Summary of Key Points
The recent severe floods caused by Typhoon “Baihaidun” have exposed the shortcomings of traditional flood control methods. AI technology is transforming the entire flood control process: extreme rainfall is not becoming more frequent, but rather more concentrated and intense, making it difficult for traditional human-based approaches to cope. AI transforms flood control from a labor-intensive effort into a data-driven strategy through prediction, monitoring, early warning, and post-disaster response. Economically developed regions such as Zhejiang and Guangdong have already adopted AI flood control technologies, but most areas in the country are still in the initial stages due to challenges with data availability and funding. At the national level, policies are being implemented to expand smart flood control from localized pilots to a nationwide system.
Detailed Analysis
1. Extreme Floods Are Getting Worse – Why Can Traditional Flood Control Methods Keep Up?
You might think that floods are occurring more frequently, but data shows that the overall number of rainy days has not changed significantly; however, the duration and intensity of individual storms have increased (for example, a single-day rainfall in Wenling, Zhejiang, broke a 70-year record). It’s like going from 10 light rains a year to 5 heavy rains—a more concentrated and destructive pattern. Traditional flood control relies on manual data analysis and experience, which is inadequate for such sudden and intense downpours (as seen in Shanghai, where 181 waterlogging points occurred, leading to the complete shutdown of the subway system). The rapid deterioration of weather conditions outpaces the improvement of traditional flood control capabilities.
2. AI as the “Super Brain” of Flood Control – Preparing for Emergencies Across the Entire Process
AI doesn’t just come into action after flooding; it covers every stage from before the rain to after the disaster:
- Pre-rainfall Prediction: By integrating data from satellites, radar, and drainage systems, AI can simulate potential waterlogging issues and recommend evacuation plans in advance.
- In-time Monitoring: Drones and smart cameras monitor for dangers such as water accumulation and pipe breaches, providing real-time alerts to officials (for example, “Long Xiaorou” in Longgang, Shenzhen, analyzed 240,000 surveillance images during the storm and issued 1,500 warnings).
- Post-disaster Response: AI coordinates with meteorological, transportation, and emergency services to dispatch rescue efforts quickly and identifies areas prone to flooding and weak drainage systems, providing insights for future improvements.
In short, AI has significantly increased the efficiency of flood control by replacing manual efforts with data-driven analysis.
3. Who Is Using AI Flood Control Technologies First?
Currently, 28 provinces across the country have deployed smart flood control systems, but the main beneficiaries are coastal and economically developed areas with frequent waterlogging problems:
- Zhejiang uses “digital twin” technology to create a real-time simulation of water flow patterns.
- Shenzhen’s “Long Xiaorou” urban intelligence system automatically patrols key areas during storms.
- Jiangsu connects digital platforms to monitor rivers and lakes and coordinate flood control efforts.
However, provinces with frequent waterlogging issues like Hunan and Jiangxi have not yet established complete monitoring systems due to high costs, including the need for numerous sensors and data platforms, as well as annual maintenance expenses that many regions cannot afford.
4. Challenges in Promoting AI Flood Control: Funding and Data Are Major Barriers
Why can’t some areas with severe waterlogging problems use AI? There are two main barriers:
- Lack of Data: Without accurate data on rainfall, hydrology, and drainage systems, AI algorithms cannot accurately assess risks.
- High Costs: The initial investment in installing sensors and developing algorithms can amount to tens of millions, with annual maintenance costs also being substantial. Many underdeveloped areas struggle financially.
5. National Efforts to Expand AI Flood Control
The good news is that the government is promoting the advancement of smart flood control systems: The Ministry of Water Resources has issued guidelines for a unified monitoring system using satellite, aerial, and ground-based data. The Ministry of Housing and Urban-Rural Development and the Ministry of Emergency Management are also focusing on AI-based early warning systems.
This means that AI flood control will not remain limited to developed regions but will be extended nationwide through national coordination. Underdeveloped areas may receive financial or technical support to address their data and infrastructure gaps. The ultimate goal is to use AI to protect every street and riverbank, making extreme floods less threatening.
Conclusion
AI flood control is not a fancy gimmick; it’s a necessary tool for dealing with extreme weather events. Although many places still cannot utilize it, with government support and decreasing technology costs, more cities will adopt these intelligent systems in the future, enhancing their resilience to natural disasters. In an era of increasing extreme weather, using technology for safety is of paramount importance.