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-3951 article 2022 Thelen, Adam and Thelen, Adam and Zhang, Xiaoge and Zhang, Xiaoge and Fink, Olga and Fink, Olga and Lu, Yan and Lu, Yan and Ghosh, Sayan and Ghosh, Sayan and Youn, Byeng D. and Youn, Byeng D. and Todd, Michael D. and Todd, Michael D. and Mahadevan, Sankaran and Mahadevan, Sankaran and Hu, Chao and Hu, Chao and Hu, Zhen and Hu, Zhen A comprehensive review of digital twin β€” part 1: modeling and twinning enabling technologies Structural and Multidisciplinary Optimization 10.1007/s00158-022-03425-4 As an emerging technology in the era of Industry 4.0, digital twin is gaining unprecedented attention because of its promise to further optimize process design, quality control, health monitoring, decision and policy making, and more, by comprehensively modeling the physical world as a group of interconnected digital models. In a two-part series of papers, we examine the fundamental role of different modeling techniques, twinning enabling technologies, and uncertainty quantification and optimization methods commonly used in digital twins. This first paper presents a thorough literature review of digital twin trends across many disciplines currently pursuing this area of research. Then, digital twin modeling and twinning enabling technologies are further analyzed by classifying them into two main categories: physical-to-virtual, and virtual-to-physical, based on the direction in which data flows. Finally, this paper provides perspectives on the trajectory of digital twin technology over the next decade, and introduces a few emerging areas of research which will likely be of great use in future digital twin research. In part two of this review, the role of uncertainty quantification and optimization are discussed, a battery digital twin is demonstrated, and more perspectives on the future of digital twin are shared. Code and preprocessed data for generating all the results and figures presented in the battery digital twin case study in part 2 of this review are available on Github.
publications-3952 article 2022 El-Din, Mohamed Nour and Pereira, Pedro F. and Martins, João Poças and Ramos, Nuno M. M. Digital Twins for Construction Assets Using BIM Standard Specifications 10.3390/buildings12122155 Digital twins (DTs) are one of the latest technology trends in all industries. However, DT development in the architecture, engineering, and construction (AEC) industry is still in its infancy. Digital twins have been proposed as tools that can be applied to several challenges in various areas of the built environment. However, their widespread use is hampered due to the slow pace of digitization of the AEC industry, in addition to the absence of a formalized standard for digital twins’ implementation. We began this study by systematically reviewing publications related to DT applications in the AEC industry in four databases, resulting in 229 publications after applying the proposed criteria. The systematic review highlighted the lack of standardization for DTs in the AEC industry. Additionally, this study assessed the current status of DTs and analyzed the evolution of the concept of DTs in the AEC industry. We also proposed a conceptual framework for DT development for construction assets, using the existing BIM information management standards (i.e., ISO 19650) to promote a better interoperable digitalized built environment.
publications-3953 article 2022 Tiedmann, Helena R. and Tiedmann, Helena R. and Spearing, Lauryn A. and Spearing, Lauryn A. and Sela, Lina and Sela, Lina and Faust, Kasey M. and Faust, Kasey M. Mapping the Data Needs and Challenges of Hydraulic Model Development during a Crisis 10.1061/9780784484258.066 When crises occur (e.g., disasters, public health emergencies), water infrastructure systems are often forced to operate outside the conditions for which they were designed. Hydraulic models can provide utilities with essential information in a crisis, allowing for near real-time system performance evaluation and informing management response. However, hydraulic modeling remains inaccessible to many water utilities due to extensive data, software, and skilled personnel requirements. Data needs are particularly troublesome because the water sector lags behind other industries in embracing advanced data management and analytics. Researchers have outlined steps to increase data analytics in the water sector and put forth new data management systems in areas such as hydrology and asset management. Notably, a classification system for hydraulic modeling data needs has not been developed. To address this gap, we documented the development of a hydraulic model of the water distribution system serving the University of Texas at Austin. In this study, we (1) classify hydraulic modeling data needs, (2) demonstrate model applications in both a crisis scenario and routine system management, and (3) assess key challenges in modeling. We found that the model can provide helpful insight in a range of management scenarios (e.g., identifying areas of poor system performance), but data-related challenges such as lack of standardization and extensive processing requirements hinder model development. As such, we recommend policy changes that incorporate model development into emergency response plans, ensuring they are in place before a crisis occurs.
publications-3954 article 2021 Ramsey, Elizabeth and Ramsey, Elizabeth and Ramsey, E. and Berglund, Emily Zechman and Berglund, Emily Zechman Developing an Agent-Based Model of Dual-Flush Toilet Adoption Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0001454 AbstractThe spread of individual water conservation behaviors within a population can have large impacts on overall water demand. Agent-based models (ABMs) represent individual actors that update t...
publications-3955 article 2021 Opoku, De-Graft Joe and Opoku, De-Graft Joe and Perera, Srinath and Perera, Srinath and Osei–Kyei, Robert and Osei-Kyei, Robert and Rashidi, Maria and Rashidi, Maria Digital twin application in the construction industry: A literature review Journal of building engineering 10.1016/j.jobe.2021.102726
publications-3956 article 2020 Darbandsari, Pedram and Darbandsari, Pedram and Kerachian, Reza and Kerachian, Reza and Malakpour‐Estalaki, Siamak and Malakpour-Estalaki, Siamak and Khorasani, Hamed and Khorasani, Hamed An agent-based conflict resolution model for urban water resources management Sustainable Cities and Society 10.1016/j.scs.2020.102112
publications-3957 article 2020 Rahim, Shamsur and Rahim, Shamsur and Nguyen, Khoi and Nguyen, Khoi Anh and Nguyen, Khoi and Nguyen, Khoi and Nguyen, Khoi Anh and Stewart, Rodney Anthony and Stewart, Rodney Anthony and Giurco, Damien and Giurco, Damien and Blumenstein, Michael and Blumenstein, Michael Machine Learning and Data Analytic Techniques in Digital Water Metering: A Review Water 10.3390/w12010294 Digital or intelligent water meters are being rolled out globally as a crucial component in improving urban water management. This is because of their ability to frequently send water consumption information electronically and later utilise the information to generate insights or provide feedback to consumers. Recent advances in machine learning (ML) and data analytic (DA) technologies have provided the opportunity to more effectively utilise the vast amount of data generated by these meters. Several studies have been conducted to promote water conservation by analysing the data generated by digital meters and providing feedback to consumers and water utilities. The purpose of this review was to inform scholars and practitioners about the contributions and limitations of ML and DA techniques by critically analysing the relevant literature. We categorised studies into five main themes: (1) water demand forecasting; (2) socioeconomic analysis; (3) behaviour analysis; (4) water event categorisation; and (5) water-use feedback. The review identified significant research gaps in terms of the adoption of advanced ML and DA techniques, which could potentially lead to water savings and more efficient demand management. We concluded that further investigations are required into highly personalised feedback systems, such as recommender systems, to promote water-conscious behaviour. In addition, advanced data management solutions, effective user profiles, and the clustering of consumers based on their profiles require more attention to promote water-conscious behaviours.
publications-3958 article 2018 Du, Kui and Du, Kun and Ding, Rong-yi and Ding, Rong-yi and Wang, Zhi-Hao and Wang, Zhi-hao and Zhang, Song and Song, Zhi-gang and Xu, Bin and Xu, Bing-feng and Zhou, Ming and Zhou, Ming and Bai, Yun and Bai, Yun and Bai, Yun and Bai, Yun and Zhang, Jin and Zhang, Jin Direct Inversion Algorithm for Pipe Resistance Coefficient Calibration of Water Distribution Systems Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0000948 AbstractTo enable a water distribution system (WDS) model to yield predictions with a reasonably good match to measurements, pipe resistance coefficients (PRCs) of the model often need to be calibr...
publications-3959 article 2021 Steffelbauer, David and Steffelbauer, D. B. and Steffelbauer, David and Steffelbauer, David and Blokker, Mirjam and Blokker, Mirjam and Blokker, E. J. M. and Buchberger, Steven G. and Buchberger, Steven G. and Knobbe, Arno and Knobbe, A. and Knobbe, A. and Knobbe, A. and Knobbe, Arno and Abraham, Edo and Abraham, Edo Dynamic Time Warping Clustering to Discover Socioeconomic Characteristics in Smart Water Meter Data Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0001360 AbstractSocioeconomic characteristics are influencing the temporal and spatial variability of water demand, which are the biggest source of uncertainties within water distribution system modeling. ...
publications-3960 article 2020 Lin, Zhulu and Lin, Zhulu and Lim, Siew Hoon and Lim, Siew Hoon and Lin, Tong and Lin, Tong and Borders, Michael and Borders, Michael Using Agent-Based Modeling for Water Resources Management in the Bakken Region Journal of Water Resources Planning and Management 10.1061/(asce)wr.1943-5452.0001147 AbstractMost agent-based model (ABM) applications in water resources management and planning relied on hypothetical systems for method testing and policy analysis. Although these ABM studies can he...