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

Deadline for manuscript submissions: closed (31 May 2023) | Viewed by 9673

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Special Issue Editor

Prof. Dr. Zengchuan Dong

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Guest Editor

College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China
Interests: sustainable development; management and utilization of water resources; hydrological regime; ecological and environmental systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues:

Global climate change and intense human activity have had a significant influence on the Earth's water resource systems during the past century, and disputes over water usage have gotten much worse. Planning and management methods for water resources must change to meet the new requirements of a changing environment if the sustainable use of water resources is to be maintained.

The purpose of this Special Issue, which is closely connected to the Sustainability journal's major focus on human environmental, economic, and social sustainability, is to collect research and studies on the rational and effective use of water resources in a changing environment.

In this Special Issue, original research articles and reviews are welcome. Research themes may include (but are not limited to) the following:

The analysis and dynamic prediction of the hydrological cycle's evolution under climate change;
Forecasting of the mechanisms and trends of interactions between the host and the object of water resources in a changing environment;
Research on multi-objective adaptive regulation strategies for water resources in a changing environment.

We look forward to receiving your contributions.

Prof. Dr. Zengchuan Dong
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.

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Keywords

water resources
economy
society
ecology
sustainability
climatic change
human activities
carbon emission

Published Papers (6 papers)

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Research

15 pages, 2232 KiB

Open AccessArticle

The Impact of Inter-Basin Water Transfer Schemes on Hydropower Generation in the Upper Reaches of the Yangtze River during Extreme Drought Years

by Fan Wen, Mingxiang Yang, Wenhai Guan, Jixue Cao, Yibo Zou, Xuan Liu, Hejia Wang and Ningpeng Dong

Sustainability 2023, 15(10), 8373; https://doi.org/10.3390/su15108373 - 22 May 2023

Cited by 1 | Viewed by 1133

Abstract

The Yangtze River Basin experiences frequent extreme heatwaves and prolonged droughts, resulting in a tight supply demand balance of electricity and negatively impacting socioeconomic production. Meanwhile, ongoing inter-basin water diversion projects are planned that will divert approximately 25.263 billion cubic meters of water from the Yangtze River Basin annually, which may further affect the power supply in the region. In this study, the CLHMS-LSTM model, a land-surface hydrological model coupled with a long short-term memory (LSTM)-based reservoir operation simulation model, is used to investigate the impact of water diversions on the power generation of the Yangtze River mainstream reservoirs under extreme drought conditions. Two different water diversion schemes are adopted in this study, namely the minimum water deficit scheme (Scheme 1) and minimum construction cost scheme (Scheme 2). The results show that the land surface–hydrological model was able to well characterize the hydrological characteristics of the Yangtze River mainstem, with a daily scale determination coefficient greater than 0.85. The LSTM reservoir operation simulation model was able to simulate the reservoir releases well, with the determination coefficient greater than 0.93. The operation of the water diversion projects will result in a reduction in the power generation of the Yangtze River mainstem by 14.97 billion kilowatt-hours. As compared to the minimum construction cost scheme (Scheme 2), the minimum water deficit scheme (Scheme 1) reduces the loss of power generation by 1.38 billion kilowatt-hours. The research results provide new ideas for the decision-making process for the inter-basin water diversion project and the formulation of water diversion plans, which has implications for ensuring the security of the power supply in the water diversion area. Full article

(This article belongs to the Special Issue Sustainable Planning, Management and Utilization of Water Resources)

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20 pages, 8574 KiB

Open AccessArticle

Probabilistic Forecast and Risk Assessment of Flash Droughts Based on Numeric Weather Forecast: A Case Study in Zhejiang, China

by Jinhua Wen, Yian Hua, Chenkai Cai, Shiwu Wang, Helong Wang, Xinyan Zhou, Jian Huang and Jianqun Wang

Sustainability 2023, 15(4), 3865; https://doi.org/10.3390/su15043865 - 20 Feb 2023

Cited by 2 | Viewed by 1752

Abstract

In recent years, flash droughts with a rapid onset and strong intensity have attracted extensive attention due to their impact on agriculture and ecosystems. However, there is still no feasible method for flash drought forecasting and early warning. This paper employs the thresholds of several meteorological variables to identify flash droughts in Zhejiang Province, China, and build a probabilistic flash drought forecasting model through numeric weather forecast (NWF) and the generalized Bayesian model (GBM). The results show that the northern part of Zhejiang Province has the highest risk of flash drought. The NWF is a viable method to provide future information for flash drought forecasting and early warning, but its forecasting accuracy tends to decline with the increase in the lead time and is very limited when the lead time is over 5 days, especially for the precipitation forecast. Due to the low performance of the NWF, the flash drought forecast based on the raw NWF may be unreliable when the lead time is over 5 days. To solve this problem, probabilistic forecasting based on GBM is employed to quantify the uncertainty in the NWF and is tested through an example analysis. In the example analysis, it was found that the probability of a flash drought exceeds 30% from the probabilistic forecasting when the lead time is 12 days, while the deterministic forecasting via the raw NWF cannot identify a flash drought when the lead time is over 5 days. In conclusion, probabilistic forecasting can identify a potential flash drought earlier and can be used to evaluate the risk of a flash drought, which is conducive for the early warning of flash droughts and the development of response measures. Full article

(This article belongs to the Special Issue Sustainable Planning, Management and Utilization of Water Resources)

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23 pages, 12472 KiB

Open AccessArticle

Analysis of Runoff Variation and Future Trends in a Changing Environment: Case Study for Shiyanghe River Basin, Northwest China

by Yiqing Shao, Zengchuan Dong, Jinyu Meng, Shujun Wu, Yao Li, Shengnan Zhu, Qiang Zhang and Ziqin Zheng

Sustainability 2023, 15(3), 2173; https://doi.org/10.3390/su15032173 - 24 Jan 2023

Cited by 4 | Viewed by 1594

Abstract

Changes in the hydrological cycle and water resources are inevitable consequences of environmental change, and runoff is an important element of the hydrological cycle. Therefore, the assessment of runoff changes is crucial for water resources management and socio-economic development. As an inland river basin in the arid zone of northwest China, the Shiyang River Basin is very vulnerable to environmental changes. Consequently, this study evaluated the past runoff evolution of the Shiyang River basin using a variety of statistical tools. In addition, the improved Soil and Water Assessment Tool (SWAT) was used to predict runoff trends from 2019 to 2050 under potential future climate change and land use projection scenarios in the future for the Shiyang River Basin. In the inland river basins, water resources mainly come from headwaters of the rivers in the upper mountainous regions, where they are more sensitive. Therefore, this study not only examined the mainstream of the Shiyang River, but also the six tributaries in the upper stream. The results indicate that the mainstream of the Shiyang River Basin and its six upstream tributaries all showed declining trends from the 1950s to 2019, and most of the rivers will continue to insignificantly decrease until 2050. Furthermore, there are two main timescales for runoff in the past as well as future: one is around 40 years and another is 20–30 years. In the meantime, the Shiyang River and its tributaries have relatively consistent change characteristics. The results of this study will provide assistance to basin management agencies in developing more appropriate water resource management plans. Full article

(This article belongs to the Special Issue Sustainable Planning, Management and Utilization of Water Resources)

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15 pages, 4474 KiB

Open AccessArticle

Monthly Runoff Forecasting Based on Interval Sliding Window and Ensemble Learning

by Jinyu Meng, Zengchuan Dong, Yiqing Shao, Shengnan Zhu and Shujun Wu

Sustainability 2023, 15(1), 100; https://doi.org/10.3390/su15010100 - 21 Dec 2022

Cited by 3 | Viewed by 1486

Abstract

In recent years, machine learning, a popular artificial intelligence technique, has been successfully applied to monthly runoff forecasting. Monthly runoff autoregressive forecasting using machine learning models generally uses a sliding window algorithm to construct the dataset, which requires the selection of the optimal time step to make the machine learning tool function as intended. Based on this, this study improved the sliding window algorithm and proposes an interval sliding window (ISW) algorithm based on correlation coefficients, while the least absolute shrinkage and selection operator (LASSO) method was used to combine three machine learning models, Random Forest (RF), LightGBM, and CatBoost, into an ensemble to overcome the preference problem of individual models. Example analyses were conducted using 46 years of monthly runoff data from Jiutiaoling and Zamusi stations in the Shiyang River Basin, China. The results show that the ISW algorithm can effectively handle monthly runoff data and that the ISW algorithm produced a better dataset than the sliding window algorithm in the machine learning models. The forecast performance of the ensemble model combined the advantages of the single models and achieved the best forecast accuracy. Full article

(This article belongs to the Special Issue Sustainable Planning, Management and Utilization of Water Resources)

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12 pages, 2132 KiB

Open AccessArticle

An Investigation on the Effect of Outliers for Flood Frequency Analysis: The Case of the Eastern Mediterranean Basin, Turkey

by Evren Turhan

Sustainability 2022, 14(24), 16558; https://doi.org/10.3390/su142416558 - 9 Dec 2022

Cited by 1 | Viewed by 1287

Abstract

Flood frequency analysis is accepted as one of the most important applications of water resource engineering. Measurements with higher and lower values, such as outliers, can be seen in hydrological data sets based on longer observation periods that extend the overall range. This study used 50 and 25 years of annual maximum flow data from 1962 to 2011 and from 1987 to 2011 from the Stream Gauging Stations (SGS) numbered 1712, 1717, and 1721 located within the borders of the Eastern Mediterranean Basin. The flood discharges were estimated using Normal, Gumbel, and Pearson Type III probability distributions. The study adopted Kolmogorov–Smirnov (K-S) and Chi-squared goodness-of-fit tests to investigate the suitability of probability distribution functions. The maximum flow rates were obtained by utilizing Normal distribution in the 2-year and 5-year return periods for the flood values calculated with the raw data; however, after the modification of the outliers, maximum flood discharges were estimated by adopting the Pearson Type III function. While the maximum discharges for the 1717 SGS were determined using the Gumbel distribution, the Pearson Type III distribution function was utilized for the 1712 and 1721 SGSs. As a result of the K-S and Chi-squared tests, it was determined that adjustment of the outliers resulted in positive goodness-of-fit results with the Pearson Type III function. Full article

(This article belongs to the Special Issue Sustainable Planning, Management and Utilization of Water Resources)

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14 pages, 8433 KiB

Open AccessArticle

Three-Dimensional Analysis of Air-Admission Orifices in Pipelines during Hydraulic Drainage Events

by Duban A. Paternina-Verona, Oscar E. Coronado-Hernández, Hector G. Espinoza-Román, Mohsen Besharat, Vicente S. Fuertes-Miquel and Helena M. Ramos

Sustainability 2022, 14(21), 14600; https://doi.org/10.3390/su142114600 - 7 Nov 2022

Cited by 6 | Viewed by 1445

Abstract

Air valves operate as protection devices in pipelines during drainage processes in order to mitigate vacuum pressures and control the transient flows. Currently, different authors have proposed one-dimensional models to predict the behaviour of orifices during filling and draining events, which offer good numerical results. However, the three-dimensional dynamic behaviour of air-admission orifices during drainage processes has not been studied in depth in the literature. In this research, the effects of air inflow on an orifice installed in a single pipe during drainage events are analysed using a three-dimensional computational fluid dynamics model by testing orifices with diameters of 1.5 and 3.0 mm. This model was validated with different experimental measurements associated to the vacuum pressure, obtaining good fits. The three-dimensional model predicts additional information associated to the aerodynamic effects that occur during the air-admission processes, which is studied. Subsonic flows are observed in different orifices with Mach numbers between 0.18 and 0.30. In addition, it is shown that the larger-diameter orifice ensures a more effective airflow control compared to the smaller-diameter orifice. Full article

(This article belongs to the Special Issue Sustainable Planning, Management and Utilization of Water Resources)

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