Scientific Results

This catalogue is obtained by conducting a systematic literature review of scientific studies and reviews related to monitoring, forecasting, and simulating the inland water cycle. The analysis maps scientific expertise across research groups and classifies findings by the type of inland water studied, application focus, and geographical scope. A gap analysis will identify missing research areas and assess their relevance to policymaking.

ID ▲	Type	Year	Authors	Title	Venue/Journal	DOI	Abstract
publications-5111	Conference paper	2023	Ivanova I.; Spasova T.; Stankova N.	Using Sentinel-2 data for Efficient Monitoring and Modeling of Wetland Protected Areas	Proceedings of SPIE - The International Society for Optical Engineering	10.1117/12.2681790	Wetlands are ecologically vital habitats that play a crucial role in supporting biodiversity and providing essential ecosystem services. They are considered to be among the most productive ecosystems on the planet that provide numerous benefits. For the purposes of this study, Straldzha Complex Protected Area, Bulgaria was chosen as the object of investigation. Straldzha Complex Protected Area includes a reservoir and surrounding wetlands and meadows, the remains of the eastern part of the former Straldzha Plateau (the largest plateau ever in Bulgaria). The wetland is sensitive to human activities, related to the water management and unsustainable use of the former plateau as agricultural land. For the purposes of this study, data from Sentinel-2 satellite of the European Space Agency were used. The monitoring was carried out during the study period 2017 - 2022. An index-based classification was used in the study, utilizing NDVI, NDWI and MSAVI2 indices for classifying the contents within the wetlands boundaries. NDGI model was applied as well, evaluating the vegetation dynamics in the marsh. The obtained results showed successful mapping and monitoring of wetlands. The wetlands are of high importance and should be protected and conserved to maintain the benefits they provide to the environment and society. The data and results of this research will be able to serve Destination Earth (DestinE), which is an ambitious initiative of the European Union to create a digital model of the Earth that will be used for monitoring the effects of natural and human activities on our planet, prediction of extreme events and adapting policies to the climate challenges. The data and models will serve the Bulgarian initiative for the construction of the Digital Twins, which is being pilot developed in the department of Aerospace Information, Space Research and Technology Institute - Bulgarian Academy of Sciences. Open Data were used in this study, with the aim of promoting the Open science policy and FAIR principles as much as possible. Β© 2023 SPIE.
publications-5112	Conference paper	2023	Pisani J.; Cavone G.; Pascucci F.; Giarre L.	Using Digital Twin to Detect Cyber-Attacks in Industrial Control Systems	EUROCON 2023 - 20th International Conference on Smart Technologies, Proceedings	10.1109/EUROCON56442.2023.10198927	The digital transition is largely impacting industrial control systems. The integration of information and communication technologies in industrial control systems on the one hand is improving the related functionalities, on the other hand is increasing the related vulnerabilities and the attack surfaces of industrial systems. This results in the non-negligible need for protection of the operational and production processes. Although many tools are available from the Information Technology sector, these are currently not appropriate to guarantee confidentiality, integrity, and availability in the industrial domain. As a consequence, it is crucial to investigate the proper strategies and methodologies to guarantee the protection of industrial control systems. In this context, this paper aims at defining a novel tool for the detection of cyber-attacks in industrial control systems, which is based on the implementation of a virtual model for both the physical and the control layers to detect attacks. In fact, the majority of literature contributions consider the implementation of a virtual model for the only physical layer. In this paper, the virtual model for the physical and the control layers is defined as a digital twin based on a hybrid automaton. The effectiveness of the proposed approach is demonstrated by considering its application to a water distribution system case study. Β© 2023 IEEE.
publications-5113	Article	2023	Huang Y.; Zhang Z.; Li Q.; Wang Q.; Chen Y.	Thinking and exploration of key technical difficulties and solutions in the construction of the Smart Yangtze River; [ζ™Ίζ…§ι•Ώζ±_x009f_ε»Ίθ®Ύε…³ι”®ζ_x008a_€ζ_x009c_―ι_x009a_Ύη‚ΉδΈ_x008e_θ§£ε†³ζ–Ήζ΅η_x009a_„ζ€_x009d_θ€ƒδΈ_x008e_ζ_x008e_Άη΄Ά]	Shuili Xuebao/Journal of Hydraulic Engineering	10.13243/j.cnki.slxb.20230015	The Smart Yangtze River supported by the Digital Twin Yangtze River is an important new infrastructure to accelerate the realization of the goals of the Safe River, the Green River, the Harmonious River, and the Beautiful River in the new stage of high-quality water conservancy development. Focusing on the short-term objectives of the construction of the Smart Yangtze River, this paper expounds the construction requirements, development background, construction goals and the overall structure of the Smart Yangtze River supported by the Digital Twin Yangtze River. Guided by the problems, this article focuses on the standardization of models, the integration of data-driven methods and mechanistic models, and the application of model configuration tools. The methods of construction a knowledge graph for flood control is proposed. On this basis, a business application for intelligent operation of water projects with forward simulation and backward deduction is presented. Finally, the implementation path for integrating new and old systems is explored, which provides technical support to further promoting the construction of the Smart Yangtze River. Β© 2023 International Research and Training Center on Erosion and Sedimentation and China Water and Power Press. All rights reserved.
publications-5114	Conference paper	2023	Habibian A.; Broz J.; Sadatiyan M.; Nicolas N.; Wood B.	Marching towards a Digital Twin: How GLWA Built a 3D Model of Its WRRF Complex Underground Utilities	Pipelines 2023: Condition Assessment, Utility Engineering, Surveying, and Multidiscipline - Proceedings of Sessions of the Pipelines 2023 Conference	10.1061/9780784485033.007	The Great Lake Water Authority (GLWA) owns and operates a 1,700 million gallons per day (MGD) water resource recovery facility (WRRF). As one of the largest single WRRF sites in the US, it has a complex yard piping network of gravity, pressurized pipes, and electrical systems. To support its ongoing asset management program, GLWA commissioned the implementation of a multi-step approach to address their needs for locating and creating a reliable geographical database of these assets. All collected data is stored in georeferenced 3D and 2D models and associated databases. Main attributes, such as pipe size, material, age, and construction project, were stored in the 3D model database to better fit planning and design project needs. A more accessible and lighter 2D GIS model of the system was developed for the day-to-day operation and decision-making processes, including critical features such as operating pressure, valve opening direction, photos, and ownership. These georeferenced models and data sets help the facility owner, consultants, and contractors better understand the system; plan accurately; track condition reliably; and improve site safety. This paper covers the multi-step process of collecting, organizing, and validating information, along with challenges encountered and best practices implemented. Β© ASCE.
publications-5115	Book chapter	2023	Wang X.; Li Y.; Zhou Z.; Lv X.; Yuan P.F.; Chen L.	Levelling Calibration and Intelligent Real-Time Monitoring of the Assembly Process of a DfD-Based Prefabricated Structure Using a Motion Capture System	Computational Design and Robotic Fabrication	10.1007/978-981-19-8637-6_45	Conventional measuring techniques and equipment such as the level and total-station are commonly used in on-site construction to measure the position of building elements. However, a motion capture system can measure the dynamic 3D movements of markers attached to any target structure with high accuracy and high sampling rate. Considering the characteristics of prefabricated structures that is composed by lot of discrete building elements, advanced requirements for the on-site assembly monitoring is required. This paper introduces an innovative real-time monitoring technique for the DfD-based (Design for Disassembly) structure with the application of motion capture system and other hardware in an IoT-based BIM system. The design and construction method of the structure system, on-site setup of monitoring system and hardware, data acquisition and analysis method, calibration algorithm as well as the BIM system are further illustrated in the paper. The proposed method is finally applied in a real building project that is composed by thousand discrete building elements and covers a large area of 5025Β m. As demonstrator, such monitoring system is applied in the real construction of a DfD-based prefabricated steel structure in the β€_x009c_Water Cubeβ€_x009d_ (Chinese National Aquatics Centre) in Beijing. The building process is successfully recorded and displayed on-site with the digital twin model in the BIM system. The construction states of the building elements are gathered with different kind of IoT techniques such as the RfID chips and QR-Codes. With the demand to control the flatness tolerance within 6Β mm (within a 2550Β m area), a large area monitoring system was applied in the project and finally reduced the construction time within 20Β days. The final tolerance is verified and further discussed2. Β© 2023, The Author(s).
publications-5116	Conference paper	2023	Suquet R.R.; Nguyen T.H.; Ricci S.; Piacentini A.; Bonassies Q.; Fatras C.; Lavergne E.; Brunato S.; Gaudissart V.; Guzzonatto E.; Froidevaux A.; Guiot A.; Valladeau G.; Poisson J.C.; Huang T.; Bretar F.; Kettig P.; Blanchet G.	The SCO-Flooddam Project: Towards A Digital Twin for Flood Detection, Prediction and Flood Risk Assessments	International Geoscience and Remote Sensing Symposium (IGARSS)	10.1109/IGARSS52108.2023.10282907	Floods are the most common natural disasters all over the world and they are increasing in frequency and intensity due to climate changes. The Space for Climate Observatory (SCO)-FloodDAM-DT project with a joint collaboration effort between CNES, NASA's partners and JPL is devoted to developing a federated Earth System Digital Twin (ESDT) for water-cycle applications focused on flood events. In particular, SCO-FloodDAM-DT project aims to provide an automated pre-operational service to reliably detect, monitor and assess floods at global scale within digital twin collaboration with NASA/JPL. The main objective is to connect data and existing models from both agencies in order to combine multi-scale simulations taking into account multiple phases of an entire flood event, from early alerts to post-event impact assessments. At the end, a proof-of-concept demonstration, planned after 18 months, will be presented with its multi-scale aspect over French and USA selected catchments. Β© 2023 IEEE.
publications-5117	Article	2023	Manocha A.; Sood S.K.; Bhatia M.	Digital Twin-assisted Fuzzy Logic-inspired Intelligent Approach for Flood Prediction	IEEE Sensors Journal	10.1109/JSEN.2023.3322535	Natural hazards causing catastrophic damage and infrastructure destruction have increased in recent decades, with floods being a serious problem that leads to crop damage, population loss, infrastructure degradation, and public service collapse. Digital Twin (DT) technology is a promising solution for alerting communities of oncoming floods and providing sufficient time for evacuation and property protection. This research introduces a digital twin-inspired intelligent framework that analyzes hydrological and meteorological parameters causing floods, validated using data from the Indian Meteorological Department (IMD). Artificial intelligence (AI) algorithms improve situational analysis and decision-making for flood forecasting, while advanced blockchain security features keep recorded and analyzed data secure. A case study demonstrates the proposed approach’s efficacy in smart catastrophe management with the best training and testing accuracy of 97.23% and 95.58%, respectively. IEEE
publications-5118	Conference paper	2023	Smerdon A.; Cook G.	A Retrofittable Instrument to Monitor and Record Strain on Subsea Structures	Proceedings of the Annual Offshore Technology Conference	10.4043/32611-MS	In mature offshore hydrocarbon fields, an increasing number of aging assets have reached or exceeded design life, meaning fatigue is of growing concern. Digital twins incorporating a fatigue model are typically used to assess structural integrity and inform decisions on life of field extension. However, they rely on idealized wave models which cannot truly reflect the hydrodynamic loading, which leads to uncertainty and conservatism. The operator of the Ninian Southern Platform in the UK North Sea concluded that if strain could be monitored in situ at key subsea locations, they could develop a more accurate relationship between sea conditions and structural loading, which could be used to calibrate the asset fatigue model, providing enhanced understanding of the jacket integrity. We describe the development, validation, installation, and first field results from an instrument designed to meet that challenge. Retrofitting strain sensors to subsea structural members presents many technical challenges, as neither conventional strain gauges nor cabled connections are feasible in the harsh subsea environment. For the first deployment, the instrumentation required robust attachment to a 1.2 m diameter tubular member situated at 43 m depth, which would withstand 100-year metocean maxima. It needed a strain transfer mechanism for autonomous measurement of the smallest fatigue-inducing strain reversals on three quadrants of the tubular over a two-year period. Strains were to be continuously sampled and recorded at a sufficient rate to accurately capture the peak values. Additionally, accelerations in three axes and wave height derived from hydrostatic pressure were to be monitored. The whole package had to be installed by ROV, and needed to deliver periodic data downloads throughout the life of the instrument. At the heart of the instrument is a set of environmentally packaged strain transfer mechanisms. These engage with the surface of the structure through spring-loaded actuators that are deployed by the ROV during installation. They allow strains to be measured directly by the instrumentβ€™s data acquisition system. These mechanisms were validated and calibrated using specially designed test equipment. Prior to deployment, the complete instrument, including its magnetic attachment system, was tested on a sample pipe section. All instrument subsystems were proven, including a high-speed optical data link for through-water transfer of recorded data, and an acoustic communication system for status updates. The instrument was successfully deployed subsea in April 2021, and one complete and continuous data set has already been retrieved. The data shows that the instrumentation is able to accurately capture a range Β© 2023, Offshore Technology Conference.
publications-5119	Conference paper	2023	Bozdal M.	Security through Digital Twin-Based Intrusion Detection: A SWaT Dataset Analysis	16th International Conference on Information Security and Cryptology, ISCTURKEY 2023 - Proceedings	10.1109/ISCTrkiye61151.2023.10336137	Digital twin, as a virtual replica of physical entity, offer valuable insights into Industrial Control System (ICS) behavior and characteristics. Leveraging the convergence of digital twins and cybersecurity, this research explores its role in securing critical infrastructure, using the Secure Water Treatment (SWaT) system as a case study. Existing intrusion detection systems (IDS) for SWaT encounter challenges related to requiring huge amounts of a dataset for training, being unable to adopt high data dimensionality, and adaptability to emerging threats. To address these issues, a hybrid digital twin model is proposed, combining physics-based models and data-driven approaches. This model facilitates precise attack localization and explainable IDS outcomes. The method exhibits promising capabilities for enhancing critical infrastructure security and adapting to evolving cyber threats. Experimental results demonstrate the ability to detect eight out of nine attack types. Β© 2023 IEEE.
publications-5120	Book	2023	Demirel Y.; Rosen M.A.	Sustainable Engineering: Process Intensification, Energy Analysis, and Artificial Intelligence	Sustainable Engineering: Process Intensification, Energy Analysis, and Artificial Intelligence	10.1201/9781003191124	Sustainable engineering is of great importance for resilient and agile technology and society. This book balances economics, environment, and societal elements of sustainable engineering by integrating process intensification, energy analysis, and artificial intelligence to reduce production costs, improve the use of material and energy, product quality, safety, societal well-being, and water usage. The book provides comprehensive discussion of topics on process intensification, energy analysis, and artificial intelligence that include optimization, energy integration, green engineering, pinch analysis, exergy analysis, feasibility analysis, life cycle assessment, circular economy, bioeconomy, data processing, machine learning, expert systems, digital twins, and self-optimized plants for sustainable engineering. Β© 2023 Taylor & Francis Group, LLC.