Avalanche Risks in Himalayan States

1. Fundamentals of Snow Avalanches: Geomorphology and Mechanics

1.1 Definition and Thermodynamic Mechanics

An avalanche is fundamentally a mass movement hazard characterized by the rapid, gravity-driven descent of snow, ice, and entrained geological debris down a mountainous slope. This geomorphic phenomenon manifests when the gravitational shear stress acting upon a snowpack exceeds the frictional resistance and internal cohesion binding the snow to the slope or to underlying snow layers. The underlying mechanics are deeply rooted in the thermodynamic metamorphism of snow. Snow is a thermodynamically highly unstable material; its constituent crystals continuously alter their size, shape, and inter-granular bonding to attain an equilibrium state. This ongoing metamorphism is dictated by ambient temperatures, temperature gradients within the snowpack, and atmospheric moisture. When these metamorphic processes lead to the formation of a weak layer—such as faceted crystals or depth hoar—beneath a cohesive, dense upper slab of snow, the slope crosses a critical threshold, priming it for a catastrophic release upon the introduction of a trigger.

1.2 Comprehensive Typology of Avalanches

The classification of avalanches is a prerequisite for accurate hazard mapping, scientific simulation, and the implementation of mitigation engineering. Avalanches are systematically categorized based on their genesis, physical composition, and dynamic behavior:

1.3 Causative Factors and Trigger Mechanisms

The genesis of an avalanche requires the spatial and temporal convergence of specific topographical features, meteorological conditions, and triggering events.
The primary topographical variable governing avalanche initiation is the slope angle. Scientific consensus indicates that avalanches predominantly occur on slopes angled between 30° and 45°. Slopes shallower than 30° generally lack the gravitational component necessary to overcome static friction, whereas slopes steeper than 45° tend to sluff off snow continuously, precluding the accumulation of massive, dangerous snow slabs. Furthermore, slope morphometry—such as convexity, which places the snowpack under tension—and leeward orientation, which acts as a catchment for wind-transported snow, heavily exacerbate instability.
Meteorological drivers are equally critical. The rapid accumulation of heavy snowfall introduces sudden, immense static weight, stressing the underlying snowpack faster than it can adapt and stabilize. Wind velocity redistributes this snow, creating dense, overhanging snowdrifts known as cornices on leeward ridges. Furthermore, temperature fluctuations dictate the strength of the snowpack. Rapid warming or the onset of freeze-thaw cycles destroys the crystalline bonds between layers, frequently triggering wet snow avalanches during the spring ablation period.
Beyond natural meteorological processes, anthropogenic and external triggers are increasingly responsible for avalanche releases. Human activities, including off-piste winter sports, large-scale deforestation, heavy vehicular vibrations, and military operations (such as artillery fire and explosive detonations), generate acoustic and kinetic shocks that shatter weak layers within the snowpack. Additionally, the high seismicity of the Himalayan tectonic zones provides a profound natural kinetic trigger capable of dislodging otherwise stable snow masses across wide regions.

2. Hazard Zonation and Vulnerability Assessment Framework

To effectively regulate regional planning, mitigate infrastructure damage, and protect human life, it is imperative to scientifically demarcate avalanche-prone regions. The National Disaster Management Authority (NDMA) outlines a stringent framework for classifying hazard zones based on the historical frequency of avalanches and the calculated kinetic impact pressure they exert.

2.1 State-Specific Vulnerability Hotspots in the Indian Himalayas

The Indian Himalayan Region (IHR) is globally recognized as an extreme avalanche environment due to its young, seismically active geology, steep morphometry, and intense winter precipitation. The Western Himalayas receive significantly higher winter precipitation via Western Disturbances compared to the Eastern Himalayas, resulting in a disproportionately high frequency of snow avalanches in specific northern states. High Mountain Asia (HMA) as a whole suffers immense casualties, with historical data indicating that Afghanistan has recorded the highest fatalities (1,057), closely followed by India (952) and Nepal (508).
Within India, the vulnerability is concentrated in distinct geographic nodes. In Jammu & Kashmir and Ladakh, the higher reaches of the Kashmir Valley, the Gurez Sector, Zoji La Pass, Kargil, and the Siachen Glacier represent extreme hazard zones. The Srinagar-Leh Highway (NH-1) faces frequent blockades near Zoji La, severing vital strategic and civilian connectivity. In Himachal Pradesh, the districts of Lahaul & Spiti, Kinnaur, Kullu, and Chamba are highly susceptible. Critical corridors such as the Rohtang Pass historically faced insurmountable avalanche disruptions until the recent construction of protective tunnels. Uttarakhand is similarly vulnerable, particularly in areas surrounding the Mana Pass, Chamoli, and Tehri Garhwal, where steep Garhwal Himalayan slopes combine with intense localized snowfall to create sudden catastrophic events.

2.2 The Combined Avalanche Vulnerability Index (CAVI)

To move beyond purely topographical hazard mapping, a seminal 2025 study conducted by researchers at the Indian Institute of Science Education and Research (IISER), Bhopal, developed the Combined Avalanche Vulnerability Index (CAVI). This advanced framework assesses district-level vulnerability in the Indian Western Himalayas through a multi-aggregation approach that evaluates exposure, sensitivity, and adaptive capacity.
Exposure in this model is driven by meteorological parameters, including extreme rainfall, snow depth, and temperature fluctuations. Sensitivity is influenced by the physical topography (slope gradients) interacting with demographic density. Crucially, the CAVI model integrates Adaptive Capacity, determined by socio-economic resilience factors such as literacy rates, healthcare accessibility, forest cover density, and the structural integrity of local housing (e.g., prevalence of concrete walls).
The application of the CAVI framework revealed profound insights. The district of Lahaul and Spiti in Himachal Pradesh ranks as the most exposed and overall most vulnerable district to snow avalanches in the studied region. Shimla, also in Himachal Pradesh, is identified as the most sensitive district, primarily due to its high population density overlapping with vulnerable slopes. In Uttarakhand, Chamoli represents the highest overall avalanche vulnerability, while Rudraprayag possesses the lowest adaptive capacity (scoring 0.3), indicating a severe inability to mitigate and recover from avalanche impacts.

3. Analytical Aspects: Climate Change, Anthropogenic Pressures, and Cascading Hazards

The contemporary understanding of snow avalanches necessitates viewing them not merely as isolated meteorological anomalies, but as complex socio-environmental events driven by the intersection of anthropogenic climate change, massive infrastructure expansion, and geopolitical border imperatives.

3.1 Climate Change and Cryosphere Destabilization

The Himalayan cryosphere is acutely sensitive to global warming, experiencing regional temperature increases that outpace global averages. This warming profoundly destabilizes historical snowpack dynamics. Elevated temperatures increase the frequency and intensity of freeze-thaw cycles, which fundamentally weaken the bonding between internal snow layers and create deep, persistent weak layers. Concurrently, shifting precipitation patterns are resulting in unseasonal, concentrated, and highly intense heavy snowfall events that rapidly overload unstable slopes, subverting historical avalanche predictability.

3.1.1 The Emerging Threat of "Hanging Glaciers"

A groundbreaking April 2026 study published in the journal npj Natural Hazards by a consortium of Indian scientists (including IISc, IIT-Bhubaneswar, and DRDO) illuminated a severe and historically overlooked consequence of climate change: the rapid proliferation of "hanging glaciers". As massive valley glaciers retreat and thin due to sustained warming, large tributary blocks of ice become detached from the main glacial bodies. These fragmented ice masses are left suspended precariously on steep mountain walls, completely lacking structural support.
The researchers conducted a comprehensive basin-scale inventory and identified 219 highly unstable hanging glaciers in the Alaknanda basin of Uttarakhand alone, covering approximately 71.7 square kilometers and containing an estimated ice volume of 2.39 cubic kilometers. These suspended ice masses are critically unstable and prone to sudden detachment, triggering massive ice and rock avalanches. Advanced avalanche simulations indicate that potential runouts from these detachments could generate flow heights exceeding 50 meters, threatening critical infrastructure and dense pilgrimage settlements in the Badrinath-Mana sector. Alarmingly, the study projects that the built-up land area exposed to these specific avalanche hazards will increase by 120% between 2000 and 2030, accompanied by a 17% rise in the exposed population.

3.2 Compound Disaster Risks (Cascading Hazards)

Avalanches in the Indian Himalayas increasingly function as the primary trigger in a chain reaction of cascading, multi-hazard disasters. When a massive avalanche containing millions of tons of snow, ice, and moraine debris descends into a narrow, highly confined river valley, it frequently dams the river, creating a temporary, highly unstable artificial lake. The inevitable catastrophic breaching of this dam results in a Glacial Lake Outburst Flood (GLOF) or a massive downstream flash flood. This compound disaster risks (cascading hazards) paradigm necessitates a fundamental shift in disaster management policy—transitioning from treating avalanches solely as localized slope hazards to recognizing them as potent instigators of basin-wide hydrological catastrophes.

3.3 Anthropogenic Pressures and Border Infrastructure

Geopolitical realities in the Indian subcontinent dictate the maintenance of extensive military deployments and the establishment of all-weather connectivity along the Line of Control (LoC) and the Line of Actual Control (LAC). These strategic imperatives have driven the rapid, large-scale construction of highways, tunnels, and hydropower projects in some of the most fragile, avalanche-prone terrains on Earth.
Activities such as aggressive road-cutting alter the natural repose angle of mountain slopes, rendering them hyper-sensitive to failure. Associated deforestation removes the natural biomechanical anchoring provided by deep root systems, further escalating slope vulnerability. Simultaneously, the aggressive promotion of pilgrimage tourism, notably the Char Dham project, has led to an explosion of built-up land area and heavy vehicular movement in high-risk zones, drastically increasing human exposure to avalanche pathways.

4. Institutional and Technological Disaster Management Framework

Recognizing the escalating threat to civilian life and strategic military assets, India has established a robust, multi-tiered institutional and technological framework to forecast and manage avalanche risks. This framework is orchestrated predominantly by the National Disaster Management Authority (NDMA) and the Defence Research and Development Organisation (DRDO).

4.1 NDMA Guidelines on Landslides and Snow Avalanches (2009)

The NDMA formalized a comprehensive disaster management strategy in its 2009 national guidelines. The core mission of this policy is to minimize vulnerability through institutionalized hazard mitigation efforts at both the national and state levels. Key directives include the systematic macro and meso-scale hazard zonation mapping of avalanche-prone regions to rigorously regulate infrastructure development. The guidelines mandate the execution of pilot projects to establish pace-setter instrument-based early warning systems (EWS). Furthermore, the NDMA emphasizes capacity building, demanding the enhancement of technical education, targeted training for professionals, and the generation of widespread public awareness regarding snow avalanche survival. The document also advocates for the establishment of an autonomous national centre dedicated to landslide and avalanche research to centralize data, standardize studies, and formulate response protocols.

4.2 The Role of DGRE (DRDO) in Avalanche Forecasting

The Defence Geoinformatics Research Establishment (DGRE), headquartered in Chandigarh, serves as the premier national nodal agency for mountain geohazard mapping, monitoring, and operational avalanche forecasting. Established in November 2020 through the strategic merger of the Snow and Avalanche Study Establishment (SASE) and the Defence Terrain Research Laboratory (DTRL), DGRE's primary mandate is ensuring the safe mobility of the Indian Armed Forces in snow-bound regions, while concurrently providing vital forecasting services to civilian populations.
To execute this mandate, DGRE relies on a sophisticated technological infrastructure. It maintains an expansive network comprising 72 manual Snow Meteorological Observatories and hundreds of Automatic Weather Stations (AWS) deployed strategically across the Northwest, Central, and Northeast Himalayas. These stations transmit real-time, high-fidelity data on snow depth, temperature gradients, and wind velocity at hourly intervals. In a major technological leap, DGRE installed India's first avalanche monitoring radar in North Sikkim, a system capable of detecting the initiation of an avalanche within three seconds of its trigger, allowing for immediate localized alerts.
DGRE's forecasting capability is underpinned by highly advanced physical and statistical predictive modeling. The establishment utilizes the SNOWPACK model, which computationally simulates the complex thermodynamic evolution and stratigraphy of snow layers to identify hidden weak interfaces. Furthermore, DGRE has developed HIM-STRAT, an Artificial Neural Network (ANN)-based model that simulates critical snowpack parameters—such as shear strength and RAM hardness—using manually observed weather data to predict avalanche hazards. For meteorological predictions, DGRE employs a Hidden Markov Model (HMM) capable of forecasting quantitative snowfall and subsequent avalanche danger levels up to two days in advance across the Pir-Panjal and Great Himalayan ranges. These internal models are fed by high-resolution global and regional weather forecasts provided daily by the National Centre for Medium Range Weather Forecasting (NCMRWF) and the Indian Meteorological Department (IMD).

4.3 The Avalanche Warning Bulletin and Dissemination

Based on the synthesis of real-time sensor data and predictive modeling, DGRE issues regular, operational Avalanche Warning Bulletins. These bulletins utilize a standardized, color-coded scale to clearly communicate danger levels to military units and civilian authorities:To ensure these critical warnings reach the last mile, the government has integrated avalanche alerts into the Common Alerting Protocol (CAP) based Integrated Alert System. This system allows for the dissemination of geo-targeted early warnings directly to citizens' mobile devices via SMS, cell broadcast, and satellite receivers (GAGAN & NavIC).

5. Mitigation Strategies: Structural and Non-Structural Paradigms

Effective avalanche risk reduction relies on a synergistic combination of highly engineered structural defenses designed to protect critical assets, and non-structural interventions focused on spatial avoidance, ecological stabilization, and early warning preparedness.

5.1 Structural Measures (Engineering Interventions)

Structural measures involve the physical modification of the terrain or the erection of heavily engineered barriers to prevent avalanche initiation, deflect moving snow mass, or completely insulate infrastructure from the hazard.
Avalanche Protection Tunnels and Galleries: The most definitive and absolute structural solution for highway safety is tunneling beneath avalanche formation zones. The Atal Tunnel (which bypasses the notoriously avalanche-prone Rohtang Pass in Himachal Pradesh) and the under-construction Zojila Tunnel (connecting Kashmir to Ladakh) are premier examples of mega-infrastructure designed to provide all-weather, year-round connectivity entirely insulated from surface avalanches. Other notable examples include the Sela, Nechiphu, and Chamba tunnels constructed by the Border Roads Organisation (BRO). For areas where tunneling is geologically unfeasible, heavily reinforced concrete avalanche galleries are constructed over highways, allowing avalanche debris to safely pass over the roof of the road.
Snow ErdoX Systems: A modern, highly effective mitigation technology increasingly deployed by organizations like the BRO. Snow ErdoX Systems (Umbrella Barriers) are advanced, self-stabilizing, pyramid-shaped metallic structures. They are designed to be lightweight, easy to transport to extreme high altitudes, and quick to install using deep soil anchors (e.g., SDA-32mm). Installed in multiple contiguous lines across the formation zones of steep slopes (such as the implementations near the Atal Tunnel's South Portal), these structures physically retain the accumulated snowpack, thereby preventing the initial fracture and slide.
Slope Modification and Static Barriers: Traditional engineering approaches include stepped terraces, which artificially reduce the effective slope angle and divide the snow cover, preventing massive continuous slides. Avalanche control piles, typically driven into the slope at 5-meter intervals, and suspended snow fences break wind momentum and limit snow accumulation in critical starting zones. Additionally, blower and collector snow fences are erected on ridge lines to prevent the formation of dangerous snow cornices. In the run-out zones, massive earthen or concrete avalanche diversion dams are constructed to physically deflect the kinetic flow of an avalanche away from vulnerable civilian settlements or military installations.
Artificial Triggering: In highly controlled environments, defense personnel or trained technicians utilize explosives or specialized artillery fire to prematurely trigger small avalanches. This proactive measure forces the snow to release before it can accumulate to catastrophic, unmanageable volumes.

5.2 Non-Structural Measures

Non-structural measures focus on policy enforcement, ecological restoration, and human behavior modification to minimize exposure and vulnerability.
Afforestation (Avalanche Prevention Forests): The targeted high-altitude planting of deep-rooted, cold-resistant tree species acts as a highly effective natural biomechanical anchor. A dense forest canopy intercepts snowfall, alters wind patterns, and drastically increases overall slope stability, effectively breaking the momentum of small slides before they propagate.
Hazard Zonation and Land Use Planning: Strictly enforcing NDMA guidelines by integrating hazard maps into municipal planning. This involves prohibiting the construction of civilian housing, military barracks, or tourism resorts in designated Red Zones, and ensuring that any development in Blue Zones adheres to rigorous structural safety codes.
Capacity Building and Community Preparedness: Training local populations, high-altitude trekking guides, and military personnel in basic rescue protocols is paramount. Personnel operating in hazard zones must be equipped with Avalanche Victim Detectors (AVDs), avalanche cords, and trained in rapid probing and digging techniques. Education emphasizes that time is the most critical factor in an avalanche rescue; survival chances plummet sharply 15 minutes after burial due to asphyxiation and trauma.

6. Current Affairs and Recent Case Studies

Analyzing recent avalanche disasters provides critical empirical insights into changing hazard profiles and the efficacy of modern mitigation and rescue operations in the Himalayas.

6.1 Mana Village Avalanche, Uttarakhand (February 2025)

In late February 2025, a massive avalanche struck a BRO construction camp near Mana Village Avalanche, Uttarakhand (February 2025), situated near the Indo-Tibetan border. Triggered by intense blizzard conditions and heavy snowfall over the preceding two days, the avalanche buried over 50 workers beneath tons of snow and debris at an altitude exceeding 3,200 meters. Analytical Takeaways: The incident showcased the life-saving potential of robust infrastructure. The remarkably high survival rate (46 rescued, 8 fatalities) was directly attributed to the workers residing in heavily reinforced steel shipping containers rather than traditional tents. Despite the containers being displaced and partially crushed by the immense kinetic force, they maintained sufficient structural integrity to prevent fatal crushing and suffocation. Furthermore, the Indian Army's rapid deployment of drone-based detection systems and avalanche rescue dogs facilitated a marathon 60-hour rescue operation in severe sub-zero (-12°C) conditions, highlighting the advancement in military rescue capabilities.

6.2 Draupadi ka Danda-II Disaster (October 2022)

A group comprising 41 individuals (34 trainees and 7 instructors) from the Nehru Institute of Mountaineering was struck by a devastating avalanche in the Gangotri range of the Garhwal Himalayas. The group was returning from the 5,670-meter peak when the avalanche hit, resulting in severe casualties (reportedly up to 29 fatalities) and marking the Draupadi ka Danda-II Disaster (October 2022) as one of the deadliest single events in Indian mountaineering history. This tragedy underscored the inherent, unpredictable risks of high-altitude human activity even outside of peak winter months, necessitating stricter protocols for civilian mountaineering expeditions.

6.3 Chamoli Disaster (February 2021)

This event serves as the ultimate contemporary example of a cascading, compound disaster. A massive chunk of a hanging glacier detached from a steep slope in the Nanda Devi biosphere, triggering a massive ice and rock avalanche. The kinetic energy of the Chamoli Disaster (February 2021) plunging into the Rishiganga river instantly mobilized water, mud, and debris into a catastrophic flash flood (functioning as a GLOF). This debris flow obliterated the Tapovan-Vishnugad and Rishi Ganga hydel projects, resulting in over 200 deaths and missing persons, highlighting the severe vulnerability of hydropower infrastructure to upstream cryosphere hazards.

6.4 Historical Context (Lahaul 1979 & Gurez 2017)

The historical record is replete with mass casualty events that shaped current policy. In 1979, the Lahaul Valley experienced a catastrophic series of avalanches that razed entire villages (such as Warring and Gardung) and claimed approximately 200 lives across the district, fundamentally demonstrating the extreme vulnerability of the region. More recently, the Gurez avalanche series in January 2017 claimed 24 lives, including 20 soldiers, highlighting the persistent threat to strategic military deployments despite modern forecasting.

7. Memory Tips for Aspirants

To effectively retain and recall the complexities of Avalanche Disasters for the UPSC Mains and Prelims examinations, candidates are advised to utilize the following mnemonic structures:

• Types of Avalanches (S-G-L-O-W-P):
  • Slab (Most Deadly, internal cohesion fractures).
  • Gliding (Smooth slide over bedrock, preceded by glide cracks).
  • Loose Snow (Point origin, spreads wide, lacks cohesion).
  • Ice (O) (Hanging Glaciers detaching).
  • Wet Snow (Meltwater percolation, highly dense debris).
  • Powder (Aerosol suspension, high aerodynamic speed).
• Causes of Avalanches (S-T-E-W):
  • Steep Slopes (30° to 45° is the critical danger zone).
  • Temperature Fluctuations (Freeze-thaw cycles weaken inter-granular bonds).
  • Earthquakes & Explosions (Seismic and anthropogenic triggers).
  • Weather (Heavy snowfall and wind cornices).
• NDMA Hazard Zones (Think Traffic Lights):
  • Red: STOP. No construction. >3 Tonnes/sqm impact pressure.
  • Blue: CAUTION. Regulated construction with safe design. <3 Tonnes/sqm.
  • Yellow: GO (with awareness). Low/occasional hazard.
• DGRE Warning Colors (G-Y-O-B):
  • Green (Safe), Yellow (Partly Unsafe), Orange (Unsafe), Black (Extremely Unsafe - Mandatory Evacuation).
• CAVI Vulnerability Hotspots (The "L-S-R" Rule from IISER Bhopal):
  • Lahaul & Spiti (Most Exposed and overall most vulnerable).
  • Shimla (Most Sensitive due to dense population).
  • Rudraprayag (Least Adaptive Capacity).

8. Executive Summary

Snow avalanches represent a formidable, recurring geohazard in the Indian Himalayan Region (IHR), driven by a complex, dynamic interplay of steep topography, intense winter meteorology, and thermodynamic instability within the snowpack. While traditionally viewed as isolated natural events affecting high-altitude military outposts or specialized mountaineers, avalanches have evolved into a major socio-economic threat. This evolution is propelled by rapid infrastructure expansion, strategic border road construction, and demographic shifts into fragile, historically undisturbed ecosystems.
The threat matrix is currently being fundamentally altered by anthropogenic climate change. As global warming destabilizes the cryosphere, phenomena such as "hanging glaciers" are proliferating. These suspended, structurally unsupported ice masses pose severe risks of catastrophic ice avalanches and subsequent downstream flash floods, evidenced by recent discoveries of 219 unstable glacial masses in the Alaknanda basin alone. Consequently, avalanches can no longer be managed in isolation; they must be viewed as potential catalysts for devastating compound, basin-wide disasters. The Combined Avalanche Vulnerability Index (CAVI) further illustrates that disaster vulnerability is a product of not just environmental exposure, but also socio-economic adaptive capacity, placing regions like Lahaul & Spiti and Chamoli at extreme, systemic risk.
To counter these escalating threats, India has established a multi-pronged institutional and mitigation framework. Guided by NDMA protocols, the Defence Geoinformatics Research Establishment (DGRE) leverages cutting-edge technology—ranging from Avalanche Monitoring Radars and Automatic Weather Stations to advanced machine-learning predictive models (HIM-STRAT, SNOWPACK, and Hidden Markov Models)—to provide critical, actionable early warnings. On the ground, the paradigm has shifted toward robust structural engineering, utilizing modern interventions such as flexible Snow ErdoX barriers, avalanche galleries, and massive bypass infrastructure like the Atal and Zojila tunnels. Moving forward, the synthesis of precise real-time forecasting, strict adherence to hazard zonation land-use policies, and the rapid deployment of Common Alerting Protocols (CAP) will be imperative to insulating the Himalayan states from the devastating impacts of snow avalanches.

9. Rapid Recall Bullet Points for Preliminary Examination

• Definition: Rapid downhill flow of snow, ice, and debris triggered when gravitational shear stress overcomes slope friction and snowpack cohesion.
• Most Dangerous Angle: Avalanches predominantly initiate on slope angles between 30° and 45°; steeper slopes sluff snow continuously, shallower slopes lack gravitational force.
• Deadliest Type: Slab Avalanches (cohesive plates of snow sliding off weak underlying layers) cause the vast majority of human fatalities.
• NDMA Zonation Threshold: The dividing metric between Red Zones (no construction) and Blue Zones (regulated construction) is a kinetic impact pressure of 3 tonnes per square metre.
• Nodal Forecasting Agency: DGRE (Defence Geoinformatics Research Establishment), formed in November 2020 under DRDO (merger of SASE and DTRL), headquartered in Chandigarh.
• Avalanche Danger Scale (DGRE): 1-Green (Safe), 2-Yellow (Partly Unsafe), 3-Orange (Unsafe), 4-Black (Extremely Unsafe).
• Predictive Models: DGRE utilizes SNOWPACK (thermodynamic simulation), HIM-STRAT (Artificial Neural Network for shear strength), and Hidden Markov Models (HMM) for advance snowfall prediction.
• Technological Milestones: India's first Avalanche Monitoring Radar is installed in North Sikkim, capable of detecting avalanches within 3 seconds of initiation.
• CAVI Index (IISER Bhopal): Measures Combined Avalanche Vulnerability Index. Lahaul and Spiti (HP) is the most vulnerable district overall; Chamoli is the most vulnerable in Uttarakhand.
• Recent Discoveries (2026): 219 unstable "Hanging Glaciers" identified in the Alaknanda Basin (Uttarakhand), posing extreme risks of compound cascading disasters.
• Modern Mitigation Structure: Snow ErdoX – advanced, flexible, pyramid-shaped metallic umbrella barriers deployed by BRO (e.g., near Atal Tunnel) to stabilize snow accumulation and prevent slab fractures.
• Current Affairs Disasters: 2025 Mana Village avalanche (survival linked to reinforced metal container housing); 2021 Chamoli disaster (ice avalanche cascaded into a flash flood/GLOF).
• Key Tunnels for Mitigation: Atal Tunnel (bypasses Rohtang Pass), Zojila Tunnel (bypasses Zoji La), and Sela/Nechiphu Tunnels (Arunachal Pradesh), providing avalanche-proof, all-weather connectivity.
• Alerting Technology: Dissemination of warnings is officially integrated into the Common Alerting Protocol (CAP) for geo-targeted SMS, cell broadcasts, and NavIC satellite receivers.