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Integrated River Basin Management and Sustainable Water Resources Management Using Innovative Approaches

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 3875

Special Issue Editor

Dr. Eui Hoon Lee

E-Mail Website
Guest Editor
School of Civil Engineering, Chungbuk National University, Cheongju 28644, Republic of Korea
Interests: non-structural measures; flood forecasting; urban drainage systems; optimization; sustainability; resilience; artificial intelligence; reliability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Integrated river basin and sustainable water resource management are very important. We must investigate river basin management for flood reduction. In addition to studies on sustainable water resources management techniques, studies that predict the risk of water system using innovative approaches such as artificial intelligence (AI) are also required. From this point of view, using various methods, such as deep learning and meta-heuristic optimization algorithms, may increase the sustainability of river basins and water resources.

This Special Issue aims to collect papers focused on new research results regarding ‘Integrated River Basin Management and Sustainable Water Resources Management Using Innovative Approaches’.

This Special Issue seeks contributions spanning a broad range of topics related, but not limited to, the following:

  • Integrated river basin management;
  • Flood forecasting using deep learning techniques;
  • Simulations/experiments on water resources management;
  • Assessments of water resources management;
  • Flood routing using meta-heuristic optimization algorithms.

I look forward to receiving your contributions.

Dr. Eui Hoon Lee
Guest Editor

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. Sustainability 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 2400 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

  • integrated river basin management
  • flood forecasting
  • deep learning
  • water resources management
  • flood routing
  • meta-heuristic optimization algorithm

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Published Papers (3 papers)

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Research

24 pages, 2839 KiB  
Article
Exploration of the Path of Industrial Structure Adjustment Forced by the Rigid Constraint of Water Ecology in the Yangtze River Economic Belt
by Jun Ma and Jiale Ji
Sustainability 2024, 16(21), 9378; https://doi.org/10.3390/su16219378 - 29 Oct 2024
Viewed by 993
Abstract
Considering the two-way influence of water ecology and industrial structure, decompose and quantify the water ecological rigidity constraints into water environment constraints and water resources constraints, construct the evaluation system based on the theoretical framework of PSR, and analyze the spatio-temporal evolution [...] Read more.
Considering the two-way influence of water ecology and industrial structure, decompose and quantify the water ecological rigidity constraints into water environment constraints and water resources constraints, construct the evaluation system based on the theoretical framework of PSR, and analyze the spatio-temporal evolution characteristics of water ecological rigidity constraints of the Yangtze River Economic Belt from 2010 to 2021 by using the entropy weighting method, the method of catastrophe progression, and the kernel density estimation. Then, putting forward the types of zoning in the Yangtze River Economic Zone through K-means algorithm analysis to explore the rigid constraints of water ecology to force the path of industrial structure adjustment. The results indicate that: (1) the water ecological rigidity constraints show a decreasing trend, and the decreasing amplitude is upstream > downstream > midstream; (2) the water ecological rigidity constraints generally show the characteristic of “gradually decreasing from east to west”, and the degree of regional differences first decreases, then increases, and then decreases again; (3) it can be divided into six types, and the zoning results gradually change from the concentration in the medium-high type and high-high type to the concentration in the low-low type and medium-low type, and the rigidity constraint of water ecology is obviously improved. In light of the findings, the Yangtze River Economic Belt is divided into five types of development regions and further discusses that the industrial restructuring in different zones has different influencing effects on the regional socio-economic development, which provides suggestions for differentiated paths of water ecological protection and industrial restructuring. Full article
(This article belongs to the Special Issue Integrated River Basin Management and Sustainable Water Resources Management Using Innovative Approaches)
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26 pages, 10660 KiB  
Article
Grid-Based Precipitation Quantile Estimation Considering Homogeneity Using ERA5-Land Data for the Korean Peninsula
by Jinwook Lee, Sejeong Oh, Jongjin Baik, Changhyun Jun, Jungho Seo and Eui Hoon Lee
Sustainability 2024, 16(21), 9295; https://doi.org/10.3390/su16219295 - 25 Oct 2024
Viewed by 909
Abstract
In this study, a grid-based precipitation quantile was estimated using long-term reanalysis precipitation data, considering the homogeneity of the annual maximum series (AMS) for the Korean Peninsula. For regions where significant changes in homogeneity were observed, the precipitation quantile was estimated using only [...] Read more.
In this study, a grid-based precipitation quantile was estimated using long-term reanalysis precipitation data, considering the homogeneity of the annual maximum series (AMS) for the Korean Peninsula. For regions where significant changes in homogeneity were observed, the precipitation quantile was estimated using only the AMS from after the change point, and these results were compared with those from the original AMS. The examination of homogeneity revealed a significant increasing trend in homogeneity variability in the southeastern region of Korea. This change was particularly pronounced in the location parameter of the Gumbel distribution, resulting in an improved model fit. The change in precipitation quantile was most noticeable for a 2-year return period with a 36 h duration, with an average increase of approximately 11.5%. The results obtained from this study are anticipated to offer crucial foundational data for the design of hydraulic structures in regions with insufficient long-term ground observation data. Full article
(This article belongs to the Special Issue Integrated River Basin Management and Sustainable Water Resources Management Using Innovative Approaches)
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21 pages, 4390 KiB  
Article
Forecasting Meteorological Drought Conditions in South Korea Using a Data-Driven Model with Lagged Global Climate Variability
by Seonhui Noh and Seungyub Lee
Sustainability 2024, 16(15), 6485; https://doi.org/10.3390/su16156485 - 29 Jul 2024
Cited by 3 | Viewed by 1482
Abstract
Drought prediction is crucial for early risk assessment, preventing negative impacts and the timely implementation of mitigation measures for sustainable water management. This study investigated the relationship between climate variations in three seas and the prediction of December meteorological droughts in South Korea, [...] Read more.
Drought prediction is crucial for early risk assessment, preventing negative impacts and the timely implementation of mitigation measures for sustainable water management. This study investigated the relationship between climate variations in three seas and the prediction of December meteorological droughts in South Korea, using the Standardized Precipitation Evapotranspiration Index (SPEI). Climate indices with multiple time lags were integrated into multiple linear regression (MLR) and Random Forest (RF) models and evaluated using Pearson’s correlation coefficients (PCCs) and the Root Mean Square Error (RMSE). The results indicated that the MLR model outperformed RF model in the western inland region with a PCC of 0.52 for predicting SPEI-2. On the other hand, the RF model effectively predicted drought states of ‘moderate drought’ or worse (SPEI < −1) nationwide, achieving an average hit rate of 47.17% and Heidke skill score (HSS) of 0.56, particularly excelling in coastal areas. Nino 3.4 turned out to be the most influential factor for short-period extreme droughts (SPEI-2) with a three-month lag, contributed by the Pacific, Atlantic, and Indian Oceans. For periods of four months or longer, climate variations had a lower predictive value. However, integrating autocorrelation functions to account for the previous month’s drought status improved the accuracy. A HYBRID model, which blends linear and nonlinear approaches, further enhanced reliability, making the proposed model more applicable for drought forecasting in neighboring countries and valuable for South Korea’s drought monitoring system to support sustainable water management. Full article
(This article belongs to the Special Issue Integrated River Basin Management and Sustainable Water Resources Management Using Innovative Approaches)
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