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GS Paper: GS1

  • 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.

  • Outdated contraception, early conception: Counting the babies that India didn’t plan for

    Why in the News

    India’s total fertility rate has fallen to the replacement level of about two children per woman, a figure widely read as proof the country has completed its demographic transition. This headline number conceals a persistent gap between how many children women actually want and how many they have, meaning India’s fertility decline is a policy problem rather than a solved story.

    What is the difference between the Total Fertility Rate and the Wanted Fertility Rate?

    1. Total Fertility Rate (TFR): TFR is the average number of births per woman across her reproductive years, counting all births including those women did not plan or want.
    2. Wanted Fertility Rate: This counts only births that match what women say they intended, revealing their actual preferred family size.
    3. The national gap: Nationally, women have an average of 2.0 children while their desired family size is about 1.6, a gap of 0.4 children per woman.
    4. States with the widest gap: Eight states, Uttar Pradesh, Bihar, Jharkhand, Rajasthan, Madhya Pradesh, Chhattisgarh, Assam and Haryana, have a gap of more than 0.3 children per woman.

    Why has India reached low fertility despite near-universal marriage?

    1. Marriage pattern: Only about 1% of women remain never married by ages 45 to 49, and the median age at first birth is 21.2 years, unlike most low-fertility countries where late marriage drives the decline.
    2. Sterilisation-led control: Indian women largely control fertility by having children, reaching their desired family size, and then permanently stopping through sterilisation, rather than through methods that space births.
    3. Missing spacing tools: Tools that help young couples delay a first birth or space children are largely missing, so unintended pregnancies cluster in the early years of marriage among the youngest women.
    4. Health consequence: This pattern is also reflected in relatively poor maternal and child health outcomes.

    Does India’s low fertility number hide a larger unmet need than it appears?

    1. Informed choice gap: Informed choice around sterilisation remains partial, with many women undergoing the procedure without fully informed consent. When these women are counted alongside those with unmet contraceptive needs, India’s “unwanted family planning” problem appears much larger than TFR figures suggest.
    2. Son preference inflation: In several states, families do not stop having children after one or two. In fact they continue until they have a son, meaning a disproportionate share of historically recorded “unwanted” births were daughters.
    3. Progress already visible: Unintended pregnancies have fallen from 21% in 2005-06 to 8% in 2019-21, and son preference is slowly weakening among younger and more educated families.

    Conclusion

    The article’s central argument is that India’s near-replacement TFR is not evidence the fertility story is finished, since it rests on a gap between wanted and actual fertility sustained by late spacing, partial informed choice, and residual son preference. What remains unresolved is the recent decline in modern contraceptive method use, which risks keeping the country’s unwanted-fertility gap in place even as the headline birth rate keeps falling.

    Back2Basics:

    Total Fertility Rate (TFR)

    1. Definition: TFR is the average number of live births a woman would have by the end of her reproductive years, calculated from age-specific fertility rates for ages 15 to 49.
    2. Source: TFR is tracked through the Sample Registration System (SRS) and the National Family Health Survey (NFHS).
    3. Replacement level: A TFR of 2.1 is generally considered replacement level; India’s national TFR has reached around 2.0, with Bihar at 2.9 against Kerala and Tamil Nadu at around 1.8.

    Understanding “Replacement Level” (2.1)

    1. The “0.1” Factor: The extra 0.1 accounts for the fact that some children do not survive to reproductive age, and slightly more boys are born than girls.
    2. Developing vs. Developed: In countries with high infant mortality rates, the replacement level can actually be much higher than 2.1 (sometimes up to 2.5 or 3.0) to stabilize the population.

    PYQ Relevance

    [UPSC 2014] While we flaunt India’s demographic dividend, we ignore the dropping rates of employability. What are we missing while doing so? Where will the jobs that India desperately needs come from? Explain.

    Linkage: The PYQ examines how demographic trends influence India’s development prospects. The article shows that replacement-level fertility alone does not ensure a demographic dividend, as unmet family planning needs persist.

  • Pollens Help Trace Why the Harappan Civilization Shrank

    Why in News?

    A study by the Birbal Sahni Institute of Palaeosciences (BSIP) has used pollen preserved in lake sediments from Deoria Tal (Garhwal Himalaya) to reconstruct past climate. The findings suggest that a prolonged weakening of the Indian Summer Monsoon (ISM) and the 4.2 ka climatic event contributed to the decline and eastward migration of the Harappan Civilization.

    Key Findings

    • Analysis of pollen and spores reconstructed vegetation and monsoon history over the last ~5,100 years.
    • Around 4200 years BP [Before Present](4.2 ka event), the region experienced an abrupt cool and dry climate with a weakened ISM.
    • Reduced monsoon weakened the perennial river systems of the Indus and Ghaggar-Hakra, making agriculture difficult.
    • This likely triggered the migration of Harappan populations towards the Ganga plains, contributing to the shrinking of the civilization.
    • The study establishes a strong link between abrupt climate change and changes in ancient human settlements.

    How Did Scientists Reconstruct the Past?

    • Sediment core collected from Deoria Tal in Uttarakhand.
    • Pollen analysis (Palynology) reconstructed past vegetation and climate.
    • Chronology established using 10 AMS Radiocarbon (¹⁴C) dates on Trapa (water chestnut) seed cases.
    • Changes in the Oak/Pine pollen ratio served as an indicator of changing temperature and monsoon strength.

    What is the 4.2 ka Event?

    • A major global climatic event that occurred around 4200 years ago.
    • Characterized by:
      • Weak Indian Summer Monsoon.
      • Cooler and drier climate.
      • Widespread droughts across several ancient civilizations.
    • Linked to the decline of civilizations such as Harappan Civilization, Akkadian Empire, and Old Kingdom of Egypt

    Why Did the Monsoon Weaken?

    Researchers attribute the weakened ISM to multiple interacting climatic factors:

    • Southward shift of the Inter Tropical Convergence Zone (ITCZ).
    • Strong El Niño conditions.
    • Strong negative phase of the Indian Ocean Dipole (IOD).
    • Reduced Northern Hemisphere summer insolation.

    Other Climate Phases Identified

    • Roman Warm Period (2500 to 1450 cal yr BP): Strong ISM and higher agricultural productivity.
    • Medieval Climate Anomaly (1050 to 650 cal yr BP): Strong monsoon due to northward ITCZ.
    • Little Ice Age (650 to 100 cal yr BP / CE 1350 to 1850): Weak ISM associated with stronger westerlies, ENSO and southward ITCZ.

    [2026] Consider the following statements about the archaeological findings in Harappan towns:
    I. There is wide occurrence of spindle-whorls in the houses but absence of spinning wheels.
    II. Weights and measurement scales, complete with graduations have been discovered.
    III. There are houses built in large part with baked bricks, around relatively spacious courtyards, with their own wells, bathing platforms, and large rooms.
    Which of the following inferences can be drawn from the above statements?
    1. Statement I suggests that spinning was a laborious activity done at home.
    2. Statement II suggests the extent of the scientific knowledge that the Harappans possessed.
    3. Statement III suggests the emergence of a common property system.
    Select the answer using the code given below :

    [A] 1 and 2 only

    [B] 2 and 3 only

    [C] 1 and 3 only

    [D] 1, 2 and 3

  • Pandavani Legend Teejan Bai Passes Away

    Why in News?

    Padma Vibhushan awardee Teejan Bai (1956–2026), the foremost exponent of Pandavani, passed away at AIIMS Raipur. She played a pivotal role in taking Chhattisgarh’s traditional folk art to the global stage.

    Key Highlights

    • Born in Ganiyari village (Durg district), Chhattisgarh.
    • Learned Pandavani from her maternal grandfather Brajlal Pardha and gave her first public performance at 13 years of age.
    • Broke gender barriers by performing in the Kapalika style, traditionally reserved for men.
    • Performed in over 17 countries, popularising Indian folk traditions worldwide.
    • Received the Padma Shri, Padma Bhushan, and Padma Vibhushan.

    About Pandavani

    • A traditional folk storytelling and musical art form of Chhattisgarh.
    • Narrates episodes from the Mahabharata through singing, narration, acting, and dialogue.
    • The performer uses a tanpura (tambura) as both a musical instrument and a symbolic prop.

    Two Styles of Pandavani

    • Vedamati Style: Performed while sitting, with greater emphasis on narration.
    • Kapalika Style: Performed while standing, combining dramatic acting, gestures, expressions, and dialogue.

    [2014] A community of people called Manganiyars is well-known for their:

    (a) Martial arts in North-East India

    (b) Musical tradition in North-West India

    (c) Classical vocal music in South India

    (d) Pietra dura tradition in Central India.

  • A growth story that needs women at work

    Mentor’s Comment

    With India’s youth unemployment already double its 2012 rate and GDP growth slower than official figures suggest, critics argue that India cannot sustain rapid growth or reach Viksit Bharat by 2047 while excluding half its population, women, from productive work.

    Why does raising female work participation matter for growth itself, not just for equity?

    1. Direct growth arithmetic: A 10 percentage point rise in India’s female Work Participation Rate (WPR) could add nearly two percentage points to GDP growth.
    2. Labour supply channel: More women in paid work expands the economy’s productive capacity and raises household incomes, consumption, and savings.
    3. Human capital channel: Higher household incomes from women’s earnings improve children’s nutrition, education, and healthcare, strengthening long term human capital.
    4. Productivity channel: Citing Nobel laureate Claudia Goldin, gender diverse workplaces are more efficient, creative, and competitive, making women’s inclusion a productivity strategy, not only a welfare measure.

    What explains the decline and stagnation in women’s work participation since the 1980s?

    1. Structural shift away from farming: As structural transformation reduced agriculture’s role between 2004-05 and 2012, mechanisation and falling demand for manual labour pushed rural women out of the workforce.
    2. The COVID reversal was distress, not choice: Post-2020 gains in women’s participation followed a GDP slowdown since 2017; return migration from cities pushed women into unpaid family labour in subsistence agriculture, a “distress driven feminisation of agriculture.”
    3. Capital intensive growth excludes women: India’s recent GDP growth has concentrated in capital intensive sectors like finance and information technology, which absorb few workers, while labour intensive sectors such as textiles and garments saw absolute employment fall between 2013 and 2019.
    4. Manufacturing’s broken promise: Fewer women were employed in manufacturing in 2019 than in 2004, despite Make in India and Performance-Linked Incentive (PLI) schemes; women’s manufacturing employment did not recover to 2004 levels until 2022.

    Why does Tamil Nadu succeed where most of India does not?

    1. Tamil Nadu’s outsized concentration: More than 40% of India’s women factory workers are employed in Tamil Nadu, a state with only 5% to 6% of India’s population.
    2. Sectoral base: This concentration rests on strong textile and garment hubs in Tiruppur and Coimbatore, footwear, electronics assembly in Sriperumbudur, and automobile components.
    3. Enabling conditions: Higher female literacy, greater mobility, and well developed hostel and transport facilities for women workers underpin the sector’s ability to employ women at scale.
    4. The Hindi belt contrast: States there need investment in health (not merely insurance) and public education for girls and women to bring down malnutrition and stunting before they can replicate Tamil Nadu’s outcomes.

    Conclusion

    India’s growth story is incomplete without raising female work participation, and the deficit is concentrated in exactly the sectors, labour intensive manufacturing, that once absorbed women workers and have since collapsed for them. Closing the north-south divide by replicating Tamil Nadu’s combination of sectoral investment, education, and mobility infrastructure is presented as the precondition for India to be “Viksit” by 2047.

    Back2Basics

    1. Work Participation Rate (WPR): The proportion of the population that is economically active (working or seeking work); distinct from the unemployment rate, which measures only those seeking work among the labour force.
    2. U-shaped curve (Claudia Goldin): The empirical pattern where female labour force participation first falls as an economy industrialises and household incomes rise, then rises again as education and the services sector expand, a pattern India’s data through 2018-19 is shown to follow.

    Question (2014): Discuss the various economic and socio-cultural forces that are driving increasing feminization of agriculture in India.

  • Gujarat deluge erases monsoon deficit, but overall rain still low

    Why in News?

    Heavy rainfall in Gujarat erased India’s July rainfall deficit, but the overall southwest monsoon (June-September) remains below normal.

    Key Highlights

    • Cumulative rainfall since 1 June is 16.1% below normal.
    • East & Northeast India: 31.9% rainfall deficit.
    • South Peninsula: 26.8% deficit.
    • Heavy rainfall in Gujarat resulted from a low-pressure system interacting with a Western Disturbance.
    • Over 40,500 people were evacuated and 6,367 rescued due to flooding.
    • Ahmedabad recorded 294.6 mm rainfall in 24 hours, its highest since 2000.
    • Weak El Niño conditions have contributed to uneven monsoon distribution, affecting agriculture.

    El Niño

    • Warm phase of the El Niño-Southern Oscillation (ENSO).
    • Characterised by warming of the central and eastern equatorial Pacific Ocean.
    • Generally leads to weaker southwest monsoon and below-normal rainfall in India.

    IMD Classification of Rainfall

    • Normal: 96% to 104% of Long Period Average (LPA).
    • Below Normal: 90% to 96% of LPA.
    • Deficient: Less than 90% of LPA.

    Southwest Monsoon

    • Contributes nearly 75% of India’s annual rainfall.
    • Normally spans June to September.
    • Two branches:
      • Arabian Sea Branch
      • Bay of Bengal Branch

    PYQ (2014, GS1, 10 Marks) Most of the unusual climatic happenings are explained as an outcome of the El Niño effect. Do you agree?
    [2020] With reference to Ocean Mean Temperature (OMT), which of the following statements is/are correct?

    1.OMT is measured up to a depth of 26ºC isotherm which is 129 meters in the south-western Indian Ocean during January-March.
    2.OMT collected during January-March can be used in assessing whether the amount of rainfall in monsoon will be less or more than a certain long-term mean.
    Select the correct answer using the code given below:
    a) 1 only
    b) 2 only
    c) Both 1 and 2
    d) Neither 1 nor 2

  • What India’s Young People Are Saying About Families

    Why in the News

    UNFPA’s Demographic Futures Survey, released on World Population Day 2026 and covering over 1,08,000 young adults across 73 countries, finds India’s fertility rate has settled at two children per woman, below the replacement level of 2.1. The finding exposes a gap between how policymakers read this number, as either alarming decline or policy success, and what young Indians themselves report about wanting families but facing specific obstacles.

    Is India’s below replacement fertility a crisis to fear or an achievement to credit?

    1. The number: India’s total fertility rate has settled at two children per woman, below the replacement level of 2.1.
    2. Alarmist reading: Some describe this as a “baby bust” or “population crisis.”
    3. UNFPA’s reading: The agency frames it as the outcome of sustained government investment in girls’ education, the National Health Mission, and expanded contraceptive and maternal health choice.
    4. Supporting indicator: The share of young women married before age 18 fell from 23.3% to 20.1% in recent years.
    5. Caution: Stopping at the achievement reading risks missing what young people are actually saying about the conditions they face.

    What specifically is stopping young Indians who want children from having them?

    1. Stated preference intact: Four in 10 women and a third of men say two children is their ideal family size, matching the same global pattern found across the 73 country survey.
    2. Money first: Financial constraint is the most cited barrier, named by nearly four in 10 respondents.
    3. Housing second: Housing availability and affordability is the next most cited constraint.
    4. Job security third: Stable employment ranks third among stated barriers.
    5. Care capacity fourth: The ability to adequately care for children is the fourth concern raised.

    Why does the care worry fall on women rather than being shared within the family?

    1. Time use gap: Young Indian women spend over five hours a day on unpaid housework and caregiving, against about half an hour for young men.
    2. Workforce gap: Only 15 of every 100 young women are in paid work, compared with 55 of every 100 young men.
    3. Consequence: This asymmetry forces many capable women into a career versus family trade off that men do not face in the same way.

    Does climate anxiety add a distinctly new pressure beyond economic insecurity?

    1. Near universal disruption: Nearly all surveyed young people say climate change is disrupting their lives.
    2. Mental health toll: About half say climate change affects their peace of mind.
    3. Compounded worry: Nearly half of young Indians report being very worried about conflict, economic insecurity and environmental risk simultaneously, among the higher rates recorded in the survey.
    4. Reframing: Combined with high youth unemployment and an emerging mental health conversation, this points to a generation questioning whether conditions are stable enough to build a family on.

    Why can’t a single national policy fit India’s fertility realities?

    1. Wide range: Bihar’s fertility rate stands at 2.7, against Sikkim’s 1.0.
    2. Regional pattern: Kerala, Delhi and Tamil Nadu have long settled below replacement level, while Bihar, Uttar Pradesh and Jharkhand are still catching up.
    3. Implication: India’s demographic transition is proceeding at different speeds across States, requiring State differentiated rather than uniform national responses.

    What would translate these stated needs into policy support?

    1. Childcare access: High quality, affordable and accessible childcare is identified as a priority.
    2. Shared caregiving: Policy should promote families sharing caregiving more equally.
    3. Stable work: Continued investment in stable, dignified work for young people entering the labour force.
    4. Mental health: Greater attention to youth mental health, including climate anxiety, within family planning conversations.
    5. Private sector role: Parental leave, flexible work arrangements and family friendly workplaces are identified as necessary complements to state policy.
    6. Stakes: India’s 255 million people aged 15 to 24 represent its demographic dividend.
      • Note: Demographic Dividend: The growth potential arising from a large working age population relative to dependents, creating an opportunity for faster economic growth.

    Conclusion

    Young Indians have not turned away from family life; survey evidence shows they still want roughly two children on average, but face a gap between that aspiration and stated preconditions of money, housing, job security, care capacity, and now climate anxiety. Realising India’s demographic dividend depends on closing this gap, particularly the unequal care burden carried by women, rather than treating below replacement fertility itself as the problem.

    Question (2023, GS1): Do you think marriage as a sacrament is losing its value in Modern India?

  • 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.

  • Australia Repatriates Three Antiquities to India

    Why in News?

    Australia announced the repatriation of three Chola-era antiquities stolen from temples in Tamil Nadu during Prime Minister Narendra Modi’s visit.

    Key Highlights

    • Australia will return:
      • Bronze Trident (Trishul) of Goddess Bhadrakali
      • Granite Nandi idol
      • Basalt sculpture of six-headed Karthikeya (Shanmukha)
    • The artefacts date to the 11th-12th century (Chola period).
    • They were housed in the National Gallery of Australia.

    Legal Basis

    • Repatriation is being carried out under the India-Australia Mutual Legal Assistance Treaty (MLAT).
    • Investigation by the Tamil Nadu Idol Wing CID established that the artefacts were illegally removed from temples and trafficked overseas.

    Original Temples

    • Bhadrakali Trident: Sri Kasi Viswanatha Swamy Temple, Kollumangudi, Tiruvarur.
    • Karthikeya Idol: Naganathaswamy Temple, Manambadi, Thanjavur.
    • Nandi Idol: Identified as originating from a temple in Tamil Nadu.

    [2025] Who among the following led a successful military campaign against the kingdom of Srivijaya, the powerful maritime State, which ruled the Malay Peninsula, Sumatra, Java and the neighbouring islands?

    [A] Amoghavarsha (Rashtrakuta)

    [B] Prataparudra (Kakatiya)

    [C] Rajendra 1 (Chola)

    [D] Vishnuvardhana (Hoysala)

  • Mount Marapi Eruption in Indonesia

    Why in News?

    Mount Marapi, one of Indonesia’s most active volcanoes, erupted again, sending an ash column about 2 km high into the sky over West Sumatra’s Tanah Datar District. Authorities continue to enforce a 3 km exclusion zone around the volcano.

    Note: This volcano is Mount Marapi (West Sumatra), not Mount Merapi (Central Java). They are two different active volcanoes in Indonesia.

    Key Highlights

    • The eruption produced an ash plume reaching approximately 2 km above the summit.
    • A 3 km exclusion zone remains in force following the deadly eruption in December 2023.
    • Authorities have advised residents and tourists to stay away from the crater due to the risk of further eruptions.
    • Indonesia frequently experiences volcanic eruptions because of its tectonic setting.

    About Mount Marapi

    • Located in West Sumatra Province, Indonesia.
    • Elevation: 2,891 metres.
    • It is one of the most active volcanoes in Sumatra.
    • It is a stratovolcano (composite volcano) characterized by frequent explosive eruptions.

    What is a Stratovolcano?

    • A stratovolcano is formed by alternating layers of lava, volcanic ash, and pyroclastic material.
    • It has steep slopes and is associated with explosive eruptions because of silica-rich, viscous magma.
    • Examples include Mount Fuji (Japan), Mount Merapi (Indonesia), and Mount St. Helens (USA).

    Why is Indonesia Highly Prone to Volcanic Activity?

    • Indonesia lies on the Pacific Ring of Fire, a zone of intense volcanic and seismic activity.
    • It is located at the convergence of the Indo Australian, Eurasian, Pacific, and Philippine Sea tectonic plates.
    • The country has more than 120 active volcanoes, the highest number in the world.

    Prelims Facts

    • Pacific Ring of Fire contains about 75% of the world’s active volcanoes and experiences nearly 90% of global earthquakes.
    • Volcanic hazards include ashfall, lava flows, pyroclastic flows, volcanic gases, and lahars (volcanic mudflows).

    [2024] Consider the following:
    1. Pyroclastic debris
    2. Ash and dust
    3. Nitrogen compounds
    4. Sulphur compounds
    How many of the above are products of volcanic eruptions?

    [A] Only one

    [B] Only two

    [C] Only three

    [D] All four