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Integrated Water Resources Management Promoting Achievement of Multiple Sustainable Development Goals (SDGs)

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

Deadline for manuscript submissions: closed (23 April 2023) | Viewed by 7661

Special Issue Editors

Prof. Dr. Yingchun Ge

E-Mail Website
Guest Editor
Laboratory of Remote Sensing and Geogrpahic Information Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu Province, China
Interests: water resources management; sustainable development; decision support system
Dr. Erhu Du

E-Mail Website
Guest Editor
School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
Interests: hydrology and water resources; river basin management; environmental economics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Co-action of climate change and human activities on hydrological processes is essentially threatening water resources availability (quantity and quality) across space and over time. It also increases the complexity of water resources management, which involves more and more disciplines and sectors, and thus poses a huge challenge for achieving multiple sustainable development goals (SDGs). Despite that many researchers, international organizations, government policies, water-related legislation and engineering practices have focused on water resources management for half a century, many studies showed that inefficient water management is still a main reason that leads to negative impacts on sustainability of many regions or sectors due to the silo management paradigm, the gap between science and decision-making and water self-interested psychology. Accordingly, water resources management needs more comprehensive integrations, which include coordination of the scientific community and policymakers, novel ideas and approaches and different types and sources of data, as well as unified management of surface water, groundwater, meteoric water and recycling water, to meet the obstinate problems such as Aral Sea syndrome, global desertification, and water scarcity towards sustainability. In particular, there is still a lack of available approaches to effectively translate scientific outcomes into available decision-making information on water management. Furthermore, an in-depth understanding of the water-related nexuses (e.g., water-food-energy nexus, water-food-energy-climate nexus, water-energy-land nexus, and water-energy-people nexus) is also needed to promote achievement of multiple SDGs.

This Special Issue focuses on promoting the comprehensive integration of water resources management towards the achievement of multiple sustainable development goals.

Increasing complexity of water resources management is challenging existing water resources management paradigms and impedes the achievement of diverse sustainable development targets. Despite understanding interactions between hydrological system and other systems including ecosystems, economic systems and social systems by means of scientific modeling approaches, the environmental tragedy still occurs around the world. Many studies show that poor management of water resources is one of the key reasons that leads to the tragedy. In addition, the intertwining of water-related SDG targets poses a huge challenge for sustainable water resources management. Therefore, it is urgent to further develop integrated water resources management approaches that couples a wide range of factors in climate, hydrology, ecology, society, economy, psychology, management, and policy and sustainability science, through which we can better identify the interactions between water and other SDG targets. Significantly, how to translate these outcomes of integrated water resources management into available information supporting decision actions is a prerequisite for achieving SDG targets.

Hence, this Special Issue, “Integrated water resources management promoting achievement of multiple SDGs”, welcomes the papers covering methodologies, models, tools, and case studies in integrated water resources management and environmental sustainability. We envision that these research efforts will promote sustainable water resources management practices towards achieving more SDGs.

Thus, the topics covering the Special Issue include, but are not limited to, the following:

  • New methodologies and models of integrated water resources management;
  • Joint management of surface water, groundwater, rain water and recycling water;
  • Water-related nexus and environmental sustainability;
  • Sustainability shift in water management paradigm;
  • Optimal water allocation;
  • Water pollution;
  • Flood control and risk assessment;
  • Water-borne diseases;
  • Water-related SDG targets interaction;
  • Virtual water and water footprint;
  • Sustainable water management method;
  • Water resources management decision support system;
  • Water security;
  • Cast study of successful water management practices;
  • Reservoir operation and reoperation;
  • Inter- and intra-basin water resources transfers.

Prof. Dr. Yingchun Ge
Dr. Erhu Du
Guest Editors

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.

Published Papers (5 papers)

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Research

18 pages, 12813 KiB  
Article
Research on Renewal Design of College Campus Based on Flood Bearing Resilience
by Shengfang Li, Yi Zhu, Jian Yang and Bin Gong
Sustainability 2023, 15(15), 11489; https://doi.org/10.3390/su151511489 - 25 Jul 2023
Viewed by 998
Abstract
In view of the flooding problems faced by colleges and universities, we first reviewed current research on flood bearing resilience in order to clarify the ideas put forth by previous studies regarding the improvement of flood bearing resilience. Then, using the China University [...] Read more.
In view of the flooding problems faced by colleges and universities, we first reviewed current research on flood bearing resilience in order to clarify the ideas put forth by previous studies regarding the improvement of flood bearing resilience. Then, using the China University of Geosciences, Wuhan, as an example, a framework for promoting the cooperation of various ecosystems on the college campuses to cope with flooding was established. This framework makes it possible to effectively enhance the flood bearing resilience of the college campus and promote ecological, sustainable development therein. It includes a design strategy for renewal and renovation of college campuses that can improve their resilience to flooding. In partnership with natural systems, semi-artificial and artificial ecosystems on the college campus will be redesigned to cope with rainfall and flooding. In order to increase flood bearing resilience, the proposed strategy involves systematically renovating the site, using the China University of Geosciences, Wuhan (hereinafter referred to as the CUG, Wuhan) and its surrounding area as the experimental object. This strategy of renewal has already been proven effective in and around the koi pond at CUG, Wuhan. Full article
(This article belongs to the Special Issue Integrated Water Resources Management Promoting Achievement of Multiple Sustainable Development Goals (SDGs))
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14 pages, 2918 KiB  
Article
Evaluating the Feedback of the Reservoir Methane Cycle to Climate Warming under Hydrological Uncertainty
by Yunying Li, Wenjie Fan, Guni Xiang and Zhihao Xu
Sustainability 2023, 15(12), 9197; https://doi.org/10.3390/su15129197 - 7 Jun 2023
Cited by 1 | Viewed by 1049
Abstract
Freshwater reservoirs are widely recognized as methane (CH4) emission hotspots. Existing research has shown that temperature and hydrological conditions significantly affect wetland CH4 cycling processes. However, the feedback of the CH4 cycle to climate warming remains unclear for deep [...] Read more.
Freshwater reservoirs are widely recognized as methane (CH4) emission hotspots. Existing research has shown that temperature and hydrological conditions significantly affect wetland CH4 cycling processes. However, the feedback of the CH4 cycle to climate warming remains unclear for deep reservoirs where seasonal water thermal stratification exists. This study combined a reservoir CH4 cycling model and a Statistical DownScaling Model (SDSM) to evaluate reservoir CH4 cycling feedbacks under multiple climate change scenarios while accounting for hydrological uncertainty. Daily air temperatures in 2100 were predicted by the combination of the CanESM5 model and a SDSM. To address hydrological uncertainty, we selected three representative hydrological years (i.e., wet, normal, and dry) to create hydrological scenarios. Results showed that annual sediment CH4 production increased with warming, ranging 323.1–413.7 × 103 t C year−1 among multiple scenarios. Meanwhile, the CH4 oxidation percentage decreased with warming, which meant warming promoted sediment CH4 release non-linearly; 67.8–84.6% of sediment ebullient flux was ultimately emitted to the atmosphere (51.3–137.7 × 103 t C year−1), which showed ebullition was the dominant emission pathway. Higher air temperatures and drier conditions generally promote reservoir emissions. This study is helpful for predicting reservoir emissions while directing decision-making for reservoir sustainability. Full article
(This article belongs to the Special Issue Integrated Water Resources Management Promoting Achievement of Multiple Sustainable Development Goals (SDGs))
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14 pages, 3064 KiB  
Article
Ecological Health Assessment of an Urban River: The Case Study of Zhengzhou City, China
by Jie Li, Lintong Huang and Kai Zhu
Sustainability 2023, 15(10), 8288; https://doi.org/10.3390/su15108288 - 19 May 2023
Cited by 3 | Viewed by 1684
Abstract
Urban river ecological health assessment is an effective means to manage urban rivers, and combining principles of landscape ecology can provide new help for the ecological restoration of urban rivers and improving their ecosystem service value. From the perspective of important functions of [...] Read more.
Urban river ecological health assessment is an effective means to manage urban rivers, and combining principles of landscape ecology can provide new help for the ecological restoration of urban rivers and improving their ecosystem service value. From the perspective of important functions of ecosystems, based on typical sample site investigations of different river sections, questionnaire surveys, and remote sensing technology, a fuzzy comprehensive evaluation model based on the factor analysis method was used to construct an indicator system that can quantitatively reflect the ecological health of urban rivers. This comprehensive evaluation index system includes five major functions: social function, habitat and corridor function, water ecological function, water landscape function, and spatial enclosure function. The study identified key areas, key rivers, key river sections, and main indicator projects for the ecological restoration of the urban river landscape corridors in Zhengzhou. The study results also showed that the urban river landscape corridors in Zhengzhou have prominent problems in social function, water ecological function, and habitat and corridor function, and 62.1% of the river sections are currently in a sub-healthy state. The flood control function, eutrophication of water body, naturalization rate of revetment, and five other indicators in the old city district are significantly lower than those in the new city district, and the old city district should be the focus of the ecological restoration of urban river corridors. From the evaluation of the ecological health status of typical river sections, the Jinshui River and Xionger River have a larger number of river sections that urgently need restoration. This study provides a reference for the ecological restoration of urban rivers in Zhengzhou, a rapidly urbanizing region, and has reference significance for the construction of water landscapes in small and medium-sized cities with low levels of urbanization. Full article
(This article belongs to the Special Issue Integrated Water Resources Management Promoting Achievement of Multiple Sustainable Development Goals (SDGs))
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12 pages, 958 KiB  
Article
Operating Multi-Purpose Reservoirs in the Red River Basin: Hydropower Benefit Optimization in Conditions Ensuring Enough Water for Downstream Irrigation
by Dung Thien Nguyen
Sustainability 2023, 15(6), 5444; https://doi.org/10.3390/su15065444 - 20 Mar 2023
Cited by 3 | Viewed by 1401
Abstract
Operational management of multiple reservoirs and hydropower plants in the Red River Basin (RRB) in Vietnam was investigated for optimal benefit of hydropower generation and to ensure the water supply for agricultural and social–economic development downstream during the dry season. This research will [...] Read more.
Operational management of multiple reservoirs and hydropower plants in the Red River Basin (RRB) in Vietnam was investigated for optimal benefit of hydropower generation and to ensure the water supply for agricultural and social–economic development downstream during the dry season. This research will investigate the operation of three hydropower reservoirs, including Hoa Binh, Thac Ba, and Tuyen Quang reservoirs. Those reservoirs are managed under the operating Decision No. 740 of the Prime Minister in 2019, which stipulates the dry season and water - enhanced discharge period to supply water for agriculture and ensures that the minimum water level in Hanoi is above 2.2 m, which may lead to lack of water for hydropower plants. To do this, I used the optimization approach to determine the optimal water discharge scenario in these three reservoirs during the enhanced discharge period (irrigation water supply). Based on the optimal scenario, I calculated the amount of saved water which is then compared with the standard discharge scenario under Decision No. 740. This study also found that there is an increasing economic benefit from saved water and hydropower generation during peak hours (after the winter–spring crop). Addtionally, the results demonstrated that the economic value added by the power generation of three reservoirs is about 401.7 billion VND. If compared with using thermal power plants, it saves 858.0 billion VND. Full article
(This article belongs to the Special Issue Integrated Water Resources Management Promoting Achievement of Multiple Sustainable Development Goals (SDGs))
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19 pages, 3855 KiB  
Article
Incorporating Empirical Orthogonal Function Analysis into Machine Learning Models for Streamflow Prediction
by Yajie Wu, Yuan Chen and Yong Tian
Sustainability 2022, 14(11), 6612; https://doi.org/10.3390/su14116612 - 28 May 2022
Cited by 4 | Viewed by 1888
Abstract
Machine learning (ML) models have been widely used to predict streamflow. However, limited by the high dimensionality and training difficulty, high-resolution gridded climate datasets have rarely been used to build ML-based streamflow models. In this study, we developed a general modeling framework that [...] Read more.
Machine learning (ML) models have been widely used to predict streamflow. However, limited by the high dimensionality and training difficulty, high-resolution gridded climate datasets have rarely been used to build ML-based streamflow models. In this study, we developed a general modeling framework that applied empirical orthogonal function (EOF) analysis to extract information from gridded climate datasets for building ML-based streamflow prediction models. Four classic ML methods, namely, support vector regression (SVR), multilayer perceptron (MLP), long short-term memory (LSTM) and gradient boosting regression tree (GBRT), were incorporated into the modeling framework for performance evaluation and comparison. We applied the modeling framework to the upper Heihe River Basin (UHRB) to simulate a historical 22-year period of daily streamflow. The modeling results demonstrated that EOF analysis could extract the spatial information from the gridded climate datasets for streamflow prediction. All four selected ML models captured the temporal variations in the streamflow and reproduced the daily hydrographs. In particular, the GBRT model outperformed the other three models in terms of streamflow prediction accuracy in the testing period. The R2, RMSE, MAE, NSE and PBIAS were equal to 0.68, 9.40 m3/s, 5.18 m3/s, 0.68 and −0.03 for the daily streamflow in the Taolai River Watershed of the UHRB, respectively. Additionally, the LSTM method could provide physically based hydrological explanations of climate predicators in streamflow generation. Therefore, this study demonstrated the unique capability and functionality of incorporating EOF analysis into ML models for streamflow prediction, which could make better use of the readily available gridded climate data in hydrological simulations. Full article
(This article belongs to the Special Issue Integrated Water Resources Management Promoting Achievement of Multiple Sustainable Development Goals (SDGs))
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