Shallow Samples Research Articles

Cation exchange and leakage as dominant processes in controlling salinity and strontium in sandy and argillaceous coastal aquifer: Insights from hydrochemistry and multi-isotopes

Coastal groundwater is crucial for supporting ecosystems and meeting the water needs of coastal communities. However, over-exploitation of groundwater resources, including fresh water and deep brine, leads to groundwater depletion and exacerbates saline intrusion, posing significant challenges to sustainable development. This study focuses on the south bank of Laizhou Bay, a typical area threatened by saline intrusion due to the salt industry’s extraction of deep brine and over-exploitation of fresh groundwater. To assess the impact on salinization processes, we employed hydrochemistry and multi-isotope techniques to study strontium (Sr) distribution and salinization in coastal groundwater, unraveling their origins and explaining hydrochemical processes. The hydrochemical analysis revealed that evaporite dissolution primarily contributes to salinity, especially in deep brine and saline water (TDS > 30 g/L). The relationship between 87Sr/86Sr and chlor-alkali index (CAI) and saturation index (SI) indicated distinct sources of Sr. In fresh and brackish water (<10 g/L), Sr originates from mineral weathering and dissolution (SIs of albite and calcite increase with salinity), while in deep brine and saline water, Sr is influenced by cation exchange (with CAI-Ⅰ and CAI-Ⅱ greater than 0). Additionally, the interplay of anthropogenic input (nitrate), Sr, and EC highlights the differential anthropogenic impact on shallow groundwater, emphasizing the relatively closed environment of deep brine. Multi-isotope analysis showed that the average 87Sr/86Sr of shallow groundwater samples in the cone depression is 0.7112, between that of upstream surface water and shallow groundwater (0.7119) and deep brine and saline water (0.7101), indicating groundwater extraction induces deep brine leakage into shallow groundwater, elevating salinity and Sr concentrations. This poses a direct threat to local water security, including irrigation suitability and health risks of drinking water.In conclusion, we categorized the relationships between 87Sr/86Sr and Sr under different hydrochemical processes into different end-members based on their origins. This offers valuable insights in comparable regions for identifying groundwater salinization and saline intrusion, and the use of Sr and its isotopes can also help trace cation exchange and deep brine leakage in coastal aquifers.

Behavior of helium diffusion sinks in apatite: Evidence from continuous ramped heating analysis of borehole and well-characterized samples

Diffusion sinks have been proposed to explain the complex high-temperature 4He release often seen in Continuous Ramped Heating (CRH) analysis of apatites, which often correlates with over-dispersed and anomalously old (U-Th)/He ages. In this work, we first conducted CRH experiments with various ramping rates and cycled CRH experiments that confirm that the high-temperature 4He release from diffusion sinks is systematically temperature sensitive at laboratory time scales. We then analyzed apatite grains from the KTB borehole (German Continental Deep Drilling program) that have well-constrained thermal histories to test whether different thermal histories could alter the trapping of 4He at geologic time scales. The KTB samples show large intra-sample single-grain age dispersion, with most ages being older than predictions from a 4He radiation-damage diffusion model RDAAM. Individual grains from shallower depths show complex 4He outgassing behaviors, including the expected low-temperature volume-diffusion loss, sudden release spikes, and a higher- temperature-dependent component. Grains from the current partial retention zone and greater depths retain considerable helium and exhibit exclusively complex outgassing behavior dominated by high-temperature release in the laboratory. KTB samples show a systematic difference with depth in the proportion of low- and high-temperature gas-release gas components. Deeper samples, having long open-system thermal histories, contain a greater proportion of 4He that appears to have been trapped compared to the simpler volume-diffusion behavior exhibited by shallower samples that experienced a simpler monotonic cooling history. While greatly reduced, the high-temperature component is still present in the highest-temperature samples analyzed, well hotter than the partial retention zone. These observations confirm that in apatite trapping and release of helium from sinks is temperature dependent at geological time scales as well. This supports the suggestion that additional thermal-history information from apatites might be obtained using 4He/3He analysis, with laboratory release of 3He providing information about trap distribution and kinetics and 4He providing information about the geologic thermal history.

Fine-grained Coverage-based Fuzzing

Fuzzing is a popular software testing method that discovers bugs by massively feeding target applications with automatically generated inputs. Many state-of-the-art fuzzers use branch coverage as a feedback metric to guide the fuzzing process. The fuzzer retains inputs for further mutation only if branch coverage is increased. However, branch coverage only provides a shallow sampling of program behaviors and hence may discard interesting inputs to mutate. This work aims to take advantage of the large body of research in defining finer-grained code coverage metrics (such as control-flow, data-flow, or mutation coverage) and to evaluate how fuzzing performance is impacted when using these metrics to select interesting inputs for mutation. We propose to make branch coverage-based fuzzers support most fine-grained coverage metrics out of the box (i.e., without changing fuzzer internals). We achieve this by making the test objectives defined by these metrics (such as conditions to activate or mutants to kill) explicit as new branches in the target program. Fuzzing such a modified target is then equivalent to fuzzing the original target, but the fuzzer will also retain inputs covering the additional metric objectives for mutation. In addition, all the fuzzer mechanisms to penetrate hard-to-cover branches will help in covering the additional metric objectives. We use this approach to evaluate the impact of supporting two fine-grained coverage metrics (multiple condition coverage and weak mutation) over the performance of two state-of-the-art fuzzers (AFL++ and QSYM) with the standard LAVA-M and MAGMA benchmarks. This evaluation suggests that our mechanism for runtime fuzzer guidance, where the fuzzed code is instrumented with additional branches, is effective and could be leveraged to encode guidance from human users or static analyzers. Our results also show that the impact of fine-grained metrics over fuzzing performance is hard to predict before fuzzing and most of the time either neutral or negative. As a consequence, we do not recommend using them to guide fuzzers, except maybe in some possibly favorable circumstances yet to be investigated, like for limited parts of the code or to complement classical fuzzing campaigns.

Evaluation of the hillslope fine-scale morphology under forest cover with pit-mound topography - Integration of geomorphometry, geophysical methods, and soil features

Forested hillslopes are zones of specific surface hydrology and geomorphic activity regimes. Their distinct properties, namely terrain microrelief (<10 m in diameter and height), are often a result of past disturbances that control forest stand conditions, soil formation processes, and superficial processes. A clear bioindicator of the past forest disturbance is pit-mound topography, which, however, is challenging to study because of its complexity and relatively small sizes of individual forms (usually <5 m in diameter). The present study analyzed the spatial representation, geomorphometric, and geophysical evaluation of the rare pit-mound topography in the Karkonosze Mountains National Park, SW Poland, Central Europe. For this task, two digital terrain models (DTMs) have been considered and were based on different quality point clouds collected during airborne and terrestrial laser scanning (ALS and TLS, respectively). The first data allowed the production of the DTM in 1 × 1 m spatial resolution, while the second data offered the DTM in 0.025 × 0.025 m resolution. Various geomorphometric derivatives (Terrain Ruggedness Index, Geomorphons, Topographic Wetness Index, Valley Depth, and Negative Openness) were applied and compared based on these models. In the further part of the study, we applied electrical resistivity tomography (ERT) and electromagnetic induction (EMI), assisted by shallow soil sampling and analyses to support the interpretation of geophysical models.Our TLS-based DTM offered higher-quality models and a better representation of pit-mound topography. The high-quality TLS-based DTM elevation model can support close-to-reality hydrological and geomorphic modeling. The geophysical investigation allowed us to isolate a critical difference between treethrow pits and mounds better represented by ERT models than shallow EMI models. The differences were partly supported by soil properties, namely lower electrical resistivity in treethrow pits were related to higher moisture conditions, organic matter, organic carbon, and silt content in pits. As a general property, pit-mound topography resulting from tree uprooting adds to the complexity of forested hillslope hydrology and geomorphic activity. The surficial heterogeneity in hillslope topography was also evident in soil properties with sharp changes in short distances between treethrow mounds and pits.

Sources of per- and polyfluoroalkyl substances in an arid, urban, wastewater-dominated watershed

Per- and polyfluoroalkyl substances (PFAS) enter surface waters from various sources such as wastewater treatment plants, fire-fighting sites, and PFAS-producing and PFAS-using industries. The Las Vegas Wash in Southern Nevada of the United States (U.S.) conveys wastewater effluent from the Las Vegas metropolitan area to Lake Mead, a drinking water source for millions of people in the U.S. Southwest. PFAS have previously been detected in the Las Vegas Wash, but PFAS sources were not identified. In this study, upstream wash tributaries, wastewater treatment effluents, and shallow groundwater wells were sampled in multiple campaigns during dry-weather conditions to investigate possible PFAS sources. Out of 19 PFAS, two short-chain PFAS—perfluoropentanoic acid (48 % of the total molar concentration) and perfluorohexanoic acid (32 %)—comprised the majority of PFAS loading measured in the Las Vegas Wash, followed by perfluorooctanoic acid (9 %). On a mass loading basis, the majority of total measured PFAS (approximately 90 %) and at least 48 % of each specific PFAS in the Las Vegas Wash likely entered via municipal wastewater effluents, of which the main source was likely residential wastewater. One of the drainage areas with a major civilian airport was identified as a potential source of relatively enriched perfluorosulfonic acids to a small wash tributary and shallow groundwater samples. Nonetheless, that tributary contributed at most 15 % of any specific PFAS to the mainstem of the Las Vegas Wash. Total PFAS concentrations were relatively low for the small tributary associated with an urban smaller airport and the lack of flow in the tributary channel immediately downgradient of an Air Force base indicates the smaller airport and base were unlikely significant PFAS sources to the Las Vegas Wash. Overall, this study demonstrated effective PFAS source investigation methodology and the importance of wastewater effluent as a PFAS environmental pathway.

Using low volume eDNA methods to sample pelagic marine animal assemblages.

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380-1800 mL) collected at depths of 0-2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

Shallow groundwater quality and health risk assessment of fluoride and arsenic in Northwestern Jiangsu Province, China

Assessing groundwater quality is critical to regional water resource conservation and human health safety, especially in areas with co-existence of toxic constituents fluoride (F−) and arsenic (As). In this study, fourteen groundwater samples were collected in Feng County, Northwestern Jiangsu Province to identify dominant contaminants and their spatial distribution and health risk. The composition and variation characteristics of major ions (K+, Na+, Ca2+, Mg2+, Cl−, SO42−, HCO3−, and NO3−) and trace elements (F−, As, and Mn) were analyzed. The hydrochemical results revealed that high F− groundwater was mainly distributed in the northern areas whereas As-riched groundwater was primarily distributed in southern areas. Notably, over 85.7% and 21.4% of the shallow groundwater samples exceeded the drinking water quality standard of 1.5 mg/L for F− and 10 µg/L for As, respectively. Based on the water quality index (WQI) appraisal result, 71.4% of the groundwater in the study area is classified as “poor”, and thus unsuitable for drinking directly. We assessed the human non-carcinogenic health risk of F− (HQFluoride) and As (HQArsenic) and the carcinogenic health risk of As (CRArsenic). The calculated hazard quotient (HQ) for F− indicated nearly all groundwater samples have an unacceptable risk (HQ > 1) for each age group. However, HQArsenic values revealed that 28.6%, 21.4%, 21.4%, and 21.4% of groundwater samples posed potential non-carcinogenic health risks for infants, children, females, and males, respectively. The calculated results of CRArsenic showed that 0%, 21.4%, 28.6%, and 28.6% of groundwater samples posed unacceptable health risks (CR > 1.0 × 10−4) to infants, children, females, and males, respectively. The groundwater irrigation suitability assessment results showed that 21.4% of samples were doubtful to unsuitable for irrigation, and 85.7% owed magnesium hazards. The findings of this study will assist policymakers in formulating proper remedial policies and mitigation strategies to ensure the safety of drinking and irrigation water.

Investigation into hydraulic fracture propagation behavior during temporary plugging and diverting fracturing in deep coal seam

In this study, we conducted indoor temporary plugging and diverting fracturing (TPDF) experiments on samples of natural deep and shallow coal seams using a small-scale true triaxial fracturing simulation system. By integrating high-precision CT scanning technology and crack reconstruction techniques, and relying on the quantitative characterization of the crack complexity coefficient, we investigated the differences in internal structures between deep and shallow coal seam samples and the variations in the expansion of TPDF cracks. Furthermore, the study primarily focused on exploring the influence of temporary plugging agent (TPA) parameters (quantity and particle size) on the expansion patterns of TPDF cracks in deep coal seam coal-rock samples. The experimental results reveal that in shallow coal samples, artificially induced fractures are notably longer and extend to various surfaces of the samples. Conversely, in deep coal samples, the expansion of artificially induced fractures is influenced by well-developed cleavage and cleats. The crack complexity coefficient of artificial fractures in deep coal samples is 1.54 higher than that in shallow coal samples, with an increased crack width of 98 μm. However, the expansion distance of the fractures is shorter and does not extend to the S3 and S6 surfaces. Increasing the dosage of the TPA is advantageous for inducing frequent redirection of fractures and communication with previously untouched areas. When the dosage of the TPA is increased from 30 g/L to 60 g/L, the expansion distance of artificial fractures significantly increases, extending to various surfaces of the samples. The crack complexity coefficient increases by 1.1, and the crack width enlarges by 84 μm. Appropriate particle sizes of the TPA can effectively form seals. However, small particle sizes (200/400 mesh) struggle to seal initial fractures, while large particle sizes (10/20 mesh) can lead to excessive wellhead blockage, causing rapid shut-in pressure, destructive fracturing in deep coal samples, and the generation of a large amount of coal fines. This study holds significant guidance for the optimal selection of process parameters in the temporary plugging hydraulic fracturing of deep coal rock.

Spatio-temporal distribution and carcinogenic assessment due to potentially toxic elements in aquifer water of Ganga and Yamuna River basins, India

The spatial and temporal dispersion of potentially toxic elements (PTE) are evaluated for shallow groundwater samples of Delhi and Patna considering PTE pollution index (HPIPTE), evaluation index (HEIPTE), cancerous and non-cancerous effects, hazard coefficient index (HQI) and overall hazard index (HInc) considering fuzzy entropy weights and source identification is done through PCA. The evaluation of groundwater indicators as pH, TDS and PTE (As, Ni, Mn, B, Pb, Fe and Zn) indicated 6.67% and 3.33% of sampling stations exceeded the threshold limit, HPIPTE > 100 for arid and humid periods of Delhi, whereas 3.33% and 13.33% of sampling stations come under high contamination in the banks of the Ganga in arid and humid seasons respectively. The hazard coefficient index (HQI), only 18% and 21% of the specimens were in the grade of low pollution in both the seasons of Delhi and Patna. The trend of HQI is followed as, HQIAs>HQIPb>HQIFe>HQIMn>HQINi≥HQIZn>HQIB in Delhi region for both Young and elders in both seasons, while the sequence is followed as, HQIAs>HQIPb>HQIFe>HQIMn>HQIZn>HQINi>HQIB in the Ganga River basin area for elders and Young. The index (HInc) found 4 Young & 3 elders and 4 Young & 4 elders (Patna, arid and humid seasons) whereas 6 Young and 5 elders (Delhi, arid and humid seasons) affected as per the index per 1000 cases reported. The PC1 (As, Fe, Mn, and Pb) and PC2 (pH, As, Fe, and Pb) extracted from PCA pointed to the effects of evolution of contamination, hydrogeochemical reaction, disintegration of rocks, its dissolution, dispersion, and dilution in unconfined deep aquifers. Rapid depletion of groundwater table may cause the influx of As contamination in the shallow groundwater, whereas high Pb, Fe, Mn and Ni may be the reasons of nearby industries and improper waste disposal process. The findings and GIS mappings may put some light on the PTE over the Rivers which can help the local government and decision makers to formulate safe and protective bounds, to reduce the rate of contamination and to protect the water ecology and environmental system.

Irrigation impact on water quality and aquifer vulnerability in Kala Oya basin, Sri Lanka

The impact of precipitation and irrigation return flow on water quality and groundwater vulnerability was investigated in the Kala Oya basin, Sri Lanka using the Weighted Arithmetic Water Quality Index, DRASTIC Index, and isotope hydrology. Groundwater and surface water were analyzed for water quality parameters and stable isotopes (18O and 2H) in dry and wet seasons. In both seasons, neutral to alkaline water was observed. Electrical conductivity (EC) and major ions were higher in shallow (EC: 718.3 ± 323.8 μS/cm; Ca2+: 49.54 ± 32.99 mg/L) and deep groundwater (EC: 708.1 ± 321.5 μS/cm; Ca2+: 37.06 ± 11.21 mg/L) than in surface water (EC: 371.7 ± 154.4 μS/cm; Ca2+: 29.66 ± 11.64 mg/L), while similar values of EC and major ions were reported in both shallow and deep groundwater samples. Ca–Mg–HCO3 was the dominant groundwater type which was derived from silicate and carbonate rock weathering. Observations in the wet season revealed δ2H ranged from −47.97 to −16.71‰ and δ18O ranged from −7.56 to −2.87‰, while in the dry season, δ2H ranged from −44.90 to −14.06‰, and δ18O ranged from −7.69 to −2.08‰. The enriched δ18O and δ2H groundwater values were mainly the result of progressive evaporative concentration of the heavier isotopes before water infiltration and groundwater recharge. The solute concentrations were enriched in groundwater by agricultural irrigation returns and associated evaporation indicating the influence of irrigation return flow on groundwater. It is suggested that agricultural practices increase groundwater vulnerability, which recommends special attention to long-term groundwater quality and quantity monitoring, hydrological modelling, land-use planning, and the development of sustainable policies in the basin.

Hydrochemical Characteristics and Control Factors of Shallow Groundwater in Anqing Section of the Yangtze River Basin

Shallow groundwater is the main source of water for living and industrial and agricultural production in Anqing City, which is an important basic guarantee to maintain the sustainable development of the social economy and regional ecological environment. In order to further study the water chemical characteristics and controlling factors of shallow groundwater in Anqing City, 196 groups of shallow groundwater samples were collected. A Piper diagram graph, Gibbs chart, ion ratio, and mathematical statistics were comprehensively used to study the water chemical characteristics and controlling factors of groundwater in Anqing City, and the contribution of different sources to the water chemical components of groundwater was quantitatively evaluated. The results showed that the shallow groundwater in Anqing City was weakly alkaline, with pH values ranging from 5.84 to 8.38, with an average value of 7.21. The TDS ranged from 47 to 1 620 mg·L-1, with an average of 324.21 mg·L-1. HCO3- and Ca2+ were the main anions, and the water chemical type was HCO3-Ca type. The chemical components of groundwater were affected by rock weathering leaching, cation alternating adsorption, mineral dissolution and precipitation, and human activities. Ca2+, Mg2+, and HCO3- were mainly derived from the weathering dissolution of carbonate and silicate; Na+, Cl-, and SO42- were affected by industrial activities and domestic sewage discharge; and K+ and NO3- were affected by agricultural activities. The APCS-MLR receptor model analysis further revealed that the chemical components of groundwater were mainly geological factors, industrial factors, agricultural factors, and unknown sources, and their contribution rates were 45.35%, 14.19%, 25.38%, and 15.08%, respectively. Geological factors were important sources of hydrochemical components of shallow groundwater, and human activities aggravated the evolution of groundwater hydrochemistry.

Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm

Based on data on the shear wave speed and physical properties of the shallow sediment samples collected in the northwest South China Sea, the hyperparameter selection and contribution of the characteristic factors of the machine learning model for predicting the shear wave speed of seafloor sediments were studied using the eXtreme Gradient Boosting (XGBoost) algorithm. An XGBoost model for predicting the shear wave speed of seafloor sediments was established based on four physical parameters of the sediments: porosity (n), water content (w), density (ρ), and average grain size (MZ). The result reveals that: (1) The shear wave speed has a good correlation with n, w, ρ, and MZ, and their Pearson correlation coefficients are all above 0.75, indicating that they can be used as the suitable characteristic parameters for predicting the shear wave speed based on the XGBoost model; (2) When the number of weak learners (n_estimators) is 115 and the maximum depth of the tree (max_depth) is 6, the XGBoost model has a very high goodness of fit (R2) of the validation data of 0.914, the very low mean absolute error (MAE) and mean absolute percentage error (MAPE) of the predicted shear wave speed are 3.366 m/s and 9.90%, respectively; (3) Compared with grain-shearing (GS) model and single- and dual-parameter regression equation prediction models, the XGBoost model for the shear wave speed of seafloor sediments has higher fitting goodness and lower prediction error.

Machine learning of the chemical elements for enhanced interpretation of depositional environments: Upper Jurassic strata case study in central Saudi Arabia

To explore how machine learning (ML) techniques can enhance the interpretation of depositional environments using chemical elemental data, this study analyzes data from 156 shallow marine strata samples. Several advanced machine learning (ML) techniques were integrated to predict lithofacies and stratigraphic units of shallow marine carbonate strata, focusing on the Arab-D reservoir equivalent outcrops in Central Saudi Arabia. Utilizing a detailed geochemical dataset comprising major, trace, and rare earth elements, we aimed to determine the feasibility of using chemical elemental data in sedimentary geology for predictive modeling. The studied strata are categorized into two lithological units based on depositional settings: one unit comprises rocks that dominantly deposited below the storm wave base with a single lithofacies association, whereas the other includes rocks dominantly deposited above the storm wave base, and consists of two lithofacies associations. The study demonstrates the efficacy of ML algorithms in distinguishing these two lithological units, with a minimum prediction accuracy of 76%. Four ML techniques, including K-nearest neighbors (KNN); random forest classifier (RFC); gradient boosting classifier (GBC); and multi-layer perceptron neural network (MLP-NN) were used, two of them (RFC and GBC) achieved 89% and 92% prediction accuracy. However, a slightly poorer performance was observed in predicting fine-scale lithofacies associations of these lithological units, especially for the lithofacies association representing a transitional interval between the two lithofacies units. Expanding the scope of the study, we tested the ML models against geochemically similar strata from the Oligocene shallow marine reef carbonates. These strata are globally comparable and provide an external validation for the predictive models developed from the Saudi Arabian dataset. GBC and RFC maintained a higher accuracy level than KNN and MLP, demonstrating their robustness and transferability across diverse geological settings. Based on these results, the study underscores the significance of specific oxides and elements as distinctive geochemical markers, elucidating the environmental conditions of the depositional environments and their deposits. This research advances the application of ML in interpreting the depositional environments of shallow marine strata using elemental data, as the majority of the existing researches focus on employing unsupervised machine learning for cluster analysis.

Hydrogeochemical characterization, quality assessment, and potential nitrate health risk of shallow groundwater in Dongwen River Basin, North China.

Assessing groundwater geochemical formation processes and pollution circumstances is significant for sustainable watershed management. In the present study, 58 shallow groundwater samples were taken from the Dongwen River Basin (DRB) to comprehensively assess the hydrochemical sources, groundwater quality status, and potential risks of NO3- to human health. Based on the Box and Whisker plot, the cation's concentration followed the order of Ca2+ > Mg2+ > Na+ > K+, while anions' mean levels were HCO3- > SO42- > NO3- > Cl-. The NO3- level in groundwater samples fluctuated between 4.2 and 301.3mg/L, with 67.2% of samples beyond the World Health Organization (WHO) criteria (50mg/L) for drinking. The Piper diagram indicated the hydrochemical type of groundwater and surface water were characterized as Ca·Mg-HCO3 type. Combining ionic ratio analysis with principal component analysis (PCA) results, agricultural activities contributed a significant effect on groundwater NO3-, with soil nitrogen input and manure/sewage inputs also potential sources. However, geogenic processes (e.g., carbonates and evaporite dissolution/precipitation) controlled other ion compositions in the study area. The groundwater samples with higher NO3- values were mainly found in river valley regions with intense anthropogenic activities. The entropy weight water quality index (EWQI) model identified that the groundwater quality rank ranged from excellent (70.7%) and good (25.9%) to medium (3.4%). However, the hazard quotient (HQ) used in the human health risk assessment (HHRA) model showed that above 91.38% of groundwater samples have a NO3- non-carcinogenic health risk for infants, 84.48% for children, 82.76% for females, and 72.41% for males. The findings of this study could provide a scientific basis for the rational development and usage of groundwater resources as well as for the preservation of the inhabitants' health in DRB.

Hydrochemical Characteristics, Controlling Factors and Strontium Enrichment Sources of Groundwater in the Northwest Plain of Shandong Province, China

To elucidate the hydrochemical characteristics, controlling factors, sources and mechanisms of strontium ion enrichment in groundwater in the northwest plain of Shandong Province, China, 88 groundwater samples were collected, including 51 shallow pore groundwater samples, 29 deep pore groundwater samples and 8 karst groundwater samples. The hydrochemical characteristics of the different types of groundwater were quite different. The karst groundwater samples were all fresh water with a single hydrochemical type, either HCO3-Ca or HCO3-Ca·Mg. The deep pore groundwater samples were mainly brackish water, and the shallow pore groundwater samples were brackish water–salt water, which has complex hydrochemical types. The hydrochemical characteristics of all the types of groundwater were controlled by mineral dissolution and active positive cation exchange. In shallow pore groundwater, deep pore groundwater and karst groundwater, the dissolution of silicate, evaporite and carbonate minerals dominated the hydrogeochemical process. The strontium in groundwater was derived from the dissolution of minerals with strontium isomorphism. The average contents of strontium in shallow, deep and karst groundwater were 1.59 mg/L, 0.58 mg/L and 0.50 mg/L, respectively. The strontium in shallow pore groundwater was mainly derived from the enrichment of groundwater runoff, and its sources are abundant, with silicic rock being the main source. The deep pore groundwater mainly derived from the evaporative minerals containing strontium, and the karst water mainly derived from carbonate rock dissolution with similar characteristics.

Chemical Characteristics of Shallow Groundwater in the Yellow River Diversion Area of Henan Province and Identification of Main Control Pollution Sources

The northern plain of Henan in the lower reaches of the Yellow River is an area where the Yellow River is frequently diverted. The shallow groundwater quality in this area is poor， and many types of components have been found to be exceeding the limit value； however， the contribution of various environmental factors to water quality needs to be further quantified. In order to clarify the genesis of water quality of shallow groundwater in the study area， 330 groups of shallow groundwater samples were collected via a regional water quality survey. The evolution of shallow groundwater quality in the Yellow River diversion area of northern Henan was revealed using the principal component-absolute principal component score-multiple linear regression （PCA-APCS-MLR） model. The results showed that the components with a shallow groundwater excess rate greater than 10% in descending order were manganese， iron， total hardness， total dissolved solids， sodium， fluoride， arsenic， chloride ions， sulfate， and ammonium. In particular， the excess rate of manganese reached 76%. The four factors of dissolution enrichment， native origin of soil， redox conditions， and agricultural activities were identified as the main reasons for poor groundwater quality， which accounted for 71.24% of the cumulative interpretation rate of variance. In addition， the recharge from the surface water also influenced the groundwater quality. The effects of dissolution between the water and aquifer matrix and redox condition in the aquifer of the Yellow River dried-riverway like Xinxiang were significantly enhanced， resulting in the increasing concentration of iron， arsenic， total hardness， TDS， and other components in groundwater. Fluoride enrichment was caused by dissolution enrichment， the origin of the soil， and lateral replenishment of the Yellow River. Groundwater with high manganese concentration was widely affected by the soil matrix. Nitrate pollution of the groundwater was caused by the extensive use of chemical fertilizers in agricultural activities in individual areas.

Statistical characteristics of convective and stratiform precipitation during the rainy season over South China based on GPM-DPR observations

South China is one of the wettest regions in the world, and is prone to precipitation-related disasters. The GPM-DPR product is utilized in this study to investigate the vertical structure and drop size distribution (DSD) characteristics of different precipitation types, i.e., stratiform precipitation (SP) and convective precipitation (CP) in South China. The precipitation frequency and accumulation in South China are dominated by SP and deep CP, respectively. Shallow CP has comparable occurrence ratio to deep CP, but the mean intensity is much lower. As such, it contributes <5% to the total rainfall. Vertical features differ among precipitation types and intensities. Higher storm top altitude (STA) is roughly related to more intense precipitation, especially for CPs. As surface PR increases in deep CP, the contribution of increase of PR (ΔPR) in liquid-phase region to total PR also increases, from approximately 10% for 4 mm/h to 55% for 100 mm/h. The intensity of shallow CP is generally low, but ΔPR in the liquid-phase region is significant. For SP and shallow CP, higher precipitation intensity is often caused by higher hydrometer concentration. Differently, for deep CP with PR >15 mm/h, both the increases in hydrometer size and concentration contribute to the increase in PR. The collision-coalescence process is dominant in the low-level layers in SP without bright band and CP, and approximately four fifth of shallow CP samples are influenced by collision-coalescence process. Compared with inland mountainous region, collision-coalescence process plays more important role in intense precipitation in coastal region. The results of this study indicate that it is important to consider the vertical evolution and DSD characteristics of different precipitation types for improving the accuracy of near surface quantitative precipitation estimate.

Antibiotic resistance profile in sediments and bacterial isolates from a human-impacted mangrove from Bahía Magdalena, Mexico

Abstract Antibiotic-resistant bacteria (ARB) and antibiotic-resistance genes (ARGs) in the environment are considered emerging contaminants. One of the ecosystems that can harbor resistant bacteria and genes is mangroves. This report aims to assess ARB and ARG's presence at two mangrove locations in Bahia Magdalena, Mexico. Bacterial isolates were selected based on their phenotypic profiles of antibiotic resistance. DNA from mangrove sediments and bacterial isolates was tested for int1 and antibiotic resistance genes by final point PCR. From 90 ARB isolates, the phenotypic profile showed resistance to ciprofloxacin (90%), cefotaxime (85.7%), and ampicillin (78.6%), while the beta-lactamase gene (blaCTX-M) was present in 72.9% of the isolates. Antibiotic resistance genes identified in sediments were found even at 30–50 cm depth, but the integron Class gen (int1) was found mainly in shallow samples. Principal component analysis showed a close relationship between the integron gene, vancomycin, and sulfonamides resistance genes. No correlation was found between the phenotypic and genotypic profiles of the bacterial isolates. Also, no differences were observed between the two mangrove ecosystems studied. The impact of anthropogenic activities was equally significant on both sites. The role of mangrove ecosystems in the dispersion of antibiotic resistance needs to be further explored.

Integrating multivariate hydrogeochemical analysis with human health risk assessment: An inverse geochemical and statistical modeling approach

Chandigarh, an urban center meticulously planned in India, partially relies on groundwater for its water supply. However, rapid urbanization, geological heterogeneity, and anthropogenic actions have elevated the significance of ensuring water quality. This research employs advanced methodologies including inverse geochemical modeling through PHREEQC, multivariate statistics, and the Nemerow Pollution Index (NPI) to discern the governing factors influencing water quality. Furthermore, a human health risk assessment evaluates the potential non-carcinogenic impacts of NO3− and F− on human health. Results indicate during PRM (pre-monsoon), 90 % of shallow aquifer samples exceed an NPI value of 1.0, denoting water impurities. In POM (post-monsoon), 70 % of both shallow and deep groundwater samples surpass this threshold. Approximately 70 % of PRM deep groundwater samples and 75 % in POM exhibit “hard water” characteristics. Hydrogeochemistry is primarily influenced by rock-water interactions, corroborated by Gibb's diagram and negative values of chloro-alkaline indices (CAI-I and CAI-II) indicating cation exchange reactions. Piper's plot illustrates a prevailing Ca-Mg-HCO3 hydrochemical facies, with oversaturation of calcite, dolomite, aragonite, and fluorite at varying depths. Saturation indices (SI) affirm calcite oversaturation, implying CaCO3 precipitation and CaF2− dissolution. Additionally, 33 % of PRM and 52.4 % of POM shallow groundwater samples indicate carbonate weathering's influence on mineral content. Principal Component Analysis (PCA) and Pearson's correlation demonstrate contributions from irrigation return flows and anthropogenic activities alongside geogenic factors, enriching Na+, SO42−, NO3−, and Cl− concentrations. The combined statistical and geochemical models offer a comprehensive insight into groundwater geochemistry which will help the policy makers and municipality to manage groundwater resources effectively in the area.

Mechanism and genesis of Sanmen Bay as a sink of Holocene Yangtze River sediment, Zhejiang Province, China

Introduction: The Holocene mud deposits that extend from the Yangtze River mouth to the Taiwan Strait along the Zhejiang–Fujian coast, East China Sea (ECS), have attracted considerable research attention. However, there is a lack of consensus regarding the redistribution flux of Yangtze River sediment after it enters the sea. There are many bays along the Zhejiang and Fujian coasts, but their role in the source–sink process of Yangtze River sediment is not well-documented owing to limited data.Methods: In this study, data from shallow seismic profiles, core samples, and surface sediment samples were analysed to assess the role of Sanmen Bay, the second largest bay in Zhejiang Province, in the source–sink process of Yangtze River sediments.Results: The results showed that Sanmen Bay is an important sink for Yangtze River sediments. The characteristics of the clay minerals indicate that the fine-grained sediments in Sanmen Bay are mainly derived from Yangtze River sediments. The thickness of Holocene deposits in Sanmen Bay ranges from 8.2 to 32.0 m, with an average of 23.4 m and a total sediment volume of 5.06 × 104 Mt, accounting for 1% of Yangtze River sediment in this time period. The Bayesian age-depth model based on borehole accelerator mass spectrometry (AMS) 14C dating shows that a high sedimentation rate occurred in the early and late Holocene but decreased significantly in the mid-Holocene, which is similar to that of the inner shelf of the East China Sea (ECS).Conclusion: The variation in the Holocene sedimentation rate in Sanmen Bay is related to the southward transport process and mechanism of Yangtze River sediments. The results of this study provide a basis for understanding the source–sink process of sediment in large rivers.