Digital Twin water management platform Digital Garam+

Advancement of Digital Twin Technology-based Dam Operation Decision-Making System

K-water is in the process of developing “Digital GARAM+”, a digital twin water management platform that combines digital twin technology with existing water management technologies to prevent water disasters and advance a water management-related decision-making system to be prepared for the increase in uncertainties in water management caused by climate change.

What is the Digital Twin Water Management Platform?

A tool to support easy and efficient water management decision-making processes by comprehensively monitoring and pre-simulating water management situations in a virtual digital world that replicates the real world

• Big Data | Drone Investigation | Disaster | Control Maintenance | CCTV | IoT | Diagnosis | Big Data
• Real-time Connection | Control, Optimization | Virtualization | Monitoring, Analysis, Simulation, Prediction, Diagnosis, Solution, Alternatives
• Drone Survey | Depth Survey | 3D Dam, Barrage, Bridge | Digital Terrain Model | Ortho Imagery
• Real-time Connection - Control, Optimization

• Space Data : Ortho Imagery, Drone Imagery Geodata
• Linked Data : Meteorological Information, Water Quality Information, Water Quantity Information, Facility Information

Major Functions of Digital GARAM

Equipped with real-time monitoring, analysis, and prediction functions of water management for smart integrated water management based on a 3D virtual world. K-water developed and uses third-level simulation technology.
* (Digital Twin Development Levels) Level 1- Mirroring, Level 2- Monitoring, Level 3- Simulation, Level 4- Federation, Level 5- Autonomous

Digital Twin Level 1 (Mirroring)

Construction of High-resolution 3D Terrain Information

• Construct urban area objects (LOD4) and non-urban area objects (LOD1)
• Construct dam, reservoir, and river terrain information
• Build a 3D bridge using drone mapping – equipped

Digital Twin Level 2 (Monitoring)

Provide Water Management Information

• Dam discharge restriction information (drone, 360˚ image, etc.)
• Real-time dam and river CCTV information
• Location of alarm stations, activation status, broadcast history, etc.

Real-time Sluice, Meteorological Information Monitoring

• Real-time dam-river water level and status (forecast and warning) monitoring
• Provide real-time weather information linked to the Korea Meteorological Administration
• Provide real-time GIS-based typhoon information

Digital Twin Level 3 (Simulation)

Support Real-time Water Management Analysis and Decision Making

• Equipped with a real-time hydrological and hydraulic flood analysis model
• Equipped with a 2D hydraulic flood analysis model (K-Flood)
• Equipped with a salinity monitoring and prediction model (EFDC) for the Nakdong River estuary

Advancement of Digital GARAM Functions

Promote technological development to optimally link and implement Data-Model-3D visualization

• Advancement of a water management analysis model : Improvement of model calculation speed and development of AI-based real-time analysis technology
• Development of AI water management technologies : Development of CCTV-utilized auto risk detection technologies (pedestrians, water level change, etc.)
• Provide realistic 3D spatial information : Development of virtual reality expression methods diversification, such as AR/VR Web&PC-based -> development of visualization technology such as VR, AR, etc.

Overseas Applications of Digital GARAM

Korea’s first digital twin water management platform, entering the Saudi market through public-private cooperation! “Korean government’s first digital platform export”

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  Establishment of Digital Twin Platforms for Five Cities in Saudi Arabia (Riyadh, Jeddah, Mecca, etc.)

  - Execution organizations : K-water, NAVER, LX
  - Project cost : $100 million (134 billion KRW approx.)
  - Project period : 60 months (18 months for DT construction, 42 months for operation)
  - Construction details : city monitoring, city planning, water management