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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 (12 January 2024) | Viewed by 15481

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Special Issue Editors

Dr. Johnbosco C. Egbueri

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Guest Editor

Department of Geology, Chukwuemeka Odumegwu Ojukwu University, Uli, PMB 02, Nigeria
Interests: engineering geology; hydrogeology; environmental geology; medical geology; water quality; hydrogeochemistry; health risk assessment; geoinformatics; numerical modelling; artificial intelligence; machine learning
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Prof. Dr. Peiyue Li

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Guest Editor

School of Water and Environment, Chang’an University, Xi’an 710054, China
Interests: water resources; hydrogeology; groundwater quality; groundwater pollution; groundwater modeling; health risk assessment; geochemical modeling; hyrogeochemistry
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Prof. Dr. Antonije Onjia

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Guest Editor

Faculty of Technology and Metallurgy, University of Belgrade, Belgrade, Serbia
Interests: environmental chemistry; analytical chemistry; chemometrics; environmental radioactivity; chromatographic techniques; environmental pollution; physical chemistry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The need for all humans to have access to clean water is paramount and forms a critical aspect of daily life. This was enshrined as part of the Sustainable Development Goals (SDGs). In view of this, researchers have been monitoring and assessing groundwater occurrence and distribution, groundwater quality and groundwater vulnerability, and developing innovative ways of solving groundwater pollution challenges. Several technological- and mathematical-based techniques can be used to conduct groundwater research. Intelligent systems are also reliable tools that can be employed. For decades, various geospatial (remote sensing and geographic information system (GIS)), artificial intelligence (AI), machine learning (ML), statistical, and indexical methods have been proposed and applied by numerous researchers in the field of hydrogeology and environmental water quality. Most of the previous research outputs uphold that these methods have been very useful in interpreting groundwater hydrology and groundwater quality data. The application of integrated methods for groundwater hydrology, environmental contamination and water quality research is of the utmost significance when actualizing many environmental sustainability goals.

This Special Issue, “Groundwater Hydrology, Contamination, and Sustainable Development”, aims to provide a collection of innovative, original research papers, case studies, and review papers that addresses a wide-range of issues on the hydrology, contamination, and sustainable development of groundwater. This Special Issue will also provide insights into the sustainable development of rural and urban water environments. Up-to-date recent developments on the topic and perspectives for future research will be covered.

A wide-range of article types related to the listed themes will be considered in this Special Issue. The research themes covered in this Special Issue include, but are not limited to:

Environmental groundwater quality issues in developing/developed and arid/semiarid regions.
Groundwater mapping for sustainable water resources’ development.
Integration of intelligent systems for modelling groundwater quality and pollutant transport.
Application of AI and ML techniques in modelling emerging contaminants in groundwater.
Application of remote sensing and GIS for sustainable groundwater development and management.
Development of hybrid machine learning algorithms for water quality assessment.
Novel statistical techniques for drinking, industrial, and irrigation water quality assessment.
Climate change and its impacts on groundwater hydrology and quality.
Impact of COVID-19 on groundwater hydrology and quality.
Hydrometeorological parameters as they affect groundwater occurrence and distribution.
Characterization of aquifer parameters for sustainable groundwater development.
Hydrogeochemical investigation of groundwater resources as relates to sustainable development.
Impact of anthropogenic activities on groundwater hydrology and quality.
Water scarcity in developing regions and insights for sustainable groundwater development.
Integrated modelling techniques applied for sustainable groundwater management.
Groundwater interconnections with surface hydrology.
Hydrological cycle, hydrogeological systems and natural water protection.
Emerging contaminants as threats to sustainable groundwater development.
Groundwater vulnerability mapping for sustainable rural/urban development.
Groundwater pollution and source apportionment for sustainable mitigation planning.
Human health risk assessment of contaminated groundwater.
Novel groundwater pollution indexing for sustainable groundwater management.
Remediation and treatment methods for contaminated/polluted groundwater systems.

Dr. Johnbosco C. Egbueri
Prof. Dr. Peiyue Li
Prof. Dr. Antonije Onjia
Guest Editors

Manuscript Submission Information

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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

artificial intelligence modeling
chemometric analysis
climate change
COVID-19 impact
drinking water quality
emerging contaminants
groundwater development
groundwater quality
hydrogechemistry
hydrometeorology
industrial and irrigation water quality
remote sensing and GIS
statistical methods

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Published Papers (6 papers)

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Research

27 pages, 6835 KiB

Open AccessArticle

Assessment of Groundwater Potential Zones Utilizing Geographic Information System-Based Analytical Hierarchy Process, Vlse Kriterijumska Optimizacija Kompromisno Resenje, and Technique for Order Preference by Similarity to Ideal Solution Methods: A Case Study in Mersin, Türkiye

by Mehmet Özgür Çelik, Lütfiye Kuşak and Murat Yakar

Sustainability 2024, 16(5), 2202; https://doi.org/10.3390/su16052202 - 6 Mar 2024

Cited by 5 | Viewed by 1240

Abstract

The indiscriminate use of surface water has heightened the demand for groundwater supplies. Therefore, it is critical to locate potential groundwater sources to develop alternative water resources. Groundwater detection is tremendously valuable, as is sustainable groundwater management. Mersin, in southern Türkiye, is expected to confront drought shortly due to increased population, industry, and global climate change. The groundwater potential zones of Mersin were determined in this study by GIS-based AHP, VIKOR, and TOPSIS methods. Fifteen parameters were used for this goal. The study area was separated into five categories. The results show that the study area can be divided into “Very High” zones (4.98%, 5.94%, 7.96%), followed by “High” zones (10.89%, 10.32%, 16.50%), “Moderate” zones (60.68%, 52.41%, 51.56%), “Low” zones (21.28%, 28.53%, 20.90%), and “Very Low” zones (2.18%, 2.80%, 3.07%) in turn. Data from 60 wells were used to validate potential groundwater resources. The ROC-AUC technique was utilized for this. It was seen that the performance of the VIKOR model is better than that of the AHP and TOPSIS (76.5%). The findings demonstrated that the methods and parameters used are reliable for sustainable groundwater management. We believe that the study will also help decision makers for this purpose. Full article

(This article belongs to the Special Issue Groundwater Hydrology, Contamination, and Sustainable Development)

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25 pages, 27751 KiB

Open AccessArticle

Recharge Estimation Approach in a Data-Scarce Semi-Arid Region, Northern Ethiopian Rift Valley

by Sisay S. Mekonen, Scott E. Boyce, Abdella K. Mohammed, Lorraine Flint, Alan Flint and Markus Disse

Sustainability 2023, 15(22), 15887; https://doi.org/10.3390/su152215887 - 13 Nov 2023

Cited by 5 | Viewed by 2325 | Correction

Abstract

Sustainable management of groundwater resources highly relies on the accurate estimation of recharge. However, accurate recharge estimation is a challenge, especially in data-scarce regions, as the existing models are data-intensive and require extensive parameterization. This study developed a process-based hydrologic model combining local and remotely sensed data for characterizing recharge in data-limited regions using a Basin Characterization Model (BCM). This study was conducted in Raya and Kobo Valleys, a semi-arid region in Northern Ethiopia, considering both the structural basin and the surrounding mountainous recharge areas. Climatic Research Unit monthly datasets for 1991 to 2020 and WaPOR actual evapotranspiration data were used. The model results show that the average annual recharge and surface runoff from 1991 to 2020 were 73 mm and 167 mm, respectively, with a substantial portion contributed along the front of the mountainous parts of the study area. The mountainous recharge occurred along and above the valleys as mountain-block and mountain-front recharge. The long-term estimates of the monthly recharge time series indicated that the water balance components follow the temporal pattern of rainfall amount. However, the relation of recharge to precipitation was nonlinearly related, showing the episodic nature of recharge in semi-arid regions. This study informed the spatial and temporal distribution of recharge and runoff hydrologic variables at fine spatial scales for each grid cell, allowing results to be summarized for various planning units, including farmlands. One third of the precipitation in the drainage basin becomes recharge and runoff, while the remaining is lost through evapotranspiration. The current study’s findings are vital for developing plans for sustainable management of water resources in semi-arid regions. Also, monthly groundwater withdrawals for agriculture should be regulated in relation to spatial and temporal recharge patterns. We conclude that combining scarce local data with global datasets and tools is a useful approach for estimating recharge to manage groundwater resources in data-scarce regions. Full article

(This article belongs to the Special Issue Groundwater Hydrology, Contamination, and Sustainable Development)

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17 pages, 3545 KiB

Open AccessArticle

Analysis of Steady Groundwater Flow in Confined Aquifer Due to Long-Strip Pit Dewatering with Suspended Cut-Off Wall

by Weijia Tan, Haibo Kang, Jin Xu and Xudong Wang

Sustainability 2023, 15(22), 15699; https://doi.org/10.3390/su152215699 - 7 Nov 2023

Viewed by 1411

Abstract

This study investigates the steady flow resulting from dewatering by a partially penetrating well in a confined aquifer with a cut-off barrier. By considering flow in both horizontal and vertical directions and incorporating the barrier and pumping well as flow boundary conditions, separate mathematical models are established for the inside and outside of the cut-off barrier. The interaction between these zones is ensured through continuous conditions along the opening of the two zones. A semi-analytical solution is derived for the problem using the finite Fourier cosine transform and boundary transformation methods. The effectiveness of the method is verified by comparing it with the finite element numerical results and pumping test data respectively. Based on the proposed solutions, we proceed to analyze the influence of some relevant factors: the extent to which the cut-off wall is embedded within the confined aquifer, the depth of the partially penetrating well, and the distance to the lateral head boundary. Results indicate that a greater depth of the cut-off wall leads to a reduced pumping rate requirement for achieving a desired drawdown of the confined water level within the excavation. According to the presented solution, placing pumping wells near the top of the confined aquifer in excavation dewatering projects can facilitate a faster reduction of the confined water head at the excavation bottom. Additionally, proximity of lateral head boundary could significantly impact dewatering, with closer boundaries reducing dewatering effectiveness due to improved aquifer recharge. Finally, the use of the Fourier method showcases impressive convergence properties in the approach presented in this study. The computed results maintain a high level of approximation quality, even with extremely coarse discretization. Full article

(This article belongs to the Special Issue Groundwater Hydrology, Contamination, and Sustainable Development)

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17 pages, 5718 KiB

Open AccessArticle

Physicochemical Parameters of Water and Its Implications on Avifauna and Habitat Quality

by Arun Pratap Mishra, Sipu Kumar, Rounak Patra, Amit Kumar, Himanshu Sahu, Naveen Chandra, Chaitanya B. Pande and Fahad Alshehri

Sustainability 2023, 15(12), 9494; https://doi.org/10.3390/su15129494 - 13 Jun 2023

Cited by 13 | Viewed by 5181

Abstract

Wetland ecosystems are essential for maintaining biological diversity and are significant elements of the global landscape. However, the biodiversity of wetlands has been significantly reduced by more than 50% worldwide due to the rapid expansion of urban areas and other human activities. The aforementioned factors have resulted in drastic antagonistic effects on species composition, particularly aquatic avifauna. The decline in wetland avifauna, which can be attributed to changes in water quality that impact aquatic habitats, is a major concern. In this study, we evaluated the impact of physicochemical parameters on aquatic avifauna in India’s first Conservation Reserve, a Ramsar site and an Important Bird Area. Water samples were collected on a monthly basis across nine different sites and various parameters, such as temperature, electrical conductivity, pH, biological oxygen demand, dissolved oxygen, total dissolved solids and salinity, were analyzed for pre-monsoon and post-monsoon seasons, while point count surveys were conducted to assess species richness and the density of waterbirds. Our findings show a positive correlation of species density with water temperature (r = 0.57), total dissolved solids (r = 0.56) and dissolved oxygen (r = 0.6) for pre-monsoon season and a negative correlation for dissolved oxygen (r = −0.62) and biological oxygen demand (r = −0.69) for post-monsoon season. We suggest that a synergistic effect of pH, salinity, biological oxygen demand and total dissolved solids may affect aquatic bird populations in Asan Conservation Reserve. Poor water quality was observed in a few sampling sites, which may negatively affect the number and density of waterbirds present. The findings of this study emphasize the importance of water quality in wetland conservation, particularly for aquatic avifauna. Full article

(This article belongs to the Special Issue Groundwater Hydrology, Contamination, and Sustainable Development)

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33 pages, 10613 KiB

Open AccessArticle

Characterization of the Hydrochemistry, Scaling and Corrosivity Tendencies, and Irrigation Suitability of the Water of the Rivers Karawa and Iyiaji

by Ogechi Lilian Alum, Hillary Onyeka Abugu, Vivian Chinekwu Onwujiogu, Arinze Longinus Ezugwu, Johnbosco C. Egbueri, Chiedozie Chukwuemeka Aralu, Ifeanyi Adolphus Ucheana, Jude Chukwudi Okenwa, Chidinma Christiana Ezeofor, Samuel Ibezim Orjiocha and Janefrances Ngozi Ihedioha

Sustainability 2023, 15(12), 9366; https://doi.org/10.3390/su15129366 - 9 Jun 2023

Cited by 18 | Viewed by 1573

Abstract

Assessing water quality is necessary to ascertain its viability for domestic, industrial, and agricultural purposes. A total of 48 water samples were, respectively, drawn from the Rivers Karawa and Iyiaji located in Ezeagu and Uzo-uwani which are typical rural areas in Enugu State, Nigeria. These samples were taken in two seasons (early rainy season and late dry season). Physicochemical properties were determined using standard methods. The scaling and corrosivity potentials of the water were evaluated using the Larson-Skold index, aggressive index, Puckorius scaling index, and Ryznar stability index models. Additionally, seven irrigation evaluation criteria, as well as spatial distribution maps, were used to determine the suitability of the river waters for irrigation purposes and to interpolate the spatial distribution of the river water quality parameters. Major ion chemistry was used in the assessments. The physicochemical properties of river waters fell within the recommended standard values. However, NO₃⁻ greatly exceeded the recommended range in both rivers. The cations and anions from River Karawa were Ca²⁺ > Mg²⁺ > K⁺ > Na⁺ and NO₃⁻ > Cl⁻ > SO₄²⁻ > HCO₃⁻ > CO₃⁻ > PO₄⁻, while those from River Iyiaji were Ca²⁺ > Mg²⁺ > Na⁺ > K⁺ and Cl⁻ > SO₄²⁻ >NO₃⁻ > PO₄⁻ > HCO₃⁻ > CO₃⁻. A piper plot showed the predominance of Ca²⁺ and Mg⁺, as well as SO₄²⁻ and Cl⁻, in both rivers. The seven irrigation assessment indices indicated that the water of the Rivers Karawa and Iyiaji is suitable for irrigation purposes. In addition, the scaling and corrosivity models predicted that the river waters have high scaling and corrosivity potentials. Specifically, while the aggressive index suggested that it is severely corrosive, the Langelier saturation index suggested that the water from both rivers is supersaturated and, thus, has potential to scale. Full article

(This article belongs to the Special Issue Groundwater Hydrology, Contamination, and Sustainable Development)

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17 pages, 4804 KiB

Open AccessArticle

Prediction of Sodium Hazard of Irrigation Purpose using Artificial Neural Network Modelling

by Vinay Kumar Gautam, Chaitanya B. Pande, Kanak N. Moharir, Abhay M. Varade, Nitin Liladhar Rane, Johnbosco C. Egbueri and Fahad Alshehri

Sustainability 2023, 15(9), 7593; https://doi.org/10.3390/su15097593 - 5 May 2023

Cited by 81 | Viewed by 2668

Abstract

The present study was carried out using artificial neural network (ANN) model for predicting the sodium hazardness, i.e., sodium adsorption ratio (SAR), percent sodium (%Na) residual, Kelly’s ratio (KR), and residual sodium carbonate (RSC) in the groundwater of the Pratapgarh district of Southern Rajasthan, India. This study focuses on verifying the suitability of water for irrigational purpose, wherein more groundwater decline coupled with water quality problems compared to the other areas are observed. The southern part of the Rajasthan State is more populated as compared to the rest of the parts. The southern part of the Rajasthan is more populated as compared to the rest of the Rajasthan, which leads to the industrialization, urbanization, and evolutionary changes in the agricultural production in the southern region. Therefore, it is necessary to propose innovative methods for analyzing and predicting the water quality (WQ) for agricultural use. The study aims to develop an optimized artificial neural network (ANN) model to predict the sodium hazardness of groundwater for irrigation purposes. The ANN model was developed using ‘nntool’ in MATLAB software. The ANN model was trained and validated for ten years (2010–2020) of water quality data. An L-M 3-layer back propagation technique was adopted in ANN architecture to develop a reliable and accurate model for predicting the suitability of groundwater for irrigation. Furthermore, statistical performance indicators, such as RMSE, IA, R, and MBE, were used to check the consistency of ANN prediction results. The developed ANN model, i.e., ANN4 (3-12-1), ANN4 (4-15-1), ANN1 (4-5-1), and ANN4 (3-12-1), were found best suited for SAR, %Na, RSC, and KR water quality indicators for the Pratapgarh district. The performance analysis of the developed model (3-12-1) led to a correlation coefficient = 1, IA = 1, RMS = 0.14, and MBE = 0.0050. Hence, the proposed model provides a satisfactory match to the empirically generated datasets in the observed wells. This development of water quality modeling using an ANN model may help to useful for the planning of sustainable management and groundwater resources with crop suitability plans as per water quality. Full article

(This article belongs to the Special Issue Groundwater Hydrology, Contamination, and Sustainable Development)

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