MTS to Forecast Flooding in Primorsky Krai
Russia experiences 40–70 major floods every year. Around 500,000 square kilometers of the country are vulnerable to flooding, including 150,000 square kilometers at risk of catastrophic consequences. Primorsky Krai is among the regions most frequently affected by floods.
MTS, in partnership with Primorsky Krai’s Agency for Hydraulic Engineering, Land Reclamation, and Hydrology, has launched a pilot digital flood-monitoring project. An automated hydrological monitoring station has been installed on the Sungacha River in the village of Markovo, within the Lesozavodsk Urban District.
A Warning System for the River
An automated hydrological station uses sensors to continuously measure water levels. The readings are transmitted automatically over a mobile network to an analytics platform, which displays current water levels and how quickly they are rising. It can also model possible scenarios. For example, if the water continues to rise at the current rate, the system can estimate where flooding may begin. When water reaches a dangerous level, the system automatically sends an alert. A dispatcher receives the warning and relays it to emergency services, giving responders time to prepare. Those extra minutes, and potentially hours, can make a difference when evacuating residents and protecting infrastructure.
MTS already plans to extend the system to another 30 rivers in the region. A single monitoring station provides a snapshot of conditions at one location. A network of interconnected sensors, by contrast, can provide early warning on a much broader scale, tracking hydrological conditions at multiple points and helping refine flood forecasts.
Advancing Through Digitalization
MTS has introduced solutions based on a similar technological approach in the Nizhny Novgorod, Samara, Chelyabinsk, Yaroslavl, and Irkutsk regions, as well as in the Sakha Republic (Yakutia). These systems monitor air quality in industrial centers, flood conditions, and water quality. They all follow the same basic model: sensors or cameras collect data, an analytics platform processes it, and a dispatcher receives an actionable alert.
Since 2023, MTS has also been developing a video-monitoring system for forest fires. Around 80 cameras are now operating in Primorsky Krai. Installed at heights of more than 70 meters, they provide 360-degree coverage at Full HD resolution. Artificial intelligence can detect smoke from up to 20 kilometers away, determine its coordinates, and relay the information to a dispatcher. The large-scale network began with just five cameras. The project shows how MTS can take a pilot initiative and turn it into a large, fully operational system.
This year, MTS and Russia’s Ministry of Emergency Situations launched a flood-monitoring system on the Birlya River in the Kaybitsky District of Tatarstan. Four measurement modules transmit data every 10 minutes on water levels, precipitation, air and soil temperatures, atmospheric pressure, and wind. AI processes the readings and generates forecasts. If water levels approach a dangerous threshold, the system automatically alerts emergency services. Depending on the results, the solution could be extended to other flood-prone areas of Tatarstan.
The effectiveness of machine learning in hydrology was also demonstrated by a joint validation exercise involving Russia’s Hydrometeorological Center, Sberbank, the Ministry of Emergency Situations, and the Federal Agency for Water Resources. Sber’s experimental AI model successfully forecast reservoir inflows and peak flood levels for the 2025 flood season across a vast area of the country. The evaluation covered 1,083 river cross-sections across almost all of Russia.
Rapid Advances in Flood Monitoring
Drones are among the most effective tools for remote reconnaissance, and Russia’s Ministry of Emergency Situations currently has more than 650 of them at its disposal.
“Satellite imagery helps professionals identify areas where hydrological conditions may deteriorate. Space-based images make it possible to compare sites over time and conduct retrospective analyses of areas that have previously experienced flooding. Using drone imagery, specialists create orthophoto maps and digital terrain models of flood-prone areas. These tools are then used to calculate inundation zones based on water-level rise scenarios forecast by Roshydromet,” said Alexander Kurenkov, Russia’s Minister for Civil Defense, Emergencies, and Disaster Relief.
MTS’s new technology is expected to be integrated with government systems operated by Roshydromet and the Ministry of Emergency Situations. The next steps include introducing predictive analytics that draw on historical data and weather forecasts, as well as automating emergency response. Together, these developments would mark an important step toward building nationwide digital infrastructure to protect people and communities from natural hazards.
