Groundwater for Sustainable Development最新文献

Hydrogeochemical, multivariate statistical analysis, and multi-isotopic (δ¹⁸O, δD, and δ³⁴S) approaches were used to identify the cause and process of groundwater salinization in the Zarabad coastal aquifer. The hydrochemical facies evolution (HFE) diagram suggests that the Na–Cl facies is the dominant hydrochemical facies. Groundwater chemistry is mostly influenced by cation exchange and its interaction with silicate rocks, as shown by the Gibbs plot. The isotopic composition of δ¹⁸O, δD, and δ³⁴S varies from −3.17‰ to −1.35‰ (with an average of −1.69‰), −25.5‰ to −9‰ VSMOW (with an average of −18.09‰) and −7.7‰–16.7‰ V-CDT (with an average of 0.54‰), respectively. The salinization of groundwater may be caused by the evaporation of water or the dissolution of evaporites. This can be inferred from the δ¹⁸O to δD data, which indicates that a majority of water falls below the GMWL, IMWL, and LMWL. The d-excess value, ranging from −19.8‰ to 5.36‰, further suggests that the groundwater has undergone evaporation before infiltration. In addition, the comparison between the δ³⁴S–SO₄^2- and SO₄²⁻ plots suggested that the dissolution of evaporites is the primary source of SO₄²⁻. Water chemistry changes in this aquifer is primarily caused by water-rock interaction, ion exchange, and evaporation.

Groundwater supports over 2.4 billion people across the globe and is critical to food security. The spatial dynamics of groundwater vary from place to place. The irregularity of groundwater resource exploitation is recognized in drought-prone areas, putting pressure on the resource. Hence, accurate groundwater potential characterization is critical for sustainable development and management of groundwater, particularly in drought-prone environments. Therefore, this study aimed at utilizing remote sensing satellite data and geospatial-based (analytical hierarchy process (AHP) and frequency ratio (FR)) algorithms to characterize groundwater potential zones (GWPZs) in the Keiskamma Catchment of South Africa. Seven (7) selected factors, including geology, soil type, slope, rainfall, drainage density, lineament density, and land use land cover, were assigned weights based on the AHP and FR algorithms. The validation results showed that the FR model performed better than the AHP, with the area under curve (AUC) accuracies of 62% and 50%, respectively. Based on the findings of this study, we infer that FR is more reliable than AHP when characterizing GWPZ. Lastly, GWPZ maps produced will be beneficial for improving efficient planning, management strategies, and decision-making.

This study examines the hydrogeochemical processes shaping groundwater quality in the Ilhas-São Sebastião aquifer system, situated at the interface of the Central and Southern Recôncavo basins in the densely populated area near the Brazilian metropolis Salvador. Analysis of 71 groundwater samples reveals distinctive hydrogeochemical compositions in aquifers. In the São Sebastião aquifer, alkalis (Na⁺ + K⁺) and strong acids (Cl⁻ and SO₄²⁻) prevail. Furthermore, a moderate correlation of Na+–Cl-marks an evolution from Mg–Ca–HCO3 to Mg–Ca–Cl and Na–Cl facies. In contrast, the Ilhas aquifer displays a Na⁺>Ca²+>Mg²⁺>K⁺ relationship for cations and HCO₃⁻ > Cl⁻ > SO₄²⁻ > CO₃²⁻ for anions and a recharge-discharge trajectory from the Mg–Ca–HCO₃ to the Ca–Na–HCO₃ facies. Additionally, it presents greater mineralization and dispersion of physicochemical parameters, especially around sub-basin depocenters. Its hydrogeochemical signature is characterized by robust correlations between TDS and EC, and between these parameters and SO₄²⁻, HCO₃⁻, Ca²⁺, and Mg²⁺, complemented by moderate correlations of EC with Na⁺ and Cl⁻. Bivariate Gibbs diagrams and ionic ratios indicate silicate weathering and ion exchange as the primary geochemical processes controlling solute concentrations in both aquifers. However, in the Ilhas aquifer, a subordinate contribution from reverse ion exchange is indicated by weak (TDS–Na⁺, TDS–K⁺, Na⁺–Ca²⁺, K⁺–Ca²⁺) and positive TDS–Ca²⁺ and TDS–Mg²⁺ correlations. Conversely, negative chloroalkaline indices and the moderate Na⁺–Cl^- correlation indicate that reverse ion exchange processes are mostly absent in the São Sebastião aquifer. Instead, both chloroalkaline imbalance reactions and silicate weathering contribute equally to the observed geochemical patterns. Groundwater geochemical signatures indicate recharge on flexural margins, active water-rock interaction in large depocenters, and mixing of hydrogeochemical facies between aquifer units. These insights contribute to a comprehensive understanding of groundwater evolution, crucial for effective water resource management in the region.

To understand groundwater pollution and its associated health hazards and to ensure the availability of a clean, safe, and sustainable water supply, comprehensive research plays a crucial role. This article presents an integrated investigation of groundwater conditions, hydrogeochemistry, and health implications arising from fluoride (F⁻) and nitrate (NO₃⁻) contamination in eastern Ghana. Analysis of 107 samples revealed variable groundwater suitability for human consumption, as indicated by Pollution Index of Groundwater (PIG) values ranging from 0.11 to 1.19. The study highlights significant variations in health hazard risks due to F⁻ and NO₃⁻ exposure. Hazard indices (HIs) for nitrate ingestion range from 0.000 to 16.321, for fluoride ingestion from 0.000 to 17.426, and for the combined ingestion risks from 0.000 to 17.602. Dermal absorption risk for nitrate is minimal, with values between 0.000 and 0.049. Spatially distinct contamination and health risks were mapped using GIS, to pinpoint vulnerable localities in the study region. Hydrochemical investigations, confirmed by clustering and factor analyses, revealed that natural geological processes are the primary drivers of groundwater quality and mineralization, with limited anthropogenic impacts. Further, an artificial neural network model with an impressive R² of 0.976 and low statistical errors demonstrated strong potential for accurate prediction of groundwater quality. The holistic study approach significantly advances groundwater research in the region, paving the way for effective resource management strategies by revealing areas of concern, understanding the contamination drivers, and predicting future water quality with high accuracy.

Groundwater resource management is a critical component of sustainable water use, necessitating accurate and nuanced mapping of groundwater potential zones. This study analyzed the groundwater potential of Algeria's 43,750 km² Chelif Basin (more than 17% of the area of Northern Algeria) using a combination of both subjective and objective mapping techniques. The adopted approaches encompass the benchmark analytical Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and the DEcision MAking Trial and Evaluation Laboratory (DEMATEL) methodologies to quantify interdependencies of criteria related to groundwater potential. The analysis focused on ten criteria related to groundwater potential, including core moisture availability and key hydrological factors like distance to river, topographic wetness index, and hydrological soils. Fuzzy-AHP achieved slightly higher groundwater prospecting accuracy (AUC = 0.730) than classic AHP (0.716), with benchmarking against 15 related studies indicating robust performance. Instead of the most commonly used criteria in groundwater literature such as lineament, stream order, recharge rate, and drainage density, this study employed alternative factors to challenge and validate the efficacy of the proposed methodology. The decision to omit certain criteria facilitated a more focused and manageable analysis, yet still delivered a robust evaluation of groundwater potential in the studied area. Moreover, this approach underscores the adaptability of the proposed methodology to accommodate varying sets of criteria, tailored according to the availability of data and specific research objectives. Additionally, the DEMATEL evaluation reveals new insights into subtle prioritization divergences, specifically between domain specialist opinions and analytical assessments of the criteria. The integration of fuzzy logic and causal relationship mapping through DEMATEL provides a comprehensive and robust foundation for groundwater potential modeling.

Groundwater protection requires an understanding of different hydrogeochemical processes and this study synthesised and analysed a large hydrogeochemical dataset (1030 data points over 15 years) of published data in western Iran, to gain a deeper understanding and reveal the main factors controlling groundwater geochemistry. Furthermore, non-carcinogenic effects on human health related to nitrate (NO₃⁻) concentrations were assessed. In terms of the measured parameters, four distinct clusters were identified Ca–HCO₃, Na–HCO₃, Na–SO₄, and Na–SO₄–Cl. Cluster 1 (68% of samples) had higher average pH while exhibiting lower average electrical conductivities (ECs), cations, and anions than the other clusters and had a lower average weighted arithmetic than the other clusters. 28.5%, 51.9%, 16.3%, 2.1%, and 1.2% of total water samples rated as excellent, good, poor, extremely poor, and undrinkable, respectively, implying that about 80.4% of the groundwater samples are potable. Multi-linear regression models based on pH and EC values can predict cation and anion concentrations in groundwater with high accuracy. The significance of the findings lies in their potential to facilitate the comprehension, modeling, and eventual forecasting of the fate of anions and cations in semi-arid and arid environments, as well as similar groundwaters, using common water characteristics. In order to lower the non-carcinogenic health risks to the local population, the appropriate actions should be taken. The majority of the region's agricultural areas have primary soil textures that are sandy and prone to NO₃⁻ leaching. Therefore, in order to maintain the quality of the groundwater in the study region, excessive use of chemical and organic fertilizers should be avoided. These findings will contribute to understanding and safeguarding groundwater quality, while also informing management strategies in arid and semi-arid regions with similar environmental characteristics.

This study investigates the sources and formation of spring water in the southwestern coastal regions of the Indian subcontinent. It involves sampling and analysing spring water, groundwater, rainwater of the region and biogeochemical tracers. The springs of the region were found to be cold (27.2–29.5 °C), acidic (pH = 3.43–6.83), freshwater dominant (Cl⁻ = 10.10 – 43.67 mg L⁻¹), and moderately oxygenated (DO = 5.08–9.43 mg L⁻¹). Using a binary mixing model with biogeochemical tracers (total alkalinity and Cl⁻), the study identified precipitation and groundwater as primary contributors, with sea water also influencing coastal springs. The binary model indicates a higher precipitation contribution (85–100%) to spring water compared to groundwater (0–68%). The basin-wise variability of contribution by different water masses evidenced spatial variation of precipitation is not only acting as the major driving force to build the spring water mass, it is also intricately linked with the geochemical factors controlled by the hydraulic gradient between spring and groundwater systems.

This study aims to reconstruct total water storage anomalies (TWSa) derived from GRACE satellite data using the LightGBM algorithm. It integrates hydroclimatic and environmental covariates including precipitation, land surface temperature (LST), evapotranspiration (ET), and vegetation cover along with topographical factors such as elevation and slope. This study investigates the long-term impacts of these variables on TWSa and examines potential delayed effects of GRACE signals. Guided by a robust theoretical framework that considers the intricate interplay of climatic and environmental factors on water storage, the research design employs a comparative modeling approach. LightGBM, random forest (RF), and support vector machine (SVM) models were implemented using GRACE and GRACE-Follow On (GRACE-FO) data from 2002 to 2022 in Iran. Key findings reveal that all three models achieved similar accuracy (RMSE ≈ 1.39 cm, R-squared ≈ 0.94, and NSE ≈ 0.89). However, LightGBM demonstrated superior computational efficiency, operating several hundred times faster than SVM and RF, making it advantageous for large-scale studies. Further, incorporating the time variable significantly enhanced predictive accuracy, surpassing the influence of ET and LST. The study also found that lagged effects of GRACE signals had a negligible impact on reconstruction accuracy. These findings suggest that LightGBM is a promising algorithm for efficiently and accurately reconstructing TWSa, with potential applications in large-scale hydrological studies.

Streptomycin (STR) is a widely used antibiotic to treat various infectious diseases in humans and animals. Increased STR production and distribution result in harmful residue in soil and water. Consequently, STR exists in biotic- and abiotic-counterpart of the environment and poses potential toxicity and risk due to its bioaccumulation and biomagnification properties. Sustainable remediation of STR from wastewater requires selective, minimal, low-cost, regenerable, and reusable materials as adsorbents. In this study, magnetic-halloysite incorporated polymer composite beads (SPHM) were synthesized and used for the efficient clean-up of toxic STR from wastewater. SPHM has a mesoporous structure with an abundance of oxygen-containing functional groups and exhibits a synergistic STR clean up performance (q_m = 235.71 ± 13.98 mg/g). Sorption and interfacial studies revealed that diffusion, hydrophobic and ionic interactions, including electrostatic interaction, are involved in STR remediation. Electrostatic interaction plays a vital role alongside the physical sorption mechanism due to the presence of hydroxyl and carboxyl groups induced from poly (vinyl alcohol) and sodium alginate. Moreover, X-ray photoelectron spectroscopy (XPS) and Time-of-flight secondary ion mass spectrometry (ToF-SIMS) analyses confirm the involvement of opposing charged groups of SPHM and STR in adsorption. SPHM can be magnetically separated in just 20 s and is regenerable and reusable up to 10 times, with outstanding performance and stability. The sorption process requires only a minimal amount of SPHM, i.e., 0.5 g/L for STR clean-up. Even the natural surface water composition did not affect its performance. Hence, natural nanoclay-based, biocompatible and low-cost SPHM has a great potential for the sustainable remediation of streptomycin and other similar antibiotics from wastewater.

Several Telluric Electric Frequency Selection Method (TEFSM) geophysical equipment is now available for groundwater exploration. However, case studies on its application in different hydrogeological settings are limited. This study investigates the TEFSM geophysical approach's application to identify groundwater potential sites for drilling production boreholes in a dolomite aquifer in South Africa. Field tests comprised geophysical surveys using the TEFSM approach to collect vertical and horizontal electrical potential difference profile data from four sites. Evaluation of the potential difference profile data before borehole drilling indicated that two sites had groundwater potential. Two sites were therefore prepared for drilling. Corroboration of the survey data and drilling lithology show that the TEFSM investigated up to 230 m depth and delineated the thickness of the dolomite aquifer from 170 m to 210 m. The dolomite aquifer was delineated based on low EPD contrast ranging from 0.042 to 0.083 mV. The ability of the TEFSM to delineate the dolomite aquifer at a depth of 170–210 m highlights the technical capability of the approach in exploring deeper aquifers that are important to meet the rising demand for freshwater. More research is necessary to establish the EPD ranges of aquifer lithology in different hydrogeological settings. It will assist in the interpretation of the data by field practitioners to optimise the application of this TEFSM technology in groundwater investigations.