Overview
India is among the world's most disaster-prone countries — approximately 59% of its landmass is vulnerable to earthquakes, 40 million hectares are flood-prone, 68% of net sown area is drought-vulnerable, and ~12.6% of land area is landslide-prone. Understanding the spatial distribution of natural hazards, the agencies responsible for mapping them, and the vulnerability assessment frameworks is essential for both GS1 (Physical Geography) and GS3 (Disaster Management).
Global Seismic Belts
Major Earthquake Zones of the World
| Belt | Extent | Share of Global Earthquakes |
|---|---|---|
| Circum-Pacific Belt (Ring of Fire) | ~40,000 km encircling the Pacific Ocean — from New Zealand through Indonesia, Japan, Kamchatka, Alaska, and down the western Americas to Chile | ~90% of the world's earthquakes; ~80% of the world's largest earthquakes |
| Alpide (Mediterranean-Himalayan) Belt | ~15,000 km from Indonesia through the Himalayas, Iran, Turkey, Mediterranean, and into the Atlantic | ~17% of the world's largest earthquakes; second most seismically active belt |
| Mid-Atlantic Ridge | Running through the centre of the Atlantic Ocean | Divergent plate boundary; mostly submarine earthquakes; less destructive |
| East African Rift | From Afar Triangle through Ethiopia, Kenya, Tanzania to Mozambique | Divergent plate boundary; moderate seismicity |
For Prelims: Ring of Fire = ~90% of world's earthquakes; Alpide Belt = ~17% of world's largest earthquakes. India lies in the Alpide Belt — the Himalayan zone is one of the most seismically active continental collision zones on Earth.
Seismic Zones of India
BIS Seismic Zonation
The Bureau of Indian Standards (BIS) divides India into seismic zones based on the Modified Mercalli Intensity (MMI) scale and historical earthquake data. The zonation is used for earthquake-resistant building design codes.
Traditional Classification (IS 1893)
| Zone | Intensity (MMI) | Risk Level | Regions |
|---|---|---|---|
| Zone II | VI (Low) | Low damage risk | Most of peninsular India — parts of Rajasthan, Madhya Pradesh, Maharashtra, Karnataka, Tamil Nadu, Odisha |
| Zone III | VII (Moderate) | Moderate damage risk | Parts of Kerala, Goa, Lakshadweep, remaining Rajasthan, parts of Punjab, UP, Bihar, West Bengal, Jharkhand |
| Zone IV | VIII (Severe) | High damage risk | Jammu (parts), Delhi, parts of Haryana, Punjab, Bihar (northern), parts of UP, Sikkim, parts of Maharashtra |
| Zone V | IX and above (Very Severe) | Very high damage risk | Kashmir Valley, Western Himachal Pradesh, Eastern Uttarakhand, Kutch (Gujarat), Northern Bihar, entire Northeast India, Andaman and Nicobar Islands |
Area Distribution
| Zone | Percentage of India's Area |
|---|---|
| Zone V | ~11% |
| Zone IV | ~18% |
| Zone III | ~30% |
| Zone II | ~41% |
For Prelims: ~59% of India's landmass is in Zone III or above (moderate to very high risk). Zone V covers the entire Northeast, Kashmir Valley, Kutch, and Andaman and Nicobar Islands. Delhi is in Zone IV.
Updated Seismic Zonation (BIS, 2025)
In 2025, the BIS released an updated earthquake design code introducing a new Zone VI (Super-Critical) covering the entire Himalayan arc. Key changes:
| Change | Detail |
|---|---|
| New Zone VI | Entire Himalayan arc placed in the newly introduced highest-risk Zone VI |
| Impact | ~61% of Indian landmass now lies in moderate to high hazard zones |
| Purpose | Reflects improved understanding of seismicity from the Nepal earthquake (2015), recent Himalayan tremors, and better probabilistic seismic hazard analysis |
| Building codes | Stricter design requirements for structures in Zone VI |
Major Earthquakes in India
| Earthquake | Year | Magnitude | Zone | Impact |
|---|---|---|---|---|
| Assam | 1897 | 8.7 | V | One of the largest recorded; devastated Shillong Plateau |
| Kangra | 1905 | 7.8 | V | ~20,000 deaths; Himachal Pradesh |
| Assam-Tibet | 1950 | 8.6 | V | Caused massive landslides and flooding; altered river courses |
| Latur (Killari) | 1993 | 6.2 | III (previously Zone I) | ~10,000 deaths; revealed vulnerability of "stable" peninsular India; led to reclassification |
| Bhuj | 2001 | 7.7 | V | ~20,000 deaths; most destructive in recent Indian history; Kutch, Gujarat |
| Kashmir | 2005 | 7.6 | V | ~86,000 deaths (mostly in Pakistan-administered Kashmir); severe damage in Indian Kashmir |
| Nepal-Bihar | 2015 | 7.8 | V | ~9,000 deaths in Nepal; tremors felt across Bihar, UP, Delhi |
For Mains: The Latur earthquake (1993) is a landmark event — it occurred in what was then Zone I (lowest risk), demonstrating that peninsular India is NOT immune to earthquakes. This led to the abolition of Zone I and the reclassification of the entire country into Zones II–V. It also catalysed the creation of the National Disaster Management Authority (NDMA) framework.
Flood-Prone Areas of India
Scale of the Problem
| Metric | Figure | Source |
|---|---|---|
| Total flood-prone area | 40 million hectares (~12% of total geographical area) | National Flood Commission |
| Average annual damage | Varies — Rs 10,000–50,000 crore depending on the monsoon year | CWC |
| Most affected river basins | Brahmaputra, Ganga, Mahanadi, Godavari, Krishna, Narmada | NDMA / CWC |
Major Flood-Prone Basins
| River Basin | Flood-Prone States | Key Characteristics |
|---|---|---|
| Brahmaputra-Barak | Assam, Arunachal Pradesh, Meghalaya, Manipur | Most flood-prone basin in India; Brahmaputra carries enormous sediment; Assam floods are annual; Majuli (world's largest river island) shrinks every year |
| Ganga | Uttarakhand, UP, Bihar, West Bengal, Jharkhand | Bihar is the worst-affected state — the Kosi (India's "Sorrow of Bihar") and Gandak cause devastating floods; 23.29 million people affected in the basin |
| Mahanadi | Chhattisgarh, Odisha | Odisha faces both floods (Mahanadi basin) and cyclones (Bay of Bengal coast) — double vulnerability |
| Godavari-Krishna | Andhra Pradesh, Telangana, Maharashtra | Flash floods in upper catchments; deltaic flooding in coastal AP |
| Narmada-Tapi | Madhya Pradesh, Gujarat, Maharashtra | Flash floods in narrow valleys; Tapi flooding affects Surat |
Causes of Flooding in India
| Cause | Explanation |
|---|---|
| Heavy monsoon rainfall | India receives 80% of annual rainfall in 4 months (June–September); concentrated rainfall overwhelms river capacities |
| Deforestation | Loss of forest cover in catchment areas reduces water absorption, increases runoff and soil erosion |
| Encroachment on floodplains | Urbanisation and agriculture in natural flood basins eliminate the river's natural overflow space |
| Siltation | Rivers like the Brahmaputra and Kosi carry massive sediment loads; riverbed rising reduces carrying capacity |
| Glacier melt / GLOF | Climate change increases glacial lake outburst floods (GLOFs) in the Himalayas — the South Lhonak Lake GLOF in Sikkim (October 2023) killed 40+ people |
| Dam mismanagement | Sudden release of dam water during heavy rainfall (e.g., Idukki dam releases during Kerala floods, 2018) |
Cyclone Tracks in India
Bay of Bengal vs Arabian Sea
| Feature | Bay of Bengal | Arabian Sea |
|---|---|---|
| Cyclone frequency | ~4–5 times more frequent than Arabian Sea | Less frequent but increasing with warming seas |
| Peak season | October–December (post-monsoon); also May–June (pre-monsoon) | May–June (pre-monsoon); October–November |
| Typical track | North-westerly initially; then curves towards Odisha–West Bengal (October), Andhra Pradesh (November), Tamil Nadu (December) | North-westerly towards Arabian Peninsula; some curve north-eastward and strike Gujarat coast |
| Vulnerable coasts | Odisha, West Bengal, Andhra Pradesh, Tamil Nadu, Puducherry | Gujarat, Maharashtra, Kerala (rare), Lakshadweep |
| Why more in Bay of Bengal? | Higher sea surface temperature; convergence of moisture; absence of strong wind shear; geographical funnel shape of the bay | Stronger wind shear; dry air intrusion from Arabian landmass; relatively cooler SST (historically) |
IMD Cyclone Classification
| Category | Wind Speed (km/h) | Example |
|---|---|---|
| Depression | 31–49 | Frequent during monsoon; generally causes heavy rain, not wind damage |
| Deep Depression | 50–61 | — |
| Cyclonic Storm | 62–88 | Named at this stage by IMD |
| Severe Cyclonic Storm | 89–117 | — |
| Very Severe Cyclonic Storm | 118–167 | Cyclone Fani (2019) — hit Odisha; 175 km/h |
| Extremely Severe Cyclonic Storm | 168–221 | Cyclone Amphan (2020) — hit West Bengal; 185 km/h |
| Super Cyclonic Storm | 222+ | Super Cyclone 1999 (Odisha) — winds up to 260 km/h; ~10,000 deaths |
For Prelims: IMD classifies cyclones into 7 categories (depression to super cyclonic storm). Cyclones are named at the "Cyclonic Storm" stage (62–88 km/h). The Bay of Bengal generates 4–5 times more cyclones than the Arabian Sea. The Super Cyclone of 1999 (Odisha) was the deadliest in recent Indian history.
Landslide Vulnerability
Scale in India
| Metric | Figure | Source |
|---|---|---|
| Landslide-prone area | ~4.3 lakh sq. km (~12.6% of India's land area) | GSI (Geological Survey of India) |
| States/UTs covered by mapping | 19 states and UTs | GSI (NLSM programme) |
| Historical landslides documented | 91,000 (33,904 field-validated) | GSI database |
Vulnerable Regions
| Region | Share of Landslide-Prone Area | Key Areas |
|---|---|---|
| Northwest Himalayas | ~66.5% | Jammu & Kashmir, Himachal Pradesh, Uttarakhand — steep slopes, heavy rainfall/snowfall, seismic activity |
| Northeast Himalayas | ~18.8% | All NE states, especially Mizoram, Nagaland, Manipur, Meghalaya, Arunachal Pradesh |
| Western Ghats | ~14.7% | Kerala, Karnataka, Goa, Maharashtra — heavy monsoon rainfall on steep laterite slopes; Wayanad landslide (2024) |
| Eastern Ghats | Minimal | Isolated areas in Odisha, Andhra Pradesh |
Triggering Factors
| Factor | Explanation |
|---|---|
| Heavy rainfall | Primary trigger — saturates soil, increases pore water pressure, reduces slope stability |
| Earthquakes | Seismic shaking destabilises slopes — particularly in Zone IV and V (Himalayan region) |
| Deforestation | Removal of root systems that bind soil; loss of canopy reduces rainfall interception |
| Road construction | Hill-cutting for roads creates unstable slopes — major issue along highways in Uttarakhand, HP |
| Mining | Quarrying destabilises slopes — sand and stone mining in Western Ghats |
| Climate change | Increased intensity of extreme rainfall events; permafrost thaw in higher Himalayas |
GSI Mapping and Early Warning
| Initiative | Detail |
|---|---|
| National Landslide Susceptibility Mapping (NLSM) | GSI has mapped ~4.3 lakh sq. km across 19 states/UTs covering Himalayan, NE, and Western Ghats regions |
| Bhooskhalan App | GSI's mobile app for landslide reporting and awareness |
| Bhukosh Portal / NGDR | National Geoscience Data Repository — landslide inventory accessible digitally |
| Regional Landslide Forecasting System (RLFS) | Developed since 2020; combines rainfall thresholds, weather prediction, and real-time data; collaboration between GSI, IMD, ISRO, NCMRWF |
Drought-Prone Areas
Scale of Drought Vulnerability
| Metric | Figure | Source |
|---|---|---|
| Net sown area vulnerable to drought | ~68% (of 140 million hectares) | Government of India |
| "Severe" drought-prone area | ~50% of the vulnerable area — drought occurs with near-regular frequency | NDMA |
| Drought-prone states | 13 states accounting for ~68% of India's geographical area and 600+ million people | Government of India |
Major Drought-Prone Regions
| Region | States | Causes |
|---|---|---|
| Western Rajasthan (Thar) | Rajasthan | Extreme aridity; <250 mm annual rainfall; sandy soil with negligible water retention |
| Gujarat (Kutch, Saurashtra) | Gujarat | Low and erratic rainfall; saline groundwater; high evaporation |
| Deccan Plateau (Rain Shadow) | Maharashtra (Marathwada, Vidarbha), Karnataka (northern), Telangana, parts of AP | Rain shadow of Western Ghats; <750 mm rainfall; black cotton soil cracks during dry season |
| Tamil Nadu | Tamil Nadu | Depends on NE monsoon (October–December), which is less reliable than SW monsoon |
| Rayalaseema | Andhra Pradesh | Semi-arid; low rainfall; rocky terrain with poor groundwater |
| Bundelkhand | UP, MP | Degraded land; erratic rainfall; poor irrigation infrastructure |
| Kalahandi-Bolangir-Koraput (KBK) | Odisha | Chronic drought despite being in a moderate rainfall zone — poor irrigation, poverty |
NRSC and ISRO in Drought Mapping
| Initiative | Detail |
|---|---|
| NRSC Drought Assessment | National Remote Sensing Centre conducts sub-district-level agricultural drought vulnerability assessment using remote sensing data |
| Indicators used | Vegetation indices (NDVI), soil moisture, rainfall departure, cropping pattern, groundwater levels |
| Bhuvan (ISRO) | Provides drought monitoring data; hosts spatial data for vulnerability assessment |
| NADAMS | National Agricultural Drought Assessment and Monitoring System — uses satellite data for near-real-time drought monitoring during the kharif season |
GLOF (Glacial Lake Outburst Flood)
| Feature | Detail |
|---|---|
| What | Sudden release of water from a glacial lake when its moraine dam (natural earthen/ice dam) breaches due to an earthquake, avalanche, or excess meltwater — sends a wall of water, debris, and ice downstream |
| India's risk | ~7,500 glacial lakes across 11 Himalayan river basins; NDMA has identified 189–195 lakes with high GLOF potential |
| Recent event | South Lhonak Lake GLOF, Sikkim (October 2023) — breached the moraine dam; flash flood down Teesta River; destroyed Chungthang Dam; 40+ deaths |
| Monitoring | ISRO/NRSC satellite monitoring; Bhuvan platform; NDEM (National Database for Emergency Management) |
| Mitigation | Early warning systems, hazard mapping, structural de-pressurisation (controlled lowering of lake levels), sensor-based monitoring, community awareness |
| NDMA programme | US $20 million GLOF risk mitigation programme targeting high-risk lakes |
| Climate link | Rising temperatures accelerate glacier retreat, expand existing glacial lakes, and create new ones — increasing GLOF frequency |
For Mains: GLOFs represent the intersection of climate change and disaster risk. The Sikkim GLOF (2023) demonstrated the cascading nature of these events — a glacial lake breach destroyed a hydropower dam downstream, raising questions about the environmental clearance of infrastructure projects in GLOF-prone Himalayan zones.
Multi-Hazard Vulnerability Mapping
BMTPC Vulnerability Atlas of India
| Feature | Detail |
|---|---|
| Agency | Building Materials and Technology Promotion Council (BMTPC), Ministry of Housing and Urban Affairs |
| First edition | 1997 — prepared following the World Conference on Natural Disaster Reduction (1994) |
| Third edition | 2019 — released at the Global Housing Technology Challenge |
| Hazards covered | Earthquakes, cyclones, floods — state-wise hazard maps |
| Purpose | Provides vulnerability data for building codes, urban planning, and disaster preparedness |
NDMA's Role
| Function | Detail |
|---|---|
| Guidelines | NDMA issues hazard-specific guidelines — earthquake, flood, cyclone, landslide, GLOF, heat wave, chemical disasters |
| Early warning | Coordinates with IMD (cyclones, rainfall), GSI (landslides), ISRO/NRSC (satellite monitoring), CWC (floods) |
| National Disaster Management Plan | Comprehensive plan covering all phases — prevention, mitigation, preparedness, response, recovery |
| State coordination | Each state has a SDMA (State Disaster Management Authority) and DDMA (District Disaster Management Authority) |
ISRO/NRSC in Hazard Mapping
| Initiative | Detail |
|---|---|
| Flood Atlas of India | NRSC prepared a satellite-based flood atlas mapping inundation history |
| Bhuvan | ISRO's geoportal — hosts flood, drought, GLOF, and landslide vulnerability layers |
| NDEM | National Database for Emergency Management — centralised disaster data repository |
| Cartosat / RISAT | Indian satellites used for high-resolution terrain mapping, flood monitoring, and damage assessment |
| Decision Support Centre | NRSC's DSC provides near-real-time satellite-based support during disasters to NDMA and state agencies |
Multi-Hazard Approach
| Principle | Detail |
|---|---|
| What | Assessing ALL hazards that affect a given area (earthquake + flood + landslide + cyclone) rather than treating each hazard in isolation |
| Why | Many areas face multiple, overlapping hazards — NE India (earthquake + flood + landslide); Odisha (flood + cyclone); Gujarat (earthquake + cyclone + drought) |
| How | Overlay hazard maps for different risks; assess combined vulnerability; design infrastructure and land-use plans accordingly |
| Example | BMTPC's Vulnerability Atlas overlays earthquake, cyclone, and flood risk for each state |
UPSC Relevance
Prelims Focus Areas
- India: ~59% landmass earthquake-prone; Zone V = NE India, Kashmir, Kutch, A&N
- Zone II = lowest risk; Zone V = highest risk (traditional); Zone VI introduced 2025
- Flood-prone area: 40 million hectares; worst basins = Brahmaputra, Ganga
- Drought: 68% of net sown area vulnerable; 13 states
- Landslide: 12.6% of land area (~4.3 lakh sq. km); GSI mapping; NW Himalayas most prone
- Ring of Fire = ~90% of world's earthquakes; Alpide Belt = second most active
- IMD cyclone classification: 7 categories (depression to super cyclonic storm)
- Bay of Bengal: 4–5 times more cyclones than Arabian Sea
- BMTPC: Vulnerability Atlas of India (first edition 1997, third edition 2019)
- GLOF: South Lhonak Lake, Sikkim, 2023; ~7,500 glacial lakes in Indian Himalayas
- Latur earthquake (1993): led to abolition of Zone I
Mains Focus Areas
- Multi-hazard vulnerability of India — why India is uniquely disaster-prone (tectonic setting, monsoon climate, diverse topography)
- Seismic risk in the Himalayas — implications for hydropower, infrastructure, urbanisation
- Flood management: structural (dams, embankments) vs non-structural (floodplain zoning, early warning, insurance) approaches
- GLOF as a climate-disaster nexus — infrastructure development in Himalayan GLOF zones
- Drought management: rainfall dependency, irrigation gaps, and the role of remote sensing (NRSC, NADAMS)
- Cyclone preparedness: India's improvement in cyclone management (zero-casualty approach) — comparing 1999 Super Cyclone (10,000 deaths) with Cyclone Fani (2019, 64 deaths) and Amphan (2020, 98 deaths)
- Role of ISRO/NRSC, GSI, IMD, CWC, BMTPC, and NDMA in hazard mapping and early warning
- Landslide risk and the development-environment balance in hill states
Vocabulary
Moraine
- Pronunciation: /məˈreɪn/
- Definition: A mass of rocks, sediment, and debris deposited by a glacier at its edges (lateral moraine), at its terminus (terminal moraine), or beneath it (ground moraine) — terminal moraines often form natural dams that impound glacial lakes, making them critical to GLOF hazard assessment.
- Origin: From French moraine, possibly from Savoyard dialect morena ("mound of earth"); first used in geological literature in the 18th century to describe the ridges of debris observed at the margins of Alpine glaciers.
Seismic Zonation
- Pronunciation: /ˈsaɪzmɪk zoʊˈneɪʃən/
- Definition: The division of a region into zones of varying earthquake risk based on historical seismicity, tectonic setting, geological conditions, and probabilistic hazard analysis, used to determine building design codes and land-use planning standards for earthquake-resistant construction.
- Origin: From Greek seismos (σεισμός, "earthquake, shaking") + English zonation (from Greek zone, "belt, girdle"); in India, seismic zonation is governed by BIS code IS 1893, first published in 1962 and most recently updated in 2025 with the introduction of Zone VI.
Vulnerability Atlas
- Pronunciation: /ˌvʌlnərəˈbɪlɪti ˈætləs/
- Definition: A comprehensive cartographic document that maps the spatial distribution of natural hazard risks — earthquakes, cyclones, floods, landslides — across a country or region, using historical data, geological analysis, and remote sensing to assess the vulnerability of buildings, infrastructure, and populations.
- Origin: Vulnerability from Late Latin vulnerabilis ("capable of being wounded"), from vulnerare ("to wound"); atlas from Greek mythology — Atlas, the Titan who held up the sky, whose image appeared on the cover of Gerardus Mercator's 1595 book of maps, giving the word its modern meaning.
Key Terms
Ring of Fire
- Pronunciation: /rɪŋ ɒv ˈfaɪər/
- Definition: A horseshoe-shaped belt of intense seismic and volcanic activity stretching approximately 40,000 km around the margins of the Pacific Ocean, from New Zealand through Indonesia, Japan, Kamchatka, Alaska, and down the western coasts of North and South America to Chile — accounting for approximately 90% of the world's earthquakes and 75% of its active volcanoes.
- Context: The Ring of Fire is formed by subduction zones where oceanic plates (Pacific, Nazca, Philippine Sea) plunge beneath continental plates, generating earthquakes and magma that fuels volcanic eruptions; India does NOT lie in the Ring of Fire but in the Alpide (Mediterranean-Himalayan) Belt.
- UPSC Relevance: GS1 (Physical Geography). Prelims: Ring of Fire = ~90% of world's earthquakes; ~40,000 km; surrounds the Pacific; India is in the Alpide Belt, not the Ring of Fire. Mains: asked to compare the two global seismic belts and discuss India's tectonic vulnerability in the Himalayan collision zone.
GLOF (Glacial Lake Outburst Flood)
- Pronunciation: /dʒiː ɛl oʊ ɛf/
- Definition: A sudden and catastrophic release of water from a glacial lake when its moraine or ice dam is breached by an earthquake, avalanche, landslide, or excessive meltwater inflow, sending a destructive flood of water, sediment, and debris downstream — a growing hazard in the Himalayas due to climate-change-driven glacier retreat.
- Context: India has approximately 7,500 glacial lakes across 11 Himalayan river basins, of which 189–195 have been identified as having high GLOF potential; the South Lhonak Lake GLOF in Sikkim (October 2023) breached a moraine dam, destroyed the Chungthang Dam downstream, and killed 40+ people — highlighting the cascading risk of hydropower infrastructure in GLOF-prone zones.
- UPSC Relevance: GS1 (Physical Geography), GS3 (Disaster Management, Climate Change). Prelims: definition; South Lhonak Lake GLOF (2023, Sikkim); ISRO/NRSC monitoring role. Mains: asked to discuss GLOFs as a climate-disaster nexus — the tension between Himalayan hydropower development and GLOF risk; the role of satellite monitoring and early warning systems; and NDMA's mitigation strategies.
Sources: BIS (IS 1893 — Seismic Zonation), NDMA (ndma.gov.in), GSI (Geological Survey of India — Landslide Hazard Zonation, bhusanket.gsi.gov.in), NRSC/ISRO (Bhuvan, Flood Atlas, GLOF monitoring), BMTPC (Vulnerability Atlas of India), CWC (Central Water Commission), IMD (Cyclone Classification), National Flood Commission, pib.gov.in
BharatNotes