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Corrigendum: Journal of Hydroinformatics 1 January 2024; 26 (1): 304–318. Experimental and numerical investigation of Engineered Injection and Extraction (EIE) induced with three-dimensional flow field. Farsana M. Asha, N. Sajikumar, E. A. Subaida. https://doi.org/10.2166/hydro.2023.427 J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01
Abstract not available
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Temporal and spatial satellite data augmentation for deep learning-based rainfall nowcasting J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Özlem Baydaroğlu, Ibrahim Demir
The significance of improving rainfall prediction methods has escalated due to climate change-induced flash floods and severe flooding. In this study, rainfall nowcasting has been studied utilizing NASA Giovanni satellite-derived precipitation products and the convolutional long short-term memory (ConvLSTM) approach. The goal of the study is to assess the impact of data augmentation on flood nowcasting
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Smart River Information Services in managing Nile River navigation system J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Noha Kamal
View largeDownload slide View largeDownload slide Close modal In terms of the significance of incorporating smart techniques into large river navigation systems to increase inland navigation competitiveness, this article introduces the development of smart River Information Services (RIS) in Egypt based on smart information and communication technologies as real-time tracking systems, Open Geographic
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Estimating critical depth and discharge over sloping rough end depth using machine learning J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Ahmed Y. Mohammed, Parveen Sihag
This study uses machine learning (ML) to predict the end-depth structure's discharge and critical depth (yc). Linear regression, M5P, random forest, random tree, reduced error pruning tree, and Gaussian process (GP) are the ML methods used in this investigation. The findings indicate that the radial kernel function-based GP model is most suitable compared to other applied models with the lowest root-mean-square
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Automatic calibration of SWMM parameters based on multi-objective optimisation model J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Tao Wang, Longlong Zhang, Jiaqi Zhai, Lizhen Wang, Yifei Zhao, Kuan Liu
View largeDownload slide View largeDownload slide Close modal To address the issue of low accuracy and inefficiency in the traditional parameter calibration methods for the SWMM model, this paper constructs an automatic parameter calibration model based on multi-objective optimisation algorithms. Firstly, the Sobol method and GLUE method are utilised to determine sensitive parameters and their ranges
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Understanding the impact of population dynamics on water use utilizing multi-source big data J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Guihuan Zhou, Zhanjie Li, Wei Wang, Qianyang Wang, Jingshan Yu
Population movement, such as commuting, can affect water supply pressure and efficiency in modern cities. However, there is a gap in the research concerning the relationship between water use and population mobility, which is of great significance for urban sustainable development. In this study, we analyzed the spatial–temporal dynamics of the population and its underlying mechanisms, using multi-source
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Water distribution system modelling of GIS-remote sensing and EPANET for the integrated efficient design J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Pranit Dongare, Kul Vaibhav Sharma, Vijendra Kumar, Aneesh Mathew
Urban settlement depends on water distribution networks for clean and safe drinking water. This research incorporates geographic information systems (GIS), remote sensing (RS), and hydraulic modelling software EPANET to analyse and construct water distribution systems in Bota town, India. Satellite images and hydrological data have been utilized for the management of the Bota town's water supply network
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Analysis of characteristic index and prediction of river bottom tearing scour in the Yellow River J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Longfei Sun, Yanhui Liu, Yuanjian Wang, Qinghao Dong, Wanjie Zhao
View largeDownload slide View largeDownload slide Close modal River bottom tearing scour (RBTS) has a strong effect on the scouring and moulding of channel in the Yellow River. Due to the special forming conditions, complex influencing factors, and limited observed data, it is difficult to predict whether RBTS will occur accurately. By collecting and disposing of the hydrodynamic, sediment, and initial
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Water quality emergency monitoring networks: A method for identifying non-critical variables based on Shannon's entropy J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01 Fábio Monteiro Cruz, Talita Fernanda das Graças Silva
View largeDownload slide View largeDownload slide Close modal In the occurrence of environmental disasters involving water resources, deploying an emergency monitoring network for assessing water quality is within the first measures to be taken. Emergency networks usually cover a large set of water quality variables and monitoring stations along the watershed. Focusing on variables that represent greater
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Corrigendum: Journal of Hydroinformatics 25 (6), 2643–2659: Enhanced forecasting of multi-step ahead daily soil temperature using advanced hybrid vote algorithm-based tree models, Javad Hatamiafkoueieh, Salim Heddam, Saeed Khoshtinat, Solmaz Khazaei, Abdol-Baset Osmani, Ebrahim Nohani, Mohammad Kiomarzi, Ehsan Sharafi and John Tiefenbacher, https://doi.org/10.2166/hydro.2023.188 J. Hydroinform. (IF 2.7) Pub Date : 2024-03-01
Abstract not available
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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