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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 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 Q2 Engineering Pub Date : 2024-03-01 DOI: 10.2166/hydro.2024.002
Abstract not available
无摘要
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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 Q2 Engineering Pub Date : 2024-03-01 DOI: 10.2166/hydro.2024.001
Abstract not available
无摘要
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引用次数: 0
Automatic calibration of SWMM parameters based on multi-objective optimisation model 基于多目标优化模型的 SWMM 参数自动校准
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-02-15 DOI: 10.2166/hydro.2024.282
Tao Wang, Longlong Zhang, Jiaqi Zhai, Lizhen Wang, Yifei Zhao, Kuan Liu
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, aiming to narrow down the solution space and expedite the model-solving speed. Secondly, the NSGA-3 multi-objective optimisation algorithm based on the Pareto theory is applied for the optimisation and calibration of sensitive parameter sets. The model is validated in the rainwater drainage system with independent runoff in a residential area in a northwestern city in China. The results show that parameters such as N-Imperv and KSlope are highly sensitive to the model output under the land-use conditions of the study area. The simulation accuracy of the multi-objective continuous optimisation algorithm is significantly better than that of the single-objective genetic algorithm. The simulation results of the SWMM model under multi-objective optimisation demonstrate a certain level of reliability and stability. The research findings can provide technical support for the automatic calibration of SWMM model parameters, accurate model simulation, and application.
针对传统 SWMM 模型参数校核方法精度低、效率低的问题,本文构建了基于多目标优化算法的参数自动校核模型。首先,利用 Sobol 法和 GLUE 法确定敏感参数及其范围,以缩小解空间,加快模型求解速度。其次,应用基于帕累托理论的 NSGA-3 多目标优化算法对敏感参数集进行优化和校准。该模型在中国西北某城市居民区独立径流的雨水排水系统中进行了验证。结果表明,在研究区域的土地利用条件下,N-Imperv 和 KSlope 等参数对模型输出高度敏感。多目标连续优化算法的模拟精度明显优于单目标遗传算法。多目标优化下的 SWMM 模型模拟结果具有一定的可靠性和稳定性。研究成果可为 SWMM 模型参数的自动标定、模型的精确模拟和应用提供技术支持。
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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 Q2 Engineering Pub Date : 2024-02-01 DOI: 10.2166/hydro.2024.212
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 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.

水文信息学的一个最新趋势是数据、模型和网络工具的数量不断增加,这些工具都可以通过网络访问,其目的都是通过网络技术改进水文领域的常见研究任务。将基于网络的模型和工具结合在一起,有望形成一个综合环境,促进社区参与、合作和科学复制。有许多服务器端水文信息资源耦合的例子,其中一个通用标准就是接口。然而,客户端资源耦合的例子,尤其是采用通用规范的例子,却少之又少。为此,我们在 JavaScript 编程语言中实现了基本模型接口(BMI)规范,这是网络上使用最广泛的编程语言。通过使用 BMI,我们将两个客户端水文应用程序(HydroLang 和 HLM-Web)耦合在一起,利用降雨数据和客户端水文模型对历史事件进行降雨-径流模拟,作为案例研究示范。通过这一过程,我们展示了如何通过采用通用标准来简化一项常见且往往乏味的任务--两个独立网络资源的耦合。此外,该标准的应用还促进了水文模型向客户端 "模型即服务 "的可能性迈进了一步。
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引用次数: 0
Meteorological characteristics of line-shaped rainbands in northern Japan and its surrounding seas under climate change 气候变化下日本北部及其周边海域线状雨带的气象特征
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-02-01 DOI: 10.2166/hydro.2024.121
Yuta Ohya, Tomohito J. Yamada
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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 conditions. Our study investigates the link between LRBs and weather patterns in Hokkaido during July and August, using historical and climate prediction

查看 largeDownload 幻灯片查看 largeDownload 幻灯片 关闭模态近年来,日本北海道的线状雨带(LRBs)有所增加。历史上,线状雨带曾多次引发洪水灾害,因此需要对导致线状雨带的天气模式进行研究。本研究旨在从统计学角度了解气候变化条件下夏季线状雨带与天气模式之间的关系。我们的研究利用历史和气候预测模型,调查了北海道 7 月和 8 月的低洼地带洪水与天气模式之间的关系。如果全球气温上升 2°/4°,该地区的枸杞多糖发生率将增加约 1.51/2.07 倍。低气压带发生率最高与来自南方的水汽通量增加和太平洋上空的正气压异常有关。有三种主要的天气模式对低气压带的发生有重要影响:(1)附近的低压系统;(2)加强的太平洋高锋模式;(3)接近或登陆北海道的台风。这些模式使 LRB 发生概率增加了一倍,这是在过去和预测气候(+2K 和 +4K 实验)中观察到的特征。这些都是未来洪水风险管理的重要启示。
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引用次数: 0
Evaluation of satellite rainfall estimates using PERSIANN-CDR and TRMM over three critical cells in Jordan 利用 PERSIANN-CDR 和 TRMM 对约旦三个关键小区的卫星降雨量估算进行评估
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-02-01 DOI: 10.2166/hydro.2024.154
Mohanned Al-Sheriadeh, Anas Riyad Al-Sharman
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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 evaluation techniques, and the use of short evaluation durations. To improve our understanding of SREs, this study evaluated the long-term performance of

查看大尺寸下载幻灯片查看大尺寸下载幻灯片 关闭模版水资源的有效管理在很大程度上取决于对降雨模式的准确了解。卫星降雨估测(SRE)由于能够提供空间降雨数据而越来越受欢迎。然而,卫星降雨量估算的准确性受到多种因素的限制,包括缺乏观测、评估技术不足以及使用的评估持续时间较短。为了增进我们对 SRE 的了解,本研究通过分析热带降雨测量使命(TRMM)和 PERSIANN-CDR 的时空模式,评估了它们的长期性能。使用统计量和约旦三个关键小区 71 个雨量计 2000 年至 2013 年的数据,对日、月、季和年降水量估计值进行了评估。结果表明,虽然两个 SRE 的日精度都较低,但 TRMM 3B43 的月精度优于 PERSIANN-CDR。此外,TRMM 3B43 在暴雨季节表现出更优越的性能,而 PERSIANN-CDR 在其他季节则表现出更好的结果。在年度研究中,发现 TRMM 3B43 在北部和南部小区的精度高于 PERSIANN-CDR,而 PERSIANN-CDR 在中部小区的相关系数更高。这些发现有助于开发更可靠、更准确的 SRE,从而改进水资源管理研究。
{"title":"Evaluation of satellite rainfall estimates using PERSIANN-CDR and TRMM over three critical cells in Jordan","authors":"Mohanned Al-Sheriadeh, Anas Riyad Al-Sharman","doi":"10.2166/hydro.2024.154","DOIUrl":"https://doi.org/10.2166/hydro.2024.154","url":null,"abstract":"<div><div data- reveal-group-><div><img alt=\"graphic\" data-src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\" path-from-xml=\"hydro-d-23-00154gf01.tif\" src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;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/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\" path-from-xml=\"hydro-d-23-00154gf01.tif\" src=\"https://iwa.silverchair-cdn.com/iwa/content_public/journal/jh/26/2/10.2166_hydro.2024.154/1/m_hydro-d-23-00154gf01.png?Expires=1712246905&amp;Signature=l7k9ixdsA6TvOf4cuuVzLNAo8suokFyYQaEjqpHVCPG66-4u~GJsd5D4TZDRd0rVz70ykR0UyLf34NDPsGd8qQ6jNW0bhGPpqGTz2SME1Apw23RLHbpdLJkNXCgufLrbQJOXg-pXfq4Uo0pYjsVYH8M8OtuFjgGLXju0BKnLSjUBo1qCz~nYYD6dhv~eiGcB1R5Y5x9yeRAj02lHfhNH7RDgJPultNx1QFQd3FWSH1vp0eSFYixbu6Mirm5yi94MwYkrf9gS3MnJq-1zIS8HKGlLm6CzoUVr4t2JFbXEd4dKbkus8NiwQkzbdaF-r8o63eCFH9BBtKSgEmXkwj4Sfw__&amp;Key-Pair-Id=APKAIE5G5CRDK6RD3PGA\"/><div>View largeDownload slide</div></div><i> </i><span>Close modal</span></div></div><p>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 evaluation techniques, and the use of short evaluation durations. To improve our understanding of SREs, this study evaluated the long-term performance of ","PeriodicalId":54801,"journal":{"name":"Journal of Hydroinformatics","volume":null,"pages":null},"PeriodicalIF":2.7,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140005485","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
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 勘误:《水文信息学杂志》,2023 年 11 月 1 日;25 (6):2253-2267;饮用水网络中自主机器人的最佳充电站位置,Mario Castro-Gama、Yvonne Hassink-Mulder
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-01-17 DOI: 10.2166/hydro.2023.401
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引用次数: 0
Fast high-fidelity flood inundation map generation by super-resolution techniques 利用超分辨率技术快速生成高保真洪水淹没图
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-01-02 DOI: 10.2166/hydro.2024.228
Zeda Yin, Yasaman Saadati, Beichao Hu, Arturo S. Leon, M. H. Amini, Dwayne McDaniel
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 methods can provide high-fidelity results, but they are time-consuming, particularly when pursuing high accuracy. Conversely, neural networks can provide results in a matter of seconds, but they have shown low accuracy in flood map generation by all existing methods. This work combines the strengths of numerical methods and neural networks and builds a framework that can quickly and accurately model the high-fidelity flood inundation map with detailed water depth information. In this paper, we employ the U-Net and generative adversarial network (GAN) models to recover the lost physics and information from ultra-fast, low-resolution numerical simulations, ultimately presenting high-resolution, high-fidelity flood maps as the end results. In this study, both the U-Net and GAN models have proven their ability to reduce the computation time for generating high-fidelity results, reducing it from 7–8 h down to 1 min. Furthermore, the accuracy of both models is notably high.
洪水是最常见的自然灾害之一,造成的经济损失比其他所有自然灾害都大。快速准确的洪水预测对于保护生命、减少经济损失和降低公共卫生风险具有重要意义。然而,目前的方法无法同时实现快速和准确。数值方法可以提供高保真结果,但耗费时间,尤其是在追求高精度时。相反,神经网络可以在几秒钟内提供结果,但在所有现有方法中,神经网络生成洪水地图的准确性较低。这项工作结合了数值方法和神经网络的优势,建立了一个框架,可以快速、准确地模拟出具有详细水深信息的高保真洪水淹没图。在本文中,我们采用 U-Net 和生成式对抗网络 (GAN) 模型,从超快、低分辨率的数值模拟中恢复丢失的物理和信息,最终呈现出高分辨率、高保真的洪水地图。在这项研究中,U-Net 和 GAN 模型都证明了它们有能力缩短生成高保真结果的计算时间,将计算时间从 7-8 小时缩短到 1 分钟。此外,这两种模型的精确度都非常高。
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引用次数: 0
Experimental and numerical investigation of Engineered Injection and Extraction (EIE) induced with three-dimensional flow field 三维流场诱导的工程喷射与萃取(EIE)的实验和数值研究
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-01-01 DOI: 10.2166/hydro.2023.427
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 additional flow fields. Conventional EIE studies were based on flow fields in two dimensions. There are only limited experimental and theoretical studies exploring the potential of inducing a three-dimensional flow field using EIE. The present study experimentally and numerically evaluates the effect of a three-dimensional flow field induced by partially screened wells. EIE experiments were conducted on a laboratory-scale aquifer model with laterite soil as the porous medium. Tracer transport in porous medium was studied by measuring the concentration at various observation points and enhanced dilution was observed when EIE was employed with partially screened wells. Experimental observations were also used to calibrate and validate the numerical model developed using Visual MODFLOW Flex. Enhancement in spreading was quantified in terms of concentration mass attenuation and maximum mass attenuation was observed when EIE was employed with partially screened wells.

地下水原位修复技术是处理受污染地下水及其相关多孔介质的常用方法。工程注入和抽取(EIE)是一种经过改进的原位修复方法,通过在处理区域周围连续注入和抽取清洁水,诱导额外的流场,从而加强处理试剂的扩散。传统的 EIE 研究基于二维流场。只有有限的实验和理论研究探讨了利用 EIE 诱导三维流场的潜力。本研究通过实验和数值方法评估了部分屏蔽井诱导三维流场的效果。EIE 实验是在以红土为多孔介质的实验室规模含水层模型上进行的。通过测量不同观测点的浓度,研究了示踪剂在多孔介质中的迁移情况。实验观测结果还用于校准和验证使用 Visual MODFLOW Flex 开发的数值模型。以浓度质量衰减的方式对扩散的增强进行了量化,当 EIE 与部分屏蔽井一起使用时,观察到了最大的质量衰减。
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引用次数: 0
PAVLIB4SWAT: a Python analysis and visualization tool and library based on Kepler.gl for SWAT models PAVLIB4SWAT:基于 Kepler.gl 的 Python 分析和可视化工具及库,用于 SWAT 模型
IF 2.7 3区 工程技术 Q2 Engineering Pub Date : 2024-01-01 DOI: 10.2166/hydro.2023.182
Qiaoying Lin, Dejian Zhang, Jiefeng Wu, Yihui Fang, Xingwei Chen, Bingqing Lin
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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 considered fully fledged and are technically intensive to implement. This study focuses on addressing these issues by establishing a tool and library (n

查看大图查看大图 关闭模态水土评估工具(SWAT)已被广泛应用于模拟水文循环、研究因果关系和辅助决策,以改善流域管理。然而,用于模型数据集分析和可视化以支持网络环境中的知情决策的软件工具尚未完全成熟,而且实施起来技术要求很高。本研究的重点是通过建立一个工具和库(命名为 PAVLIB4SWAT)来解决这些问题,该工具和库可以在很大程度上降低开发人员的专业技术要求,使开发人员可以根据自身需求采用和定制这项工作。具体来说,我们在 Kepler.gl widget 的基础上创建了 PAVLIB4SWAT,以便通过动态交互式地图可视化 SWAT 模型数据,包括流域划分过程中的形状文件、模型输入和模拟结果。我们通过晋江流域 SWAT 模型使用案例对 PAVLIB4SWAT 进行了评估,以展示其实用性和易用性。案例研究表明,PAVLIB4SWAT 可为 SWAT 模型提供各种地理空间分析和制图功能,并能以独立离线网页和网络服务器的形式灵活发布可视化结果。此外,PAVLIB4SWAT 是一个开源项目,纯粹用 Python 编程语言实现,因此开发人员可以很容易地对其进行调整和定制,以满足自己的需求。
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Journal of Hydroinformatics
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