Digital Amur: A Virtual Twin to Forecast Environmental Threats With Precision
Researchers at Pacific National University have developed a high-precision digital twin of the Amur River and its tributaries. The virtual replica of one of the planet’s largest river systems could transform how an entire region prepares for climate-driven environmental risks.
A River Inside a Computer
Climate patterns are becoming less predictable, and ecological challenges are growing in scale. Scientists are responding by developing new tools to manage natural forces more effectively. Over the past century, the Amur River has experienced 110 floods, 17 of them catastrophic. In 2013, the Russian Far East faced its largest flood in 115 years of observations. Around 170,000 people were affected, approximately 13,000 homes were inundated, and the damage reached 92 billion rubles, roughly $1.1 billion at current exchange rates. Accurate forecasting of such disasters means protecting communities and preventing massive economic losses.
This ambitious scientific project was created at Pacific National University, known in Russian as Tikhookeansky gosudarstvenny universitet. The model integrates data collected via drones, sonar systems, and laser scanners that mapped every bend of the riverbed and shoreline of the vast and unpredictable Amur. The result is a highly detailed digital twin that is continuously updated and ready for analysis. Instead of presenting static water-level statistics, the model visualizes and calculates flood scenarios based on rainfall, ice melt, soil conditions, and other variables. The digital twin enables earlier deployment of protective measures and strengthens oversight of water protection zones by detecting illegal activity and assessing risks of ecological degradation.
In Line With a Global Trend
Digital twins of water resources are becoming a new management standard, combining artificial intelligence, GIS technologies, and big data to forecast risk. These systems significantly enhance early warning capabilities and improve decision-making processes.
In Siberia, researchers are developing a digital twin of Lake Baikal to monitor the ecological condition of the Baikal Natural Territory in real time and run scenario-based projections of potential changes. A digital twin of the Caspian Sea is also in preparation. Its objective is to track sea-level changes in operational mode and forecast the consequences of geological shifts and new infrastructure development.
To support freight transport development, experts have proposed creating a virtual replica of the Irtysh River. It is expected to improve navigation safety by at least 20% and increase vessel speeds by 10 to 15%. In this context, the Khabarovsk-based team’s work is relevant not only to the Russian Far East but also aligns with international scientific standards for hydrological modeling.
Expanding Horizons
The Khabarovsk project could form the foundation of a national monitoring and early-warning system for extreme hydrological events. For hydrologists and environmental scientists, it represents a powerful research platform. The technology carries substantial export potential, particularly for countries with complex flood regimes or advanced hydrological infrastructure. A tourism application featuring augmented reality for virtual rafting along the Amur, including underwater visualizations, demonstrates how advanced environmental science can generate accessible and engaging tools for broader audiences.
The application of such systems is expected to expand. Integrating digital twins into natural risk management, including flood control, erosion prevention, and pollution monitoring, is likely to become a common operational standard.
