# Digital Twins' Application for Geotechnical Engineering:
## 2 The Current Situation of Digital Twins in Geotechnical Engineering
[36] proposed a digital twin-based holistic framework and data integration model for intelligent dam construction management through GIS-BIM data fusion, microservices architecture design, and big data analytics, with practical implementation cases. [PERSON] et al. [37] established a 3D GIS and spatiotemporal data-driven visual safety monitoring system for hydraulic projects based on digital twin technology. This system enables intuitive visualization of terrain, geomorphology, safety monitoring models, and analytical results, while achieving 3D data simulation and visualization. [PERSON] et al. [38] developed an intelligent integrated simulation cloud platform for hydraulic engineering through customized development for industry-specific scenarios. Building upon the Tianhe Engineering Simulation Cloud Platform, they integrated cloud computing, big data, and AI technologies with field-measured and experimental data, addressing the growing cloud-based trends in engineering simulations and digital twin platforms. [PERSON] et al. [14] proposed a digital twin technology framework for safety monitoring and management of earth-rock dams. This study significantly improved the accuracy of dam deformation prediction by integrating Finite Element Modeling (FEM) with real-time monitoring data and a Bayesian updating method. The research team verified the effectiveness of the technology in the right-bank core-wall rockfill dam project in Danjiangkou, and they achieved three functions of real-time simulation, future prediction, and extreme scene deduction, which provided a dynamic and intelligent solution for the safety management of aging dams. This achievement not only promotes the transformation of dam monitoring from static-passive to dynamic-active but also provides an important technical reference for 94 digital twin dam projects in China. [PERSON] et al. [39] defined the concept of \"digital twin watershed\" and established its fundamental model, comprising physical watershed, virtual watershed, real-time interaction interfaces, digital-enabled services, and twin watershed data/knowledge. Their work identified critical scientific challenges and technical frameworks for digital twin watershed implementation, providing valuable insights for smart watershed research and digital technology applications in basin governance. Figure 5 shows the basic framework of the digital twin watershed. Digital twin technology plays a pivotal role across the design, construction, and operational phases of hydraulic engineering. Through real-time data integration and virtual model establishment, DT technology not only enhances management efficacy but  
Figure 5: Basic framework of digital twin watershed (reproduced from [PERSON] et al. [39]). also empowers hydraulic systems to better mitigate natural disasters, optimize resource allocation, improve ecological conservation, and advance the sector toward intelligent, refined, and sustainable development. In the field of the mining industry:  
Digital twin technology is progressively demonstrating transformative potential in mining operations, particularly in mineral extraction, resource management, equipment maintenance, safety monitoring, and environmental protection. With the deepening integration of intelligent mining and virtual reality technologies, DT-enabled unmanned precision mining and transparent extraction systems are emerging as frontier solutions. [PERSON] et al. [40] pioneered China's first integrated, unmanned, and intelligent solution for open-pit mines--the Intelligent Mining Operating System (IMOS)--by synergizing smart mining philosophies, ACP parallel intelligence theory, and next-generation AI technologies, thereby proposing a unified framework for parallel mine management. [PERSON] et al. [41] elaborated on DT's applications in the digital transformation of mining, showcasing innovative implementations through case studies.