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Subject: Disaster Management

  • How common are cloudbursts in India?

    Why in the News?

    Flash floods triggered by a cloudburst struck Pahalgam in Anantnag on 12 July. Last week, the India Meteorological Department (IMD) rejected claims that cloudbursts caused the recent floods in Assam and Nagaland. The two events have renewed attention on the scientific definition of a cloudburst and its frequent misuse in public discourse.

    What counts as a cloudburst under the IMD’s definition?

    1. Threshold: The IMD defines a cloudburst as 10 centimetres or more of rainfall in an hour over a small area of around 20 to 30 square kilometres.
    2. Scale comparator: Indore receives about 1,062 millimetres of rain in an average year, so a single cloudburst can dump close to 10% of a full year’s rainfall in 60 minutes.
    3. Related category: Some scientists have proposed a mini cloudburst category for 5 centimetres of rain in an hour over the same area, since local topography can make even this devastating.

    How does a cloudburst form?

    1. Initial lift: Warm, moist air rises rapidly through convection, and in mountainous terrain this rise is intensified by orographic lifting, where monsoon winds are forced upward by steep slopes.
    2. Cloud growth: As the rising air cools, water vapour condenses into towering cumulonimbus clouds that can reach up to 15 kilometres in height.
    3. Suspension: Strong upward currents keep forming raindrops suspended in the cloud for longer instead of letting them fall immediately.
    4. Discharge: When the weight of accumulated water exceeds what the updraft can hold, or the updraft weakens, the suspended water falls in one release rather than as steady rain.

    How common are cloudbursts in India, and why are they hard to count?

    1. Historical count: Parliament was told in 2019 that the IMD recorded only around 30 cloudburst incidents between 1970 and 2016, a figure many experts consider an underestimate.
    2. Rising frequency: Global warming increases the amount of moisture the atmosphere can hold, making cloudbursts more frequent even though they remain rare compared with ordinary heavy rain.
    3. Monitoring gap: Most cloudbursts occur in remote, high altitude regions where rain gauges and weather stations are sparse, so an event even a few kilometres from a monitoring station may go officially unrecorded despite causing large scale destruction downstream.
    4. Regional concentration: Uttarakhand, Himachal Pradesh, and Jammu and Kashmir have reported a recent surge in events described locally as cloudbursts, particularly in July and August.

    Does the label obscure accountability for poor planning?

    1. Blame diffusion: Calling a heavy downpour a cloudburst turns it into a singular, unforeseeable act of nature, which is harder to do when the stated cause is heavy rain combined with poor drainage.
    2. Dharali precedent: During the 2025 Dharali floods in Uttarakhand, initial reports blamed a cloudburst, but meteorological data later showed the rainfall rate was well below the cloudburst threshold. The underlying causes were illegal construction on riverbeds, deforestation that left soil vulnerable to erosion, and the absence of drainage infrastructure along new all weather roads.
    3. Assam and Nagaland claims: The IMD last week rejected reports that cloudbursts caused recent floods in Assam and Nagaland, including the Upper Assam floods.
    4. Accountability questions avoided: Had the Dharali downpour genuinely been a cloudburst, officials could have avoided questions about why the state permitted construction in high risk zones and why early warning systems failed.

    Why are cloudbursts difficult to forecast?

    1. Model resolution: Weather models estimate average conditions across grid cells, while a cloudburst occurs over an area smaller than a single cell, so detecting one requires high resolution models needing computing power not always available.
    2. Speed of formation: Cloudbursts develop and strike quickly, unlike cyclones or monsoon systems that can be tracked for weeks, leaving forecasters far less data to work with.
    3. Terrain interference: Doppler weather radars emit and receive beams that mountains can block, creating blind spots in exactly the high altitude terrain where cloudbursts are most common.
    4. Sparse instrumentation: Rugged terrain also means fewer automatic weather stations, leaving fewer ground sensors to feed real time data into short term prediction.

    What is India doing to improve cloudburst forecasting?

    1. Nowcasting: The IMD is developing nowcasting technology to issue short term alerts every few hours rather than long range forecasts.
    2. Mission Mausam: Under the government’s Mission Mausam programme, India plans to more than double its radar network from about 40 radars currently and use artificial intelligence to better predict hyperlocal events.
    3. Persistent limits: Even with better technology, a cloudburst is expected to remain harder to predict than a typical rainstorm because of how localised and fast forming it is.

    Conclusion

    A cloudburst is a specific meteorological event defined by the IMD’s own rainfall threshold, not a synonym for any destructive downpour. Attributing flood damage to a cloudburst without checking recorded rainfall data lets authorities treat the disaster as an unforeseeable act of nature rather than examine illegal construction, deforestation and drainage failure. India’s forecasting improvements under Mission Mausam target the science of prediction, but they do not by themselves fix the planning failures the label has repeatedly been used to obscure.

    Back2Basics:

    Mission Mausam

    1. Nodal ministry: Ministry of Earth Sciences.
    2. Launch year: 2024.
    3. Aim: Improve weather and climate forecasting through expanded observation networks, high performance computing and artificial intelligence based prediction.
    4. Key features: Expansion of Doppler weather radar coverage, next generation satellites, and impact based forecasting for more precise, localised warnings.

    PYQ Relevance

    [UPSC 2024] What is the phenomenon of ‘cloudbursts’? Explain.

    Linkage: The PYQ explains cloudbursts, their causes, and forecasting challenges. It updates the topic with IMD clarifications, Mission Mausam, and disaster accountability.

  • Cloudbursts in India

    Why in News?

    Recent flash floods in Himalayan States have brought cloudbursts into focus. The IMD has clarified that many reported “cloudbursts” do not meet its scientific definition, highlighting the need for accurate terminology and better disaster planning.

    What is a Cloudburst?

    • According to the India Meteorological Department (IMD), a cloudburst is 100 mm (10 cm) or more rainfall in one hour over a 20 to 30 sq. km area.
    • Key Features
      • Highly localized and short-duration event.
      • Causes sudden flash floods and landslides due to rapid runoff.
      • Much rarer than normal heavy monsoon rainfall.
      • Mini-cloudburst (proposed): Some scientists suggest a category of 50 mm rainfall in one hour over the same area, as it can also cause severe damage.

    How Common are Cloudbursts in India?

    • Cloudbursts are rare, but their frequency is increasing due to global warming, as warmer air can hold more moisture.
    • IMD recorded around 30 cloudbursts between 1970 and 2016, though experts believe many events went unrecorded.
    • Most occur in remote Himalayan regions, where monitoring stations are sparse.
    • Frequently reported in Uttarakhand, Himachal Pradesh, Jammu & Kashmir, Assam, and the Northeast, especially during July-August.

    How Do Cloudbursts Form?

    Why are Cloudbursts Difficult to Forecast?

    • Highly localized, smaller than weather model grid sizes.
    • Develop rapidly, leaving very little lead time.
    • Mountains block Doppler Weather Radar signals, creating blind spots.
    • Limited Automatic Weather Stations (AWS) in high-altitude areas reduce real-time observations.
    • Hyperlocal prediction requires high-resolution models and massive computing power.

    What is India Doing?

    • IMD Nowcasting for short-term weather alerts.
    • Mission Mausam to strengthen hyperlocal forecasting.
    • Expansion of the Doppler Weather Radar (DWR) network.
    • Installation of more Automatic Weather Stations (AWS).
    • Use of Artificial Intelligence (AI) for improved weather prediction and early warnings.

    Challenges

    • Sparse observation network in mountainous terrain.
    • Radar blind spots due to topography.
    • Limited computing capacity for hyperlocal models.
    • Growing climate change-induced extreme rainfall.
    • Weak enforcement of land-use regulations.

    [2026] Which of the following statements with regard to India’s indigenous new high resolution weather model, the ‘Bharat Forecast System,’ is/are correct?
    1. Its objective is to generate forecasts at the Panchayats cluster level.
    2. It was developed by IIT Delhi.
    Select the answer using the code given below:

    [A] 1 only

    [B] 2 only

    [C] Both 1 and 2

    [D] Neither 1 nor 2

  • In Assam, floods shift course. State response is static.

    Why in the News

    Flooding is a chronic feature of Assam’s monsoon, but this year, Upper Assam districts far from the Brahmaputra’s main channel and without a history of severe floods, Sivasagar, Charaideo, Jorhat and Golaghat, have borne the brunt. More than 20 people died within 24 hours on Monday after a wall of water from Nagaland’s Mon district spilled into Assam over open terrain, and the State Government called the devastation unforeseeable.

    What made this year’s floods different from Assam’s usual monsoon pattern?

    1. Districts without flood history hit hardest: The state government has called the scale of devastation in Sivasagar, Charaideo, Jorhat and Golaghat “unprecedented.“
    2. Casualty toll: More than 20 people died within 24 hours on Monday after a wall of water from Nagaland’s Mon district spilled into Assam and surged over embankments.
    3. An unusual drainage path: The floodwater is draining into the Brahmaputra over open terrain rather than through the tributaries as usual.
    4. The government’s stated position: The Assam government told the state assembly that “no one could have been prepared” for the calamity.

    Why is the “unforeseeable calamity” explanation unconvincing?

    1. A known river behaviour: The floods’ trajectory is a fallout of Assam’s topography and the Brahmaputra’s well-documented tendency to shift course.
    2. Sediment deposition raises the riverbed: After entering the Assam valley near Pasighat in Arunachal Pradesh’s East Siang district, the sharp reduction in gradient slows the river and causes it to deposit sediment, raising the riverbed and reducing the channel’s flood capacity.
    3. Channel abandonment: The Brahmaputra periodically abandons old channels and carves new ones, making it impossible to confine the river within embankments permanently.
    4. A static strategy for a shifting river: Assam’s flood management strategy continues to rely primarily on embankments despite this known channel-shifting behaviour.

    What triggered the immediate disaster in Nagaland and Assam?

    1. Extreme localised rainfall: Mon district received more than one-third of its average July rainfall in about eight hours on Sunday.
    2. Saturated slopes: Hills in the region were already saturated from heavy rain earlier in the month.
    3. Landslides in Nagaland: The saturated slopes collapsed, triggering landslides that killed nine people in Nagaland.
    4. Resulting surge into Assam: The destruction that followed in Assam was a direct consequence of this upstream rainfall and landslide event.

    What institutional response does this demand?

    1. A shared-system approach needed: The situation underscores the need for an institutional mechanism that treats rivers as shared ecological systems across states, with timely warning and coordinated action.
    2. The Brahmaputra Board’s capacity gap: The Brahmaputra Board has long been hampered by staff shortages and inadequate technical capacity. (Brahmaputra Board is a statutory body set up under the Brahmaputra Board Act, 1980 under the Ministry of Jal Shakti, Department of Water Resources, River Development & Ganga Rejuvenation. The jurisdiction of the Brahmaputra Board includes both the Brahmaputra and Barak Valley and covers all the States of the North Eastern Region, including Sikkim and part of West Bengal, which fall under the Brahmaputra basin.)
    3. A call to reinvigorate the agency: With extreme weather becoming more frequent, the Centre and State Governments need to reinvigorate the Brahmaputra Board.

    Conclusion

    The Brahmaputra’s documented tendency to deposit sediment, raise its bed and shift channels, not an unforeseeable event, pushed this year’s floods into Upper Assam districts with no history of severe flooding. Assam’s embankment-only strategy cannot contain a river that periodically abandons its channels, and the underlying institutional gap, an understaffed, under-resourced Brahmaputra Board, must be addressed before climate change intensifies these ruptures further.

    PYQ Relevance

    [UPSC 2020] Account for the huge flooding of million cities in India including the smart ones like Hyderabad and Pune. Suggest lasting remedial measures.

    Linkage: The PYQ tests the geographical and anthropogenic causes of floods and the need for long-term flood management strategies. The Brahmaputra floods article extends this theme to riverine flooding. It shows that how geomorphological processes such as sediment deposition and channel migration, combined with extreme rainfall, demand basin-wide management rather than an embankment-centric approach.

  • [23rd July 2026] The Hindu OpED: Buried questions: On the Sikkim tunnel accident

    PYQ Relevance[UPSC 2016] The Himalayas are highly prone to landslides. Discuss the causes and suggest suitable measures of mitigation.
    Linkage: The PYQ examines the geological fragility of the Himalayas and the need for mitigation measures while undertaking developmental activities. The Teesta-VI blast highlights that infrastructure projects in the young and unstable Himalayan geology require rigorous geological investigations, continuous hazard monitoring, and strict compliance with environmental clearance conditions.

    Mentor’s Comment

    An explosion triggered by trapped methane in an NHPC (formerly National Hydroelectric Power Corporation) Limited tunnel at the Teesta Stage-VI hydroelectric project in Sikkim has killed at least 15 workers. What remains unresolved is not whether the hazard existed, but whether the environmental clearance conditions meant to guard against it were ever verified in practice.

    Why was gas in the Teesta-VI tunnel foreseeable rather than a surprise?

    1. Geological setting: The Teesta basin sits in a seismically active zone with young, heavily fractured rock capable of trapping compressed gas pockets laid down long ago.
    2. Known hazard type: Methane is a well-recognised hazard in underground excavation generally, not specific to this project.
    3. The real open question: What is unresolved is not whether gas could exist, but whether its risk was assessed and modelled during project planning, and whether detection and ventilation safeguards were functioning.

    What does the region’s recent history of underground disasters show?

    1. Meghalaya, February 2026: An explosion at an illegal coal mine killed about 30 workers.
    2. Uttarakhand, 2023: A road tunnel under construction collapsed, trapping 41 workers for 17 days before rescue.
    3. South Lhonak lake, October 2023: A glacial lake outburst flood destroyed the Teesta-III dam and killed more than 100 people downstream.
    4. Pattern, not exception: Together, these episodes show underground and Himalayan infrastructure work carries recurring risk, not isolated misfortune.

    What complicates accountability for Teesta-VI specifically?

    1. Change of developer: Teesta-VI was absorbed by the public-sector NHPC Limited after its original private developer, unable to afford escalating costs, went into insolvency.
    2. Carried-over clearance conditions: A change in developer partway through a project raises the question of whether environmental-clearance conditions were re-verified under the new operator.
    3. Internal inquiry is not an oversight: NHPC has announced its own investigation, but an internal inquiry by the project operator is not a substitute for independent verification of clearance compliance.

    What must happen once the emergency response ends?

    1. Immediate priority: Relief and rescue for workers still trapped must remain the first priority.
    2. No isolated-incident framing: The government must not treat the disaster as an isolated misfortune once the emergency passes.
    3. Independent review required: An independent review is needed to verify whether the environmental clearance conditions attached to Teesta-VI were strictly met in practice, not merely granted on paper.

    Conclusion

    The Teesta-VI blast is the latest in a pattern of underground and Himalayan project disasters recurring because environmental clearance compliance is not independently verified after approval. Once relief operations conclude, the government must order an independent review of whether the clearance conditions attached to Teesta-VI, and comparable Himalayan hydropower projects, were actually met in practice.

  • Landslides: The Need for Early Warning Systems

    Why in the News?

    Recent landslides across the Western Ghats and other parts of India have revived the debate on installing early warning systems (EWS) for landslides. The renewed discussion exposes a gap between what landslide-prediction technology has already proven capable of and the absence of any single, scaled system deploying it nationally.

    Why has landslide prediction returned to the policy conversation, and does the science actually work?

    1. Trigger: Recent landslides in the Western Ghats and other parts of India reignited discussion on installing EWS for such events.
    2. Proven feasibility: Landslides can be predicted in high-risk zones. The 2024 Wayanad landslide killed more than 300 people, illustrating the human cost when prediction is absent.
    3. Working precedent: Two weeks before the Wayanad disaster, landslides in Munnar caused no fatalities. The Idukki district administration evacuated residents on the advice of an Amrita University research team, led by Maneesha Vinodini Ramesh, that was testing an EWS.
    4. Global validation: EWS already operates effectively in multiple countries, establishing that the underlying approach is proven rather than experimental.

    What are the two competing methodologies India is currently developing for landslide early warning?

    1. Amrita University approach: Deploys a network of on-site sensors, tilt meters, pressure gauges, accelerometers, at high-risk slopes to measure vibration and ground movement.
    2. Threshold-based alerts: When sensor readings cross well-defined thresholds, an automated warning is issued, allowing the administration to act.
    3. IIT Mandi approach: Professor Dericks Praise Shukla’s team uses probabilistic forecasting instead of physical sensors, currently being validated against ongoing landslide events in the Himalayan region.
    4. Satellite-based mapping: The IIT Mandi team has mapped vulnerable spots across the Himalayan region using a satellite-based database of past landslide events.
    5. Multi-factor modelling: The probabilistic model factors in localised rainfall forecasts along with soil conditions, rock stability, extent of slope, and population density.

    Why does neither current methodology, on its own, deliver a complete early warning solution?

    1. Sensor method’s blind spot: Amrita’s sensor network reports data only for the specific slope where instruments are installed. Neighbouring slopes remain unmonitored, even though landslides are highly localised events.
    2. Rainfall model’s lead-time constraint: Shukla’s probabilistic model depends on rainfall forecasts, but highly localised forecasts are currently available only for the day of the event or one day earlier, giving very little lead time.
    3. Trade-off exposed: The sensor method provides adequate lead time but incomplete geographic coverage. The probabilistic method provides wider coverage but insufficient lead time.
    4. Scale limitation: Both methods remain validated only at pilot or regional scale. Neither is currently integrated into a single nationwide operational system.

    What must change before India moves from pilot-scale projects to a comprehensive national system?

    1. Precondition 1: high-risk zone identification: A comprehensive system first requires identifying high-risk areas where landslides are frequent, before sensors or models can be meaningfully deployed at scale.
    2. Risk zones already flagged: Shukla identifies the north-western Himalayan region and parts of Manipur and Mizoram as highly vulnerable. Sikkim is relatively less vulnerable due to a less dense road network, which implies greater slope stability.
    3. Precondition 2: higher-resolution rainfall forecasting: The probabilistic method’s lead-time limitation can only be resolved once the India Meteorological Department develops higher-resolution rainfall forecasts, which is currently in progress.
    4. Timeline and resourcing: A comprehensive and effective landslide EWS can be built in about two years if resources and effort are properly dedicated to it, according to Shukla.
    5. Sequencing: The stated roadmap identifies high-risk zones nationally first, and installs sensors at selected sites only afterward, mapping precedes instrumentation, not the reverse.

    Conclusion

    Landslide early warning technology is scientifically proven and has already prevented casualties in India, as seen in Munnar in 2024. No standardised national system exists, however; current efforts are split between a sensor-based method and a rainfall-probability-based method, each constrained by a different limitation, localised coverage in one case, short lead time in the other. Scaling to a comprehensive national system depends on two preconditions currently absent: systematic identification of high-risk zones across India, and higher-resolution rainfall forecasting infrastructure from the India Meteorological Department. Until both are in place, early warning capability will remain confined to isolated pilot projects rather than a nationwide shield.

    PYQ Relevance

    [UPSC 2021] Describe the various causes and the effects of landslides. Mention the important components of the National Landslide Risk Management Strategy.

    Linkage: The PYQ examines India’s institutional approach to landslide risk reduction through the National Landslide Risk Management Strategy (NLRMS) and disaster preparedness. The article directly complements this PYQ by highlighting early warning systems, sensor networks, vulnerability mapping, localized rainfall forecasting, and timely evacuation, all of which are core components of proactive landslide risk management envisaged under the NLRMS.

  • How important are vulnerability and risk assessment for pre-disaster management. As an administrator ,what are key areas that you would focus in a disaster management

  • Drought has been recognised as a disaster in view of its party expense, temporal duration, slow onset and lasting effect on various vulnerable sections. With a focus on the September 2010 guidelines from the National disaster management authority, discuss the mechanism for preparedness to deal with the El Nino and La Nina fallouts in India.

  • The frequency of earthquakes appears to have increased in the Indian subcontinent. However, India’s preparedness for mitigating their impact has significant gaps. Discuss various aspects.

  • The frequency of urban floods due to high intensity rainfall is increasing over the years. Discussing the reasons for urban floods. highlight the mechanisms for preparedness to reduce the risk during such events.

  • With reference to National Disaster Management Authority (NDMA) guidelines, discuss the measures to be adopted to mitigate the impact of the recent incidents of cloudbursts in many places of Uttarakhand.