Machine Learning in Water Distribution Systems and Sewage Systems

Dear Colleagues,

Water distribution systems and sanitary and rainwater sewage systems are very expensive and require appropriate planning with a long time horizon, the proper design of individual elements, and the efficient operation and management of the existing infrastructure. Many aspects related to urban development must be taken into account in the initial planning phase, and then, calculations and numerical simulations are required during the design process. In the case of sewerage, we can deal with a distribution or combined sewerage. In the case of rainwater drainage, there is a problem of change in land use, thus increasing land sealing and surface runoff from the catchment. Water distribution and sewage systems have a wide spatial range, which greatly complicates their construction, operation, and modernization. Therefore, planning and designing water distribution and sewerage systems requires calculations and many analyses to lead to the best solution. The correct implementation of the calculations requires a thorough assessment of the results obtained and the correctness of the solutions used. Currently, water distribution and wastewater systems are very often equipped with measuring devices with the ability to transmit data to a central management center. This allows for the collection of many parameters, which, when properly used, can allow for the improvement in processes in the planning, design, and operation of water distribution and sewage systems. In the analysis of the functioning of systems, data obtained as a result of computer simulations are often used. The proposed Special Issue will focus on the different stages of construction and operation of water distribution and wastewater disposal systems.

• Planning of systems at the most general level with a large time horizon, staging of system expansion, assessment of planned system variants from the technical, economic, and reliability point of view, zoning of systems, planning of the system of pipelines and channels, and location of technical facilities (e.g., pumping stations, tanks, control fittings, etc.).
• Design and calculations of water supply and sewage systems (e.g., hydraulic calculations, pressure losses, flow velocity control, sewer filling calculations, sewer capacity, etc.), design of specific devices (e.g., diameters of water supply pipelines, diameters of sewers for distribution or combined systems, water pumping stations, sewage pumping stations, water supply tanks, retention reservoirs in rainwater drainage, and others), introduction of methods machine learning in order to accelerate numerical calculations, reporting on calculation errors, verification of the correctness of the applied technical solutions, supporting designers in the field of applied solutions, and location of technical objects.
• Operation of water distribution and sewage systems, e.g., flushing of water supply pipelines, cleaning of sewage systems, technical maintenance of equipment and fittings, removal of failures, planning repairs, observation, and prevention of any irregularities, maintaining an appropriate level of water supply reliability.

The purpose of this Special Issue is to propose machine learning (ML) models to improve the various types of processes in water distribution and wastewater systems that occur during the planning, design, and operation stages. A special release may include supervised learning algorithms, unsupervised learning algorithms, and reinforcement learning algorithms, such as the following:

• Deep learning models;
• Decision tree;
• Fuzzy inference;
• SVM (Support Vector Machine) algorithm;
• Evolutionary computation;
• Naive Bayes algorithm;
• KNN algorithm;
• K-means;
• Random forest algorithm;
• Dimensionality reduction algorithms;
• Logistic Regression;
• PCA (Principal Component Analysis) algorithm.

We invite researchers, practitioners, and policymakers to submit original research papers, reviews, and case studies.

Dr. Jacek Piekarski
Dr. Jacek Dawidowicz
Guest Editors

Manuscript Submission Information

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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.

• water distribution systems
• sewage systems
• stormwater systems
• hydraulic simulations
• artificial intelligence models
• machine learning
• deep learning models
• evolutionary computation
• fuzzy inference