LANDSLIDE RESILIENCE THROUGH EARLY WARNING SYSTEMS
Syllabus Mapping: GS3: Disaster and Disaster Management.
India is among the world’s most landslide-prone countries, with nearly 12.6% of its geographical area vulnerable to landslides. The increasing frequency of extreme rainfall and unplanned development has highlighted the need to shift from a reactive disaster response to anticipatory risk reduction, where Early Warning Systems (EWS) form the first line of defence.
Why are Landslides Increasing in India?
- Climate-Induced Slope Instability: Climate change has increased the frequency of high-intensity, short-duration rainfall, saturating slopes and triggering slope failures. Eg: Wayanad (2024) and recurrent landslides in Himachal Pradesh following cloudbursts.
- Unscientific Infrastructure Development: Road widening, hydropower projects, tunnelling and hill cutting destabilise fragile slopes by altering natural drainage and geological stability. Eg: Char Dham Road Project has raised concerns over slope destabilisation in the Himalayas.
- Ecosystem Degradation: Loss of forest cover reduces root reinforcement, increases surface runoff and weakens soil cohesion, making slopes more vulnerable. Eg: Plantation expansion and quarrying in the Western Ghats.
- Expansion into Hazard-Prone Areas: Rapid urbanisation, tourism and settlements on unstable hill slopes increase both the frequency of slope failures and disaster exposure. Eg: Construction along hill slopes in Shimla, Mussoorie and Joshimath.
- Geological Fragility of the Himalayas: The young fold mountains, active tectonics and seismicity make the Himalayan region inherently prone to landslides. Eg: Around 70% of India’s landslides occur in the Himalayan belt (GSI).
- Mining and Quarrying Activities: Unregulated extraction of minerals and stone disturbs slope geometry and weakens rock formations. Eg: Quarrying concerns highlighted in parts of Kerala’s Western Ghats.
- Weak Hazard Zonation and Risk-Informed Planning: Limited integration of landslide susceptibility maps into urban planning and infrastructure development results in repeated exposure to high-risk zones.
Challenges in Developing Effective Landslide Early Warning Systems in India
- Complex and Localised Nature of Landslides: Unlike cyclones or floods, landslides are highly site-specific, triggered by a combination of geology, rainfall, slope stability and land use, making prediction difficult.
- Limited Monitoring and Observation Network: Sparse deployment of rainfall gauges, ground sensors, geotechnical instruments and real-time monitoring stations reduces forecasting accuracy in vulnerable regions.
- Data and Technology Gaps: Fragmented geological, hydrological and meteorological databases, along with limited AI-based modelling, constrain accurate impact-based forecasting.
- Weak Last-Mile Dissemination: Warnings often fail to reach remote hill communities due to poor digital connectivity, language barriers and inadequate community awareness.
- Poor Integration with Land-Use Planning: Landslide susceptibility maps are not adequately integrated into infrastructure approvals, urban planning or road construction. Eg: Continued construction in high-risk zones despite GSI Landslide Susceptibility Zonation
- Institutional Coordination Challenges: Multiple agencies—IMD, NDMA, SDMAs, ISRO and local bodies—often operate in silos, delaying coordinated risk communication and response.
- Climate Change and Dynamic Hazard Profiles: Changing rainfall patterns, cloudbursts and glacial processes are making historical landslide thresholds less reliable, demanding continuous recalibration of forecasting models. Eg: Increasing cloudburst-induced landslides in Himachal Pradesh and Uttarakhand.
Role of Early Warning Systems in Building Landslide Resilience
- Shift from Reactive Relief to Anticipatory Risk Reduction: Early Warning Systems enable authorities to act before disasters strike, minimising casualties and economic losses rather than merely responding after the event. Eg: National Landslide Forecasting Centre (NLFC, 2025) issues district-level landslide forecasts.
- Protecting Lives through Impact-Based Forecasting: Risk-based warnings facilitate timely evacuation of vulnerable communities significantly reducing fatalities. Eg: Pre-emptive evacuations during extreme rainfall in Nilgiris and Sikkim.
- Enabling Risk-Informed Development Planning: Hazard forecasts support safer infrastructure siting, hill-road engineering and land-use regulation, preventing creation of new disaster risks. Eg: GSI’s Landslide Susceptibility Zonation (LSZ)
- Building Climate-Resilient Infrastructure: Forecast-based maintenance and temporary closures protect highways, railways, hydropower projects and communication networks from cascading failures. Eg: Monitoring vulnerable stretches along Char Dham routes and the Konkan Railway.
- Technology-Enabled Risk Intelligence: Integration of LiDAR, remote sensing, Doppler Weather Radars and satellite observations enables real-time monitoring and high-precision forecasting.
- Strengthening Community-Centric Preparedness: Last-mile dissemination through mobile alerts, local volunteers and Panchayats converts scientific forecasts into timely community action. Eg: Common Alerting Protocol (CAP) under NDMA.
- Minimising Socio-Economic Disruptions: Early action protects livelihoods, tourism, agriculture and critical supply chains by enabling preventive closures and contingency planning. Eg: Temporary suspension of tourism and traffic during red alerts.
- Operationalising the Sendai Framework: Multi-hazard Early Warning Systems strengthen disaster resilience by prioritising prevention, preparedness and resilience-building over relief-centric approaches. Eg: UN’s Early Warnings for All Initiative (2027) and Sendai Framework (2015–30).
PRELIMS BOOSTERS
1 . Weekly Basal Insulin (Insulin Icodec / Awiqli)
- Recently, Novo Nordisk launched Awiqli (Insulin Icodec) in India—the world’s first once-weekly basal insulin for adults with Type 1 and Type 2 diabetes, reducing injections from 365 to 52 per year.
- Insulin Icodec is a long-acting basal insulin analogue that provides a steady background insulin level for an entire week through prolonged albumin binding and slower receptor clearance.
- It is intended to improve treatment adherence and reduce injection burden, especially in patients requiring long-term insulin therapy.
- It is not a replacement for mealtime (bolus) insulin in all patients; many people with Type 1 diabetes still require rapid-acting insulin before meals.
- Insulin is secreted by β-cells of the Islets of Langerhans in the pancreas; glucagon is secreted by α-cells.
- Basal insulin maintains blood glucose during fasting and between meals, whereas bolus (prandial) insulin controls the rise in glucose after meals.
- HbA1c (Glycated Haemoglobin) reflects the average blood glucose over the previous 2–3 months and is the standard indicator for long-term glycaemic control.
- Insulin is a peptide hormone; therefore, it is not administered orally because it is degraded in the gastrointestinal tract.
- Type 1 Diabetes Mellitus (T1DM): Autoimmune destruction of pancreatic β-cells leading to absolute insulin deficiency; lifelong insulin therapy is essential.
- Type 2 Diabetes Mellitus (T2DM): Characterised by insulin resistance with progressive β-cell dysfunction; accounts for over 90% of diabetes cases.
2. National CAMPA approves Conservation Projects for Four Species
- National CAMPA has approved four new species-specific conservation projects for the Gangetic River Dolphin, Snow Leopard, Wild Water Buffalo and Indian Rhinoceros.
- The projects include population estimation, habitat restoration, scientific monitoring, recovery planning and landscape-level conservation.
- They will be implemented with financial support under the Compensatory Afforestation Fund (CAF).
- The approval reflects a shift from afforestation alone towards species-centric conservation.
- CAMPA (Compensatory Afforestation Fund Management and Planning Authority) is a statutory authority constituted under the Compensatory Afforestation Fund Act, 2016.
- It manages funds collected for Compensatory Afforestation, Net Present Value (NPV) and other forest-related charges when forest land is diverted for non-forest purposes under the Forest (Conservation) Act, 1980 (now Van (Sanrakshan Evam Samvardhan) Adhiniyam, 1980).
- National CAMPA functions under the Ministry of Environment, Forest & Climate Change (MoEFCC), while every State/UT has a State CAMPA.
- CAMPA funds can be utilised for afforestation, wildlife conservation, assisted natural regeneration, forest fire prevention, habitat improvement and soil & water conservation.
3. Inflation & Monetary Policy Committee (MPC)
- Retail inflation (CPI) is expected to move close to or slightly above the RBI’s medium-term target of 4%, largely driven by transport inflation, reflecting higher fuel prices and freight costs.
- Inflation Target: 4% ± 2% (i.e., 2%–6%) as notified by the Central Government in consultation with the RBI.
- MPC Composition (6 Members):
- 3 from RBI – Governor (Chairperson), Deputy Governor (Monetary Policy), one RBI nominee.
- 3 external members appointed by the Central Government.
- Decision-making: Each member has one vote; in case of a tie, the RBI Governor has a casting vote.
- Quorum: 4 members.
- Meeting Frequency: At least four meetings every year (currently scheduled bi-monthly, i.e., six meetings annually).
- If inflation remains outside the 2%–6% band for three consecutive quarters, the RBI must submit a report to the Central Government
- Headline Inflation in India is measured by the Consumer Price Index (CPI-Combined) compiled by the National Statistics Office (NSO), Ministry of Statistics & Programme Implementation (MoSPI).
