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Water
Special Issues
Managing Water Resources and Socio-Hydrologic Systems: New Understanding and Solutions
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Managing Water Resources and Socio-Hydrologic Systems: New Understanding and Solutions

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 25 February 2025 | Viewed by 2895

Special Issue Editors

Prof. Dr. Dengfeng Liu

E-Mail Website
Guest Editor
School of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China
Interests: watershed hydrological modeling; hydrological model; ecohydrological modeling; socio-hydrological modeling; ecohydrology
Special Issues, Collections and Topics in MDPI journals
Dr. Yuanyuan Yang

E-Mail Website
Guest Editor Assistant
School of Water Resources and Hydropower, Xi’an University of Technology, Xi’an 710048, China
Interests: hydrological modeling; stormwater management; watershed hydrology; integrated water resources management; geological hazard

Special Issue Information

Dear Colleagues,

As the increase of the impact of global climate change and human activities, the sustainable management of water resources has become a challenge in many river basins all over the world. The third IAHS Scientific Decade will be dedicated to local solutions under the global water crisis. The short name will be HELPING, and stand for Hydrology Engaging Local People IN one Global world. So Managing Water Resources and Socio-Hydrologic Systems will be an urgent topic for hydrologists, scientists, and decision-makers. Based on the progress of study on water resources management and socio-hydrologic systems, new understanding and solutions are vital for the sustainable management of water resources and socio-hydrologic systems to meet the challenge of the local water crisis.

We invite original research articles that contribute to new understanding and solutions for managing water resources and socio-hydrologic systems on the watershed scale or regional scale. Among the topics of interest for this Special Issue are:

  • new understanding of managing water resources
  • local solutions for water resources management at the watershed scale or regional scale
  • new understanding of socio-hydrologic systems
  • new understanding of interactions of social process and hydrologic process
  • new solutions to simulate socio-hydrologic processes
  • new solutions to predict the evolution of socio-hydrologic systems

Prof. Dr. Dengfeng Liu
Guest Editor

Dr. Yuanyuan Yang
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • water resources
  • socio-hydrology
  • socio-hydrologic systems
  • socio-hydrological model
  • socio-ecohydrological process
  • trade-off
  • watershed scale

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Published Papers (3 papers)

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Research

29 pages, 2243 KiB  
Article
Factors Influencing Water Resource Levels Under the Water Resource Carrying Capacity Framework: A Dynamic Qualitative Comparative Analysis Based on Provincial Panel Data
by Zehua Li, Yanfeng Wu, Zhijun Li, Wenguang Zhang and Yuxiang Yuan
Water 2024, 16(20), 3006; https://doi.org/10.3390/w16203006 - 21 Oct 2024
Viewed by 592
Abstract
Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River [...] Read more.
Most existing evaluation frameworks for water resource carrying capacity (WRCC) neglect the interdependencies between subsystems. To fill this gap, we introduce a dynamic qualitative comparative analysis (QCA) model to evaluate WRCC and apply it to a vital economic development corridor, the Yangtze River Economic Belt (YREB). Ecological, social, and economic subsystems are defined as condition subsystems, while the water resource subsystem is defined as the outcome subsystem. The entropy weight method is used to calculate and calibrate the comprehensive score of each subsystem. By analyzing the necessity of a single condition subsystem and the sufficiency of condition subsystem configuration via a dynamic QCA, we qualitatively analyze the impact extent and pathways of the ecological, social, and economic subsystems on the water resource subsystem within the WRCC framework. The results reveal generally stable water resource levels despite regional variances, thereby pinpointing the influence pathways, including ecological–social and ecological–economic configurations. The 2011–2015 period saw poor stability, which subsequently improved until 2019 before declining in 2020 in the YREB. The middle-reach urban cluster showed the highest stability, which was less impacted by condition subsystems. These findings could enable provinces and municipalities to tailor policies and enhance subsystem levels for better water resource management. Full article
(This article belongs to the Special Issue Managing Water Resources and Socio-Hydrologic Systems: New Understanding and Solutions)
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21 pages, 10530 KiB  
Article
Multivariate Validation at Multistation of Distributed Watershed Hydrological Modeling Based on Multisource Data on Chinese Loess Plateau
by Peiling Liu, Dengfeng Liu, Mohd Yawar Ali Khan, Xudong Zheng, Yun Hu, Guanghui Ming and Man Gao
Water 2024, 16(13), 1823; https://doi.org/10.3390/w16131823 - 26 Jun 2024
Viewed by 1020
Abstract
Earlier, hydrological simulation calibration and validation relied on flow observations at hydrological stations, but multisource observations changed the basin hydrological simulation from single-flow validation to multivariate validation, including evaporation, soil water, and runoff. This study used the Soil and Water Assessment Tool (SWAT) [...] Read more.
Earlier, hydrological simulation calibration and validation relied on flow observations at hydrological stations, but multisource observations changed the basin hydrological simulation from single-flow validation to multivariate validation, including evaporation, soil water, and runoff. This study used the Soil and Water Assessment Tool (SWAT) distributed hydrological model to simulate and investigate hydrological processes in the Jinghe River Basin in China. After a single-station, single-variable calibration using flow observation data at the Zhangjiashan Hydrological Station, multisource data were used to validate actual evaporation, soil water, and runoff. Using the flow station data from Zhangjiashan station for parameter calibration and validation, the simulated values of R2, NSE, and KGE were all above 0.64, the PBIAS was within 20%, and the values of all the metrics in the calibration period were better than those in the validation period. The results show that the model performed satisfactorily, proving its regional applicability. Qingyang, Yangjiaping, and Zhangjiazhan stations had R2, NSE, and KGE values above 0.57 and PBIAS within 25% during regional calibration, considering spatial variability. Additionally, simulation accuracy downstream increased. R2, NSE, and KGE were above 0.50, and PBIAS was within 25% throughout validation, except for Qingyang, where the validation period was better than the calibration period. The Zhangjiashan station monthly runoff simulation improved after regional calibration. Runoff validation performed highest in the multivariate validation of evaporation–soil water–runoff, followed by actual evaporation and soil water content in China. The evaluation results for each hydrological variable improved after additional manual calibration. Multivariate verification based on multisource data improved the hydrological simulation at the basin scale. Full article
(This article belongs to the Special Issue Managing Water Resources and Socio-Hydrologic Systems: New Understanding and Solutions)
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17 pages, 7479 KiB  
Article
Monthly Runoff Prediction for Xijiang River via Gated Recurrent Unit, Discrete Wavelet Transform, and Variational Modal Decomposition
by Yuanyuan Yang, Weiyan Li and Dengfeng Liu
Water 2024, 16(11), 1552; https://doi.org/10.3390/w16111552 - 28 May 2024
Cited by 1 | Viewed by 859
Abstract
Neural networks have become widely employed in streamflow forecasting due to their ability to capture complex hydrological processes and provide accurate predictions. In this study, we propose a framework for monthly runoff prediction using antecedent monthly runoff, water level, and precipitation. This framework [...] Read more.
Neural networks have become widely employed in streamflow forecasting due to their ability to capture complex hydrological processes and provide accurate predictions. In this study, we propose a framework for monthly runoff prediction using antecedent monthly runoff, water level, and precipitation. This framework integrates the discrete wavelet transform (DWT) for denoising, variational modal decomposition (VMD) for sub-sequence extraction, and gated recurrent unit (GRU) networks for modeling individual sub-sequences. Our findings demonstrate that the DWT–VMD–GRU model, utilizing runoff and rainfall time series as inputs, outperforms other models such as GRU, long short-term memory (LSTM), DWT–GRU, and DWT–LSTM, consistently exhibiting superior performance across various evaluation metrics. During the testing phase, the DWT–VMD–GRU model yielded RMSE, MAE, MAPE, NSE, and KGE values of 245.5 m3/s, 200.5 m3/s, 0.033, 0.997, and 0.978, respectively. Additionally, optimal sliding window durations for different input combinations typically range from 1 to 3 months, with the DWT–VMD–GRU model (using runoff and rainfall) achieving optimal performance with a one-month sliding window. The model’s superior accuracy enhances water resource management, flood control, and reservoir operation, supporting better-informed decisions and efficient resource allocation. Full article
(This article belongs to the Special Issue Managing Water Resources and Socio-Hydrologic Systems: New Understanding and Solutions)
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