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Multidisciplinary Advances in Water Resources Engineering: A Special Issue in...
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Multidisciplinary Advances in Water Resources Engineering: A Special Issue in Honor of Prof. Dr. Prabhata Kumar Swamee

A special issue of J (ISSN 2571-8800). This special issue belongs to the section "Engineering".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 6981

Special Issue Editors

Dr. Pushpa Rathie

E-Mail Website
Guest Editor
Department of Statistics, University of Brasilia, Brasilia 70910-900, Brazil
Interests: special functions; mathematical statistics; algebra of random variables; complex analysis; information theory; applied mathematics; applied statistics
Prof. Dr. Bhagu Ram Chahar

E-Mail Website
Guest Editor
Institute Chair Professor (2019-21) & HAG Professor of Civil Engineering, Indian Institute of Technology, Delhi, India
Interests: canal design; groundwater modeling and recharge; seepage and drainage; stream-aquifer interaction; numerical techniques; optimization
Dr. Luan Carlos de Sena Monteiro Ozelim

E-Mail Website
Guest Editor
Department of Civil and Environmental Engineering, University of Brasilia, Brasília 70910-900, Brazil
Interests: special functions; mathematical statistics; geotechnical engineering; hydraulics; numerical methods; deep learning; machine learning; artificial intelligence

Special Issue Information

Dear Colleagues,

Water Resources Engineering emerged as a branch of Civil Engineering, but now can be thought of as a completely independent area of study. It encompasses several sub-areas, as well as mixes specifics concepts from Statistics, Applied Mathematics, Economy and Fluid Dynamics. 

With almost sixty years of teaching, research and industry experience in water resources engineering and statistics, Prof. Dr. Prabhata K. Swamee, who regretfully passed away on the 18th of April in Delhi, was an inspiration to several generations of engineers. Not only in the early formation stages, when students learn about the Swamee-Jain equation during Hydraulics courses but also in graduate-level studies, Prof. Swamee’s impact on the academic community was undeniable. 

Prof. Swamee collaborated with about 100 co-authors on several themes, including several Water Resources topics, Statistics, Mathematics, Fluid Dynamics and so on. His contributions to Statistics led him to define two new statistical distributions. Prof. Swamee has also co-authored two books, has to his credit more than 110 papers published in international journals and guided 19 Ph.D. dissertations. As a recognition of his career, he was appointed as a Fellow of the Indian National Academy of Engineering and of the ISH. 

Having the University of Roorkee (now IIT Roorkee), India, as his alma mater, his academic background was entirely built in this University. He obtained his B.E. title (Civil Engineering) in 1962. Then, he obtained his M.E. title (Hydraulic Engineering) in 1966 and, finally, he completed his PhD in civil engineering in 1974. 

Prof. Swamee's contributions were multidisciplinary, therefore, the present Special Issue is launched in his honor and shall gather contributions on mathematical/statistical applications in Water Resources Engineering and correlated fields. The topics of interest are: 

  • Channel flow problems 
  • Pipe-flow problems 
  • Engineering and Cost aspects of pipe networks design 
  • Statistical modelling of water quality indices 
  • Statistical applications in Hydrology and Hydraulics. 
  • Newtonian and Non-Newtonian Fluid Flow 
  • Irrigation and Drainage Engineering 
  • Groundwater flow problems  
  • Well hydraulics 

Dr. Pushpa Rathie
Prof. Dr. Bhagu Ram Chahar
Dr. Luan Carlos de Sena Monteiro Ozelim
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. J is an international peer-reviewed open access quarterly 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 1200 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

  • hydraulics
  • hydrology
  • channel flow
  • pipe-flow
  • pipe networks
  • water quality index
  • applied statistics
  • statistical distributions
  • fluid flow
  • irrigation
  • drainage
  • groundwater flow
  • well hydraulics

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Published Papers (3 papers)

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17 pages, 1779 KiB  
Article
Multicomponent Stress–Strength Reliability with Extreme Value Distribution Margins: Its Theory and Application to Hydrological Data
by Rebeca Klamerick Lima, Felipe Sousa Quintino, Melquisadec Oliveira, Luan Carlos de Sena Monteiro Ozelim, Tiago A. da Fonseca and Pushpa Narayan Rathie
J 2024, 7(4), 529-545; https://doi.org/10.3390/j7040032 - 1 Dec 2024
Viewed by 862
Abstract
This paper focuses on the estimation of multicomponent stress–strength models, an important concept in reliability analyses used to determine the probability that a system will function successfully under varying stress conditions. Understanding and accurately estimating these probabilities is essential in fields such as [...] Read more.
This paper focuses on the estimation of multicomponent stress–strength models, an important concept in reliability analyses used to determine the probability that a system will function successfully under varying stress conditions. Understanding and accurately estimating these probabilities is essential in fields such as engineering and risk management, where the reliability of components under extreme conditions can have significant consequences. This is the case in applications where one seeks to model extreme hydrological events. Specifically, this study examines cases where the random variables X (representing strength) and Y (representing stress) follow extreme value distributions. New analytical expressions are derived for multicomponent stress–strength reliability (MSSR) when different classes of extreme distributions are considered, using the extreme value H-function. These results are applied to three l-max stable laws and six p-max stable laws, providing a robust theoretical framework for multicomponent stress–strength analyses under extreme conditions. To demonstrate the practical relevance of the proposed models, a real dataset is analyzed, focusing on the monthly water capacity of the Shasta Reservoir in California (USA) during August and December from 1980 to 2015. This application showcases the effectiveness of the derived expressions in modeling real-world data. Full article
(This article belongs to the Special Issue Multidisciplinary Advances in Water Resources Engineering: A Special Issue in Honor of Prof. Dr. Prabhata Kumar Swamee)
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20 pages, 11248 KiB  
Article
Application of AI-Based Techniques on Moody’s Diagram for Predicting Friction Factor in Pipe Flow
by Ritusnata Mishra and Chandra Shekhar Prasad Ojha
J 2023, 6(4), 544-563; https://doi.org/10.3390/j6040036 - 7 Oct 2023
Viewed by 2350
Abstract
The friction factor is a widely used parameter in characterizing flow resistance in pipes and open channels. Recently, the application of machine learning and artificial intelligence (AI) has found several applications in water resource engineering. With this in view, the application of artificial [...] Read more.
The friction factor is a widely used parameter in characterizing flow resistance in pipes and open channels. Recently, the application of machine learning and artificial intelligence (AI) has found several applications in water resource engineering. With this in view, the application of artificial intelligence techniques on Moody’s diagram for predicting the friction factor in pipe flow for both transition and turbulent flow regions has been considered in the present study. Various AI methods, like Random Forest (RF), Random Tree (RT), Support Vector Machine (SVM), M5 tree (M5), M5Rules, and REPTree models, are applied to predict the friction factor. While performing the statistical analysis (root-mean-square error (RMSE), mean absolute error (MAE), squared correlation coefficient (R2), and Nash–Sutcliffe efficiency (NSE)), it was revealed that the predictions made by the Random Forest model were the most reliable when compared to other AI tools. The main objective of this study was to highlight the limitations of artificial intelligence (AI) techniques when attempting to effectively capture the characteristics and patterns of the friction curve in certain regions of turbulent flow. To further substantiate this behavior, the conventional algebraic equation was used as a benchmark to test how well the current AI tools work. The friction factor estimates using the algebraic equation were found to be even more accurate than the Random Forest model, within a relative error of ≤±1%, in those regions where the AI models failed to capture the nature and variation in the friction factor. Full article
(This article belongs to the Special Issue Multidisciplinary Advances in Water Resources Engineering: A Special Issue in Honor of Prof. Dr. Prabhata Kumar Swamee)
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16 pages, 7457 KiB  
Article
Evaluating Preventive Measures for Flooding from Groundwater: A Case Study
by Raaghul Kumar and Munshi Md. Shafwat Yazdan
J 2023, 6(1), 1-16; https://doi.org/10.3390/j6010001 - 26 Dec 2022
Viewed by 2921
Abstract
Groundwater (GW) flooding mechanisms differ from river flooding, both spatially and temporally, and preventative methods against groundwater flooding must take this into account. Although groundwater flooding caused by a rise of river water seldom occurs, it can occasionally become severe and last for [...] Read more.
Groundwater (GW) flooding mechanisms differ from river flooding, both spatially and temporally, and preventative methods against groundwater flooding must take this into account. Although groundwater flooding caused by a rise of river water seldom occurs, it can occasionally become severe and last for a long time if the river is significantly flooded. In the southwest portion of the research domain, Friedrichshafen, Germany, with a few urban communities, the level of the groundwater table was discovered to be roughly 1 m below the surface. In the study region, it is typical for the bottom level of the foundation of a single-story building to extend up to a depth of about 1.5 m. Therefore, flood mitigation methods are taken into account for the southwest portion of the study region. In this study, FEFLOW is used to explore the preventative methods for groundwater flooding caused by river water increase in urban settings, the spread of contamination, and the strategizing of effective mitigation solutions for flooding. The installation of a pumping well, drainage, and a barrier in the affected area are three different flood control strategies that are taken into consideration for the study area. Pumping well installation, reducing up to 1.5 m of hydraulic head, was found to be the most effective flood control measure locally in a small region. By contrast, removing groundwater by building drainage and barriers was shown to be ineffective for lowering the groundwater table over an extended region, and was significantly more expensive than the installation of wells. Additionally, when river flooding is taken into account, compared to the default scenario where no intake of water from the river is included along the western border of the study area, it was discovered that the spread of pollution (nitrate concentration) is significantly greater. Full article
(This article belongs to the Special Issue Multidisciplinary Advances in Water Resources Engineering: A Special Issue in Honor of Prof. Dr. Prabhata Kumar Swamee)
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