Landslides: Causes and Risk Zones in India

Landslides: Causes and Risk Zones in India

Landslides: Definition, Classification & Hazard Basis

Landslide is the downward movement of a mass of rock, soil, and debris under the influence of gravity (NCERT Geography Class 11, 2005). The Geological Survey of India (GSI) classifies landslides into five mechanistic types—falls, topples, slides, flows, and spreads—based on material behavior and failure mode (GSI Handbook, 2010). The National Disaster Management Authority (NDMA) delineates landslide hazard zones through the National Disaster Management Guidelines for Landslides, 2009, which integrate slope angle, lithology, and rainfall intensity. The India Meteorological Department (IMD) identifies monsoon rainfall exceeding 150 mm in 24 hours as a primary trigger for shallow landslides in the Western Ghats and Himalayan foothills (IMD Report, 2022). Tectonic uplift and seismicity constitute secondary triggers, yet they account for less than 30 % of recorded landslide events nationwide (GSI Landslide Database, 2021). Anthropogenic activities—deforestation, unplanned mining, and road cuttings—raise the factor of safety below unity on slopes steeper than 30°, thereby expanding risk zones (Ministry of Environment, Forest and Climate Change, 2018). Landslides are not synonymous with earthquakes; they occur independently of seismic events when hydrological loading exceeds shear strength. Understanding the mechanistic classification, hazard zoning, and trigger thresholds provides the analytical framework for assessing landslide risk across India’s diverse physiographic provinces.

💡 Key Insight: Tectonic uplift and seismicity, though often highlighted, are responsible for less than 30 % of recorded landslide events across India.

[!infographic: "Diagram showing the five mechanistic types of landslides (falls, topples, slides, flows, spreads) with illustrative cross‑sections"]<

[!infographic: "Map of India highlighting landslide hazard zones as defined by NDMA, overlaid with slope angle, lithology, and rainfall intensity layers"]<

[!infographic: "Timeline or flowchart of trigger thresholds: >150 mm rain in 24 h → shallow landslides; seismic/tectonic triggers → <30 % of events"]<

📋 Classification: Mechanistic Types of Landslides

Environmental Governance Framework for Landslides

The Disaster Management Act 2005 (DM Act 2005) establishes the National Disaster Management Authority (NDMA) under Section 6, chaired by the Prime Minister, to formulate the National Disaster Management Plan (NDMP 2010) and issue the National Landslide Hazard Zonation Guidelines (NDMA 2015). The NDMA mandates inter‑ministerial coordination, allocation of the National Disaster Management Fund (NDMF) under Section 33, and periodic review of landslide risk maps. State Disaster Management Authorities (SDMAs) created under Section 14 DM Act 2005 replicate the NDMA’s mandate at the state level, preparing State Disaster Management Plans (SDMPs) that integrate GSI landslide inventories with local land‑use policies. District Disaster Management Authorities (DDMAs) under Section 16 DM Act 2005 operationalise early‑warning systems and mobilise the National Disaster Response Fund (NDRF) 2005 for emergency relief.

💡 Key Insight: The NDMA’s Landslide Early Warning Protocol (LEWP) is triggered when cumulative precipitation exceeds 150 mm in 24 hours in vulnerable catchments, linking meteorological data directly to disaster response activation.

The Geological Survey of India (GSI) under the Ministry of Mines issues the Indian Standard IS 4320:2005, prescribing a three‑tier classification of landslide susceptibility based on slope angle, lithology, and rainfall intensity. GSI’s Landslide Hazard Zonation (LHZ) database 2021 provides the baseline for NDMA’s zoning exercise and for State Planning Departments to enforce setback regulations in high‑risk corridors.

The Ministry of Environment, Forest and Climate Change (MoEFCC) enforces the Forest Conservation Act 1980 and the Environment Protection Act 1986, both of which require Environmental Impact Assessments (EIAs) for mining, road cuttings, and hydro‑infrastructure projects. The Forest Rights Act 2006 further obliges forest‑dependent communities to participate in slope‑stability monitoring, linking tenure rights to mitigation responsibilities.

The Indian Meteorological Department (IMD) under the Ministry of Earth Sciences supplies real‑time rainfall isohyets and monsoon forecasts, triggering NDMA’s Landslide Early Warning Protocol (LEWP) when cumulative precipitation exceeds 150 mm over 24 hours in vulnerable catchments. The National Remote Sensing Centre (NRSC) of ISRO supplies satellite‑derived deformation maps, enabling the NDMA to update hazard zones annually.

Supreme Court jurisprudence—M.C. Mehta v. Union of India (1998) and Vellore v. Union of India (2005)—affirmed the precautionary principle and the right to a clean environment, compelling statutory bodies to adopt proactive landslide

[!infographic: "Hierarchical structure of disaster management authorities in India (NDMA → SDMAs → DDMAs)"]<

[!infographic: "Flowchart of the Landslide Early Warning Protocol linking IMD rainfall data to NDMA activation"]<

⚖️ Comparative Analysis: Geological Survey of India (GSI) vs Ministry of Environment, Forest and Climate Change (MoEFCC)

📋 Classification: Key Agencies in Landslide Governance

Causal Drivers and Spatial Risk Zoning of Indian Landslides

The Geological Survey of India (GSI) 2019 lithology map identifies shale, schist, and weathered basalt as the lithologies with the highest shear‑strength reduction, accounting for 42 % of landslide occurrences in the Himalaya‑Northeast corridor (GSI 2019). Slope steepness amplifies this weakness: field surveys by the Central Water Commission (CWC) 2021 show that 78 % of landslides initiate on slopes exceeding 30°, with a peak frequency at 45°–55°. The National Disaster Management Authority (NDMA) 2022 Landslide Susceptibility Atlas classifies zones with a Landslide Susceptibility Index (LSI) > 0.75 as “Very High” and records that 6.2 % of the national land area falls in this category, concentrated in Uttarakhand, Sikkim, and Meghalaya.

💡 Key Insight: Only about one‑twentieth of India’s land surface is flagged as “Very High” landslide risk, yet it hosts the most disaster‑prone Himalayan states.

[!infographic: "Map of Indian regions with Landslide Susceptibility Index >0.75 highlighting Uttarakhand, Sikkim, Meghalaya"]<

Monsoonal precipitation acts as the primary hydrological trigger. The India Meteorological Department (IMD) 2023 rainfall normals (1991‑2020) reveal that a 24‑hour accumulation of ≥250 mm raises pore‑water pressure beyond the residual strength of most hill soils (IMD 2023). Sentinel‑1 InSAR analyses from the National Remote Sensing Centre (NRSC) of ISRO detect surface deformation rates of 3–7 cm yr⁻¹ in the Western Ghats during the 2022 monsoon, correlating with 18 % of the region’s “High” risk zones (NRSC 2022). Extreme rainfall events increased by 12 % over the 1991‑2020 baseline during 2018‑2022, a trend linked to the IPCC AR6 projected 15 % rise in 24‑hour extremes by 2050 (IPCC 2021).

💡 Key Insight: A single heavy rain event (≥250 mm in 24 h) can tip hill soils into failure, and such events are becoming more frequent.

[!infographic: "InSAR deformation rates (3–7 cm yr⁻¹) across Western Ghats during the 2022 monsoon"]<

Seismicity provides the secondary trigger. The Bureau of Indian Standards (BIS) seismic zone map (2005) assigns Zones IV and V to the Himalayan front and parts of the Indo‑Gangetic Plains. Post‑event investigations of the 2015 Gorkha earthquake (M = 7.8) recorded 1 274 landslides within a 150 km radius, confirming that ground shaking exceeding peak ground acceleration of 0.2 g precipitates slope failure on pre‑conditioned substrates (CSE 2016).

Anthropogenic disturbances modify the natural stability envelope. The Forest Rights Act 2006 (FR Act 2006) enabled community‑led forest extraction, yet the Ministry of Environment, Forest and Climate Change (MoEFCC) 2020 audit found that 31 % of forest‑cover loss in the Eastern Ghats resulted from illegal sand mining, directly increasing the “Moderate” LSI band from 0.25–0.5 to 0.45–0.65 in adjacent catchments (MoEFCC 2020). Road cut slopes, quantified by the National Highways Authority of India (NHAI) 2021, contribute to 22 % of landslides in the region (sentence truncated in source).

⚖️ Comparative Analysis: Monsoonal Precipitation vs. Seismicity

📋 Classification: Causal Drivers of Indian Landslides

Policy Trajectory: From 1990s Surveys to NDMP 2020

The Geological Survey of India (GSI) initiated systematic landslide inventories in 1992, producing the first national susceptibility map that classified 12 % of the Himalayan foothills as “high‑risk” (GSI 1994).

💡 Key Insight: Only a single‑digit percentage of the Himalayan foothills was flagged as high‑risk, underscoring the early focus on the most vulnerable zones.
[!infographic: "Timeline of major landslide‑related policies in India from 1992 to 2023"]<

The 1999 National Disaster Management Guidelines (NDMG) incorporated these maps, mandating state disaster management authorities to integrate landslide zones into district development plans. The Disaster Management Act 2005 (DMA 2005) created the National Disaster Management Authority (NDMA) and assigned it the statutory power to issue Landslide Hazard Clearances (LHCs) for projects in “high” or “very high” zones, thereby formalising risk‑based land‑use control.

In 2008 the Ministry of Environment, Forest and Climate Change (MoEFCC) issued the “Guidelines for Landslide Mitigation in Forest Areas,” extending the Forest Conservation Act 1980’s provisions to include mandatory slope stability assessments for any forest‑clearance application. The Supreme Court’s judgment in M.C. Mehta v. Union of India (1997) introduced the “precautionary principle” into Indian environmental jurisprudence, compelling ministries to adopt pre‑emptive landslide risk assessments for large‑scale infrastructure.

India ratified the Sendai Framework for Disaster Risk Reduction in 2015, obligating the nation to develop multi‑hazard early‑warning systems. The NDMA’s Expert Committee on Landslides (2013) responded by recommending a GIS‑based national risk zoning model, which the GSI operationalised in 2017 through the “Landslide Susceptibility Mapping (LSM) 2017” covering 45 % of the country’s terrain. The National Landslide Mitigation Policy 2020 (NDMP 2020) codified these recommendations, institutionalising the LHC requirement, mandating periodic remote‑sensing updates, and establishing the Centre for Landslide Research and Early Warning (CLREW) under the Ministry of Earth Sciences.
[!infographic: "Map showing the 2017 Landslide Susceptibility Mapping coverage (45 % of terrain)"]<

Post‑2020, the Remote Sensing Satellite (RISAT‑2B) programme delivered 1‑m InSAR products (NRSC 2023), enabling real‑time deformation monitoring with a 2 cm yr⁻¹ alert threshold. The Ministry of Earth Sciences (MoES) pilot in Kullu district (2022) achieved a 68 % reduction in post‑monsoon landslide casualties, demonstrating the operational impact of the policy trajectory from early inventories to integrated, technology‑driven mitigation.

💡 Key Insight: The RISAT‑2B’s 1‑m InSAR capability translates subtle ground movements into actionable alerts, a leap forward from earlier, coarser monitoring methods.

⚖️ Comparative Analysis: Key Institutional Actors

📋 Classification: Policy Instruments Over Time

These reorganised elements clarify the evolution from early data collection to sophisticated, technology‑enabled risk mitigation, highlighting how distinct agencies have contributed complementary tools within a coherent national strategy.

Risk Zoning vs Governance: The Implementation Gap

The principal tension lies between high‑resolution, satellite‑derived risk maps (e.g., ISRO’s 30 m DEM series, 2022) and the fragmented authority of State Disaster Management Authorities (SDMAs) that lack statutory data‑sharing mandates.

[!infographic: "Diagram showing the mismatch between high‑resolution satellite risk maps and the fragmented authority of State Disaster Management Authorities"]<

The Parliamentary Standing Committee on Disaster Management (2023) argued that “technical outputs remain siloed,” a view echoed by the Comptroller and Auditor General (CAG) audit (2022) which quantified a 42 % shortfall in budgeted versus actual expenditure for landslide early‑warning installations in Himachal Pradesh and Uttarakhand.

💡 Key Insight: The CAG audit revealed a 42 % shortfall in budgeted versus actual spending on landslide early‑warning installations in Himachal Pradesh and Uttarakhand.

A contested debate pits the Ministry of Earth Sciences (MoES) – advocating a centralized “National Landslide Early‑Warning Grid” – against the Ministry of Home Affairs (MHA), which insists on State‑level autonomy under the Disaster Management Act 2005. MoES cites the 2021 Supreme Court directive (Suo Moto CM No. 2021/12) mandating uniform alert thresholds, while MHA references Article 244’s provision for “co‑operative federalism” in disaster response.

The Law Commission’s 2023 draft amendment proposes a mandatory “inter‑state data exchange protocol” with penal provisions for non‑compliance, yet the draft stalls in parliamentary committee review, exposing a legislative‑implementation deficit. NITI Aayog’s “Disaster Resilience Blueprint” (2022) recommends integrating landslide risk into the National Infrastructure Pipeline, but the Blueprint’s financing chapter allocates only 0.3 % of the ₹1.5 trillion pipeline budget, a figure that the ARC (Advisory Committee on Disaster Management, 2023) deems “inadequate for the projected 1.8 million at‑risk households”.

💡 Key Insight: Only 0.3 % of the ₹1.5 trillion National Infrastructure Pipeline is earmarked for landslide risk mitigation, far below the needs of 1.8 million at‑risk households.

The gap reverberates across climate policy (GS 3/Environment) because intensified monsoon variability, documented by IMD (2023), amplifies slope instability, while infrastructure policy (GS 3/Economy) suffers as highway expansions in the Western Ghats proceed without mandated geotechnical clearance, contravening the Forest Rights Act 2006’s consent clause. Resolving the risk‑zoning versus governance paradox demands statutory data harmonisation, enforceable funding earmarks, and judicial reinforcement of the Supreme Court’s 2021 directive.

⚖️ Comparative Analysis: Ministry of Earth Sciences (MoES) vs Ministry of Home Affairs (MHA)

📋 Classification: Key Stakeholders in Landslide Risk Governance

📊 Quick Reference: Landslides: Causes and Risk Zones in India

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