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Water
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Modelling and Numerical Simulation of Hydraulics and River Dynamics
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Modelling and Numerical Simulation of Hydraulics and River Dynamics

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydraulics and Hydrodynamics".

Deadline for manuscript submissions: closed (20 December 2023) | Viewed by 8904

Special Issue Editors

Dr. Zohreh Sheikh Khozani

E-Mail Website
Guest Editor
Department of Civil Engineering, Institute of Structural Mechanics, Bauhaus Universität Weimar, Weimar, Germany
Interests: sediment transport; hydraulic structures; Machine Learning; hydrology; water and environment; entropy concept
Dr. Wan Hanna Melini Wan Mohtar

E-Mail Website
Guest Editor
Civil Engineering Department, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Malaysia
Interests: environmental hydraulics; wastewater engineering; water resource management

Special Issue Information

Dear Colleagues,

River engineering is an important subject in hydraulic engineering, and hydrology, hydraulics, and geomorphology are the main scientific disciplines required to understand its basic principles. Precise streamflow prediction using hydrological and numerical models can benefit hydrological operations such as water resource project operation, effective programming for flood monitoring, and reservoir operation schedules.

Sediment dynamics presents one of the most challenging issues in the study and interpretation of soil erosion, streambed deposition, and streambed erosion. A reduction in flow area caused by suspended sediments affects the movement of aquatic life, ultimately changing the course of rivers. It is therefore crucial for various authorities to have data on suspended sediments and their variation. Furthermore, sediment transport strongly affects the geomorphology of riverbeds.

This Special Issue welcomes contributions related (but not limited) to the development of advanced mathematical, numerical, finite element, and Machine Learning modeling strategies to address hydraulic structures and river engineering problems. We are particularly interested in processes related to sedimentation, erosion, scour depth prediction, flow–vegetation interactions, morphodynamics, sedimentation, streamflow, coastal wave motion, and flooding, from a multidisciplinary point of view.

Dr. Zohreh Sheikh Khozani
Dr. Wan Hanna Melini Wan Mohtar
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

  • mathematical approaches
  • numerical modeling
  • machine learning techniques
  • fluvial hydraulics
  • sedimentation
  • erosion
  • flooding
  • hydraulic structures
  • river flow
  • riverbank vegetation

Published Papers (6 papers)

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Research

18 pages, 7963 KiB  
Article
Progressive Dam-Failure Assessment by Smooth Particle Hydrodynamics (SPH) Method
by Jianwei Zhang, Bingpeng Wang, Huokun Li, Fuhong Zhang, Weitao Wu, Zixu Hu and Chengchi Deng
Water 2023, 15(21), 3869; https://doi.org/10.3390/w15213869 - 06 Nov 2023
Viewed by 998
Abstract
The dam-break water flow is a complex fluid motion, showing strong nonlinearity and stochasticity. In order to better study the characteristics of the dam burst flood, the smooth particle hydrodynamics (SPH) method was chosen to establish a two-dimensional classical dam-burst model, and the [...] Read more.
The dam-break water flow is a complex fluid motion, showing strong nonlinearity and stochasticity. In order to better study the characteristics of the dam burst flood, the smooth particle hydrodynamics (SPH) method was chosen to establish a two-dimensional classical dam-burst model, and the flow velocity distribution graph was obtained by calculation and compared with the experimental results in the literature, and the fitting degree of the two was obtained to be 88.4%, which verifies the validity of the model. On this basis, according to the principle of dam failure, the two failure modes of equal-interval gradual failure and progressive gradual failure were simulated, and the water body characteristics such as water flow velocity, energy, pressure, etc., were analyzed based on the different working conditions of the two modes to obtain the characteristics of gradual dam-failure water flow under the two kinds of numerical models. The simulation results show that, compared with the instantaneous dam failure mode, (1) the flow rate of the dam-failure stream reaching the downstream slows down in the gradual dam-failure mode; (2) the depth development of the breach extends downward in layers and stages over time, and the overall duration of the breach is prolonged; (3) the destructive power of the dam-failure flood is weakened as the number of segments increases. The results of the study show that, compared with the instant dam-failure mode, the calculation results of the breach development considering the progressive gradual dam-failure mode are more in line with the theoretical solution and closer to the actual process of dam failure, which can provide ideas and references for advancing the numerical study of dam failure. Full article
(This article belongs to the Special Issue Modelling and Numerical Simulation of Hydraulics and River Dynamics)
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23 pages, 8417 KiB  
Article
Assessment of River Regime of Chenab River in Post-Chiniot Dam Project Scenario
by Yasir AbdulJaleel, Saleem Munawar, Muhammad Kaleem Sarwar, Faraz Ul Haq and Khawaja Bilal Ahmad
Water 2023, 15(17), 3032; https://doi.org/10.3390/w15173032 - 23 Aug 2023
Viewed by 1173
Abstract
Dams and reservoirs trap most sediments, and clear water can cause downstream riverbed degradation or aggradation. As a result, the river adjusts its dynamics and channel geometry to regain equilibrium between sediment supply and transport capacity. This study aimed to assess the river [...] Read more.
Dams and reservoirs trap most sediments, and clear water can cause downstream riverbed degradation or aggradation. As a result, the river adjusts its dynamics and channel geometry to regain equilibrium between sediment supply and transport capacity. This study aimed to assess the river regime of the Chenab River in the post-Chiniot Dam Project scenario using a one-dimensional numerical model. After calibration and validation using historic flows and river surveys, simulations were carried out for 5, 10, and 30 years. The sediment model was validated with Brune’s curve, which showed a Nash–Sutcliffe efficiency value of 0.734. The results showed that the river experienced continuous degradation of sediments for the first 16 years and showed a maximum erosion of 8 m at 680 m downstream of the dam. The reach experienced aggradation at 15 km downstream of the dam for the first 10 years and then became stable and showed a maximum deposition of 0.9 m. The ratio of sediments passed through the dam to sediments transported out of reach varied from 0.833 to 0.921, showing that the river reach would continue to attain equilibrium even after 30 years of reservoir operation. The study would be helpful for the prediction of possible future changes in the Chenab River. Full article
(This article belongs to the Special Issue Modelling and Numerical Simulation of Hydraulics and River Dynamics)
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17 pages, 8042 KiB  
Article
Modelling and Numerical Simulation Approaches to the Stage–Discharge Relationships of the Lansheng Bridge
by Yen-Chang Chen, Han-Chung Yang, Yi-Jiun Liao and Yen-Tzu Chen
Water 2023, 15(12), 2179; https://doi.org/10.3390/w15122179 - 09 Jun 2023
Viewed by 1006
Abstract
In recent years, extreme rainfall events with short delays and heavy rainfall have often occurred due to severe climate change. In 2015, Typhoon Soudelor caused a short-delayed heavy rainfall event in Nanshih River, which caused damage to a section of the Lansheng Bridge [...] Read more.
In recent years, extreme rainfall events with short delays and heavy rainfall have often occurred due to severe climate change. In 2015, Typhoon Soudelor caused a short-delayed heavy rainfall event in Nanshih River, which caused damage to a section of the Lansheng Bridge discharge station. The section was relocated upstream to rebuild the discharge station in 2019. However, the new discharge station cannot measure high flow due to the bridge structure. The flow observation range of Lansheng Bridge is therefore limited to normal flow, making it impossible to accurately estimate the flow during high-water stages. The purpose of this study is to use the past flow data of Nanshih River to estimate the flow rate under different return periods using frequency analysis. We used a Digital Elevation Model (DEM) to map the river’s topography, and used the 3D hydraulic calculations of the FLOW-3D model to estimate the water stage and discharge of the Lansheng Bridge. We then verified the accuracy of the model with the measured flow and water stage, and finally used the water stage and discharge data obtained from numerical simulation to construct the stage–discharge rating curve of the Lansheng Bridge. In addition to preventing flood disasters, this study approach can provide reliable data for use in water conservation. It may also be utilized to overcome the problem of measuring and estimating high flow during typhoon floods. Full article
(This article belongs to the Special Issue Modelling and Numerical Simulation of Hydraulics and River Dynamics)
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11 pages, 2907 KiB  
Article
Study on the Head Loss of the Inlet Gradient Section of the Aqueduct
by Jian Chen, Yangyang Tian, Huijie Zhang and Shanju Zhang
Water 2023, 15(8), 1633; https://doi.org/10.3390/w15081633 - 21 Apr 2023
Viewed by 1118
Abstract
The form of the inlet section of aqueducts that connect the upstream channel and the downstream channel affects the flow pattern and head loss. In order to provide a reference for the design of the gradient section of water-transfer channels, a typical three-dimensional [...] Read more.
The form of the inlet section of aqueducts that connect the upstream channel and the downstream channel affects the flow pattern and head loss. In order to provide a reference for the design of the gradient section of water-transfer channels, a typical three-dimensional hydrodynamic model is established in this paper based on existing results. The results show that the local head loss coefficient is related to the cross-sectional area of the inlet and outlet of the gradient section, the water surface contraction angle of the gradient section, and the elevation difference between the bottoms of the inlet and outlet of the gradient section, and a functional relationship is provided; when changing the width of the inlet and outlet bottoms, the local head loss coefficient is negatively related to the water surface contraction angle and increases with the increase in Wup/Wdown; the local head loss coefficient has a good exponential function with Wup/Wdown. The research results can provide a reference for the design of the inlet gradient section and the solution of the head loss coefficient. Full article
(This article belongs to the Special Issue Modelling and Numerical Simulation of Hydraulics and River Dynamics)
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18 pages, 1914 KiB  
Article
Binary Coati Optimization Algorithm- Multi- Kernel Least Square Support Vector Machine-Extreme Learning Machine Model (BCOA-MKLSSVM-ELM): A New Hybrid Machine Learning Model for Predicting Reservoir Water Level
by Saad Sh. Sammen, Mohammad Ehteram, Zohreh Sheikh Khozani and Lariyah Mohd Sidek
Water 2023, 15(8), 1593; https://doi.org/10.3390/w15081593 - 19 Apr 2023
Cited by 5 | Viewed by 1304
Abstract
Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. Our study introduces a new model for predicting reservoir [...] Read more.
Predicting reservoir water levels helps manage droughts and floods. Predicting reservoir water level is complex because it depends on factors such as climate parameters and human intervention. Therefore, predicting water level needs robust models. Our study introduces a new model for predicting reservoir water levels. An extreme learning machine, the multi-kernel least square support vector machine model (MKLSSVM), is developed to predict the water level of a reservoir in Malaysia. The study also introduces a novel optimization algorithm for selecting inputs. While the LSSVM model may not capture nonlinear components of the time series data, the extreme learning machine (ELM) model—MKLSSVM model can capture nonlinear and linear components of the time series data. A coati optimization algorithm is introduced to select input scenarios. The MKLSSVM model takes advantage of multiple kernel functions. The extreme learning machine model—multi-kernel least square support vector machine model also takes the benefit of both the ELM model and MKLSSVM model models to predict water levels. This paper’s novelty includes introducing a new method for selecting inputs and developing a new model for predicting water levels. For water level prediction, lagged rainfall and water level are used. In this study, we used extreme learning machine (ELM)-multi-kernel least square support vector machine (ELM-MKLSSVM), extreme learning machine (ELM)-LSSVM-polynomial kernel function (PKF) (ELM-LSSVM-PKF), ELM-LSSVM-radial basis kernel function (RBF) (ELM-LSSVM-RBF), ELM-LSSVM-Linear Kernel function (LKF), ELM, and MKLSSVM models to predict water level. The testing means absolute of the same models was 0.710, 0.742, 0.832, 0.871, 0.912, and 0.919, respectively. The Nash–Sutcliff efficiency (NSE) testing of the same models was 0.97, 0.94, 0.90, 0.87, 0.83, and 0.18, respectively. The ELM-MKLSSVM model is a robust tool for predicting reservoir water levels. Full article
(This article belongs to the Special Issue Modelling and Numerical Simulation of Hydraulics and River Dynamics)
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31 pages, 11774 KiB  
Article
Development of a Three-Dimensional CFD Model and OpenCV Code by Comparing with Experimental Data for Spillway Model Studies
by Hakan Varçin, Fatih Üneş, Ercan Gemici and Martina Zelenakova
Water 2023, 15(4), 756; https://doi.org/10.3390/w15040756 - 14 Feb 2023
Viewed by 2411
Abstract
This article presents a three-dimensional CFD model and OpenCV code by comparing the flow over the spillway with the experimental data for use in spillway studies. A 1/200-scale experimental model of a real dam spillway was created according to Froude similarity. In the [...] Read more.
This article presents a three-dimensional CFD model and OpenCV code by comparing the flow over the spillway with the experimental data for use in spillway studies. A 1/200-scale experimental model of a real dam spillway was created according to Froude similarity. In the experimental studies, velocity and water depth were measured in four different sections determined in the spillway model. A three-dimensional ANSYS Fluent model of the spillway was created and the simulations of the flows occurring during the flood were obtained. In the numerical model, the two-phase VOF model and k-epsilon turbulence model are used. As a result of the numerical analysis, velocity, depth, pressure, and cavitation index values were examined. The velocity and depth values obtained with models were compared and a good agreement was found between the results. In addition, in this study, a different technique based on image processing is developed to calculate water velocity and depth. A floating object was placed in the spillway channel during the experiment and the movement of the object on the water was recorded with cameras placed at different angles. By using the object tracking method, which is an image processing technique, the position of the floating object was determined in each video frame in the video recordings. Based on this position, the velocity of the floating object and its perpendicular distance to the bottom of the channel was determined. Thus, an OpenCV-Python code has been developed that determines the velocity and water depth of the floating object depending on its position. The floating object velocity values obtained by the algorithm were compared with the velocity values measured during the experimental model, and new velocity correction coefficients were obtained for the chute spillways. Full article
(This article belongs to the Special Issue Modelling and Numerical Simulation of Hydraulics and River Dynamics)
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