In the coming period, Vietnam’s meteorology and hydrology sector will prioritize comprehensive digital transformation, with many initiatives, including building a national Big Data architecture, developing modern forecasting systems, and strengthening data-sharing networks with domestic and international organizations.
Simultaneously, the sector aims to modernize its observation network by expanding automated monitoring stations, utilizing satellite data, and developing multi-hazard warning platforms.
Another critical goal is to deliver alerts to the public faster and more accessibly via digital platforms, mobile devices, and multi-channel communication systems.
These strategic directions were highlighted by Deputy Minister of Agriculture and Environment Le Cong Thanh at a workshop titled “New Technologies in Natural Disaster Forecasting and Early Warning,” held on March 18 in Hanoi.
According to Mr. Thanh, climate change is significantly altering natural disaster patterns both globally and in Vietnam.
Between 2021 and 2025, Vietnam has been impacted by an average of 10 to 12 storms and tropical depressions in the East Sea annually, along with hundreds of heavy rain events and other extreme weather phenomena.
Over the past five years, natural disasters have claimed more than 1,500 lives (including those reported missing) and caused economic losses totaling hundreds of trillions of VND (VND1 trillion is equivalent to around $38 million).
Notably, many recent disasters have occurred on a localized scale but carried immense destructive power. Meanwhile, traditional forecasting methods have shown limitations, particularly regarding accuracy and timeliness. This has created an urgent need for innovation in technology and forecasting approaches.
Facing these challenges, Deputy Minister Thanh stated that management agencies have identified technology as a "breakthrough" solution. Specifically, AI, Big Data, remote sensing, smart sensor systems, and high-resolution numerical weather prediction models will play a pivotal role.
The application of these technologies helps shorten data processing times, improve forecast precision, and support the creation of effective response scenarios. In particular, real-time data analysis allows for the early detection of anomalies, enabling the issuance of timely warnings, he said.
From a community perspective, Dr. Cao Duc Phat, Chairman of the Vietnam Disaster Prevention Community Foundation, noted that the integration of AI into weather forecasting is yielding positive results. Specifically, AI can improve short-term storm intensity forecasting accuracy by 10-20%, while enabling the automated identification of storm locations and intensity from satellite data with an accuracy rate exceeding 90%.
Furthermore, ultra-short-term warning systems for thunderstorms, tornadoes, and heavy rain are being developed using multi-source data—including radar, satellite imagery, lightning detection, and automated monitoring stations—allowing for early warnings ranging from 30 minutes to several hours.
"Real-time monitoring and warning platforms for flash floods and landslides are also being gradually deployed, with the capability to provide details down to the commune level. At the same time, modern hydrological and hydraulic models support flood and saltwater intrusion forecasting for specific river basins, enhancing the overall effectiveness of disaster prevention and control," said Mr. Phat.
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