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Energies
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Integration of Water Systems for Energy-Efficient and Sustainable Environment
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Integration of Water Systems for Energy-Efficient and Sustainable Environment

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "B: Energy and Environment".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 3331

Special Issue Editors

Prof. Dr. Sanghyun Kim

E-Mail Website
Guest Editor
Department of Environmental Engineering, Pusan National University, Busan, Republic of Korea
Interests: watershed hydrology; hillslope hydrology; pipeline hydraulics; water quality modeling; leakage detection in pipeline systems
Dr. Seong Jin Noh

E-Mail Website
Guest Editor
Department of Civil Engineering, Kumoh National Institute of Technology (KIT), Gumi, Republic of Korea
Interests: integrated hydrologic modeling; data assimilation; urban flood and water cycle; climate-adaptive water resources management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Water system research requires interactions between modelling and validation processes. Current water system research tends to focus on the practical aspects as well as the process-based implementation to understand the system behavior. The energy efficiency and sustainable environment in water systems are an important contemporary issue for system managers in the context of practical application. Communication between field conditions and modelling procedures has evolved not only to maximize the reality in the cyber world (e.g., data assimilation, digital twins, and smart water systems), but also to virtually obtain energy efficiency and environmental sustainability for real-life systems. The topics for this Special Issue are as follows:

  • Urban water systems;
  • Smart water in watershed;
  • Digital twins in hydro-systems;
  • Artificial intelligence in water systems;
  • Design, optimization, and management of pipeline systems;
  • Metaverse in hydro-systems;
  • Water systems for sustainable environment;
  • Energy efficiency.

The aim of the Special Issue is to discuss relevant studies on topics described above to highlight trends and challenges for the integration of water systems aiming at energy efficiency and environmental sustainability through an interdisciplinary approach including hydrology, hydraulics, water quality, hydrometeorology, water resources management, remote sensing and information technology. Original research papers presenting theoretical developments, field studies, and analyses related to environmental, social, economic and technical dimensions of water systems are welcome. Submissions of quantitative and qualitative approaches as well as review articles are strongly encouraged.

Prof. Dr. Sanghyun Kim
Dr. Seong Jin Noh
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • water systems
  • energy efficiency
  • cyber-physical systems
  • digital twins
  • information technology
  • sustainability
  • smart water

Published Papers (2 papers)

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Research

15 pages, 4889 KiB  
Article
Enhancing Tidal Wave Predictions for the Estuary of the Nakdong River Using a Fixed-Lag Smoother
by Hyeonjin Choi, Bomi Kim, Garim Lee and Seong Jin Noh
Energies 2023, 16(1), 237; https://doi.org/10.3390/en16010237 - 26 Dec 2022
Cited by 1 | Viewed by 1590
Abstract
The prediction of tidal waves is essential for improving not only our understanding of the hydrological cycle at the boundary between the land and ocean but also energy production in coastal areas. As tidal waves are affected by various factors, such as astronomical, [...] Read more.
The prediction of tidal waves is essential for improving not only our understanding of the hydrological cycle at the boundary between the land and ocean but also energy production in coastal areas. As tidal waves are affected by various factors, such as astronomical, meteorological, and hydrological effects, the prediction of tidal waves in estuaries remains uncertain. In this study, we present a novel method that can be used to improve short-term tidal wave prediction using a fixed-lag smoother based on sequential data assimilation (DA). The proposed method was implemented for tidal wave predictions of the estuary of the Nakdong River. As a result, the prediction accuracy was improved by 63.9% through DA and calibration using regression. Although the accuracy of the DA diminished with the increasing forecast lead times, the 1 h lead forecast based on DA still showed a 44.4% improvement compared to the open loop without DA. Moreover, the optimal conditions for the fixed-lag smoother were analyzed in terms of the order of the smoothing function and the length of the assimilation window and forecast leads time. It was suggested that the optimal DA configuration could be obtained with the 8th-order polynomial as the smoothing function using past and future DA assimilation windows assimilated 6 h or longer. Full article
(This article belongs to the Special Issue Integration of Water Systems for Energy-Efficient and Sustainable Environment)
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18 pages, 4513 KiB  
Article
Development of a Water Quality Event Detection and Diagnosis Framework in Drinking Water Distribution Systems with Structured and Unstructured Data Integration
by Taewook Kim, Donghwi Jung, Do Guen Yoo, Seunghyeok Hong, Sanghoon Jun and Joong Hoon Kim
Energies 2022, 15(24), 9300; https://doi.org/10.3390/en15249300 - 8 Dec 2022
Viewed by 1208
Abstract
Recently, various detection approaches that identify anomalous events (e.g., discoloration, contamination) by analyzing data collected from smart meters (so-called structured data) have been developed for many water distribution systems (WDSs). However, although some of them have showed promising results, meters often fail to [...] Read more.
Recently, various detection approaches that identify anomalous events (e.g., discoloration, contamination) by analyzing data collected from smart meters (so-called structured data) have been developed for many water distribution systems (WDSs). However, although some of them have showed promising results, meters often fail to collect/transmit the data (i.e., missing data) thus meaning that these methods may frequently not work for anomaly identification. Thus, the clear next step is to combine structured data with another type of data, unstructured data, that has no structural format (e.g., textual content, images, and colors) and can often be expressed through various social media platforms. However, no previous work has been carried out in this regard. This study proposes a framework that combines structured and unstructured data to identify WDS water quality events by collecting turbidity data (structured data) and text data uploaded to social networking services (SNSs) (unstructured data). In the proposed framework, water quality events are identified by applying data-driven detection tools for the structured data and cosine similarity for the unstructured data. The results indicate that structured data-driven tools successfully detect accidents with large magnitudes but fail to detect small failures. When the proposed framework is used, those undetected accidents are successfully identified. Thus, combining structured and unstructured data is necessary to maximize WDS water quality event detection. Full article
(This article belongs to the Special Issue Integration of Water Systems for Energy-Efficient and Sustainable Environment)
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