figure/2 description: A map of Bhutan showing its river and basin systems, along with the distribution of potentially dangerous glacial lakes (PDGLs). The map includes a north arrow, latitude and longitude lines from 27°0'0"N to 28°0'0"N and 89°0'0"E to 92°0'0"E, and a scale bar in kilometers. The legend details various features: Rivers (blue lines), Sub-basin boundaries (dashed lines), the Punatsangchhu basin (shaded gray), the Bhutan boundary (solid outline), Glaciers (light blue areas in the north), Main Roads (brown lines), and Urban Areas (yellow patches). The map also plots PDGLs as circles, categorized into two groups. The first group, 'PDGLs(sq.km)', is shown in purple with sizes corresponding to areas: 0.1 - 0.67, 0.67 - 1.46, and 1.46 - 2.9 sq.km. The second group, 'PDGLs(sq.km)-safe', is shown in green with sizes for areas: 0-0.06, 0.06-0.34, and 0.34-0.58 sq.km. Several lakes in the northern region are labeled, including Rapstreng Lake, Thorthomi Lake, and Luggye Lake.


Document: 1 Introduction
Section: 1 Introduction > 1.5 The focus of our study
Type: figure
Figure: Figure 1. A map showing the rivers and basin system of Bhutan, as well as the distribution of potentially dangerous glacial lakes, the main road network, and major urban areas. Bubbles are scaled to total lake area and colour-coded for classification. PDGLs stand for potentially dangerous glacial lakes. Data source: National Center for Hydrology and Meteorology (NCHM).

**Figure 1.** A map showing the rivers and basin system of Bhutan, as well as the distribution of potentially dangerous glacial lakes, the main road network, and major urban areas. Bubbles are scaled to total lake area and colour-coded for classification. PDGLs stand for potentially dangerous glacial lakes. Data source: National Center for Hydrology and Meteorology (NCHM).


Document: 1 Introduction
Section: 1 Introduction > 1.5 The focus of our study
Type: text

- estimating the geometry and water volume of Thorthomi lake using available glacial lake geometry data;
- estimating the potential outburst flood hydrograph using a dam breach model, BREACH, with available physical parameters; and
- 3. assessing Thorthomi GLOF hazards and potential risks using a 2D hydraulic model.


Document: 1 Introduction
Section: 1 Introduction > 1.6 Structure of the paper
Type: text

The paper contains six sections. Section 1 introduces the overall concept of a GLOF and provides information obtained from previous studies and information related to GLOFs in the context of Bhutan. Section 2 describes the study area and the GLOF event used for model validation and calibration. We explain materials and methods in Sect. 3. Obtained results are reported in Sect. 4. Based on the results, we discuss the consequences of a Thorthomi GLOF in Sect. 5. We conclude our study in Sect. 6.

1 Introduction
1.6 Structure of the paper


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: text

We assessed flood risk for a catchment of under-construction hydropower plants, specifically the Punatsangchhu Hydroelectric Project Authority (PHPA-I and II), caused by a GLOF from Thorthomi lake. The catchment is the upper part of the Punatsangchhu river basin (PRB), located within the central portion of Bhutan and indicated by the grey area in Fig. 2a. PRB is one of the largest basins in Bhutan, spanning an approximate area of 9760 km², which covers approximately 25 % of the total area of the country (38 394 km²), and is drained by the Phochhu and Mochhu rivers (Fig. 2a) to the Indian plains. The annual averaged discharge of the basin ranges from 194 to 374 m³ s-1, with the highest recorded discharge of 2654 m³ s-1, observed at the WangdiRapid station (location shown in Fig. 2c), occurring in 2009 during Cyclone Aila.

The Phochhu river, one of the main tributaries of the Punatsangchhu river, originates from the high mountains of Lunana, in northern Bhutan, and flows some 90 km downstream, where it joins Mochhu at Punakha Dzong (monastery) (Fig. 2c), and flows from this area as the Punatsangchhu river. The Thorthomi glacial lake, considered to be one of the most dynamic and dangerous glacial lakes within Bhutan, with an area of 4.3 km2 (NCHM, 2019), is


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: figure
Figure

Image /page/3/Figure/2 description: The image displays three maps labeled (a), (b), and (c), detailing a study area in Bhutan. Map (a) is an inset showing the location of the Punatsangchu Basin (shaded gray) and a smaller study basin (outlined in red) within Bhutan, which borders China and India. Map (b) is a topographic map of the study basin, with an elevation scale ranging from 1153 m to 7207 m and a distance scale up to 40 kilometers. Map (c) is the main, detailed map of the area. It includes a legend defining symbols for River, Glacial lake, Study Basin, Punatsangchu\_Basin, Settlement Points (circle), Gauging Station (green square), and Power Plant (green triangle). This map shows the Phochhu river and its tributaries, the Mochhu and Dangchhu. Key locations identified include the glacial lakes Thorthomi Lake and Luggye Lake, and settlement points such as Lhedi, Thanza, Dangsa, Samdingkha, Punakha Dzong, Khuruthang, Jagathang, and Bajo. It also marks the WangdiRapid Station (a gauging station), two hydropower plants under construction (PHPA-I & II), and the confluence points of the Phochhu with the Mochhu and Dangchhu rivers. The map indicates the flow direction of the Phochhu river and labels the administrative regions of GASA, PUNAKHA, and WANGDUE.


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: figure
Figure: Figure 2. Map of the study area. (a) A Bhutan map showing rivers and river basins (the grey area shows the Punatsangchhu river basin). (b) The elevation distribution of the study area (the catchment area of PHPA-I and II excludes the Mochhu river basin). (c) Major settlement points within the study area.

**Figure 2.** Map of the study area. (a) A Bhutan map showing rivers and river basins (the grey area shows the Punatsangchhu river basin). (b) The elevation distribution of the study area (the catchment area of PHPA-I and II excludes the Mochhu river basin). (c) Major settlement points within the study area.


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: text

located at the headwater of the Phochhu sub-basin at over 4440 m above sea level. The Thorthomi glacial lake is widely recognised as the likely consequence of climate warming and, since feeding glaciers terminating in the lake rapidly melt, is expanding each year. Based on a comprehensive analysis of cryospheric, geotechnical, and geomorphological factors, Rinzin et al. (2023) concluded that Thorthomi lake is highly susceptible to GLOF events.

The PRB consists of five administrative districts: Gasa, Punakha, Wangdue Phodrang, Dagana, and Tsirang. These districts constitute 16.6 % (735 533) of the total population of Bhutan (NSB, 2018). The Punakha and Wangdue Phodrang districts (Fig. 2) within the PRB are renowned as Bhutan's primary rice production regions, contributing 16 % and 11 %, respectively, to the nation's total rice output (NSB, 2021). The area is also rich in historical and cultural heritage, with notable landmarks such as Punakha Dzong, which served as the former capital of Bhutan. Fertile flood plains are located along the Phochhu and Punatsangchhu rivers, and the region encompasses settlements such as Samdingkha and Jagathang, together with major towns such as Khuruthang and Bajo. The floodplain of the Punatsangchhu river accommodates these settlements, while downstream, approximately 115 km away from Thorthomi lake, two significant


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: figure
Figure

Image /page/3/Figure/6 description: A topographic map showing four glacial lakes in a mountainous region. The lakes are labeled from left to right (west to east): Rapstreng Lake, Thorthomi Lake, Luggye Lake, and DrukChung Lake. A river, identified as 'Lake Outflow', flows along the southern side of the lakes. An arrow indicates the 'Flow Direction' is from east to west (right to left). A legend in the top right corner defines the symbols used: a blue shape for 'Glacial lake', a thin blue line for 'Lake Outflow', and a black dot for 'Lake outlet'. Each lake has a designated outlet marked on the map. In the bottom left, there is a scale bar indicating a length of 4 kilometers. A north arrow is located in the top left corner. The background of the map consists of gray contour lines representing the terrain.


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: figure
Figure: Figure 3. Four glacial lakes within the Lunana region (the Lunana complex).

**Figure 3.** Four glacial lakes within the Lunana region (the Lunana complex).


Document: 1 Introduction
Section: 2 Study area and GLOF events
Type: text

hydropower plants, PHPA-I and II, are currently under construction (see the bottom of Fig. 2c for locations of the two hydropower plants). Given the exposure of critical infrastructure and settlements to potential GLOFs from PDGLs, especially the Thorthomi glacial lake, an assessment of hazards within this area is of paramount importance.

The Luggye glacial lake is one of the PDGLs in Lunana, Bhutan's northern region. The lake is one of four glacial lakes in an area that spans a few kilometres (Fig. 3) and had an outburst in 1994. Although there is no detailed official documentation on the GLOF at the Luggye glacial lake, reports and articles describing the event do exist (e.g. Koike and Takenaka, 2012; Meyer et al., 2006; Richardson and Reynolds, 2000; Watanabe and Rothacher, 1996). The event was also documented in a technical report (Leber et al., 2000), when the Royal Government of Bhutan launched a major investigative project in 2000 to study the cause of the event.

The 1994 Luggye GLOF was a cascading phenomenon, where sudden drainage of the upstream Druk Chung glacial lake (Fig. 3) into Luggye lake increased hydrostatic pressure on the moraine dam of Luggye lake, releasing  $18 \times 10^6$  m3 of flood water (Leber et al., 2000). The 1994 Luggye GLOF claimed the lives of 21 people and inflicted major damage to infrastructure and downstream settlements; notably, the Punakha Dzong (monastery) suffered significant damage, although it is located 93 km downstream from the lake (Richardson and Reynolds, 2000; Watanabe and Rothacher, 1996). During this period, a peak flow rate of  $2539 \,\mathrm{m}^3 \,\mathrm{s}^{-1}$ was observed at the WangdiRapid gauging station, located 15 km downstream of Punakha Dzong (Fig. 2) and approximately 108 km downstream of the flood source (data from NCHM). Contributions from the Mochhu (96  $\mathrm{m}^3$  s-1 on 7 October 1994), Dangchhu basins (no gauging station in the basin), and other small tributaries to the peak flow rate should have been minor due to limited base flow during the season.

To estimate the breach outflow hydrograph, several studies have attempted to reconstruct the 1994 Luggye GLOF event (e.g. JICA, 2001; Koike and Takenaka, 2012; Meyer et al., 2006). Koike and Takenaka (2012) estimated that peak discharge from the Luggye lake breach ranged from 1800 to

 $2500 \,\mathrm{m}^3 \,\mathrm{s}^{-1}$ , depending on inflow conditions measured by Yamada et al. (2004).


Document: 1 Introduction
Section: 3 Materials and methods
Type: text

A schematic diagram showing input data, used models/methods, and outputs is provided in Fig. 4. We reconstructed the 1994 GLOF event to verify (1) a glacial lake geometry estimation model, (2) a dam breach model, (3) a digital elevation model and its error correction method, and (4) Manning's coefficient. Then, the same models were used to predict the potential risk caused by a Thorthomi GLOF.


Document: 1 Introduction
Section: 3 Materials and methods > 3.1 Uncertainty in GLOF bathymetry
Type: text

The volume and geometry of a glacial lake are regulating factors of the glacial lake outburst process. Glacial lakes are generally formed from a depression left behind by retreating glaciers, which, in most cases, are produced when a moraine is filled with meltwater. Depending on geomorphology, the presence of sediment, and glacial over-deepening capacity, formed glacial lakes can manifest specific lake bathymetry and influence glacial hydrology (Cook and Swift, 2012). Due to remote locations and high elevations, accessing and conducting field surveys to map glacial lake bathymetry is challenging.

Despite challenges, measurements of lake bathymetry are crucial for determining a lake's volume and surface area and are necessary for assessing potential flood volumes and the risk of GLOFs. In 2019, the National Centre for Hydrology and Meteorology (NCHM) conducted bathymetric surveys in 14 of the 25 identified potentially dangerous glacial lakes and mapped their maximum depth and volume. However, even though the Thorthomi glacial lake is considered to be a critical lake that could burst in the future, due to the difficulty associated with conducting a survey, the bathymetry of the Thorthomi glacial lake remains unknown. Since lake geometry is a crucial parameter for dam breach modelling and subsequent hydraulic routing, lake depth and volume needed to be estimated.

3 Materials and methods
3.1 Uncertainty in GLOF bathymetry