Groundwater for Sustainable Development最新文献

The Saïss basin in the Fez-Meknes region of Morocco, covering approximately 2100 km², faces increased water demand due to population growth, economic development, and climate change, making groundwater a crucial resource. This study aims to delineate areas with groundwater potential (GWP) and evaluate the performance of various machine learning, deep learning, and hybrid ensemble models in predicting GWP. Using a dataset of 440 springs and wells, and 20 groundwater conditioning factors (GWCF) including topographical, hydrological, geological, and hydrogeological features, the study employed multi-collinearity analysis, variance inflation factor (VIF), tolerance (Tol) assessments, and an Information Gain (IG) test to analyze these factors. The study compared the performance of three machine learning algorithms (Gaussian Naive Bayes (GNB), k-Nearest Neighbors (KNN), Gradient Boosting Classifier (GBC)), three deep learning algorithms (Deep Learning Neural Networks (DLNN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN)), and a hybrid ensemble model (Random Forests (RF), Support Vector Machine (SVM), Logistic Regression (LR)) using the area under the receiver operating characteristic curve (ROC-AUC) as the evaluation metric. The results showed that the hybrid ensemble model had the highest AUC of 0.86, followed by GBC (AUC = 0.85), DLNN (AUC = 0.84), CNN (AUC = 0.83), KNN (AUC = 0.79), RNN (AUC = 0.78), and GNB (AUC = 0.75). The study revealed that 45% of the Saïss Basin exhibits high to very high GWP, particularly in Ain Taoujdat, Haj Kaddour, and Boufekrane districts, with lithology, slope, and transmissivity being the most influential factors. The resulting GWP map can guide decision-makers in planning well and borehole drilling for drinking water and agriculture, as well as artificial recharge projects, thus promoting sustainable groundwater management in the Saïss basin.

In the tapestry of life, water is the essential thread weaving through our existence. Imagine this thread not just as a simple element, but as the very pulse that sustains our communities. This study unravels the nuanced interplay between community engagement and sustainable water solutions in District Karak, shining a spotlight on a crucial but often overlooked aspect of rural water programs. Employing the theoretical framework of Social Capital Theory by Robert Putnam and Pierre Bourdieu, our research investigates the interconnected relationship between community participation and the long-term viability of water supply initiatives. Focusing randomly on three selected water supply schemes, we employed a sampling technique and collected data from 330 respondents through interviews. Community members, Community-Based Organizations (CBOs), and executing agencies were sampled to analyze the extent and impact of engagement across program phases. The findings underscore the pivotal role of participatory approaches facilitated by CBOs and executing agencies, revealing active community engagement as a linchpin for sustained water supply success. Results of the study reveal that the synergy of community satisfaction and engagement paves the way for a resilient water future, offering a blueprint for District Karak and similar regions to pursue a more secure water future and mitigate the adverse effects of water scarcity through the promotion of community participation.

The main objectives of this research were to the hydrogeochemical processes that control the groundwater chemistry, groundwater quality, and assessment of health risks of water. The drinking water that supplies the community of Santa María del Rio, S.L.P., comes from groundwater, in some municipality localities, groundwater Fluorine and arsenic are reported. Twenty-one representative groundwater samples were taken. Physicochemical parameters in situ: pH, OD, ORP, Alkalinity, STD, EC, Salinity, Total Coliforms, and E-coli, were analyzed, and in the laboratory, the heavy metals, metalloids and major constituents, cations: calcium, sodium, magnesium, and potassium, were determined by the ICP, and anions: chlorides, and sulfates, by colorimetry techniques. The results of the analyses were compared with the Mexican and EPA drinking water standards to verify their suitability and ensure that they do not exceed the permitted limit values. The results of the chemistry of the principal groundwater ions in the study area suggest that the main hydrogeochemical process that controls the variation of groundwater quality is the rock–water interaction. Groundwater has been classified into two hydrochemical facies, CaMgHCO₃ and NaHCO₃, consistent with the type of rock. The samples with the CaMg–HCO₃ facie are associated with less evolved waters located in areas with local recharge. The dominant reactions in the aquifer are calcite, dolomite, and gypsum solutions. The presence of the N–NO₃^- ion is associated with agricultural and urban zone influence, which indicates that this activity has impacted the water quality. The risk index (HI) results show that values > 0.1 < 1 of HI, for Pb present low chronic risks for adults and children. In contrast, HI values > 4 for both population groups represent high chronic risk. Excessive use of fertilizers should be controlled in the study area to prevent groundwater contamination by heavy metals and metalloids and be measured regularly to check drinking water quality.

Varanasi is an exponentially developing city in the Himalayan-sourced Ganges river basin. To understand the sustainable groundwater-sourced drinking water in Varanasi, it is essential to study the land use-land cover that reflects the surface geomorphology vis-a-vis sub-surface geology, and influence groundwater conditions. We incorporate lithological and groundwater data obtained from an extensive network of boreholes in and around the city at 110 sites, reaching a maximum depth of 100 m below ground level (bgl). The unconsolidated subsurface are primarily composed of sand, silt, clay, and gravel where, silty clay layer. Groundwater quality and stresses were determined through multi-dimensional hydrogeological approaches. The data were analyzed through multivariate statistics (Principal Component Analyses to identify the governing factor influencing the broad hydrogeochemistry. PC1 for urban areas has higher loading values for Fe, Cl⁻ compared to Semi-urban areas highlighting contamination by municipal wastewater. PC2 for urban areas shows higher loading values for Mg²⁺ and HCO₃⁻ compared to semi-urban areas. Due to heavy urbanization in Varanasi, the aquifer suffers substantial groundwater abstraction during particular times of the day compared to the agricultural lands. An increase of about 9% in built-up areas within a span of 10 years (2012–2022) poses a threat to the aquifer system of our study area, jeopardizing access to sustainable drinking water. With the expansion of urbanization and unregulated groundwater extraction, the vulnerability of the aquifer system will probably increase in the foreseeable future. Implementation of sustainable water management policies, engaging all economic sectors of the population in Varanasi, can expedite the process and safeguard the aquifer from attaining its emerging vulnerability. Thus, comprehending evolving groundwater risks through non-invasive methods like that discussed in the present study, holds significant promise for effectively targeting safe groundwater availability in future.

Groundwater quality is a crucial aspect especially in the arid and semi-arid segments of the world due to its restricted availability. With increasing consumptions over time period, it is essential to ensure its quality by appraising complex hydro-geochemistry. In the present study, an attempt has been made to evaluate the groundwater hydro-geochemistry in the arid and semi-arid segment of Rajasthan, India and to fill the gap in understanding of groundwater quality by incorporating eXplainable Artificial Intelligence (XAI). 120 groundwater samples were collected during post monsoon season of 2022 and sixteen physico-chemical parameters were analyzed and corresponding inferences were drawn. The hydro-chemical facies indicated Na–Cl composition of groundwater with the dominance of evaporation. Majority of the samples showed reverse ion exchange process along with positive Saturation Index value of Calcite (CaCO₃) and tendency towards leaching F⁻ in the groundwater. Water Quality Index for drinking as well as irrigation purpose showed relatively better quality in the central segment than the marginal region. The SHAP values derived from the XGBoost model depicted fluoride (F-) as the primary feature influencing overall groundwater quality for drinking purposes, whereas the Sodium Absorption Ratio (SAR) emerged as the key predictor influencing overall groundwater quality for irrigation. The implication of proposed method signifies the importance of incorporating hydro-geochemical inferences with machine learning technique to understand the complex character of groundwater. Further, due to its robustness as well as cost-effectiveness, the application of the method would be helpful in policymaking to safeguard the groundwater resource in arid and semi-arid regions at global scale.

Developing wastewater treatment technologies is crucial for enhancing treatment efficiency and promoting the reuse of treated water. In this article, the Algal-Bacterial integrated system (ABIS) is employed to treat municipal wastewater collected from the Zenin wastewater treatment plant in Giza governorate, Egypt. This system relies on the synergy between heterotrophic bacteria and microalgae to form a biofilm capable of absorbing contaminants from the wastewater. The main objective of this study is to optimize the factors influencing the treatment efficiency using response surface methodology derived from the experimental design software of Design Expert 6.0.8. The optimal results revealed that using an absorber amount of 0.18 g/L for a hydraulic retention time of 1.4 d provides removal efficiency of BOD, COD, TSS, and turbidity are 88.57%, 82.7 %, 94.90%, and 95.91%, respectively. These findings were experimentally and statistically verified with an accuracy exceeding a 95% confidence interval and 95% prediction interval. The physicochemical characteristics, algal community structure, as well as the density of total coliform, fecal coliform, and Escherichia coli (E. coli), were determined for the treated wastewater and compared to the Egyptian code of practice for the use of treated municipal wastewater for agricultural purposes to assess its suitability for unrestricted irrigation.

Despite meeting legal standards, drinking water quality in sparsely populated areas with scattered groundwater resources in medium mountain ranges may be compromised. This results from inaccurate assessments of human activities, such as forest exploitation, on groundwater intake watersheds or insufficient monitoring frequency to understand their full impact on groundwater quality. This study involved a 3-year monthly monitoring of 18 groundwater intakes for drinking water supply, situated in areas with crystalline bedrocks, a temperate climate, and surrounded by forest exploitation. The quality of groundwater collected from alterites up to 15 m deep was evaluated over time. The correlation between the groundwater physico-chemical parameters (measured through 382 samples between March 2017 and December 2020) and the groundwater intakes’ environment - such as the geological and pedological context, land use, climate, and depth of drains - was investigated to understand their potential impact on groundwater quality. This study revealed a significant degradation in shallow groundwater quality (up to 5 m deep) concerning dissolved aluminum (concentration up to 2 mg L⁻¹), which results from land use and is climate dependent. Indeed, dissolved aluminum concentrations in groundwater can be correlated with the pH of the upper soil horizons, which are mostly impacted by forestry practices, as well as with rainfall events. The results of this study highlight that by integrating efforts to preserve the soil and change forestry practices (e.g., selective logging, avoiding rapid rotations), more efficient protection of groundwater quality can be achieved in the context of acidic soils present on crystalline bedrock.

Microplastics (MPs) and nanoplastics (NPs) have gained increasing attention in environmental research due to their ubiquitousness and potential impacts on natural environments and human health as per the UN Sustainable Development Goals (SDGs), particularly SDG-14 to address global threats where at least 12 SDGs, directly/indirectly impacts. Present review is undertaken to highlight the process of breakdown of diverse groups of plastic products in soil, surface water, and groundwater under the influence of different factors (UV, light, heat, microbe, etc.), which are mobilized as MPs/NPs to the surface water, groundwater, air, soil, and living organisms by different natural and anthropogenic processes. Review also highlights a comprehensive overview of the methodology for sampling, characterization, and analysis for these minuscule plastic particles (PPs) in various environmental samples, encompassing surface/subsurface water, sediments, soils, and biological organisms. The collection, extraction, and characterization of MPs/NPs, typically employ filtration processes, wherein a known volume of water is passed through a fine mesh to capture MPs/NPs from water samples. Sediment/soil samples require sieving and density separation techniques to isolate PPs from the surrounding matrix. Biological samples require digestion steps to remove organic matter, leaving behind plastics for analysis. Fourier-transform infrared (FTIR) spectroscopy, Raman spectroscopy, and scanning electron microscopy (SEM) are commonly utilized to determine the polymer composition, size, shape, and surface characteristics of PPs. Quantification involves several approaches, visual counting, image analysis, and spectroscopic techniques. Abundance of MPs/NPs in the respective environmental samples (water, air, soil, etc.) can be determined by comparing the richness (i.e., number/mass) of plastics to the volume or weight of the original sample. Such comprehensive analytical methodologies contribute to understand the scope and magnitude of plastic pollution and its potential repercussions for ecosystems and human well-being, which are essential for developing the effective strategies to mitigate these pressing global environmental challenges for sustainable development.

The renewable groundwater resources in Egypt are restricted close to the Nile River. In the study area, two major water bearings are near the Nile: The Quaternary and the Eocene aquifers. Remote sensing (ASTER DEM, Landsat-8, and Sentinal-1 InSAR images), geochemical modeling, and isotopic constraints (δ¹⁸O and δ²H) were employed and integrated with the GIS framework for delineating the low saline and sustainable groundwater zones. Remote sensing data indicates intensive structure lineaments in the middle-eastward part, spatially congruent with subsurface features deduced from radar satellites, facilitating hydraulic connections with the Nile water. The soil moisture index, land surface temperature, and salinity index in irrigated areas, reveal a strong association between in situ electrical conductivity values and satellite-derived spectral indices. The higher groundwater salinity in the middle eastern region coincided with high lineament density zones, and higher temperature zones, leading to increased rock water interaction that leads to groundwater salinization. The isotopic composition of the Quaternary aquifer ranges between −1.30 ‰ and +5.53 ‰ for δ¹⁸O, while δ²H ranges between −11.49 ‰ and +34.47 ‰. In the Eocene aquifer, δ¹⁸O ranges between −0.46 and +3.45 ‰, while the δ²H ranges between −3.16 ‰ and +23.50 ‰, indicating subsurface recharge from the Nile water. The simulation of the mass transport geochemical NETPATH model revealed mixing ratios from the Nile water ranging from 3.4% to 93.7%. Based on the results, the area is classified into four classes, class (1) represents samples of high conduit with Nile water (<50% mixing), class (2) represents samples of moderate conduit with Nile water (10–50% mixing), class (3) represents samples of low conduit with Nile water (<1–10% mixing), class (4) represents samples of water-rock interaction. The findings would be of great importance for delineating sustainable zones of the Nile Valley aquifers.

Excessive fluoride levels in drinking water are problematic in several countries, particularly those which are relatively poor. Thus, there is a need to create cost effective sorbents which can easily be applied to make the water safe to use. Therefore, this study focussed on Al₂O₃/TiO₂ sorbents which appear to address issues with commercially available alumina such as aluminium dissolution. Adjusting the alumina/titania ratio significantly influenced not only the fluoride uptake capacity but also the uptake of a wide range of contaminants found in groundwater. The exchange kinetics were relatively fast regardless of mixed oxide composition with equilibrium obtained within 6 h. Equilibrium isotherms were unfavourable for fluoride removal where titania compositions were dominant. In contrast, favourable isotherms were noted when alumina was the dominant oxide present. Barium, calcium, strontium, boron, iron, manganese, zinc, potassium, lithium, and silica were all substantially removed by varying the alumina/silica ratio in the sorbent. This behaviour may be valuable for broader remediation of dissolved species in groundwater (not just fluoride). Based upon the tests data a 70% Al₂O₃ – 30% TiO₂ material was recommended to be the preferred composition for comprehensive treatment of groundwater. The sorbents appeared to comprise of alumina and titania with surface areas between 129 and 255 m²/g. There was no evidence for new oxide phases nor for a relationship between surface area and performance. Mechanistically both ion exchange and surface complexation may occur when treating groundwater.