Q1. Most of India’s urban infrastructure is not climate-smart. Explain with recent examples. Discuss how housing, transport and municipal services can be planned to make Indian cities more climate-resilient.
Syllabus: GS-III (Urbanisation, Infrastructure, Environment & Ecology – Climate Change Adaptation)
Word limit / Marks: 15 marks – ~250 words
Source: What India should do to build climate-resilient cities, The Indian Express, 8 September 2025
Model Answer:
Introduction:
India’s cities are projected to host nearly 1 billion people by 2050, with 144 million new homes needed by 2070. Yet, most urban infrastructure today is not climate-smart, being highly vulnerable to floods, heatwaves, and pollution.
Body:
Evidence of non-resilient urban infrastructure
- Floods: Over two-thirds of urban residents face pluvial flood risks. The 2023 Chennai floods exposed inadequate stormwater systems, while Kolkata (2024) relied on ad hoc pumping during monsoon inundations.
- Heatwaves: Urban Heat Island (UHI) effect raises night temperatures by 3–5°C. Ahmedabad has faced severe heat stress, leading to health crises among outdoor workers.
- Transport disruptions: One-fourth of urban roads are flood-prone. In Mumbai, inundation of 10–15% of arterial roads paralyses nearly half of transport networks.
- Housing vulnerability: Informal settlements in Guwahati and Bengaluru remain exposed to floods and landslides, lacking resilient designs.
Building climate-smart housing, transport and services
Housing:
- Adopt compact city designs with zoning of no-build floodplains.
- Use cool roofs, ventilation, and tree canopies (as in Ahmedabad’s Heat Action Plan).
Transport:
- Kolkata’s city-level flood forecasting system with 450+ sensors offers early warnings.
- Chennai is upgrading stormwater management to protect roads.
Municipal services
- Waste-to-energy initiatives in Indore and Surat improve waste resilience.
- Nature-based drainage (wetlands, mangrove restoration) in Mumbai buffers flood impacts.
- Digital platforms for citizen participation in Pune support climate-smart planning.
Conclusion:
India has a narrow window. Early investment in climate-resilient housing, transport, and municipal services can avert billions in annual damages, safeguard lives, and make cities inclusive engines of growth.
Note on word limit: Although UPSC prescribes ~250 words, this model answer is longer (~300 words) to include sector-wise strategies and authentic case studies for better understanding.
Q2. Technology is increasingly used to address urban climate risks such as heat and floods. Examine the potential and limitations of tools like AI, remote sensing and citizen-led mapping in strengthening urban resilience in India.
Syllabus: GS-III (Science & Technology; Environment & Ecology; Disaster Management)
Word limit / Marks: 10 marks – ~150 words
Source: Case studies on AI, IoT, remote sensing and participatory platforms in Indian cities (e.g., IMD AI forecasts, Kolkata flood sensors, satellite mapping of heat islands)
Model Answer:
Introduction:
Urban India is highly exposed to floods, heatwaves, and pollution. New technologies like AI, remote sensing, and citizen-led mapping are being applied to improve climate resilience, though challenges remain.
Body:
Potential of technologies
AI applications:
- The India Meteorological Department’s AI-driven Mausamgram platform has improved rainfall forecast accuracy by 40–50%.
- Tamil Nadu integrates AI with GIS and weather models for real-time flood alerts.
- Bengaluru’s AI-based traffic system has cut travel times by 33%, lowering heat and emissions.
Remote sensing & geospatial analytics:
- ISRO’s VEDAS platform uses high-resolution satellite data to track urban heat islands and wetlands.
- The National Geospatial Mission (2023) integrates drones and satellites for flood-risk mapping.
- Ahmedabad and Surat use thermal remote sensing to identify hotspots for cool roof and green canopy interventions.
Citizen-led mapping:
- Community platforms in Kolkata feed data into the city’s flood warning system.
- Participatory digital mapping in Pune has helped identify low-lying slums for targeted interventions.
Limitations:
- High energy consumption of data centers, inconsistent datasets, and limited municipal technical capacity.
- Governance challenges and risk of excluding poor communities from digital platforms.
Conclusion:
Technology can provide granular, real-time solutions, but its effectiveness depends on integration with institutional planning, capacity-building, and inclusive participation.
Note on word limit: The prescribed limit is ~150 words, but this answer (~190 words) provides fuller coverage with case studies (IMD, Kolkata, Ahmedabad, Pune) for deeper practice.