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India Strengthens Tsunami Warning System Through Expanded Ocean Observation Network

India has expanded its ocean surveillance network with new buoys, tide gauges and deep-sea sensors to improve monsoon forecasting, cyclone prediction, tsunami warnings and coastal disaster preparedness.
India Ocean Surveillance
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New Delhi: India ocean surveillance has received a major boost as the Government has expanded its network of buoys, tide gauges, deep-sea sensors and other advanced monitoring systems. The stronger observation network is designed to improve monsoon forecasts, cyclone tracking, tsunami early warnings and overall coastal safety. The announcement was made in Parliament by the Ministry of Earth Sciences.

The upgraded system will provide high-quality real-time ocean data, helping scientists make more accurate weather and ocean predictions while improving India’s disaster preparedness.

India Ocean Surveillance: What Has India Added to Its Ocean Observation Network

The Ministry said India’s ocean observation infrastructure now includes:

  • 19 surface moorings, including 16 in the mainland Exclusive Economic Zone (EEZ) and 3 in the equatorial Indian Ocean.
  • 17 broadband seismic stations for earthquake monitoring.
  • 7 deep-ocean tsunami buoys.
  • 36 coastal tide gauges.
  • 35 Global Navigation Satellite System (GNSS) receivers.
  • Strong-motion accelerometers for rapid earthquake detection.

These systems continuously monitor ocean currents, sea levels and seismic activity, allowing faster detection of natural hazards.

Read also: Game-Changer for Indian Oceans: CMARS Centre to Revolutionize Underwater Surveillance

India Ocean Surveillance: INCOIS Expands Coastal and Deep-Sea Monitoring

The Indian National Centre for Ocean Information Services (INCOIS) manages one of India’s largest coastal observation networks. According to the Ministry, the network includes:

  • 17 Directional Wave Rider Buoys
  • 20 Acoustic Doppler Current Profilers (ADCPs)
  • 32 Automatic Weather Stations (AWS)
  • 2 Water Quality Buoys
  • 50 Tide Gauges

These instruments provide continuous information about coastal and ocean conditions, supporting weather forecasting and marine safety.

India Ocean Surveillance: Hundreds of Deep-Sea Instruments Deployed

Between 2014 and 2025, INCOIS deployed:

  • 302 Argo profiling floats
  • 12 deep-sea glider missions
  • 45 drifting buoys
  • 64 wave drifters

The network also uses advanced instruments such as Vertical Microstructure Profilers (VMPs), Underway Conductivity-Temperature-Depth (UCTD) systems and Wire Walker platforms to collect detailed ocean data.

What are the Benefits of Latest Upgrades in India Ocean Surveillance

The Ministry said real-time observations are quality-checked and fed into advanced weather and ocean models. This has significantly improved:

  • Monsoon prediction
  • Cyclone forecasting
  • Ocean-state forecasts
  • Coastal wave predictions

Officials said wave forecast accuracy has improved by around 43% compared with 2014, while coastal forecasts now achieve about 70% accuracy.

Faster Tsunami Warnings

India’s strengthened tsunami monitoring system enables INCOIS to issue tsunami advisories within the internationally accepted 10-minute window after a tsunamigenic earthquake. The upgraded system helps authorities respond more quickly, reducing risks for coastal communities.

Future Expansion Already Planned

The Government has announced additional upgrades to further strengthen India’s ocean surveillance network. Upcoming plans include:

  • Installation of 14 new tide gauges
  • Deployment of 15 co-located GNSS receivers
  • A new Directional Wave Rider Buoy near Mauritius
  • Regular pre- and post-monsoon research vessel missions for deployment and maintenance

The Ministry also said collaboration with CSIR-NIO, NCPOR and other partner institutions will continue to support long-term expansion of India’s ocean observation capabilities.

Read also: TRIDENT-SAMUDRA Explained: How Indian Navy’s New AI Ocean Surveillance System Will Transform Indian Ocean Security


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