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: 31 May 2024 | Viewed by 3857

Special Issue Editors

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
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
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

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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. J is an international peer-reviewed open access quarterly journal published by MDPI.

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Keywords

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

Published Papers (2 papers)

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Research

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 - 07 Oct 2023
Viewed by 1311
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
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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 1936
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
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