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Improving incomplete mixing modeling for junctions of water distribution networks J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Reza Yousefian, Sophie Duchesne
View largeDownload slide View largeDownload slide Close modal Most of the existing water quality models for water distribution networks assume complete mixing at junctions. Albeit few models offer the possibility to consider incomplete mixing (IM) at junctions, most of them were developed under laboratory conditions and for equal pipe size junctions. In real-world distribution networks, however, cross
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Generation of harmonised pluvial flood hazard maps through decentralised analytics J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Sascha Welten, Adrian Holt, Julian Hofmann, Sven Weber, Elena-Maria Klopries, Holger Schüttrumpf, Stefan Decker
View largeDownload slide View largeDownload slide Close modal Increasing extreme weather events pose significant challenges in hydrology, requiring tools for preparedness and prediction of intense rainfall impacts, especially flash floods. Current risk reduction measures for pluvial flood risk management rely on flood hazard maps, but inconsistencies in transregional standards that are used for risk
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Client-side web-based model coupling using basic model interface for hydrology and water resources J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Gregory Ewing, Carlos Erazo Ramirez, Ashani Vaidya, Ibrahim Demir
A recent trend in hydroinformatics has been the growing number of data, models, and cyber tools, which are web accessible, each aiming to improve common research tasks in hydrology through web technologies. Coupling web-based models and tools holds great promise for an integrated environment that can facilitate community participation, collaboration, and scientific replication. There are many examples
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Disinfection scheduling in water distribution networks considering input time-delay uncertainty J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Stelios G. Vrachimis, Demetrios G. Eliades, Marios M. Polycarpou
A significant challenge when attempting to regulate the spatial-temporal concentration of a disinfectant in a water distribution network is the large and uncertain delay between the time that the chemical is injected at the input node and the time that the concentration is measured at the monitoring output nodes. Uncertain time delays are due to varying water flows, which depend mainly on consumer
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A two-dimensional hydrodynamic urban flood model based on equivalent drainage of manholes J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Mengshi Xiang, Shanghong Zhang, Chuansen Wu, Caihong Tang
View largeDownload slide View largeDownload slide Close modal Numerical simulations of urban flood events are of great significance in flood control and disaster reduction. An important part of these numerical investigations concerns drainage, which is crucial to the accuracy of the simulation results. To overcome the difficulty of obtaining underground pipe network data and improve the traditional
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Development and application of a mathematical model for calculating the discharge of non-standard thin-plate weirs in urban combined sewer overflow systems: a case study J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Ming Tang, Yuze Wu, Qianchen Xie, Hui Chen, Wenbin Xu
View largeDownload slide View largeDownload slide Close modal The aim of this study is to address the issue of difficulty in evaluating the combined sewer overflow (CSO) pollution effectively, especially for the monitoring of overflow from non-standard thin-plate weirs (NTPWs). In order to construct a discharge calculation mathematical model (DCMM) of NTPWs in an urban combined sewer overflow system
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Meteorological characteristics of line-shaped rainbands in northern Japan and its surrounding seas under climate change J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Yuta Ohya, Tomohito J. Yamada
View largeDownload slide View largeDownload slide Close modal In recent years, line-shaped rainbands (LRBs) have increased in Hokkaido, Japan. LRBs caused several flood disasters historically, thus the weather patterns that cause them need to be investigated. This study aimed to understand statistically the relationship between LRBs and weather patterns during the summer months under climate change
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An enhanced method for automated end-use classification of household water data J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Filippo Mazzoni, Mirjam Blokker, Stefano Alvisi, Marco Franchini
View largeDownload slide View largeDownload slide Close modal An accurate estimation of residential end uses of water is helpful in developing efficient water systems. If not obtainable through direct metering, this information can be gathered by disaggregating and classifying household-level water-use data. However, most automated techniques require fine-resolution data (e.g., 1 s) and end-use parameters
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Evaluation of satellite rainfall estimates using PERSIANN-CDR and TRMM over three critical cells in Jordan J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Mohanned Al-Sheriadeh, Anas Riyad Al-Sharman
View largeDownload slide View largeDownload slide Close modal Effective management of water resources is heavily dependent on accurate knowledge of rainfall patterns. Satellite rainfall estimates (SREs) have become increasingly popular due to their ability to provide spatial rainfall data. However, the accuracy of SREs is limited by a variety of factors including a lack of observations, inadequate
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LSTM-based autoencoder models for real-time quality control of wastewater treatment sensor data J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Siddharth Seshan, Dirk Vries, Jasper Immink, Alex van der Helm, Johann Poinapen
View largeDownload slide View largeDownload slide Close modal The operation of smart wastewater treatment plants (WWTPs) is increasingly paramount in improving effluent quality, facilitating resource recovery and reducing carbon emissions. To achieve these objectives, sensors, monitoring systems, and artificial intelligence (AI)-based models are increasingly being developed and utilised for decision
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Providing solutions for data scarcity in urban flood modeling through sensitivity analysis and DEM modifications J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Lea Dasallas, Hyunuk An, Seungsoo Lee
Developing countries face significant challenges in accessing sufficient and reliable hydro-meteorological data, hindering the implementation of effective disaster management strategies. This research proposes solutions for limitations on performing flood simulations through parameter sensitivity analysis and digital elevation model (DEM) modifications. The methodology provides alternatives to account
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3D-CFD analysis of bedload transport in channel bifurcations J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Tino Kostić, Yuanjie Ren, Stephan Theobald
View largeDownload slide View largeDownload slide Close modal The aim of this research was to numerically reproduce bedload transport processes in channel bifurcations and thereby evaluate the methodology and feasibility of 3D-computational fluid dynamics (CFD) bedload transport simulations. This was carried out by numerically replicating two physical model investigations of channel bifurcations: research
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Multivariate adaptive regression splines-assisted approximate Bayesian computation for calibration of complex hydrological models J. Hydroinform. (IF 2.7) Pub Date : 2024-02-01 Jinfeng Ma, Ruonan Li, Hua Zheng, Weifeng Li, Kaifeng Rao, Yanzheng Yang, Bo Wu
Approximate Bayesian computation (ABC) relaxes the need to derive explicit likelihood functions required by formal Bayesian analysis. However, the high computational cost of evaluating models limits the application of Bayesian inference in hydrological modeling. In this paper, multivariate adaptive regression splines (MARS) are used to expedite the ABC calibration process. The MARS model is trained
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Advances in using mathematical optimization to manage floods with assessment of possible benefits using a case study J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Nesa Ilich, Ashoke Basistha
This paper presents the benefits of using mathematical optimization for reservoir operation based on the assumed availability of short-term runoff forecasts. The novelty is the inclusion of the SSARR hydrological routing as optimization constraints in multiple time step optimization, where the routing coefficients are adjusted dynamically as functions of the channel flows. The paper shows significant
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Erratum: Journal of Hydroinformatics 1 November 2023; 25 (6): 2253–2267; Optimal charging station placement for autonomous robots in drinking water networks, Mario Castro-Gama, Yvonne Hassink-Mulder J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01
Abstract not available
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Identifying the pathways of extreme rainfall in South Africa using storm trajectory analysis and unsupervised machine learning techniques J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Rhys Phillips, Katelyn Ann Johnson, Andrew Paul Barnes, Thomas Rodding Kjeldsen
View largeDownload slide View largeDownload slide Close modal This study has utilised National Oceanic and Atmospheric Administration (NOAA) NCEP/NCAR Reanalysis 1 project meteorological data and the HYSPLIT model to extract the air parcel trajectories for selected historical extreme rainfall events in South Africa. The k-means unsupervised machine learning algorithm has been used to cluster the resulting
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A robust simulator of pressure-dependent consumption in Python J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Camille Chambon, Olivier Piller, Iraj Mortazavi
View largeDownload slide View largeDownload slide Close modal Modeling of pressure-dependent users’ consumption is mandatory to simulate accurately the hydraulics of water distribution networks (WDNs). Several software solutions already exist for this purpose, but none of them actually permits the easy integration and testing of new physical processes. In this paper, we propose a new Python simulator
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A GPU-based hydrodynamic numerical model for urban rainstorm inundation simulations J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Hao Han, Jingming Hou, Zhao Jin, Pingping Luo, Guodong Li, Ye Zhang, Jiahui Gong, Da Luo, Siqi Yang
View largeDownload slide View largeDownload slide Close modal The response capacities of urban flood forecasting and risk control can be improved by strengthening the computational abilities of urban flood numerical models. In this work, a GPU-based hydrodynamic model is developed to simulate urban rainstorm inundations. By simulating rainstorm floods in a certain area of Xixian New City, the established
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Modelling public social values of flood-prone land use using the GIS application SolVES J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Izni Zahidi, Mun Ee Yau, Alex Lechner, Karen Lourdes
Social values of land use are often excluded when undertaking integrated flood management as they are harder to quantify. To fill this research gap, a geographic information system application called Social Values for Ecosystem Services was used to assess, map and quantify the perceived social values of flood-prone land use in Kuala Selangor, Malaysia. This approach was based on a non-monetary value
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Assessing the impact of an arch-dam breach magnitude and reservoir inflow on flood maps J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Daniela Elena Gogoașe Nistoran, Cristina Sorana Ionescu, Ștefan Mugur Simionescu
Different scenarios of an arch-dam breach and their impact on the time-space evolution of flood waves are analysed using numerical modelling. As the accidents involving this type of dam are among the most catastrophic ones, the 108 m in height Paltinu arch-dam, Romania, was chosen as a case study due to its problems in the past. Three dam breach magnitudes and two inflow hydrographs for the worst-case
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Numerical study of submerged hydraulic jumps over triangular macroroughnesses J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Harshit Kumar Jayant, Bharat Jhamnani
View largeDownload slide View largeDownload slide Close modal The hydraulic jump is a phenomenon that occurs in open channels. In past studies, hydraulic jumps over smooth and macrorough beds have been investigated to enhance energy dissipation, but triangular macroroughness, specifically the right-angled triangular macroroughness, has not been dealt with. The objective of this article is to numerically
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Mapping of soil erosion susceptibility using advanced machine learning models at Nghe An, Vietnam J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Chien Quyet Nguyen, Tuyen Thi Tran, Trang Thanh Thi Nguyen, Thuy Ha Thi Nguyen, T. S. Astarkhanova, Luong Van Vu, Khac Tai Dau, Hieu Ngoc Nguyen, Giang Hương Pham, Duc Dam Nguyen, Indra Prakash, Binh Pham
Soil Erosion Susceptibility Mapping (SESM) is one of the practical approaches for managing and mitigating soil erosion. This study applied four Machine Learning (ML) models, namely the Multilayer Perceptron (MLP) classifier, AdaBoost, Ridge classifier, and Gradient Boosting classifier to perform SESM in a region of Nghe An province, Vietnam. The development of these models incorporated seven factors
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EWT_Informer: a novel satellite-derived rainfall–runoff model based on informer J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Shuyu Wang, Yu Chen, Mohamed Ahmed
An accurate rainfall–runoff observation is critical for giving a warning of a potential damage early enough to allow appropriate response to the disaster. The long short-term memory (LSTM)-based rainfall–runoff model has been proven to be effective in runoff prediction. Previous research has typically utilized multiple information sources as the LSTM training data. However, when there are many sequences
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Multivariate spatio-temporal modeling of drought prediction using graph neural network J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Jiaxin Yu, Tinghuai Ma, Li Jia, Huan Rong, Yuming Su, Mohamed Magdy Abdel Wahab
View largeDownload slide View largeDownload slide Close modal Drought is a serious natural disaster that causes huge losses to various regions of the world. To effectively cope with this disaster, we need to use drought indices to classify and compare the drought conditions of different regions. We can take appropriate measures according to the category of drought to mitigate the impact of drought
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Algorithms to mimic human interpretation of turbidity events from drinking water distribution systems J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Killian Gleeson, Stewart Husband, John Gaffney, Joby Boxall
View largeDownload slide View largeDownload slide Close modal Deriving insight from the increasing volume of water quality time series data from drinking water distribution systems is complex and is usually situation- and individual-specific. This research used crowd-sourcing exercises involving groups of domain experts to identify features of interest within turbidity time series data from operational
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Discharge modeling and characteristic analysis of semi-circular side weir based on the soft computing method J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Shanshan Li, Guiying Shen, Abbas Parsaie, Guodong Li, Dingye Cao
In this study, a support vector machine (SVM) and three optimization algorithms are used to develop a discharge coefficient (Cd) prediction model for the semi-circular side weir (SCSW). After that, we derived the input and output parameters of the model by dimensionless analysis as the ratio of the flow depth at the weir crest point upstream to the diameter (h1/D), the ratio of main channel width to
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PAVLIB4SWAT: a Python analysis and visualization tool and library based on Kepler.gl for SWAT models J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Qiaoying Lin, Dejian Zhang, Jiefeng Wu, Yihui Fang, Xingwei Chen, Bingqing Lin
View largeDownload slide View largeDownload slide Close modal The Soil and Water Assessment Tool (SWAT) has been widely applied to simulate the hydrological cycle, investigate cause-and-effect relationships, and aid decision-making for better watershed management. However, the software tools for model dataset analysis and visualization to support informed decision-making in a web environment are not
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Artificial hummingbird algorithm-optimized boosted tree for improved rainfall-runoff modelling J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Lyce Ndolo Umba, Ilham Yahya Amir, Gebre Gelete, Hüseyin Gökçekuş, Ikenna D. Uwanuakwa
Rainfall-runoff modelling is a critical component of hydrological studies, and its accuracy is essential for water resource management. Recent advances in machine learning have led to the development of more sophisticated rainfall-runoff models, but there is still room for improvement. This study proposes a novel approach to streamflow modelling that uses the artificial hummingbird algorithm (AHA)
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On the operational optimization of pump storage systems in water supply systems using PATs and time-differentiated energy prices J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Flávio Lourenço, Ana Luísa Reis, António Andrade-Campos
Power generation from fossil fuels has long had a negative impact on the environment. Nowadays, a paradigm shift in power generation is being witnessed, with increasing investment in renewable energy sources. Despite this progress, efficient energy storage is still limited. Given this challenge, pumped storage technology can be one of the viable solutions. This involves storing gravitational energy
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Study on wavelet multi-scale analysis and prediction of landslide groundwater J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Tianlong Wang, Dingmao Peng, Xu Wang, Bin Wu, Rui Luo, Zhaowei Chu, Hongyue Sun
Current groundwater prediction models often exhibit low accuracy and complex parameter adjustment. To tackle these limitations, a novel prediction model, called improved Aquila optimizer bi-directional long-term and short-term memory (IAO-BiLSTM) network, is proposed. IAO-BiLSTM optimizes the hyperparameters of the BiLSTM network using an IAO algorithm. IAO incorporates three novel enhancements, including
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Improved monthly runoff time series prediction using the CABES-LSTM mixture model based on CEEMDAN-VMD decomposition J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Dong-mei Xu, An-dong Liao, Wenchuan Wang, Wei-can Tian, Hong-fei Zang
View largeDownload slide View largeDownload slide Close modal Accurate runoff prediction is vital in efficiently managing water resources. In this paper, a hybrid prediction model combining complete ensemble empirical mode decomposition with adaptive noise, variational mode decomposition, CABES, and long short-term memory network (CEEMDAN-VMD-CABES-LSTM) is proposed. Firstly, CEEMDAN is used to decompose
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Experimental and numerical investigation of Engineered Injection and Extraction (EIE) induced with three-dimensional flow field J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Farsana M. Asha, N. Sajikumar, E. A. Subaida
In situ groundwater remediation technique is a commonly adopted method for the treatment of contaminated groundwater and the porous media associated with it. Engineered Injection and Extraction (EIE) has evolved as an improved methodology for in situ remediation, where sequential injection and extraction of clean water around the treatment area enhances the spreading of treatment reagents by inducing
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Fast high-fidelity flood inundation map generation by super-resolution techniques J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Zeda Yin, Yasaman Saadati, Beichao Hu, Arturo S. Leon, M. Hadi Amini, Dwayne McDaniel
View largeDownload slide View largeDownload slide Close modal Flooding is one of the most frequent natural hazards and causes more economic loss than all the other natural hazards. Fast and accurate flood prediction has significance in preserving lives, minimizing economic damage, and reducing public health risks. However, current methods cannot achieve speed and accuracy simultaneously. Numerical
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Analysis of discharge characteristics of a symmetrical stepped labyrinth side weir based on global sensitivity J. Hydroinform. (IF 2.7) Pub Date : 2024-01-01 Wuyi Wan, Guiying Shen, Shanshan Li, Abbas Parsaie, Yuhang Wang, Yu Zhou
In this paper, the discharge coefficient prediction model for this structure in a subcritical flow regime is first established by extreme learning machine (ELM) and Bayesian network, and the model's performance is analyzed and verified in detail. In addition, the global sensitivity analysis method is introduced to the optimal prediction model to analyze the sensitivity for the dimensionless parameters
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Daily rainfall assimilation based on satellite and weather radar precipitation products along with rain gauge networks J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Maria Asucena Rodriguez-Ramirez, Óscar Arturo Fuentes-Mariles
View largeDownload slide View largeDownload slide Close modal The analysis of the spatial and temporal distribution of storm events contributes to a better use of water resources, for example, the supply of drinking water, irrigation practices, electricity generation and management of extreme events to control floods and mitigate droughts, among others. The traditional observation of rainfall fields
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Predicting cyanobacteria abundance with Bayesian zero-inflated models J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Yirao Zhang, Nicolas M. Peleato
Cyanobacterial blooms are a persistent concern to water management and treatment, with blooms potentially causing the release of toxins and degrading water quality. However, previous models have not considered the zero inflation of cyanobacteria count data. Typically, a relatively large proportion of measured count data are zeros or non-detects of cyanobacteria, representing either no cyanobacteria
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Assessing the performances and transferability of graph neural network metamodels for water distribution systems J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Bulat Kerimov, Roberto Bentivoglio, Alexander Garzón, Elvin Isufi, Franz Tscheikner-Gratl, David Bernhard Steffelbauer, Riccardo Taormina
Metamodels accurately reproduce the output of physics-based hydraulic models with a significant reduction in simulation times. They are widely employed in water distribution system (WDS) analysis since they enable computationally expensive applications in the design, control, and optimisation of water networks. Recent machine-learning-based metamodels grant improved fidelity and speed; however, they
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Data-driven and echo state network-based prediction of wave propagation behavior in dam-break flood J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Changli Li, Zheng Han, Yange Li, Ming Li, Weidong Wang, Ningsheng Chen, Guisheng Hu
View largeDownload slide View largeDownload slide Close modal The computational prediction of wave propagation in dam-break floods is a long-standing problem in hydrodynamics and hydrology. We show that a reservoir computing echo state network (RC-ESN) that is well-trained on a minimal amount of data can accurately predict the long-term dynamic behavior of a one-dimensional dam-break flood. We solve
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Optimal charging station placement for autonomous robots in drinking water networks J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Mario Castro-Gama, Yvonne Hassink-Mulder
View largeDownload slide View largeDownload slide Close modal Drinking water utilities and commercial vendors are developing battery-powered autonomous robots for the internal inspection of pipelines. However, these robots require nearby charging stations next to the pipelines of the water distribution networks (WDN). This prompts practical questions about the minimal number of charging stations and
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Quantitative estimation and fusion optimization of radar rainfall in the Duanzhuang watershed at the eastern foot of the Taihang Mountains J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Ting Zhang, Yi Li, Jianzhu Li, Zhixia Li, Congmei Wang, Jin Liu
View largeDownload slide View largeDownload slide Close modal The temporal and spatial resolutions of rainfall data directly affect the accuracy of hydrological simulation. Weather radar has been used in business in China, but the uncertainty of data is large. At present, research on radar data and fusion in small and medium-sized basins in China is very weak. In this paper, taking the Duanzhuang watershed
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Study on the influencing parameters of rough-strip energy dissipators of curved spillways based on orthogonal tests and numerical simulation J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Honghong Zhang, Zhenwei Mu, Yiyun Wang, Zhen Zhou, Fan Fan, Fanqi Li, Hao Ma
View largeDownload slide View largeDownload slide Close modal Rough-strip energy dissipators (R-SEDs) can be arranged at the bend bottom of curved spillways to dissipate energy and divert flow for bend flow. Using the entropy weight and TOPSIS methods, a multi-criteria evaluation system was established for comprehensive energy dissipation and flow diversion effects of R-SEDs. Orthogonal tests and numerical
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UAV-based approach for municipal solid waste landfill monitoring and water ponding issue detection using sensor fusion J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Syed Zohaib Hassan, Peng Sun, Mert Gokgoz, Jiannan Chen, Debra R. Reinhart, Sarah Gustitus-Graham
View largeDownload slide View largeDownload slide Close modal Municipal solid waste (MSW) landfills need regular monitoring to ensure proper operations and meet environmental protection requirements. One requirement is to monitor landfill gas emissions from the landfill cover while another requirement is to monitor the potential settlement and damage to MSW landfill covers. Current surveying methods
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Optimal consequence management of pollution intrusion into water distribution networks considering demand variation and pipeline leakage: a case study J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Seyed Ghasem Razavi, Sara Nazif, Mehdi Ghorbani
View largeDownload slide View largeDownload slide Close modal To ensure the preservation of public health during periods of water distribution network (WDN) contamination, implementing effective consequence management (CM) plans is crucial. This study aimed to minimize the number of operational interventions and mitigate adverse effects on public health by considering WDN leakage and demand changes
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Influence of the channel bed slope on Shannon, Tsallis, and Renyi entropy parameters J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Gurpinder Singh, Rakesh Khosa, Manoj Kumar Jain, Tommaso Moramarco, Vijay P. Singh
View largeDownload slide View largeDownload slide Close modal Velocity distribution plays a fundamental role in understanding the hydrodynamics of open-channel flow. Among a multitude of approaches, the entropy-based approach holds great promise in achieving a reasonable characterisation of the velocity distribution. In entropy-based methods, the distribution depends on a key parameter, known as the
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Distributed Muskingum model with a Whale Optimization Algorithm for river flood routing J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Vida Atashi, Reza Barati, Yeo Howe Lim
This research introduces a novel nonlinear Muskingum model for river flood routing, aiming to enhance accuracy in modeling. It integrates lateral inflows using the Whale Optimization Algorithm (WOA) and employs a distributed Muskingum model, dividing river reaches into smaller intervals for precise calculations. The primary goal is to minimize the Sum of Square Errors (SSE) between the observed and
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Hydrodynamics of laminar pipe flow through an extended partial blockage by CFD J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Nuno M. C. Martins, Dídia I. C. Covas, Silvia Meniconi, Caterina Capponi, Bruno Brunone
In this paper, an advanced three-dimensional (3D) computational fluid dynamics (CFD) model is used to analyse the steady-state hydrodynamics of laminar flow through an extended partial blockage (PB) in a pressurised pipe. PB corresponds to one of the main faults affecting pipelines. In fact, it reduces its carrying capacity with economic consequences, and as it does not give rise to any external evidence
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Leak detection in water distribution networks based on graph signal processing of pressure data J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Daniel Bezerra Barros, Rui Gabriel Souza, Gustavo Meirelles, Bruno Brentan
Leakages in water distribution networks (WDNs) affect the hydraulic state of the entire or a large part of the network. Statistical correlation computed among pressure sensors monitoring network nodes aids the detection and localization of such leaks. This opens the possibility to work with water network databases, where graph signal processing (GSP) tools aid in understanding changes in pressure signals
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Sensor placement in water distribution networks using centrality-guided multi-objective optimisation J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Kegong Diao, Michael Emmerich, Jacob Lan, Iryna Yevseyeva, Robert Sitzenfrei
View largeDownload slide View largeDownload slide Close modal This paper introduces a multi-objective optimisation approach for the challenging problem of efficient sensor placement in water distribution networks for contamination detection. An important question is how to identify the minimal number of required sensors without losing the capacity to monitor the system as a whole. In this study, we
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Two different approaches for monitoring planning in sewer networks: topological vs. deterministic optimization J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Antonietta Simone, Alessandra Cesaro, Cristiana Di Cristo, Oreste Fecarotta, Maria Cristina Morani
View largeDownload slide View largeDownload slide Close modal Monitoring of sewer networks (SNs) is an important task whose planning can be related to various purposes, for example contaminant detection and epidemiological studies. This paper proposes two different approaches for the identification of a monitoring system in SNs. The first one proposes the identification of the best monitoring points
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Advancing integrated river basin management and flood forecasting in the Cagne catchment: a combined approach using deterministic distributed models J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Mingyan Wang, Paguédame Game, Philippe Gourbesville
View largeDownload slide View largeDownload slide Close modal To achieve an integrated river basin management for the Cagne catchment (France) and better predict floods, various modelling tools are integrated within a unified framework, forming a decision support system (DSS). In the paper, an integrated modeling approach employing deterministic distributed hydrological (MIKE SHE), hydraulic (MIKE
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F28: A novel coupling strategy for 1D/2D hydraulic models for flood risk assessment of the Mekong Delta J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Giang Song Le, Long Thanh Tran, Loc Huu Ho, Edward Park
Coupling models of different dimensions is one of the most important yet under-represented challenges. This paper introduces a new modeling strategy to streamline a more flexible and effective integrated one-dimensional (1D)/two-dimensional (2D) model for floodplains along lowland rivers. The 1D model, utilizing the finite volume method, solves the Saint–Venant equations, while the 2D mesh employs
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Prediction of multi-sectoral longitudinal water withdrawals using hierarchical machine learning models J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Julie Shortridge
Accurate models of water withdrawal are crucial in anticipating the potential water use impacts of drought and climate change. Machine learning methods can simulate the complex, nonlinear relationship between water use and potential explanatory factors, but rarely incorporate the hierarchical nature of water use data. This work presents a novel approach for the prediction of water withdrawals across
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A methodology for integrating time-lagged rainfall and river flow data into machine learning models to improve prediction of quality parameters of raw water supplying a treatment plant J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Christian Ortiz-Lopez, Andres Torres, Christian Bouchard, Manuel Rodriguez
View largeDownload slide View largeDownload slide Close modal Rainfall and increased river flow can deteriorate raw water (RW) quality parameters such as turbidity and UV absorbance at 254 nm. This study aims to develop a methodology for integrating both time-lagged watershed rainfall and river flow data into machine learning models of the quality of RW supplying a drinking water treatment plant (DWTP)
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Prediction of scour hole characteristics caused by water jets using metaheuristic artificial bee colony-optimized neural network and pre-processing techniques J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Veysi Kartal, Muhammet Emin Emiroglu, Okan Mert Katipoglu, Erkan Karakoyun
Preventing plunge pool scouring in hydraulic structures is crucial in hydraulic engineering. Although many studies have been conducted experimentally to determine relationship between the scour depth and water jets in several fields, available equations have deficiencies in calculating the exact scour due to complexity of scour process. This study investigated local scour depth in plunge pool using
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From digital twin paradigm to digital water services J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Francesco Gino Ciliberti, Luigi Berardi, Daniele Biagio Laucelli, Andres David Ariza, Laura Vanessa Enriquez, Orazio Giustolisi
In the context of water distribution networks (WDNs), researchers and technicians are actively working on new ways to transition into the digital era. They are focusing on creating standardized methods that fit the unique characteristics of these systems, with a strong emphasis on developing customized digital twins. This involves combining advanced hydraulic modeling with advanced data-driven techniques
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Experimental study on non-Darcian flow through a single artificial fracture for different fracture apertures and surface roughness J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Snigdha Pandey, Pramod Kumar Sharma
View largeDownload slide View largeDownload slide Close modal This study aims to explore the influence of various geometrical and hydraulic parameters on flow behavior and hydraulic conductivity in a single artificial fracture through a series of laboratory experiments. Laboratory experiments were conducted to examine unconfined groundwater flow through an artificially constructed single fracture.
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Discharge estimation in a compound channel with converging and diverging floodplains using ANN–PSO and MARS J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Divyanshu Shekhar, Bhabani Shankar Das, Kamalini Devi, Jnana Ranjan Khuntia, Tapas Karmaker
The discharge estimation in rivers is crucial in implementing flood management techniques and essential flood defence and drainage systems. During the normal flood season, water flows solely in the main channel. During a flood, rivers comprise a main channel and floodplains, collectively called a compound channel. Computing the discharge is challenging in non-prismatic compound channels where the floodplains
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A comprehensive study of various regressions and deep learning approaches for the prediction of friction factor in mobile bed channels J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Akshita Bassi, Ajaz Ahmad Mir, Bimlesh Kumar, Mahesh Patel
View largeDownload slide View largeDownload slide Close modal A fundamental issue in the hydraulics of movable bed channels is the measurement of friction factor (λ), which represents the head loss because of hydraulic resistance. The execution of experiments in the laboratory hinders the predictability of λ over a short period of time. The major challenges that arise with traditional forecasting approaches
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Knowledge-driven intelligent recommendation method for emergency plans in water diversion projects J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Lihu Wang, Xuemei Liu, Yang Liu, Hairui Li, Jiaqi Liu
View largeDownload slide View largeDownload slide Close modal The emergency plans for water diversion projects suffer from weak knowledge correlation, inadequate timeliness, and insufficient support for intelligent decision-making. This study incorporates knowledge graph technology to enable intelligent recommendations for emergency plans in water diversion projects. By employing pre-trained language
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Modeling ion constituents in the Sacramento-San Joaquin Delta using multiple machine learning approaches J. Hydroinform. (IF 2.7) Pub Date : 2023-11-01 Peyman Namadi, Minxue He, Prabhjot Sandhu
Salinity is of paramount importance in shaping water quality, ecosystem health, and the capacity to sustain diverse human and environmental demands in estuarine environments. Electrical conductivity (EC) is commonly utilized as an indirect measure of salinity, serving as a proxy for estimating other ion constituents within the Sacramento-San Joaquin Delta (Delta) of California, United States. This