Artificial Intelligence in Water Resources Management

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: 31 May 2024 | Viewed by 3316

Special Issue Editors


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Guest Editor
Department of Civil Engineering and Construction, Faculty of Engineering and Design, Atlantic Technological University, Sligo, Ireland
Interests: water resources management; hydrology; climate change; machine learning techniques; multi-objective optimization

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Guest Editor
College of Engineering and Science, Victoria University, Melbourne 8001, Australia
Interests: urban water management; resilient urban water systems hydrologic and hydraulic modeling; hydroinformatics
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Guest Editor
School of Engineering and Computing, University of Central Lancashire, Fylde Rd, Preston PR1 2HE, UK
Interests: climate change; GIS; coastal vulnerability; geo hazards; geomorphology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Artificial intelligence (AI) plays an important role in predicting the majority of non-linear scenarios in engineering applications. Out of them, water resources management is significant due to its non-linear applications, including flash floods, drinking water supply, wastewater treatment, hydropower development, irrigation, etc. Therefore, the usage of AI systems in water resources management is quite popular in today’s world. Nevertheless, the research depth of AI is being further developed along with new advances, including the expandability of AI. Therefore, the outcomes are evolving, and better solutions to non-linear systems in water resources management are being promoted. Therefore, this Special Issue proposes to publish novel research views of AI in water resource management and to form a discussion forum where researchers can share their state-of-the-art findings.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  1. Prediction of flash floods under changing climatic scenarios;
  2. Natural disasters involved in hydrological cycle;
  3. Irrigation water management;
  4. Hydropower development under climatic scenarios;
  5. Drinking water supply systems;
  6. Energy enhancing through water supply systems;
  7. Wastewater system management;
  8. Wastewater treatment operation.

We look forward to receiving your contributions.

Dr. Upaka Rathnayake
Dr. Nitin Muttil
Dr. Komali Kantamaneni
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. Water 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

  • machine learning approaches
  • expandability
  • soft computing approaches
  • water resources

Published Papers (1 paper)

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Review

26 pages, 2306 KiB  
Review
Artificial Intelligence Technologies Revolutionizing Wastewater Treatment: Current Trends and Future Prospective
by Ahmed E. Alprol, Abdallah Tageldein Mansour, Marwa Ezz El-Din Ibrahim and Mohamed Ashour
Water 2024, 16(2), 314; https://doi.org/10.3390/w16020314 - 17 Jan 2024
Cited by 1 | Viewed by 2968
Abstract
Integration of the Internet of Things (IoT) into the fields of wastewater treatment and water quality prediction has the potential to revolutionize traditional approaches and address urgent challenges, considering the global demand for clean water and sustainable systems. This comprehensive article explores the [...] Read more.
Integration of the Internet of Things (IoT) into the fields of wastewater treatment and water quality prediction has the potential to revolutionize traditional approaches and address urgent challenges, considering the global demand for clean water and sustainable systems. This comprehensive article explores the transformative applications of smart IoT technologies, including artificial intelligence (AI) and machine learning (ML) models, in these areas. A successful example is the implementation of an IoT-based automated water quality monitoring system that utilizes cloud computing and ML methods to effectively address the above-mentioned issues. The IoT has been employed to optimize, simulate, and automate various aspects, such as monitoring and managing natural systems, water-treatment processes, wastewater-treatment applications, and water-related agricultural practices like hydroponics and aquaponics. This review presents a collection of significant water-based applications, which have been combined with the IoT, artificial neural networks, or ML and have undergone critical peer-reviewed assessment. These applications encompass chlorination, adsorption, membrane filtration, monitoring water quality indices, modeling water quality parameters, monitoring river levels, and automating/monitoring effluent wastewater treatment in aquaculture systems. Additionally, this review provides an overview of the IoT and discusses potential future applications, along with examples of how their algorithms have been utilized to evaluate the quality of treated water in diverse aquatic environments. Full article
(This article belongs to the Special Issue Artificial Intelligence in Water Resources Management)
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