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 â–² Type Year Authors Title Venue/Journal DOI Research type Water System Technical Focus Abstract Link with Projects Link with Tools Related policies ID
publications-4981 Article 2023 Manocha A.; Sood S.K.; Bhatia M. Artificial intelligence-assisted water quality index determination for healthcare Artificial Intelligence Review 10.1007/s10462-023-10594-1 Groundwater resource analysis is an important technological means of avoiding disease and controlling water pollution. In this field of study, water quality assessments are conducted using sequential parametric values collected in real time. For evaluation reasons, several state-of-the-art water quality evolution mechanism typically employs a single time-invariant model to determine the quality of Water. As a result, it is challenging to illustrate the importance of randomness and contingency in the process of water quality assessment, leading to variations and errors in the procedure of quality assessment. In consideration of these limitations, this study proposes a Digital Twin inspired Hybrid System (DTHS) for water quality assessment in real time. In addition, the degree of water quality is offered as an indication for quantitatively assessing the health risk status. Observational data from a monitoring station in Chaheru, a locality in the Phagwara district of the Indian state of Punjab, are used to demonstrate the efficacy of the proposed approach. The experimental results demonstrate the effectiveness of the proposed framework in terms of water quality determination, computational cost, and stability. The framework has achieved higher prediction accuracy (94.14%), sensitivity (93.74%), specificity (91.47%), and f-measure (92.37%), indicating its ability to accurately determine water quality. Additionally, the framework offers reduced computational delay and improved reliability and stability, making it a trustworthy solution for timely predictions with respect to water quality. Β© 2023, The Author(s), under exclusive licence to Springer Nature B.V.
publications-4982 Conference paper 2024 Kuriakose R.B.; Mokotjo H.J. Implementing Tactile Internet Using 5G Network for Cloud Manufacturing in a PLC-Driven Water Bottling Plant Lecture Notes in Networks and Systems 10.1007/978-981-99-8346-9_29 Key characteristics of a smart manufacturing environment are system automation, data storage, remote monitoring, prediction of bottlenecks, and the ability to interrupt a physical system using digital twins. Over the years, automation of smart factories has been achieved through the implementation of Tactile Internet using 3G/4G/LTE network. However, high latency, low bandwidth, limited network access, and minimal device density are some of the barriers which increase production time and in turn limit the adaptation of smart factories in time-sensitive applications. Research shows that the introduction of 5G as a network link between the physical system and cloud storage could address long-existing challenge of high latency, low bandwidth, minimal device density, and limited network access. However, there is limited research on the feasibility of this implementation and the actual results thereof. This article showcases an experimental setup to implement a 5G network link between the cloud and a water bottling plant driven by Programmable Logic Controllers, which is currently operating on a 4G network. The hypothesis is that, with the implementation of 5G, there will be a decreased production time owing to minimal latency, improved data transmission capacity, and a broader network access though cloud storage. Β© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
publications-4983 Article 2024 Curtis C.; Goodburn C. Help Wanted: Job Descriptions for Digital Workers in the Water Industry Journal - American Water Works Association 10.1002/awwa.2215 The water industry needs updated job descriptions, not just for positions requiring digital expertise but to cultivate a digital workforce that expects to learn new skills over time. Novel technologies such as digital twins, drones, and virtual reality training require new job classifications for digital workers in the water sector, now and in the future. To meet water workforce challenges like employee retention and retirements, accurate job announcements can help utilities fill vacancies faster and maintain a professionally agile staff. Β© 2024 American Water Works Association.
publications-4984 Article 2024 Liu B.; Yang L.; Cui C.; Wan W.; Liang S. Is water replenishment an effective way to improve lake water quality? Case study in Lake Ulansuhai, China Frontiers in Environmental Science 10.3389/fenvs.2024.1392768 Lakes are an important component of the global water cycle and aquatic ecosystem. Lake water quality improvement have always been a hot topic of concern both domestically and internationally. Noncompliant outflow water quality frequently occurs, especially for lakes that rely mainly on irrigation return flow as their water source. External water replenishment to improve the water quality of lakes is gradually being recognized as a promising method, which however, is also a controversial method. Lake managers, in the case of constant controversy, hesitate about the appropriateness of lake water replenishing. Thus, taking Lake Ulansuhai in China as an example, this study aimed to construct a lake hydrodynamic and water quality model, under the constraint of multiple boundary conditions, that has sufficient simulation accuracy, and to simulate and analyze the changes in COD (Chemical Oxygen Demand) and TN (Total Nitrogen) concentrations in the lake area before and after water replenishment, and explore whether water replenishment was an effective method for improving lake water quality. The results showed that when the roughness value of Lake Ulansuhai was 0.02, the TN degradation coefficient K was 0.005/d, and the COD degradation coefficient K was 0.01/d; the simulation and measured values had the best fit, and the built model is reasonable and reliable can be used to simulate lake water quality changes. By external water replenishment lasting 140Β days in the water volume of 4.925 Γ— 108Β mΒ³, the COD and TN concentrations in Lake Ulansuhai could be stabilized at the Class V water quality requirement, which helped improve the self-purification ability of the lake area. Water replenishment was proved to be an effective method for improving the water quality of the lake, but water replenishment is only an emergency measure. Lake water replenishment is more applicable to areas with abundant water resources. External source control and internal source reduction of lake pollution and protection of lake water ecology are the main ways to improve lake water quality for water-deficient areas under the rigid constraints of water resources. In the future, key technologies for reducing and controlling pollution in irrigation areas, construction of lake digital twin platforms, and active promotion of lake legislation work should be the main research direction for managing the lake water environment. Copyright Β© 2024 Liu, Yang, Cui, Wan and Liang.
publications-4985 Article 2023 Ambarita E.E.; Karlsen A.; Osen O.; Hasan A. Towards fully autonomous floating offshore wind farm operation & maintenance Energy Reports 10.1016/j.egyr.2023.09.148 Wind energy is one of the most versatile and promising sustainable energy solutions. Wind energy can be harvested in both onshore and offshore environments. Due to the environmental and societal impacts of onshore wind farms, the focus on developing offshore wind farms has been steadily increasing. For deep-water areas, floating wind turbine solutions have been developed in the past two decades. Each wind turbine is mounted on a floating structure and connected to a mooring system. While the floating wind turbine technology enables electricity generation in water depths where fixed-foundation turbines are not feasible, operation and maintenance (O&M) have become serious issues. This paper investigates the challenges and potential enabling technologies for the development of autonomous floating offshore wind farms. In particular, the paper explores the potential utilization of information and communication technology (ICT) and robotics toward fully autonomous floating offshore wind farm O&M, aiming for cost reduction and improved operational safety. The presented solutions cover fundamental aspects in floating platform design, remote operation in the form of digital twins, autonomous underwater robots and surface vehicles, and eco-friendly energy storage. Β© 2023 The Authors
publications-4986 Article 2024 Olsson D.; Filipsson P.; Trüschel A. Weather Forecast Control for Heating of Multi-Family Buildings in Comparison with Feedback and Feedforward Control Energies 10.3390/en17010261 Our joint environmental and energy commitments mean we must reduce the building’s energy use. Improved central heating control can play a role in how this is accomplished. There are three common control strategies: feedforward (traditional), feedback, and model predictive control (MPC). The latter two often work in parallel, where feedback uses indoor temperature sensors to adjust the supply water temperature. In contrast, the supply temperature setpoint is continuously calculated in MPC, fed with weather forecasts. The weather forecasts are often highlighted as essential ingredients in MPC, but at the same time, it is emphasized that temperature sensors are used to ensure a pleasant indoor temperature. To an outside observer, it is difficult to determine what is what in such combined control arrangements. Is energy saved because of the room sensors or because of the model? And what role do the weather forecasts play? This study quantifies the impact of the control strategy on energy use and indoor temperature. It concludes that PI-based feedback heating control saves approximately as much energy as MPC, and weather forecasts do not save significantly more energy than real-time weather data but are easier to obtain. The overall results for both control strategies align with the lower end of the result ranges of previous studies. The novelty is that the impact of weather forecasts has been studied separately and that different control strategies are compared against each other based on a model of a typical Swedish multi-family building. © 2024 by the authors.
publications-4987 Review 2024 Liu H.; Su H.; Li H. Study on Digital Twin Technologies for Watershed Information Modeling (WIM): A Systematic Literature Review and Bibliometric Analysis Archives of Computational Methods in Engineering 10.1007/s11831-023-09977-y Digital Twin (DT) concept has recently emerged in civil engineering; however, there are fewer applications in water conservancy and hydropower engineering, especially for smart integrated management at the watershed scale. Therefore, this study aims to gather relevant literature on the digital twin in the infrastructure domain and to review and analyse the key technologies and the current state of their integrated application from a pathway to implementation perspective. The review conducted a Systematic Literature Review (SLR) and Bibliometric-qualitative Analysis (BQA) to identify a developing base of digital twins for smart watersheds. The related research gaps were identified from the analysis regarding information integration, alignment of BIM + processes to constructor business processes and the effective governance and value of information. From this, a novel Watershed Information Modeling (WIM) research strategy utilizing a framework for BIM + and information governance coupled with knowledge-driven decision-making is outlined to further progress the smart watersheds. Β© 2023, The Author(s) under exclusive licence to International Center for Numerical Methods in Engineering (CIMNE).
publications-4988 Conference paper 2024 Zhang J.; Wang G.; Chen Y.; Tian S.; Zhao X. Digital Design of Intelligent Plant Based on Reverse Engineering Lecture Notes in Electrical Engineering 10.1007/978-981-97-0665-5_33 Digital technology is widely used in new projects of intelligent plant, but it is rarely used for renovation projects, especially industrial renovation projects. The industrial projects not only involve the civil works, water supply and drainage, electrical, heating and ventilating disciplines, but also involve process equipment and process pipelines. The disciplines are numerous and complex. Especially some renovation projects require that the production is not stopped during the renovation process, that makes renovation project more difficult. In this paper digital technology was adopted, the architectural digital twin model were created. Besides, the simulation of reconstruction and construction organization were carried out based on the digital twin model. Therefore, some unforeseen problems in the implementation process could be avoided. Finally digital delivery was achieved. It can provide data model support for later operation of intelligent plant, and promote the digital transformation strategy of companies. Β© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
publications-4989 Article 2024 Li Y.L.; Tsang Y.P.; Wu C.H.; Lee C.K.M. A multi-agent digital twin–enabled decision support system for sustainable and resilient supplier management Computers and Industrial Engineering 10.1016/j.cie.2023.109838 Industry 4.0 is reshaping the manufacturing landscape, bringing about revolutionary changes in both product manufacturing and collaborative interactions among value chain constituents. Within the manufacturing value chain process, sustainable and resilient supplier management is recognized as a strategic endeavor that drives value creation, such as enhanced product quality, risk mitigation, and improved organizational reputation. Sustainable and resilient supplier management processes necessitate the integration of multiple criteria, efficient supplier coordination, and adaptability to evolving challenges. Nonetheless, conventional supplier management practices primarily rely on expert judgment, focus on the present situation, and lack a robust decision validation mechanism, leading to a limited capability to constitute proactive managerial decision-making under uncertainty. This paper introduces a digitally enabled decision support system for facilitating an intelligent and customized supplier management process in dynamic and complex environments. The system leverages stratified fuzzy decision-making techniques to account for the potential impacts of future events. Additionally, it integrates multi-agent digital twin technology to provide a reliable validation mechanism for assessing the effectiveness of supplier development strategies. The effectiveness of the proposed system was demonstrated through its successful implementation within a multinational solar water pump manufacturing company, highlighting its promising potential for practical applications. © 2023
publications-4990 Conference paper 2023 Tang H.; Feng J.; Zhou S. Generic Ontologies for Digital Watersheds ACM International Conference Proceeding Series 10.1145/3659211.3659257 Digital Watershed represents an effective strategy for addressing floods and mitigating their associated risks. However, a notable challenge lies in the absence of a universally applicable modeling approach for constructing digital watersheds. The wealth of data and knowledge about watersheds is currently managed in a fragmented manner, impeding a comprehensive and cohesive understanding of the subject. This paper addresses the fragmented control landscape in watershed management by introducing generic ontologies, including water conservancy object ontology, model ontology, rainfall and runoff scene-mode ontology, and event ontology. These ontologies standardize the representation of water conservancy objects, hydrological models, and expert knowledge while also defining structured representations for physical events, scheduling rules, and business processes, which contribute to breaking the paradigm of "one watershed, one system"and facilitate integrated flood prediction and scheduling. Β© 2023 ACM.