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 Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-4871 Book chapter 2024 Priya P.K.; Reethika A. A Review of Digital Twin Applications in Various Sectors Transforming Industry using Digital Twin Technology 10.1007/9783031585234_12 The concept of digital twin (DT) has rapidly progressed from a theoretical concept to a practical application, with widespread adoption across multiple sectors. This chapter explores sectors like manufacturing, energy, healthcare, transportation, construction, aerospace industry, and smart cities where digital twin knowledge is being used and highlights its various applications. In the manufacturing sector, digital twins are employed to improve product quality, enhance production processes, and predict equipment failures. In the energy sector, digital twins enhance the efficiency of energy systems, predict maintenance needs, and reduce energy consumption. In healthcare, digital twins are used to create tailored patient models, simulate surgical procedures, and optimize treatment plans. In transportation, digital twins optimize logistics and reduce delivery times. In construction, they help improve project management, reduce errors, and enhance safety. In agriculture, digital twins optimize crop yields and resource management, enabling farmers to make more informed decisions about water usage, fertilizer application, and pest control. In the aerospace industry, digital twins monitor the performance of aircraft, predict maintenance needs, and improve safety. This technology reduces maintenance costs and enhances overall aircraft reliability. In smart cities, digital twins enhances various aspects of city life, such as controlling traffic flow, minimizing energy consumption, and improving public safety. Planners can test different scenarios and maximize resources for effective and environmentally friendly city living. While digital twin technology offers numerous benefits, its implementation requires a significant investment in infrastructure, data management, and expertise. These factors present challenges to widespread adoption. Despite the challenges, this chapter analyzes how digital twin technologies have the potential to revolutionize a variety of industries by giving real-time information, lowering costs, optimizing processes, and improving safety. Β© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
publications-4872 Conference paper 2024 Zamora-Sanchez D.; Armijo A.; Fernandez M.; Lochner A.; Jimenez J.C.; Arregi B. Modular Real-Time Monitoring System Architecture for Materials and Technologies to Improve Urban Heat-Island Effect and Water Runoff in HE MULTICLIMACT 2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024 - Proceedings 10.1109/MetroLivEnv60384.2024.10615312 Given the threat of climate change and the associated growth in extreme events, it is imperative to improve the planning, design, and upgrading of the built environment at different scales to effectively adapt to current and future risks. Therefore, the MULTICLIMACT project (MULTI-faceted CLIMate adaptation ACTions to improve resilience, preparedness, and responsiveness of the built environment against multiple hazards at multiple scales) seeks to provide an integrated framework of tools to assist public actors and citizens at territorial, urban and individual building levels. At all these scales, real-time monitoring and early warning systems are seen as key tools to improve preparedness and responsiveness. At the urban level, the scale of this paper, it is considered a key issue that the built environment is nowadays often itself a source of climate vulnerability rather than a safe place for its inhabitants. Based on these two key points, this contribution focuses on the design of a modular real-time monitoring system architecture, combining Internet of Things (IoT) sensor networks, signal processing, Artificial Intelligence (AI) data analysis and Building Information Modeling (BIM) visualization, along with selection or development of sensors for cost-effective monitoring of the specific solutions to be implemented in the urban scale within MULTICLIMACT, namely new optimized cool urban pavement and nature-based solutions (NBS) designs to mitigate the heat-island effect and surface runoff, both identified as major risks in Europe's hot Mediterranean cities with low seismic risk, such as Barcelona (BCN), the future pilot city for the deployment of these solutions. Β© 2024 IEEE.
publications-4873 Article 2024 Park S.H.; Koo J.; Park Y.-J.; Jang S.; Ryu H.J.; Han H.; Lee K.T. Uniformly scalable and stackable porous transport layer manufactured by tape casting and calendering for efficient water electrolysis Chemical Engineering Journal 10.1016/j.cej.2023.148276 Proton exchange membrane water electrolysis (PEMWE) stands out as the most promising and eco-friendly technology for directly converting renewable energy into hydrogen. A critical element within a PEMWE cell is the porous transport layer (PTL), typically constructed from Ti to withstand the rigorous conditions of water electrolysis. Herein, we present a cost-effective and viable fabrication process for Ti-PTLs, utilizing tape-casting method in combination with a lamination-roll calendering procedure, facilitating precise thickness control. By systematical fine-tuning the debinding conditions, we obtained a phase-pure Ti-PTL endowed with a highly-interconnected pore structure. A comprehensive analysis of digitally twinned Ti-PTL, constructed through a state-of-the-art three-dimensional (3D) reconstruction process, reveals a remarkable uniformity in the open pore structures across Ti-PTLs of varying thicknesses, highlighting their considerable practical potential. Furthermore, the electrochemical performance of PEMWE cells using our Ti-PTLs surpassed that of the benchmark commercial Ti-PTL, demonstrating the significant promise of our tape-casting process followed by lamination-roll calendering procedure in practical Ti-PTL fabrication. Β© 2023 Elsevier B.V.
publications-4874 Book chapter 2024 Farzana Tasneem M.I.; Achar P.V. Journey to cyber-physical agricultural systems digitalization and technological evolution Agri 4.0 and the Future of Cyber-Physical Agricultural Systems 10.1016/B978-0-443-13185-1.00001-0 Digital technologies are pervasive, portable, and mobile, and they are revolutionizing agricultural and food production. There is no denying that the agricultural sector is undergoing a digital transformation as mobile technologies, remote sensing services, and distributed computing are already improving smallholders’ access to information, inputs, and markets, increasing manufacturing and productivity, smooth supply chains, and embracing technology costs. The Indian economy heavily depends on agriculture. Over 60% of Indians work in agriculture, which also accounts for one-third of the nation’s income and contributes significantly to the development of the nation. Digitalization has had an impact on agricultural and food production systems, allowing for the use of technologies and advanced data processing techniques in the agricultural field. The goal is to provide a comprehensive understanding of the various effects of digital technologies on society through a framework that aims to provide a deeper understanding of the relationship between the physical, cyber and social strategies for successfully implementing the digital transformation of a system. Using an agriculture cyber-physical systems makes agriculture smarter, which connect Internet of Things with other technologies like artificial intelligence (AI) and machine learning can aid in boosting crop yields, decreasing water waste, and lowering fertilizer usage, a range of agricultural factors that have a direct impact on crop selection. Second, it transmits this data to a server that uses it to forecast farm-ready yields. Digital farming aims to solve several existing challenges in food security, climate protection, and resource management by utilizing available information from agricultural assets. The use of digital techniques is anticipated to increase optimization and decision-making support. It covers a broad framework of digital twins in agricultural fields, including soil, irrigation, robotics, farm equipment, and food postharvest processing. Data collection, modeling, including big data, AI, simulation, analysis, and prediction as well as communication components of the digital twin in agriculture are explored. As the next phase of the digitalization paradigm, digital twin technologies can assist farmers by continuously and in real-time monitoring the physical world (the farm) and updating the state of the virtual world. The potential of digital technologies to transform the agricultural and rural sectors is often seen as a promising opportunity in various aspects of society. © 2024 Elsevier Inc. All rights reserved.
publications-4875 Article 2024 Särestöniemi M.; Singh D.; Dessai R.; Heredia C.; Myllymäki S.; Myllylä T. Realistic 3D Phantoms for Validation of Microwave Sensing in Health Monitoring Applications Sensors 10.3390/s24061975 The development of new medical-monitoring applications requires precise modeling of effects on the human body as well as the simulation and the emulation of realistic scenarios and conditions. The first aim of this paper is to develop realistic and adjustable 3D human-body emulation platforms that could be used for evaluating emerging microwave-based medical monitoring/sensing applications such as the detection of brain tumors, strokes, and breast cancers, as well as for capsule endoscopy studies. New phantom recipes are developed for microwave ranges for phantom molds with realistic shapes. The second aim is to validate the feasibility and reliability of using the phantoms for practical scenarios with electromagnetic simulations using tissue-layer models and biomedical antennas. The third aim is to investigate the impact of the water temperature in the phantom-cooking phase on the dielectric properties of the stabilized phantom. The evaluations show that the dielectric properties of the developed phantoms correspond closely to those of real human tissue. The error in dielectric properties varies between 0.5–8%. In the practical-scenario simulations, the differences obtained with phantoms-based simulations in S21 parameters are 0.1–13 dB. However, the differences are smaller in the frequency ranges used for medical applications. © 2024 by the authors.
publications-4876 Article 2024 Zhang S.; Zhang Y.; Wang C.; Wang X.; Yang X.; Liang L.; Zhang L.; Liu M. Digital twin engine construction method for the operation management of water diversion and transfer project pumping station groups; [引调水工程泵站群运θ΅_x008c_η®΅ζ_x008e_§ζ•°ε­—ε­η”_x009f_εΌ•ζ“_x008e_ζ_x009e_„建方法] Qinghua Daxue Xuebao/Journal of Tsinghua University 10.16511/j.cnki.qhdxxb.2024.26.035 [Objective] Digital twin technology can improve the quality of operation management of pumping station groups in water diversion and transfer projects. However, the current application of digital twin technology in the operation management of pumping station groups remains exploratory. Moreover, certain problems persist, such as difficulties ensuring the operational performance of digital twin scenes and combining the integration of data, knowledge, and models with business, all of which hamper the application of digital twin technology. To bridge this gap, this study constructs a six-dimensional theoretical model and basic framework of a digital twin engine and proposes a high-performance digital twin engine construction method in combination with the business requirements of a pumping station group's operation management. [Methods] In terms of theoretical modeling, this paper divides the critical elements of a digital twin engine into six aspects: Physical scenes, twin scenes, services, twin data, connections, and feedback and decision-making. These elements are interrelated, thus mapping the physical scenes into twin scenes and realizing the digital twin engine's dynamic operation and virtual-real integration through services, twin data, and connections. On the basis of the theoretical model, the digital twin engine framework combines the business elements of the pumping station group's operation management. These include data collection, data storage, support, function, and display layers, which provide a data foundation, operation environment, functionservices, andinteraction windowfortheengine. Furthermore, thedigitaltwinengineconstruction methodincludesthe followingfive aspects: Twin scene generation engine, data management engine, dynamic virtual-physical mapping engine,operationsimulation and analysis engine, and realityinteraction and feedback control engine. In particular, the twin scenes generation engine generates high-performance and smooth twin scenes through lightweight BIM processing and data-knowledge-modelfusion. The data management engine builds a multiprecision, full-factor twin data resource pool. The dynamic virtual-physical mapping engine realizes real-time and dynamic iterative updating of physical scenes in twin scenes.Moreover, the operationsimulation and analysis engine supports the core business capability of the pumping station group's operation management by providing program recommendations, operation process preview, performance analysis, and other capabilitiesfor the pumping station group. The reality interaction and feedback control engine also provides the pumping station group with operational decision-making capability and a safe control environment. [Results] In practical applications through engineering cases, the digital twin engine was mainly constructed in the browser/server mode, with the desktop application as a supplement. Theresultsrevealedthatthe digitaltwinengineeffectivelysupportedthe pumpingstation group's operational management business requirements. It was found that the operation optimization capability saved 4.14% in operationcosts and 1 .59 % in energy consumption while maintaining high operation efficiency. Simultaneously, the operation scheme generated by the engine enabled a simulation preview of the entire operation process, accompanied by high-performance dynamic virtual-physical mapping. The dynamic virtual-physical mapping engine and timing database significantlyreduced the response time of data mapping, maintaining the response time for 10 000 data mappings within 300 ms. Furthermore, after undergoinglightweight processing, thetwinscene maintaineda highrunningframerate, whether deployed as a desktop application or a web-based application. Interms ofcomputerresourceconsumption, when performing a simultaneous simulation preview and utilizingthe weather system, a substantial amount of data and particle effects needed to be processed, necessitating a high-performance computer graphics processor. In contrast, digital twin engines typically operated underlow-performance stress conditions and did not demand high computer performance. [Conclusions] This work providestheoretical and methodological support, as well as serves as a practical reference, to help construct a digital twin enginethattargetsthe operation management of pumping station groupsin water diversion projects. Nonetheless, this paper describes adigitaltwinengineconstruction methodthat marksa preliminarystepinintegrating data, mechanisms, algorithms, and knowledge specific to pumping station group systems in water diversion projects. Future research should focus on enhancingthe engine's performance, determiningcomprehensiveenginefunctionsthatarecustomizedto meet various business needs, and exploringthe applications of deep mining multimodel coupling. Β© 2024 Tsinghua University. All rights reserved.
publications-4877 Article 2024 Djebko K.; Weidner D.; Waleska M.; Krey T.; Rausch S.; Seipel D.; Puppe F. Integrated Simulation and Calibration Framework for Heating System Optimization Sensors 10.3390/s24030886 In a time where sustainability and CO2 efficiency are of ever-increasing importance, heating systems deserve special considerations. Despite well-functioning hardware, inefficiencies may arise when controller parameters are not well chosen. While monitoring systems could help to identify such issues, they lack improvement suggestions. One possible solution would be the use of digital twins; however, critical values such as the water consumption of the residents can often not be acquired for accurate models. To address this issue, coarse models can be employed to generate quantitative predictions, which can then be interpreted qualitatively to assess β€_x009c_better or worseβ€_x009d_ system behavior. In this paper, we present a simulation and calibration framework as well as a preprocessing module. These components can be run locally or deployed as containerized microservices and are easy to interface with existing data acquisition infrastructure. We evaluate the two main operating modes, namely automatic model calibration, using measured data, and the optimization of controller parameters. Our results show that using a coarse model of a real heating system and data augmentation through preprocessing, it is possible to achieve an acceptable fit of partially incomplete measured data, and that the calibrated model can subsequently be used to perform an optimization of the controller parameters in regard to the simulated boiler gas consumption. Β© 2024 by the authors.
publications-4878 Article 2024 Di Gregorio S.; Lupiano V.; Forno F.; Calidonna C.R.; Catelan P.; Chidichimo F. A Transdisciplinary Analysis of the 2009 Catastrophe in Giampilieri Superiore by Land Use Evolution Over Time Earth Systems and Environment 10.1007/s41748-024-00454-5 On October 1 2009 a deluge hit the Peloritani Mountains, in NE Sicily, Italy, where the rainfall data recorded 225 mm in 9 h. Giampilieri Superiore was the most affected townlet in terms of infrastructural damages and human losses (37 dead, 37 wounded, and more than 1000 evacuees). The debris flows, triggered by flash floods wreaked havoc of the urban structure. More than 200 mln € was granted to protection works for conveying water and debris flows to bypass the town. The disaster was numerically simulated by SCIDDICA (Digital Twin) with excellent approximation, and the effects of the safety installation were tested as well, proving to offer sufficient protection for the village. The Peloritani area overlooking the Ionian See flourished during the Saracen domination, whose legacy of systems of terraces, cisterns and wells guaranteed the finest water management in steep terrains, allowing a safe emplacement of watermills, around which Giampilieri and other villages developed. This hydraulic legacy has been undermined during the last decades due to lack of appropriate maintenance because of the progressive loss of the Saracen culture. It is unconceivable that subsidies on the scale granted to Giampilieri are sustainable when facing innumerable future climatic disasters. A cheaper and more viable solution is to be found, e.g., the settlement of immigrants in the area, promoting the labor-social inclusion of those persons who already possess such a Saracen culture or are willing to acquire it from the last local depositaries, according to a retro-innovation perspective and methodology. © The Author(s) 2024.
publications-4879 Conference paper 2024 Lee A.; King K.; GraΔ_x008d_anin D.; Azab M. Experiential Learning Through Immersive XR: Cybersecurity Education forΒ Critical Infrastructures Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 10.1007/978-3-031-61382-1_4 In our modern digital world, where virtually everything is intertwined with computer systems, critical infrastructures face vulnerability to a variety of cyber-attacks, stemming from the absence of a cybersecurity mindset within these establishments. We need to efficiently educate these workers about the cybersecurity threats that exist, their potential effects, and the subsequent substantial impact on human populations. Previous research has suggested traditional non-interactive training methods are often not effective. We propose an interactive learning experience that incorporates Extended Reality, Digital Twins, and Artificial Intelligence (AI) to help workers become more aware of cybersecurity issues within their critical infrastructure. This paper introduces an innovative testbed that seamlessly integrates Artificial Intelligence (AI) and Large Language Models to create an immersive educational experience. The goal is to effectively convey complex technical concepts to users with limited background knowledge on the subject. Our specific focus lies in addressing the need for proper cybersecurity training among water treatment plant employees. The testbed presented is meticulously crafted to provide users with a tangible representation of the potential outcomes resulting from successful cyber attacks on such facilities. Through this approach, we aim to enhance the educational process and promote a deeper understanding of cybersecurity challenges in critical infrastructure like water treatment plants. Β© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
publications-4880 Conference paper 2024 Camps A.; LΓ³pez-MartΓ­nez C.; Gonga A.; Gracia G.; Perez-Portero A.; Alonso-Gonzalez A.; Vall-Llossera M.; Park H.; Perez V.; Caselles O.; Domenech C.; Catala P.; Ruiz-De-Azua J.A.; Solsona M. AI4WATER: A Digital Twin for Irrigated Agriculture International Geoscience and Remote Sensing Symposium (IGARSS) 10.1109/IGARSS53475.2024.10641740 This study presents a Digital Twin (DT) that is being created to optimize the use of the available hydric resources, and mitigate the effects of the increasing water shortage in irrigated agriculture in fields in the Urgell channel region (Lleida). A DT is "a virtual representation of an object or system that spans its lifecycle, it is updated from real-time data, and uses simulation, machine learning and reasoning to help decision-making."It will model the water fluxes using the knowledge of the amounts of water taken in, used, and returned to the environment, and other parameters that impact the water budget, such as atmospheric variables (temperature, water vapor deficit, relative humidity, solar radiance...), surface soil moisture, and evapotranspiration maps, etc. Satellite Earth Observation (EO) data, collocated with in-situ data from a network of 20 soil moisture probes and 2 meteo stations will be used to train the DT. Additionally, a rover-based ground penetrating radar will be used for cross-calibration. Β© 2024 IEEE.