| Digital twins Data from dam operation, weather forecasts, river


water level stations, and CCTV were combined and visualised on the platform. An AI-driven intelligent CCTV image analysis was added to the platform for early warning, and an automatic drone monitoring system was developed to supervise the dam reservoir and downstream river, even amid rainfall and windy conditions. In addition, seepage analysis and slope stability analysis for levees were integrated into the platform. Three types of dam and river simulations were implemented on the platform – a rainfall-runoff model, a hydraulic river flow prediction model, and a river flooding model. In addition, AI-driven smart flood prediction and an optimised dam discharge model were loaded to minimise flood damage to the downstream river and to secure dam safety. Through the platform, data-based smart water management is implemented. By linking dams and rivers into one system, the digital twin platform will contribute to a multidisciplinary model that integrates various components to enhance the productivity of water management against flooding. The authors conclude that although this is a powerful digital platform for water resource operation and management, it has only recently been launched, and further research is required for future verification and validation. Quantitative and qualitative evaluations of the digital twin dam and watershed management need to be studied, focusing on enhancing productivity and efficiency in the decision-making process.


Tailored for dams A digital twins research project which has been


described as being a paradigm shift in monitoring tailings dams, was recently awarded a prestigious prize at COP28. Digital Twins 4 Tailings Dams is a satellite- based early warning system to monitor the stability of tailings storage facilities, preventing potential catastrophic failures. It won the Data Sciences & AI- Enabled Solutions prize at the COP28 Prototypes for Humanity initiative, which finds innovative solutions for social and environmental issues. The winners were selected from more than 3000 entries submitted from 710 universities in 108 countries. The wining research group comprises PhD student Maral Bayaraa and Dr Cristian Rossi from the University of Oxford, and Dr Brian Sheil from the Laing O’Rourke Centre for Construction Engineering and Technology at the University of Cambridge in the UK. Bayaraa is from Mongolia which is one of the most


resource-rich countries in the world. “I’ve seen the huge amount of good mining can do,” she said. “But I’ve also seen the really dark side of mining and that’s why I’ve always wanted to be a part of this conversation - making mining more sustainable. I believe the award is a part of the recognition of the huge role that Earth Observation plays in tackling some of today’s biggest challenges...Our research focuses on global monitoring of critical infrastructure, such as tailings dams that contain toxic mine waste.” The World Bank highlights a need for three billion


tons of metals for the clean energy transition, which is intensifying challenges for the mining sector as over 98% of materials like copper end up as waste, stored in tailings facilities. With over 30,000 globally, a quarter of these are abandoned and unmonitored. By integrating


geotechnical engineering, satellite remote sensing, and machine learning, the Digital Twins 4 Tailings Dams project aspires to establish a digital twin system to monitor these critical infrastructures. “We are delighted to have our research on tailings


dams recognised in this way,” Dr Brian Sheil said. “This award spotlights the transformative role of satellite monitoring, machine learning, geotechnical modelling and digital twin technology will have in how we manage tailings dams worldwide. This research has been intrinsic to the wider Digital Twins research that we are carrying out in the Laing O’Rourke Centre for Construction Engineering Technology at University of Cambridge, where we are working towards achieving step-change improvements in sustainability, productivity and safety for the construction industry.”


Spanish twins on tour Spanish electricity company Endesa has created


digital twins of its hydroelectric power plants, which not only provide improved monitoring but also allow for 3D virtual tours of the facilities. “Endesa has 153 hydroelectric power plants distributed throughout Spain, their management is essential, but their location sometimes causes problems. So creating these digital twins has been crucial to improve our understanding and their operation,” said Santiago Dominguez, Endesa’s Head of Hydroelectric Generation. “When people think of hydroelectric power plants, they don’t have an idea of their size, how they work and how important they are in giving us 100% renewable supply.” The first digital twin pilot for virtual tours was


launched in 2023 at the El Pintado hydroelectric power plant near Seville. It was developed by Endesa’s Hydro Iberia Predictive Maintenance team, which developed a model similar to Street View but inside a power plant. To do this, 360-degree cameras and Lidar scanners with the latest technology were installed. And with them, it was possible to obtain the necessary depth to generate 3D spaces with high-resolution image quality. This application allows a virtual visit to the facility where all the installed equipment and infrastructure of the plant can be viewed. This model is useful in providing virtual visits for suppliers or internal personnel, visualisation of equipment and instrumentation, taking measurements on the installation, visualisation of the plan of a plant, and even making a 3D model of the entire plant. The system also allows the linking of documentation, such as plans, photographs, diagrams, manuals, and databases to individual items of equipment and the systems that make up the hydro plant, for easy consultation. Following the success of the pilot carried out at the El Pintado plant, Endesa has extended this model to nine other plants. These are Tajo de la Encantada and Guillena in Andalusia, Eume and Moncabril in Galici, Peñadrada in Castilla y León, plus Canelles, Sallente, Moralets and Serós in Catalonia. As Dominguez explained: “We have not only developed the digital twin in order to have a 360 view of the installations, we have also launched a diagnostic digital twin that receives more than 6000 analogue measurements in real time, including temperature, pressure, speed, vibration, etc, which are used to predict future values. These models are adjusted taking into account the normal behaviour of the equipment


Below: Canelles Dam in Spain is one of Endesa’s facilities to have a digital twin


Above: Digital twins simulation could help to make areas of work within the dams industry safer for workers


www.waterpowermagazine.com | April 2024 | 19


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