Article
Engineering, Civil
Wei-Jie Wang, Yan-Fang Zhao, Shi Ren, Xiao-Bo Liu, Fei Dong, Jin-Jin Li, Jing-Jing Fan, Wen-Qiang Wu
Summary: Hydrodynamics affected by vegetation in channel is an important topic in ecological hydraulics. This study derives the velocity distribution and the Darcy-Weisbach friction expression for flow with flexible vegetation. The research reveals the characteristics of velocity distribution and resistance features on vegetated riverbed.
JOURNAL OF HYDROLOGY
(2023)
Article
Geosciences, Multidisciplinary
Avihu Burg, Joseph Guttman, Israel Gev
Summary: The study analyzed step-drawdown tests of two deep artesian wells in a fractured carbonate aquifer in Israel and found that the well loss component dominated the total drawdown, leading to very low well efficiencies. This anomaly was attributed to the exceptionally high vertical flow velocities and turbulent flow within the well casings.
HYDROGEOLOGY JOURNAL
(2022)
Article
Geosciences, Multidisciplinary
Vito Ferro, Gaetano Guida
Summary: The aim of this study was to verify the applicability of a theoretical overland flow resistance law to different upland grassland types and consider the effects of vegetation growth cycles on overland flow velocity. Results showed that the proposed method accurately estimated the friction factor, considering the vegetation characteristics and seasonal variability.
Article
Engineering, Civil
Enshuai Shen, Gang Liu, Yafei Jia, Chenxi Dan, Mohamed A. M. Abd Elbasit, Chang Liu, Ju Gu, Hongqiang Shi
Summary: The study found that raindrop impact increases flow resistance, reduces flow velocity, and increases flow depth. Darcy-Weisbach resistance and Manning coefficient decreased in the slope range 2-12%, and remained almost constant in higher slope range. A critical value separating laminar and turbulent flow regime under rainfall conditions appears to be Reynolds number, Re = 800.
JOURNAL OF HYDROLOGY
(2021)
Article
Physics, Fluids & Plasmas
Francesco Coscarella, Roberto Gaudio, Gabriel G. Katul, Costantino Manes
Summary: Researchers have devoted much effort to develop the spectral link theory in order to provide a theoretical interpretation for the empirical formulas of Darcy-Weisbach friction factor in turbulent flows. The introduction of cospectral budget models has helped to clarify the connection between spectral properties of velocity fluctuations and the scaling of friction factors in turbulent pipe flows.
PHYSICAL REVIEW FLUIDS
(2021)
Article
Geochemistry & Geophysics
Ming Luo, Xufeng Yan, Er Huang
Summary: Quantifying the flow resistance in step-pool streams is important for studying the restoration of benthic animals and bedload transport. The Darcy-Weisbach friction factor is divided into components associated with grains, spills, and loose-packed particles. By considering the morphological variation induced by floods, three different morphological patterns and their corresponding flow resistance components are identified. The grain resistance has a slight impact on hydraulic parameters, while the spill resistance and resistance associated with loose-packed particles are strongly influenced by hydraulic and geometric parameters.
Article
Engineering, Civil
Farnoush Aghaee Daneshvar, Nasser Talebbeydokhti, Seyed Mehdi Dehghan, Seyed Mohammad Mehdi Elhamian
Summary: Assessment of energy head loss and friction coefficient of FARATEC glass-reinforced plastic (GRP) pipes was conducted using various profilometry methods. Surface roughness was measured by profilometry and specific instruments to calculate the roughness and friction coefficient of GRP pipes. The Darcy-Weisbach friction factor f of GRP pipes was computed based on Colebrook-White equation for different flow velocities and pipe diameters. The Surftest SJ-210 instrument provided the most accurate measurements and appropriate roughness parameters (Rz and Ra) were determined. The calculated Darcy-Weisbach f coefficients and Moody diagrams were found to accurately match the reference friction factors. Therefore, the surface roughness and friction factor (f) of commercial diameter GRP pipes fall within the range of smooth pipes.
IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING
(2023)
Article
Environmental Sciences
Amir Ghaderi, Saeed Abbasi
Summary: This study focuses on the influence of geometric appendance elements on energy dissipation performance in stepped spillways. The results indicate that the addition of elements significantly increases turbulent kinetic energy and friction, leading to a more efficient energy dissipation.
Article
Biology
Victor Kang, Robin T. White, Simon Chen, Walter Federle
Summary: Research has found that net-winged midge larvae have powerful suction organs that can withstand tremendous forces on different surfaces, thanks to the microtrichia structures on the surface of the suction organs. These findings provide new insights for designing and manufacturing suction cups capable of adhering to a wider variety of surfaces.
Article
Engineering, Marine
Andrea Farkas, Nastia Degiuli, Ivana Martic
Summary: Ship performance is significantly affected by roughness on immersed surfaces, with the prediction of roughness effects being crucial. A novel method for assessing the frictional resistance coefficient for rough surfaces is proposed, considering non-uniform distribution of friction velocity and roughness Reynolds number. The proposed method's applicability is demonstrated through comparisons with CFD approaches for different surface conditions, showing relative deviations in predicted frictional resistance coefficients lower than 2.5%.
Article
Environmental Sciences
Hanwen Cui, Stefan Felder, Matthias Kramer
Summary: In vegetated flows, hydrodynamic parameters play a crucial role in determining velocity distributions, mean velocity, and flow resistance. Previous studies have focused on specific vegetation conditions, but a comprehensive approach to estimate hydrodynamic properties across the full vegetation density spectrum is lacking. This study re-analyzed published data sets using a four-layer velocity superposition model and found that the model could accurately match measured velocity distributions and mean velocity. The study also derived an explicit equation for flow resistance based on velocity distributions.
ENVIRONMENTAL FLUID MECHANICS
(2023)
Article
Chemistry, Physical
Tomasz Trzepiecinski, Sherwan Mohammed Najm
Summary: This study investigates the impact of key parameters of the friction process on the coefficient of friction using artificial neural networks. The research found that the coefficient of friction increases with increasing surface roughness of the counter-samples. The lubrication effectiveness also improves with increasing drawing quality of the sheet metal within a specific range of surface roughness.
Article
Mechanics
Nathaporn Areerachakul, Luedech Girdwichai, Natapat Areerakulkan
Summary: The paper discusses the concept of approximating the Colebrook-White equation using Taylor series expansion and points out that the proposed 3rd order expansion offers high accuracy but poor computational performance. Lower-order approximations based on the same concept are shown to provide sufficient accuracy and greatly enhanced computational speed for engineering and scientific applications.
MECHANICS RESEARCH COMMUNICATIONS
(2021)
Article
Engineering, Mechanical
Xin Yu, Yunyun Sun, Shijing Wu
Summary: In this study, a generalized close-formed model of the friction coefficient between fractal surfaces in mixed lubrication is presented. A mathematical transformation from asperity area to oil film thickness is conducted to establish an analytical fractal model of oil film thickness. A dynamic film thickness model with external load under the determination of the surface roughness is proposed. The effects of fractal parameters and important working parameters on friction coefficient are analyzed, and comparison with experimental data is conducted. This work provides a general analytical expression for friction coefficient in mixed lubrication with explicit form and wide applications.
INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES
(2023)
Article
Engineering, Mechanical
Sahar Ghatrehsamani, Saleh Akbarzadeh, M. M. Khonsari
Summary: During the running-in stage of mechanical components, a model is developed to predict the changes in wear rate, friction coefficient, and surface asperities. Experimental results validate the predictions, showing acceptable agreement between predicted and actual data.
TRIBOLOGY INTERNATIONAL
(2022)
Article
Water Resources
Albert Z. Jiang, Edward A. McBean, Andrew D. Binns, Bahram Gharabaghi
Summary: In recent years, flood-related water damages have become the largest home insurance claims in North America. Efforts are being made to reduce flood damages, including reducing sanitary sewer backups that contribute to basement flooding. A guidance methodology on minimum data size requirements has been developed to assess the effectiveness of alternatives, such as reducing rainfall-derived inflows (RDI). The results show that collecting data for approximately 39 storm events provides valuable guidance for field collection programs.
HYDROLOGICAL SCIENCES JOURNAL
(2022)
Article
Computer Science, Interdisciplinary Applications
Iman Ahmadianfar, Mehdi Jamei, Masoud Karbasi, Ahmad Sharafati, Bahram Gharabaghi
Summary: This study combines the prediction powers of Gaussian process regression, random forest, and M5 model tree using a novel ensemble committee-based data intelligent technique to accurately estimate local scour depth around non-uniformly spaced pile groups. The ensemble model significantly outperformed existing empirical models with high correlation coefficient, low root mean square error, and mean absolute percentage of error. Sensitivity analysis showed that pile diameter is the most influential variable in estimating the scour depth.
ENGINEERING WITH COMPUTERS
(2022)
Article
Engineering, Civil
Yar M. Taraky, Yongbo Liu, Bahram Gharabaghi, Edward McBean, Prasad Daggupati, Narayan Kumar Shrestha
Summary: This research examines the impact of headwater reservoirs on climate change and flood frequency in the Kabul River Basin. The study finds that the proposed reservoirs can reduce flooding during the wet season, decrease flood frequency, and increase low flows during the dry season. Additionally, the risks and benefits of reservoirs are discussed in relation to the developmental goals of Afghanistan and Pakistan.
CANADIAN JOURNAL OF CIVIL ENGINEERING
(2022)
Article
Engineering, Civil
K. M. MacKenzie, B. Gharabaghi, A. D. Binns, H. R. Whiteley
Summary: Unmitigated urbanization can lead to the occurrence of urban stream syndrome, which includes increased stream erosion, changes in alluvial materials, and degradation of water quality. This study examines the application of regime-theory equations to identify channels with urban stream syndrome and proposes specific stream power as a reliable early detection metric for this syndrome. The study showcases the use of the GMDH model and a database of channel morphology variables to identify normal and abnormal channels.
JOURNAL OF HYDROLOGY
(2022)
Article
Environmental Sciences
Seyedahmad Kia, Manoj K. Nambiar, Jesse The, Bahram Gharabaghi, Amir A. Aliabadi
Summary: This study predicts methane emissions from a mining facility in Northern Canada using machine learning. By training multiple machine learning algorithms with near-surface observations and weather modeling data from the tailings pond and two open-pit mines, four models were identified as the most accurate in forecasting emissions.
Article
Engineering, Environmental
Ahmed S. Aredah, Omer Faruk Ertugrul, Ahmed A. Sattar, Hossein Bonakdari, Bahram Gharabaghi
Summary: The Extreme Learning Machine (ELM) approach is used to predict stream health and study the influencing factors. The models show good fit and provide better insights on factors influencing stream health, with ELM outperforming other machine learning models.
Article
Construction & Building Technology
Amir Noori, Hossein Bonakdari, Maryam Hassaninia, Khosro Morovati, Iman Khorshidi, Ali Noori, Bahram Gharabaghi
Summary: The growing problem of urban water shortage and its sustainable management methods is a critical research need globally. This study uses GIS and MCDM with triangular fuzzy sets to manage urban water supply priorities in a semi-arid region. A group decision-making approach combining FAHP and FTOPSIS models is proposed based on quantitative and qualitative criteria. A hierarchical model-based GIS and AHP are used to classify effective criteria and determine weights. FTOPSIS is used for priority ranking of scenarios. The study considers environmental, geographical, geological, economic, climatic, and social conditions. A hydrologic model with WEAP software is designed to assess water supply scenarios.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Green & Sustainable Science & Technology
Mohammad Zeynoddin, Hossein Bonakdari, Silvio Jose Gumiere, Alain N. N. Rousseau
Summary: Soil temperature has a significant impact on environmental processes, and this research introduces a technique to address the lag in the FLDAS, which is valuable in watershed-scaled hydrological research.
Article
Agronomy
Guillaume Gregoire, Josee Fortin, Isa Ebtehaj, Hossein Bonakdari
Summary: In this study, a new hybrid machine learning model combining a convolution neural network and a random forest was developed to forecast pesticide use on golf courses in Quebec, Canada. Three groups of variables, including coordinates, characteristics of golf courses, and meteorological variables, were used to estimate pesticide use. The model that considered the latitude and longitude, pesticide type, number of holes, total precipitation, and average temperature from May to November as inputs outperformed other models. The sensitivity analysis indicated that total precipitation was the most critical variable in pesticide use forecasting.
Article
Water Resources
Jean Cardi, Antony Dussel, Clara Letessier, Isa Ebtehaj, Silvio Jose Gumiere, Hossein Bonakdari
Summary: The Ottawa River Watershed is of great importance to Canada, but has experienced increased flooding due to climate change. To accurately predict floods, a combination of numerical modeling and machine learning has been utilized to develop a new ML model for estimating crucial hydrodynamic characteristics of the river.
Article
Environmental Sciences
Victor Oliveira Santos, Paulo Alexandre Costa Rocha, Jesse Van Griensven The, Bahram Gharabaghi
Summary: This study develops a model using graph neural network to predict chloride concentration in Credit River, Canada. The model outperforms other models and shows potential in real-time forecasting of water quality in urban streams.
Article
Mathematics, Interdisciplinary Applications
Mansura Jasmine, Abdolmajid Mohammadian, Hossein Bonakdari
Summary: This paper investigates the effective implementation of artificial intelligence on the prediction of evaporation for agricultural area. It presents the adaptive neuro fuzzy inference system (ANFIS) and hybridization of ANFIS with three optimizers. The results suggest that ANFIS and ANFIS-PSO are slightly better than ANFIS-FFA and ANFIS-GA. ANFIS is preferred due to its simplicity and easy operation.
MATHEMATICAL AND COMPUTATIONAL APPLICATIONS
(2022)
Article
Water Resources
Mostafa Elkurdy, Andrew D. Binns, Hossein Bonakdari, Bahram Gharabaghi, Edward McBean
Summary: The study utilized the Generalized Structure Group Method of Data Handling (GS-GMDH) to accurately predict daily and hourly flow data for the Bow River in Alberta, Canada. The model performed well in testing, but issues with horizontal error need to be addressed further.
INTERNATIONAL JOURNAL OF RIVER BASIN MANAGEMENT
(2022)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)
