Journal of Hydroinformatics最新文献

Accelerating regional-scale groundwater flow simulations with a hybrid deep neural network model incorporating mixed input types: A case study of the northeast Qatar aquifer 利用混合输入类型的混合深度神经网络模型加速区域尺度地下水流模拟：卡塔尔东北部含水层案例研究

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-06-01 DOI: 10.2166/hydro.2024.275

Ali Al-Maktoumi, Mohammad Mahdi Rajabi, Slim Zekri, Rajesh Govindan, Aref Panjehfouladgaran, Zahra Hajibagheri

{"title":"Accelerating regional-scale groundwater flow simulations with a hybrid deep neural network model incorporating mixed input types: A case study of the northeast Qatar aquifer","authors":"Ali Al-Maktoumi, Mohammad Mahdi Rajabi, Slim Zekri, Rajesh Govindan, Aref Panjehfouladgaran, Zahra Hajibagheri","doi":"10.2166/hydro.2024.275","DOIUrl":"https://doi.org/10.2166/hydro.2024.275","url":null,"abstract":"<p>This study presents the ‘Dual Path CNN-MLP’, a novel hybrid deep neural network (DNN) architecture that merges the strengths of convolutional neural networks (CNNs) and multilayer perceptrons (MLPs) for regional groundwater flow simulations. This model stands out from previous DNN approaches by managing mixed input types, including both imagery and numerical vectors. Such flexibility allows the diverse nature of groundwater data to be efficiently utilized without the need to convert it into a uniform format, which often leads to oversimplification or unnecessary expansion of the dataset. When applied to the northeast Qatar aquifer, the model demonstrates high accuracy in simulating transient groundwater flow fields, benchmarked against the well-established MODFLOW model. The model's efficacy is confirmed through <em>k</em>-fold cross-validation, showing an error margin of less than 12% across all examined locations. The study also examines the model's ability to perform uncertainty analysis using Monte Carlo simulations, finding that it achieves around 1% average absolute percentage error in estimating the mean hydraulic head. Errors are mostly found in areas with significant variations in the hydraulic head. Switching to this machine learning model from the conventional MODFLOW simulator boosts computational efficiency by about 99%, showcasing its advantage for tasks like uncertainty analysis in repetitive groundwater simulations.</p>","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":"30 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A parallel multi-objective optimization based on adaptive surrogate model for combined operation of multiple hydraulic facilities in water diversion project 基于自适应代用模型的并行多目标优化，用于引水工程中多个水利设施的联合运行

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-06-01 DOI: 10.2166/hydro.2024.285

Xiaolian Liu, Zirong Liu, Xiaopeng Hou, Yu Tian, Xueni Wang, Leike Zhang, Hao Wang

{"title":"A parallel multi-objective optimization based on adaptive surrogate model for combined operation of multiple hydraulic facilities in water diversion project","authors":"Xiaolian Liu, Zirong Liu, Xiaopeng Hou, Yu Tian, Xueni Wang, Leike Zhang, Hao Wang","doi":"10.2166/hydro.2024.285","DOIUrl":"https://doi.org/10.2166/hydro.2024.285","url":null,"abstract":"<div><div data- reveal-group-><div><img alt=\"graphic\" data-src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/6/10.2166_hydro.2024.285/1/m_hydro-d-23-00285gf01.png?Expires=1722776531&Signature=fzcnkQR2-2BId91KCizNTxQeaQ6fzTXeOpk5iiQ11CgnaJp~zCbqs-W4ADrr-4H56dTw4YpDE2umo9ru66tRlelR-HNh79KpDaxof~HKccwEiCxsi25D9WE7oZBJ9ratf6TVwKEvHV0Q8Wl6Kv7p6AyXQNk0lbqrJEJsOSQiFEoYsilEX04eciQGPQKxNlXo8eLfi3xhs5ba7DhcjXBg-KFrr1ylb03S~75HJVPRChuCN3CnZxKDGDDVixLI92fwjyunfJgAZFXIRvVEjdHsOfvmU5Z-EwBNil5ZeMJQ7vgv8eqs7xO4MIwo4j~65L3Oe~BToMRNBx6E1cdPYDNCPg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\" path-from-xml=\"hydro-d-23-00285gf01.tif\" src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/6/10.2166_hydro.2024.285/1/m_hydro-d-23-00285gf01.png?Expires=1722776531&Signature=fzcnkQR2-2BId91KCizNTxQeaQ6fzTXeOpk5iiQ11CgnaJp~zCbqs-W4ADrr-4H56dTw4YpDE2umo9ru66tRlelR-HNh79KpDaxof~HKccwEiCxsi25D9WE7oZBJ9ratf6TVwKEvHV0Q8Wl6Kv7p6AyXQNk0lbqrJEJsOSQiFEoYsilEX04eciQGPQKxNlXo8eLfi3xhs5ba7DhcjXBg-KFrr1ylb03S~75HJVPRChuCN3CnZxKDGDDVixLI92fwjyunfJgAZFXIRvVEjdHsOfvmU5Z-EwBNil5ZeMJQ7vgv8eqs7xO4MIwo4j~65L3Oe~BToMRNBx6E1cdPYDNCPg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\"/><div>View largeDownload slide</div></div></div><div content- data-reveal=\"data-reveal\"><div><img alt=\"graphic\" data-src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/6/10.2166_hydro.2024.285/1/m_hydro-d-23-00285gf01.png?Expires=1722776531&Signature=fzcnkQR2-2BId91KCizNTxQeaQ6fzTXeOpk5iiQ11CgnaJp~zCbqs-W4ADrr-4H56dTw4YpDE2umo9ru66tRlelR-HNh79KpDaxof~HKccwEiCxsi25D9WE7oZBJ9ratf6TVwKEvHV0Q8Wl6Kv7p6AyXQNk0lbqrJEJsOSQiFEoYsilEX04eciQGPQKxNlXo8eLfi3xhs5ba7DhcjXBg-KFrr1ylb03S~75HJVPRChuCN3CnZxKDGDDVixLI92fwjyunfJgAZFXIRvVEjdHsOfvmU5Z-EwBNil5ZeMJQ7vgv8eqs7xO4MIwo4j~65L3Oe~BToMRNBx6E1cdPYDNCPg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\" path-from-xml=\"hydro-d-23-00285gf01.tif\" src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/6/10.2166_hydro.2024.285/1/m_hydro-d-23-00285gf01.png?Expires=1722776531&Signature=fzcnkQR2-2BId91KCizNTxQeaQ6fzTXeOpk5iiQ11CgnaJp~zCbqs-W4ADrr-4H56dTw4YpDE2umo9ru66tRlelR-HNh79KpDaxof~HKccwEiCxsi25D9WE7oZBJ9ratf6TVwKEvHV0Q8Wl6Kv7p6AyXQNk0lbqrJEJsOSQiFEoYsilEX04eciQGPQKxNlXo8eLfi3xhs5ba7DhcjXBg-KFrr1ylb03S~75HJVPRChuCN3CnZxKDGDDVixLI92fwjyunfJgAZFXIRvVEjdHsOfvmU5Z-EwBNil5ZeMJQ7vgv8eqs7xO4MIwo4j~65L3Oe~BToMRNBx6E1cdPYDNCPg__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\"/><div>View largeDownload slide</div></div><i> </i><span>Close modal</span></div></div><p>In a complex pressurized water diversion project (WDP), the combined optimal operation of multiple hydraulic facilities is computationally expensive owing to the requirement of massive mathematical simulation model runs. A parallel multi-objective optimization based on adaptive surrogate model (PMO-ASMO) was proposed in this study to alleviate the computational burden while maintaining its effectiveness. At the simulation level, an adaptive surrogate model was established, while a paralle","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":"70 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A genetic algorithm's novel rainfall distribution method for optimized hydrological modeling at basin scales 用于流域尺度水文模型优化的遗传算法新型降雨分布方法

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-06-01 DOI: 10.2166/hydro.2024.224

Charalampos Skoulikaris, Nikolaos Nagkoulis

引用次数: 0

Advancing rapid urban flood prediction: a spatiotemporal deep learning approach with uneven rainfall and attention mechanism 推进城市洪水快速预测：具有不均匀降雨和关注机制的时空深度学习方法

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-06-01 DOI: 10.2166/hydro.2024.024

Yu Shao, Jiarui Chen, Tuqiao Zhang, Tingchao Yu, Shipeng Chu

引用次数: 0

Long-term inflow forecast using meteorological data based on long short-term memory neural networks 基于长短期记忆神经网络的气象数据长期流入量预报

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-05-01 DOI: 10.2166/hydro.2024.196

Hongye Zhao, Shengli Liao, Yitong Song, Zhou Fang, Xiangyu Ma, BinBin Zhou

引用次数: 0

Analysis of characteristic index and prediction of river bottom tearing scour in the Yellow River 黄河河底撕裂冲刷特征指标分析与预测

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-03-01 DOI: 10.2166/hydro.2024.247

Longfei Sun, Yanhui Liu, Yuanjian Wang, Qinghao Dong, Wanjie Zhao

引用次数: 0

Understanding the impact of population dynamics on water use utilizing multi-source big data 利用多源大数据了解人口动态对用水的影响

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-03-01 DOI: 10.2166/hydro.2024.179

Guihuan Zhou, Zhanjie Li, Wei Wang, Qianyang Wang, Jingshan Yu

{"title":"Understanding the impact of population dynamics on water use utilizing multi-source big data","authors":"Guihuan Zhou, Zhanjie Li, Wei Wang, Qianyang Wang, Jingshan Yu","doi":"10.2166/hydro.2024.179","DOIUrl":"https://doi.org/10.2166/hydro.2024.179","url":null,"abstract":"<p>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 geospatial big data, including Baidu heat maps (BHMs), land use parcels, and point of interest. Combined with water consumption, sewage volume, and river depth data, the impact of population dynamics on water use was investigated. The results showed that there were obvious differences in population dynamics between weekdays and weekends with a ratio of 1.11 for the total population. Spatially, the population concentration was mainly observed in areas associated with enterprises, industries, shopping, and leisure activities during the daytime, while at nighttime, it primarily centered around residential areas. Moreover, the population showed a significant impact on water use, resulting in co-periods of 24 h and 7 days, and the water consumption as well as the wastewater production were observed to be proportional to the population density. This study can offer valuable implications for urban water resource allocation strategies.</p>","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":"57 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140322494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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 Corrigendum：Journal of Hydroinformatics 1 January 2024; 26 (1)：304-318.三维流场诱导工程注采（EIE）的实验与数值研究。Farsana M. Asha, N. Sajikumar, E. A. Subaida. https://doi.org/10.2166/hydro.2023.427

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-03-01 DOI: 10.2166/hydro.2024.002

引用次数: 0

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 更正：水文信息学杂志》25 (6)，2643-2659：使用基于混合投票算法的先进树模型加强多步超前日土壤温度预报，Javad Hatamiafkoueieh、Salim Heddam、Saeed Khoshtinat、Solmaz Khazaei、Abdol-Baset Osmani、Ebrahim Nohani、Mohammad Kiomarzi、Ehsan Sharafi 和 John Tiefenbacher，https://doi.org/10.2166/hydro.2023.188。

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-03-01 DOI: 10.2166/hydro.2024.001

引用次数: 0

Client-side web-based model coupling using basic model interface for hydrology and water resources 使用水文和水资源基本模型界面的客户端网络模型耦合

IF 2.7 3区工程技术

Journal of Hydroinformatics Pub Date : 2024-02-01 DOI: 10.2166/hydro.2024.212

Gregory Ewing, Carlos Erazo Ramirez, Ashani Vaidya, Ibrahim Demir

{"title":"Client-side web-based model coupling using basic model interface for hydrology and water resources","authors":"Gregory Ewing, Carlos Erazo Ramirez, Ashani Vaidya, Ibrahim Demir","doi":"10.2166/hydro.2024.212","DOIUrl":"https://doi.org/10.2166/hydro.2024.212","url":null,"abstract":"<p>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 of server-side, hydroinformatics resource coupling, where a common standard serves as an interface. Yet, there are few, if any, examples of client-side resource coupling, particularly cases where a common specification is employed. Toward this end, we implemented the basic model interface (BMI) specification in the JavaScript programing language, the most widely used programing language on the web. By using BMI, we coupled two client-side hydrological applications (HydroLang and HLM-Web) to perform rainfall–runoff simulations of historical events with rainfall data and a client-side hydrological model as a case study demonstration. Through this process, we present how a common and often tedious task – the coupling of two independent web resources – can be made easier through the adoption of a common standard. Furthermore, applying the standard has facilitated a step toward the possibility of client-side ‘Model as a Service’ for hydrological models.</p>","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":"18 1","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0