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Sustainable Water Resources Management and Sustainable Environment

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

Deadline for manuscript submissions: closed (28 June 2023) | Viewed by 22722

Special Issue Editor

Dr. Furat Al-Faraj

E-Mail Website
Guest Editor
School of Engineering, University of Bolton, Bolton BL3 5AB, UK
Interests: water resources management; sustainable environment; water policy; environmental project management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

It is our pleasure to announce a new Special Issue on “Sustainable Water Resources Management and Sustainable Environment” in the journal Sustainability.

Water is a substantial resource for socioeconomic development and the protection of healthy environments. Sustainable management of water resources is a vital part of sustainable development. Climate change has already altered hydrological cycles, making water more unpredictable and changing the frequency, severity, spatial extent, duration, and timing of floods and droughts. Sharing transboundary waters is one of the major concerns in many regions of the world. Climate change has put additional stress on water availability, allocation, quality, and meeting growing water demands, especially in lower riparian countries. Accessing to improved water and sanitation facilities by 2030 is a major concern and challenge, particularly in developing countries. Some developing countries are still off track to achieve Sustainable Development Goal 6 by 2030.  Wetlands are important regulators of water quantity and water quality, which are essential for sustainable development in many areas worldwide. The sustainable management and conservation of wetlands become a notable challenge and concern in many regions due to a combined influence of climate change and mismanagement.

The Special Issue invites contributions, including but not limited to the following detailed topics:

  • Challenges to sustainable management of water resources;
  • Impacts of climate change on sustainable management of transboundary water resources;
  • Challenges and opportunities toward the achievement of Sustainable Development Goal 6;
  • Sustainability and environmental management;
  • Urban drainage systems for a sustainable environment;
  • Sustainable management and conservation of wetland resources.
  • Smart water systems in smart cities
  • Sustainable environment of smart cities

Dr. Furat Al-Faraj
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

  • transboundary water resources
  • sustainable urban drainage systems
  • wetlands
  • climate change impacts
  • Sustainable Development Goals
  • sustainable environment
  • smart water systems
  • smart cities

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Related Special Issue

Published Papers (7 papers)

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Research

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30 pages, 4015 KiB  
Article
Modeling Hydrologic–Economic Interactions for Sustainable Development: A Case Study in Inner Mongolia, China
by Hanzhang Zhou, Jinghao Zhang, Shibo Cui and Jianshi Zhao
Sustainability 2024, 16(1), 345; https://doi.org/10.3390/su16010345 - 29 Dec 2023
Cited by 1 | Viewed by 925
Abstract
Water shortages are major constraints on economic development in water-deficient regions such as Inner Mongolia, China. Moreover, macroscale interactions between water resources and the regional economy remain unclear. This study addresses this problem by building a network-based hydro-economic model that integrates ecological, economic, [...] Read more.
Water shortages are major constraints on economic development in water-deficient regions such as Inner Mongolia, China. Moreover, macroscale interactions between water resources and the regional economy remain unclear. This study addresses this problem by building a network-based hydro-economic model that integrates ecological, economic, social, and environmental data into a coherent framework. We assessed the relationship between water resources and economic performance under different water-saving and climate change scenarios. The results showed that both water-saving policies and increased water availability due to climate change can increase economic productivity. Water saving can also mitigate the negative impact of climate change-driven decreased rainfall by restoring the gross domestic product (GDP) to 97.3% of its former level. The interaction between water resources and economic productivity depends on specific factors that affect water availability. A trade-off relationship exists between economic development and water protection and was more discernible when the total GDP reached 10,250 billion CNY. When the trade-off ratio reaches 6:1, economic output decreases because of a lack of ecological water resources, even if further stress is placed on the objective. Thus, this study demonstrates the effect of water resources on economic growth and highlights the need for improved water management in water-deficient regions. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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19 pages, 3674 KiB  
Article
Assessing the Potential of Hybrid-Based Metaheuristic Algorithms Integrated with ANNs for Accurate Reference Evapotranspiration Forecasting
by Hadeel E. Khairan, Salah L. Zubaidi, Mustafa Al-Mukhtar, Anmar Dulaimi, Hussein Al-Bugharbee, Furat A. Al-Faraj and Hussein Mohammed Ridha
Sustainability 2023, 15(19), 14320; https://doi.org/10.3390/su151914320 - 28 Sep 2023
Viewed by 959
Abstract
Evapotranspiration (ETo) is one of the most important processes in the hydrologic cycle, with specific application to sustainable water resource management. As such, this study aims to evaluate the predictive ability of a novel method for monthly ETo estimation, using a hybrid model [...] Read more.
Evapotranspiration (ETo) is one of the most important processes in the hydrologic cycle, with specific application to sustainable water resource management. As such, this study aims to evaluate the predictive ability of a novel method for monthly ETo estimation, using a hybrid model comprising data pre-processing and an artificial neural network (ANN), integrated with the hybrid particle swarm optimisation–grey wolf optimiser algorithm (PSOGWO). Monthly data from Al-Kut City, Iraq, over the period 1990 to 2020, were used for model training, testing, and validation. The predictive accuracy of the proposed model was compared with other cutting-edge algorithms, including the slime mould algorithm (SMA), the marine predators algorithm (MPA), and the constriction coefficient-based particle swarm optimisation and chaotic gravitational search algorithm (CPSOCGSA). A number of graphical methods and statistical criteria were used to evaluate the models, including root mean squared error (RMSE), Nash–Sutcliffe model efficiency (NSE), coefficient of determination (R2), maximum absolute error (MAE), and normalised mean standard error (NMSE). The results revealed that all the models are efficient, with high simulation levels. The PSOGWO–ANN model is slightly better than the other approaches, with an R2 = 0.977, MAE = 0.1445, and RMSE = 0.078. Due to its high predictive accuracy and low error, the proposed hybrid model can be considered a promising technique. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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22 pages, 3591 KiB  
Article
Smart Rainwater Harvesting for Sustainable Potable Water Supply in Arid and Semi-Arid Areas
by Tariq Judeh, Isam Shahrour and Fadi Comair
Sustainability 2022, 14(15), 9271; https://doi.org/10.3390/su14159271 - 28 Jul 2022
Cited by 7 | Viewed by 8396
Abstract
This paper presents a smart rainwater harvesting (RWH) system to address water scarcity in Palestine. This system aims to improve the water harvesting capacity by using a shared harvesting system at the neighborhood level and digital technology. The presentation of this system is [...] Read more.
This paper presents a smart rainwater harvesting (RWH) system to address water scarcity in Palestine. This system aims to improve the water harvesting capacity by using a shared harvesting system at the neighborhood level and digital technology. The presentation of this system is organized as follows: (i) identification of the challenges of the rainwater harvesting at the neighborhood level, (ii) design of the smart RWH system architecture that addresses the challenges identified in the first phase, (iii) realization of a simulation-based reliability analysis for the smart system performance. This methodology was applied to a residential neighborhood in the city of Jenin, Palestine. The main challenges of smart water harvesting included optimizing the shared tank capacity, and the smart control of the water quality and leakage. The smart RWH system architecture design is proposed to imply the crowdsourcing-based and automated-based smart chlorination unit to control and monitor fecal coliform and residual chlorine: screens, filters, and the first flush diverter address RWH turbidity. Water level sensors/meters, water flow sensors/meters, and water leak sensors help detect a water leak and water allocation. The potential time-based reliability (Re) and volumetric reliability (Rv) for the smart RWH system can reach 38% and 41%, respectively. The implication of the smart RWH system with a dual water supply results in full reliability indices (100%). As a result, a zero potable water shortage could be reached for the dual water supply system, compared to 36% for the municipal water supply and 59% for the smart RWH system. Results show that the smart RWH system is efficient in addressing potable water security, especially when combined with a dual water supply system. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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25 pages, 2869 KiB  
Article
A Comprehensive Study of Artificial Intelligence Applications for Soil Temperature Prediction in Ordinary Climate Conditions and Extremely Hot Events
by Hanifeh Imanian, Juan Hiedra Cobo, Pierre Payeur, Hamidreza Shirkhani and Abdolmajid Mohammadian
Sustainability 2022, 14(13), 8065; https://doi.org/10.3390/su14138065 - 1 Jul 2022
Cited by 7 | Viewed by 2449
Abstract
Soil temperature is a fundamental parameter in water resources and irrigation engineering. A cost-effective model that can accurately forecast soil temperature is urgently needed. Recently, many studies have applied artificial intelligence (AI) at both surface and underground levels for soil temperature predictions. In [...] Read more.
Soil temperature is a fundamental parameter in water resources and irrigation engineering. A cost-effective model that can accurately forecast soil temperature is urgently needed. Recently, many studies have applied artificial intelligence (AI) at both surface and underground levels for soil temperature predictions. In the present study, attempts are made to deliver a comprehensive and detailed assessment of the performance of a wide range of AI approaches in soil temperature prediction. In this regard, thirteen approaches, from classic regressions to well-established methods of random forest and gradient boosting to more advanced AI techniques, such as multi-layer perceptron and deep learning, are taken into account. Meanwhile, great varieties of land and atmospheric variables are applied as model inputs. A sensitivity analysis was conducted on input climate variables to determine the importance of each variable in predicting soil temperature. This examination reduced the number of input variables from 8 to 7, which decreased the simulation load. Additionally, this showed that air temperature and solar radiation play the most important roles in soil temperature prediction, while precipitation can be neglected in forecast AI models. The comparison of soil temperature predicted by different AI models showed that deep learning demonstrated the best performance with R-squared of 0.980 and NRMSE of 2.237%, followed by multi-layer perceptron with R-squared of 0.980 and NRMSE of 2.266%. In addition, the performance of developed AI models was evaluated in extremely hot events since heat warnings are essential to protect lives and properties. The assessment showed that deep learning and multi-layer perceptron methods still have the best prediction. However, their R-squared decreased to 0.862 and 0.859, and NRMSE increased to 6.519% and 6.601%, respectively. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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23 pages, 4093 KiB  
Article
Assessment of Climate Change Impact on the Annual Maximum Flood in an Urban River in Dublin, Ireland
by Arunima Sarkar Basu, Laurence William Gill, Francesco Pilla and Bidroha Basu
Sustainability 2022, 14(8), 4670; https://doi.org/10.3390/su14084670 - 13 Apr 2022
Cited by 4 | Viewed by 2448
Abstract
Hydrological modelling to address the problem of flood risk corresponding to climate change can play an important role in water resources management. This paper describes the potential impact of climate change on an urban river catchment using a physically based hydrological model called [...] Read more.
Hydrological modelling to address the problem of flood risk corresponding to climate change can play an important role in water resources management. This paper describes the potential impact of climate change on an urban river catchment using a physically based hydrological model called Soil Water Assessment Tool (SWAT). The study area considered is the Dodder River basin located in the southern part of Dublin, the capital city of Ireland. Climate projections from three regional climate models and two representative concentration pathways (RPC 4.5 and RCP 8.5) were used to evaluate the impact of flooding corresponding to different climate change scenarios. Annual maximum flow (AMF) is generated by combining the bias-corrected climate projections with the calibrated and validated SWAT model to understand the projected changes in flood patterns for the year 2021–2100. The expected changes in flood quantiles were estimated using a generalised extreme value distribution. The results predicted up to 12% and 16% increase in flood quantiles corresponding to 50 years and 100 years return periods. Based on the flood quantiles, flood inundation maps were developed for the study area. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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21 pages, 7974 KiB  
Article
Sensitivity of Irrigation Water Requirement to Climate Change in Arid and Semi-Arid Regions towards Sustainable Management of Water Resources
by Fouad H. Saeed, Mahmoud S. Al-Khafaji and Furat A. Mahmood Al-Faraj
Sustainability 2021, 13(24), 13608; https://doi.org/10.3390/su132413608 - 9 Dec 2021
Cited by 14 | Viewed by 2426
Abstract
This study aimed to assess the spatiotemporal sensitivity of the net irrigation water requirement (NIWR) to changes in climate, for sixteen crops widely cultivated in four irrigation projects located in arid and semi-arid regions of Iraq. Using LARS-WG and five GCMs, the minimum [...] Read more.
This study aimed to assess the spatiotemporal sensitivity of the net irrigation water requirement (NIWR) to changes in climate, for sixteen crops widely cultivated in four irrigation projects located in arid and semi-arid regions of Iraq. Using LARS-WG and five GCMs, the minimum and maximum temperature and precipitation were projected for three periods from 2021–2080 with 20-year steps (P1, P2, and P3) under representative concentration pathways (RCPs) 2.6, 4.5, and 8.5. Weather data available for a reference period from 1990–2019 in four representatives’ meteorological stations were used. The climate variables and other required data were inserted into the CROPWAT 8 NIWR tool. Findings revealed that the increase in the NIWR for the considered crops due to climate change falls in the range 0.1–42.4%, 1.8–44.5%, 1.2–25.1%, and 0.7–14.7% for the North Jazeera Irrigation Project (NJIP), Kirkuk Irrigation Project (KRIP), Upper Khalis Irrigation Project (UKIP), and Dalmaj Irri-gation Project (DLIP), respectively. Barley is more susceptible to changes in climate, whereas maize, potato, soybean, and millet are found to withstand changes in climate better than others. The novel outcomes of this study support optimal spatiotemporal allocation of irrigation water requirement and the sustainable management of water resources in a changing climate in arid and semi-arid regions. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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Review

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45 pages, 4182 KiB  
Review
An Overview of Snow Water Equivalent: Methods, Challenges, and Future Outlook
by Mercedeh Taheri and Abdolmajid Mohammadian
Sustainability 2022, 14(18), 11395; https://doi.org/10.3390/su141811395 - 11 Sep 2022
Cited by 5 | Viewed by 3437
Abstract
The snow depth or snow water equivalent affects water, carbon, and energy cycles as well as surface–atmosphere interactions. Therefore, the global monitoring of spatiotemporal changes in snow water equivalent is a crucial issue, which is performed by characterizing the macrophysical, microstructural, optical, and [...] Read more.
The snow depth or snow water equivalent affects water, carbon, and energy cycles as well as surface–atmosphere interactions. Therefore, the global monitoring of spatiotemporal changes in snow water equivalent is a crucial issue, which is performed by characterizing the macrophysical, microstructural, optical, and thermal characteristics of the snowpack. This paper is a review of the retrieval methods of snow water equivalent in three main categories, including in situ measurements, reconstruction approaches, and space-borne measurements, along with their basic concepts, advantages, and uncertainties. Since satellite observations are the most important tool used to detect snow properties, the paper focuses on inversion models and techniques using microwave remote sensing. The inversion models, based on various theoretical foundations, are classified into empirical, statistical, and physical (emission) models, and the techniques are described in four groups: iterative methods, lookup table, machine learning, and data assimilation approaches. At the end, the available global and regional gridded products providing the spatiotemporal maps of snow water equivalent with different resolutions are presented, as well as approaches for improving the snow data. Full article
(This article belongs to the Special Issue Sustainable Water Resources Management and Sustainable Environment)
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