Hydrogeochemical Data Research Articles

Hydrogeochemical data from carbonate springs as an aid for delimiting catchment areas in the Rovte region, Central Slovenia

Study regionsThe Rovte region, Central Slovenia, is a rural region where karst spring waters are often used for drinking water consumption and irrigation. Study focusIn karst regions, water quickly reaches the subsurface through features ranging from thin fractures to large conduits; as such, this rapid flow leaves karst areas particularly vulnerable to pollutants. This range of permeability and frequently mixed lithologies means that catchment areas in karst regions are often difficult to determine. Here, we present a year-long dataset of hydrogeochemical monitoring of six karst springs and one river, alongside detailed geological data. The aim was to test if water geochemistry can be used to determine the geological units through which the waters flowed, and if this knowledge can help locate plausible catchment areas for springs in karst regions. New hydrological insights for the regionWe show that subtle differences in water geochemistry (including major ions, electrical conductivity, pH) and discharge rates permitted the identification of the geological units (including limestones, dolostones, marly limestones, and siliciclastics) through which the waters flowed. This led to significant modifications to the topographically-modeled catchment areas. We, therefore, advocate using water geochemistry to delineate realistic catchment areas in karst regions. Furthermore, our investigations identified trace metals, in particular Hg, which were above drinking water guideline values, under certain precursor meteorological conditions.

Characterization of Groundwater Geochemistry in an Esker Aquifer in Western Finland Based on Three Years of Monitoring Data

This study investigated the hydrogeochemistry of a shallow Quaternary sedimentary aquifer in an esker deposition in western Finland, where distinct spatial and temporal variability in groundwater hydrogeochemistry has been observed. Field investigation and hydrogeochemical data were obtained from autumn 2010 to autumn 2013. The data were analyzed using the multivariate statistical methods principal component analysis (PCA) and hierarchical cluster analysis (HCA), in conjunction with groundwater classification based on the main ionic composition. The stable isotope ratios of δ18O and δD were used to determine the origin of the groundwater and its connection to surface water bodies. The groundwater geochemistry is characterized by distinct redox zones caused by the influence of organic matter, pyrite oxidation, and preferential flow pathways due to different hydrogeological conditions. The groundwater is of the Ca-HCO3 type and locally of the Ca-HCO3-SO4 type, with low TDS, alkalinity, and pH, but elevated Fe and Mn concentrations, KMnO4 consumption, and, occasionally, Ni concentrations. The decomposition of organic matter adds CO2 to the groundwater, and in this study, the dissolution of CO2 was found to increase the pH and enhance the buffering capacity of the groundwater. The mobility of redox-sensitive elements and trace metals is controlled by pH and redox conditions, which are affected by the pumping rate, precipitation, and temperature. With the expected future increases in precipitation and temperature, the buffering capacity of the aquifer system will enhance the balance between alkalinity from bioactivity and acidity from recharge and pyrite oxidation.

Assessing groundwater quality in the northwestern coastal area of Sri Lanka using multivariate statistical techniques

The objective of the present study was to assess groundwater quality in the northwestern coastal region of Sri Lanka by analyzing hydrogeochemical data using multivariate techniques. The study examined the relationship between water quality and sources influencing groundwater quality and proposed useful statistical tools for water resource management. Descriptive, comparative, correlation, factor analysis (FA), and discriminant analysis (DA) were among the techniques used. The water quality in terms of electrical conductivity (EC), total dissolved solids (TDS), and dissolved nitrate and phosphate concentrations of the northwestern coastal area, where different aquifer conditions prevailed, were compared, and differences in the mean concentrations of the above parameters were identified. The study also employed ridge regression and support vector machines (SVM) to predict nitrate levels and validate the results using a 70:30 train/test split. The analysis found that the mean concentrations of EC, TDS, and HCO3- are higher in the sandy aquifer area, while Fe2+ and PO43- are higher in the regolith aquifer area. EC, TDS, PO43-, and HCO3- in the hard-rock aquifer area exceed permissible limits. Factor analysis identified four factors contributing to pollution, and a linear discriminant model classified all observations with 99.9% accuracy. The water quality index for Kalpitiya, Vanathavillu, and Katana-Negombo areas was 68.1, 99.2, and 287.9, respectively, while the World Health Organization (WHO) cutoff was 50. The use of multivariate statistical techniques demonstrated the value of analyzing hydrogeochemical data to gain valuable insights into the complex interplay of factors affecting groundwater quality. The SVM model, using a linear kernel, was identified as the best model to predict nitrate levels. A combination of statistical analyses reveals that, with the exclusion of a few wells, the groundwater in the study area is polluted and inappropriate for human consumption or culinary purposes. Nonetheless, the inhabitants persist in utilizing it as their primary source of drinking water. This study reveals the combination of statistical analyses is useful for the management of groundwater resources.

Toxicological risk assessment using spring water quality indices in plateaus of Giresun Province/Türkiye: a holistic hydrogeochemical data analysis

Water scarcity is a growing concern due to rapid urbanization and population growth. This study assesses spring water quality at 20 stations in Giresun province, Türkiye, focusing on potentially toxic elements and physicochemical parameters. The Water Quality Index rated most samples as "excellent" during the rainy season and "good" during the dry season, except at stations 4 (40° 35′ 12″ North/38° 26′ 34″ East) and 19 (40° 44′ 28″ North/38° 06′ 53″ West), indicating "poor" quality. Mean macro-element concentrations (mg/L) were: Ca (34.27), Na (10.36), Mg (8.26), and K (1.48). Mean trace element values (μg/L) were: Al (1093), Zn (110.54), Fe (67.45), Mn (23.03), Cu (9.79), As (3.75), Ni (3.00), Cr (2.84), Pb (2.70), Co (1.93), and Cd (0.76). Health risk assessments showed minimal non-carcinogenic risks, while carcinogenic risk from arsenic slightly exceeded safe limits (CR = 1.75E−04). Higher arsenic concentrations during the rainy season were due to increased recharge, arsenic-laden surface runoff, and human activities. Statistical analyses (PCA, PCC, HCA) suggested that metals and physico-chemical parameters originated from lithogenic, anthropogenic, or mixed sources. Regular monitoring of spring water is recommended to mitigate potential public health risks from waterborne contaminants.

Isotope Hydrology and Hydrogeochemical Signatures in the Lake Malawi Basin: A Multi-Tracer Approach for Groundwater Resource Conceptualisation

Reliance on groundwater is outpacing natural replenishment, a growing imbalance that requires detailed and multi-faceted water resource understanding. This study integrated water-stable isotopes and hydrogeochemical species to examine hydrogeochemical processes during groundwater recharge and evolution in the Lake Malawi basin aquifer systems. The findings provide insights into groundwater source provenance, with non-evaporated modern precipitation dominating recharge inputs. Grouped hydrochemical facies exhibit five groundwater water types, prominently featuring Ca-Mg-HCO3. Modelled hydrogeochemical data underscore dominant silicate dissolution reactions with the likely precipitation of calcite and/or high-Mg dolomitic carbonate constrained by ion exchange. Isotope hydrology reinforces water resource system conceptualisation. Coupled isotopic-hydrogeochemical lines of evidence reveal a discernible spatial-seasonal inhomogeneity in groundwater chemical character, revealing a complex interplay of meteoric water input, evaporative effects, recharge processes, and mixing dynamics. Findings show that measurable nitrate across Malawi highlights a widespread human impact on groundwater quality and an urgent need for detailed modelling to predict future trends of nitrate in groundwater with respect to extensive fertiliser use and an ever-increasing number of pit latrines and septic systems arising from rapid population growth. This study not only refined the Lake Malawi basin aquifer systems conceptualisation but also provided isotopic evidence of groundwater and lake water mixing. This study sets a base for groundwater management and policy decisions in support of the Integrated Water Resources Management principles and Sustainable Development Goal 6 objectives for groundwater sustainability in the transboundary Lake Malawi basin.

AOSMA-MLP: A Novel Method for Hybrid Metaheuristics Artificial Neural Networks and a New Approach for Prediction of Geothermal Reservoir Temperature

To ascertain the optimal and most efficient reservoir temperature of a geothermal source, long-term field studies and analyses utilizing specialized devices are essential. Although these requirements increase project costs and induce delays, utilizing machine learning techniques based on hydrogeochemical data can minimize losses by accurately predicting reservoir temperatures. In recent years, applying hybrid methods to real-world challenges has become increasingly prevalent over traditional machine learning methodologies. This study introduces a novel machine learning approach, named AOSMA-MLP, integrating the adaptive opposition slime mould algorithm (AOSMA) and multilayer perceptron (MLP) techniques, specifically designed for predicting the reservoir temperature of geothermal resources. Additionally, this work compares the basic artificial neural network and widely recognized algorithms in the literature, such as the whale optimization algorithm, ant lion algorithm, and SMA, under equal conditions using various evaluation regression metrics. The results demonstrated that AOSMA-MLP outperforms basic MLP and other metaheuristic-based MLPs, with the AOSMA-trained MLP achieving the highest performance, indicated by an R2 value of 0.8514. The proposed AOSMA-MLP approach shows significant potential for yielding effective outcomes in various regression problems.

Groundwater hydrochemistry, source identification and health assessment based on self-organizing map in an intensive mining area in Shanxi, China

The Changzhi Basin in Shanxi is renowned for its extensive mining activities. It's crucial to comprehend the spatial distribution and geochemical factors influencing its water quality to uphold water security and safeguard the ecosystem. However, the complexity inherent in hydrogeochemical data presents challenges for linear data analysis methods. This study utilizes a combined approach of self-organizing maps (SOM) and K-means clustering to investigate the hydrogeochemical sources of shallow groundwater in the Changzhi Basin and the associated human health risks. The results showed that the groundwater chemical characteristics were categorized into 48 neurons grouped into six clusters (C1–C6) representing different groundwater types with different contamination characteristics. C1, C3, and C5 represent uncontaminated or minimally contaminated groundwater (Ca–HCO3 type), while C2 signifies mixed-contaminated groundwater (HCO3–Ca type, Mixed Cl–Mg–Ca type, and CaSO4 type). C4 samples exhibit impacts from agricultural activities (Mixed Cl–Mg–Ca), and C6 reflects high Ca and NO3− groundwater. Anthropogenic activities, especially agriculture, have resulted in elevated NO3− levels in shallow groundwater. Notably, heightened non-carcinogenic risks linked to NO3−, Pb, F−, and Mn exposure through drinking water, particularly impacting children, warrant significant attention. This research contributes valuable insights into sustainable groundwater resource development, pollution mitigation strategies, and effective ecosystem protection within intensive mining regions like the Changzhi Basin. It serves as a vital reference for similar areas worldwide, offering guidance for groundwater management, pollution prevention, and control.

Hydrogeochemical conditions of submarine and terrestrial karst sulfur springs in the Northern Adriatic

Submarine springs near Izola, in the Northern Adriatic Sea, appear in funnel-shaped depressions and smell strongly of sulfur. Along the Mediterranean coast there are many submarine karst springs containing brackish or fresh water, but submarine sulfur springs are not particularly common. Three submarine sulfur springs and one terrestrial sulfur spring were investigated to better understand the water properties, water–rock interaction within the aquifer, and to explore the origin of the spring water. Groundwater and seawater samples were also collected for comparison. Based on the geological setting, physicochemical parameters, hydrogeochemical data, and stable isotope data (δ18O, δ2H, δ13CDIC, δ34SSO4, δ18OSO4), we can affirm that (1) the large concentration of seawater in the submarine springs samples is due to sampling challenges; (2) springs recharge from precipitation where confined karst aquifers outcrop; (3) deep water circulation is indicated; (4) redox conditions can provide a suitable environment for bacterial reduction of the marine or organic sulfate to the odorous H2S; (5) geological data suggests that the coals beneath the alveolinic-nummulitic limestones are the source of sulfur. A multi-parameter and interdisciplinary approach has proven important in assessing submarine sulfur springs affected by seawater input.

Evaluating sustainability of Bhuj aquifer system, Western India using nuclear dating techniques

Abstract Increasing population, food demands and climatic stressors pose an imminent threat to groundwater sustainability in regional aquifer systems globally. Limited availability of surface water and erratic/uncertain rainfall necessitates preservation of groundwater resources, which form reliable fresh water reserves in most of the arid regions. Bhuj Sandstone aquifer is one such fresh groundwater systems in Western India catering the domestic/irrigational needs for over 2 million population. Rapid groundwater depletion in this area warranted a mandatory conservation of groundwater resources for future sustainability. Nuclear techniques using 3H and 14C provide estimates of groundwater age that help in planning sustainable groundwater management. In this study, sustainability of deep groundwater was assessed using environmental radioactive isotopes (3H, 14C). Results indicate that 14C activity of the groundwater samples varies from 26 to 73.6 pMC (percent modern carbon). Considering the various biases and uncertainties present, multiple correction models were applied to obtain representative groundwater ages by incorporating stable (13C) isotope and hydrogeochemical data. The corrected and representative ages are found to range from 5.8 to 8.6 ka BP (thousand years before present). From the study it can be inferred that central Bhuj aquifer hosts paleo-groundwater while the western part is recently recharged. Therefore, over-exploitation of deep groundwater in central Bhuj aquifer may further lower the water levels and this would have long-term impact on the socio-economic development of Kutch region.

Hydro-chemical characteristics and groundwater quality evaluation in south-western region of Bangladesh: A GIS-based approach and multivariate analyses

The study focuses on the chemistry of groundwater and if it is suitable for drinking and for use in agriculture using water quality indices, GIS mapping, and multivariate analyses in Sharsa Upazila, Jashore district, Bangladesh. In this study, the concentration of NH4+, K+, Ca2+, EC, Turbidity overstep BDWS drinking standards in 69 %, 14 %, 100 %, 40 % (WHO), 73 % of samples respectively. The value of Water Quality Indices (WQI) results inferred that the maximum specimen was held good quality for drinking uses, and the values distributed central eastern part to the south-eastern part were good quality water in the selected studied area. The study area's PH, EC, SAR, Na (%), TH, and NO3− values were mapped using GIS tools to show their spatial distribution. The cluster and correlation matrix analyses are used to validate for Principle Component Analysis (PCA). The five PCA results exhibited that the presence of EC, turbidity, K+, SO42− and NO3− was significant and was caused by both geogenic (rock weathering and cation exchange) and anthropogenic (agrochemicals, animal feedback) factor. According to the hydro-geochemical data, the maximum number of samples is of the Ca–Mg–HCO3–Cl type and is dominated by rocks. The irrigation water indices like MH, KR, SAR, and %Na indicate show high-quality groundwater for irrigation purposes. Most of the samples were satisfactory and compiled with WHO and Bangladeshi criteria for standard drinking water guideline values.

Interprétation de l’hydrogéochimie de la Molasse d’Eau Douce Supérieure (Obere Süßwassermolasse) dans la région de Munich (Bavière, Allemagne) à l’aide d’une analyse multivariée et d’une modélisation géologique en 3D

AbstractIntense use of groundwater in urban areas requires appropriate monitoring, which in turn necessitates proper data management with employment of increasingly sophisticated statistical methods and mapping tools. An example of such an urban area with intensive use of groundwater is the study area of GeoPot Project, namely Munich (Germany) and its surroundings. The aim of the presented study was to provide a description of the hydrogeochemical characteristics of the aquifers occurring in the Quaternary and Upper Freshwater Molasse (German: Obere Süßwassermolasse – OSM) sediments and to further improve the understanding of interactions between the aquifers. The focus was put on the identification of hydrochemical facies, the chemical signatures of different water types, an understanding of occurring processes, and spatial relationships between the aquifers. In order to deal with hydrogeochemical data generated for this study, as well as with data coming from existing external databanks (e.g. BIS-BY), a methodology of quality assurance was developed. The analytical methods focused on multivariate statistics. To enhance the interpretation of the obtained clusters, a recently developed three-dimensional geological model was used for better understanding and presentation. It was found that in the study area, deeper aquifer systems represent the most distinct hydrogeochemical signature of the Na–HCO3 water type. In the remaining clusters, a transition from deeper (alkaline) to shallow (alkaline-earth) groundwater can be observed. The results of the study can be utilized for improved, sustainable groundwater management.

Multivariate statistical techniques for the evaluation of hydrogeochemical data from areas with chronic kidney disease of unknown etiology (CKDu) in Sri Lanka

Chronic Kidney Disease of unknown etiology (CKDu) ranked as one of the most attended public health issues in Sri Lanka. The etiology of the disease is believed to be environmentally induced as it appears in geographically discreet regions of the dry zone of Sri Lanka. Girandurukotte and Wilgamuwa are two regions where CKDu is more prevalent. This study performs a comparative analysis to separately identify the quantitative differences of hydrogeochemical parameters of groundwater samples consumed by the patients and non-patients in two regions. Besides, groundwater quality data of 421 wells from Girandurukotte and Wilgamuwa were used for the analysis. Out of 421 samples, 310 samples were collected from wells where patients were reported. Descriptive statistics, Correlation analysis and Factor analysis were performed. Results of comparative analysis conclude that means of iron (Fe) content in Wilgamuwa CKDu (371 μg/L) and non-CKDu (731μg/L) exceeds the WHO permissible limits. The mean ion content of F-, Cl-, NO3-, SO42- and Na+ in the water wells consumed by the CKDu patients in the Wilgamuwa region is higher in concentration than non-CKDu wells. Out of major elements, Mg2+, Ca2+, K+, Na+, NO3- and hardness contents are higher in Wilgamuwa CKDu wells compared to the Girandurukotte CKDu wells. Trace elements such as As, Cd, and Pb do not exceed the WHO recommended limits in both regions. Generally, except for Fe ion concentration, almost all the other ion concentrations are within the WHO recommended limits. Correlation analysis reveals that Total Dissolved Solids (TDS) is highly positively correlated with alkaline earth metals Mg2+ (0.93), Ca2+(0.86) and Sr2+(0.85) in Wilgamuwa CKDu water sources. Also, Electrical Conductivity (EC) is highly positively correlated with Ca2+(0.84), Ni (0.82) and Sr (0.81) in Wilgamuwa non-CKDu water sources. Factor analysis was applied to identify the chemical combinations in each cluster. Ni, Ca2+, Sr2+ and Mg2+ appear as a factor in Wilgamuwa non-CKDu water sources. Hence, alkaline earth metals are chemically associated and appear as a factor combination in Wilgamuwa non-CKDu water sources. Also, Alkalinity, Hardness, Ca2+ and Sr2+ were found as a factor in Ginnoruwa CKDu samples.

State of the Practice Worldwide: Utilizing Hydrogeochemical Data and GIS Tools to Assess the Groundwater Quality in Arid Region: Example from Wadi Feiran Basin, Southwestern Sinai, Egypt

AbstractThe paper aims to study the physio‐chemical parameters of Wadi Feiran groundwater and classify it for use for drinking and irrigation. Twenty water samples collected from the WF have revealed a number of physio‐chemical parameters such as pH, TDS, SAR, EC, ions (Na+, Mg+2, Ca+2, K+, Cl−, SO4−2, NO3−, and HCO3−), and trace elements (U, Pb, Cd, Zr, and Fe). The study clarified that the major ion parameters are within the permissible limits according to WHO 2018, except for Ca+2, Cl−, SO4−2, and NO3−, but trace elements have high concentrations, except for Zn. To recognize the association between groundwater quality parameters and their collective impact on whole groundwater quality, correlation coefficient, factor, and cluster multivariate statistical analyses were carried out and confirmed with the constructed LU/LC map. These revealed that the increase of TDS, EC, Cl, SO4, Na, Mg, and NO3 is attributed to rainfall, leakage of municipal sewage Nile water, and human actions. GIS approaches were used to create thematic layers from groundwater physio‐chemical parameters, which were then weighted and combined to produce a groundwater quality model. This model was classified into potable, marginal, and un‐potable water. Potable and marginal water can be used for drinking and irrigation, but un‐potable water can only be used for irrigation.

Predicting geogenic groundwater arsenic contamination risk in floodplains using interpretable machine-learning model

Long-term exposure to geogenic arsenic (As)-contaminated groundwater poses a severe threat to public health problems. Generally, elevated As concentrations have been observed with high amounts of ammonium in groundwater of floodplains. An extreme gradient boosting algorithm was conducted to develop a probability model based on hydrogeochemical data, which predicted the occurrence rates of groundwater As on a regional scale. Results showed that concentrations of NH4+, Eh, K, Cl−, SO42−, and NO3− were powerful predictive variables of As exposure. The model revealed the co-enrichment of As with NH4+, suggesting that the mineralization of nitrogen-containing organic matter promoted the reduction of As-bearing iron-oxides. The predicted distribution of high-As groundwater showed high consistency with known spatial distribution of As contamination, and the model also accurately predicted As concentrations in Jiangbei Plain of China and typical As-affected floodplains of Southeast Asia. The model can serve as a low-cost and rapid virtual sensor for detecting As concentrations in private or newly drilled wells, thereby providing critical information for informed management decisions, environmental protection and public health safety.

Unveiling the biogeochemical mechanism of nitrate in the vadose zone-groundwater system: Insights from integrated microbiology, isotope techniques, and hydrogeochemistry

Clarifying the biogeochemical mechanism of nitrate (NO3−) in the vadose zone-groundwater system, particularly in agricultural contexts, is crucial for mitigating groundwater NO3− pollution. However, comprehensive studies on the impacts of changes in chemical indicators and microbial communities on NO3− are still lacking. This paper aims to address this gap by employing hydrogeochemistry, stable isotopes, and microbial techniques to assess the NO3− biogeochemical processes in the vadose zone-groundwater system. The findings suggested that NO3− in upper soil layers was primarily influenced by plant root absorption, assimilation, and nitrification processes. The oxygen contents gradually decreased with the nitrification process, resulting in the occurrence of the denitrification. However, denitrification predominantly occurred in the 60–80 cm soil layer in the study area. The limited thickness of the denitrification layer results in less NO3− consumption, leading to increased NO3− leaching into groundwater. Hydrochemical and isotopic characteristics further indicated that groundwater NO3− concentrations were mainly controlled by nitrification, followed by denitrification and mixing processes. The 16S rRNA sequencing analysis revealed great influences of soil sampling depths and groundwater NO3− concentrations on the microbial community structure. Additionally, the PICRUSt2-based prediction results demonstrated a stronger potential for dissimilatory reduction of NO3− to ammonium (DNRA) in both soil and groundwater compared to the other processes, potentially due to the widespread presence of the nrfH functional genes. However, the chemical indicators and isotopes used in this study did not support the occurrence of DNRA process in the vadose zone-groundwater system. This finding highlights the importance of an integrated approach combining microbiological, isotopic, and hydrogeochemical data to comprehensive understanding biogeochemical processes. The study developed a conceptual model elucidating the NO3− biogeochemical processes in the vadose zone-groundwater system within an agricultural area, contributing to enhanced comprehension and advancement of sustainable management practices for groundwater nitrogen.

Contrasting copper concentrations and isotopic compositions in two Great Lakes watersheds

Copper (Cu) stable isotopes can elucidate the biogeochemical controls and sources governing Cu dynamics in aquatic environments, but their application in larger rivers and catchments remains comparatively scarce. Here, we use major and trace element hydrogeochemical data, Cu isotope analyses, and mixing modeling, to assess Cu loads and sources in two major river systems in Ontario, Canada. In both the Spanish River and Trent River catchments, aqueous hydrochemical compositions appeared reasonably consistent, but Cu concentrations were more variable spatially. In the Spanish River, waters near (historic) industrial mining activities displayed positive Cu isotope compositions (δ65CuSRM-976 between +0.75 ‰ and +1.01 ‰), but these signatures were gradually attenuated downstream by mixing with natural background waters (δ65Cu −0.65 ‰ to −0.16 ‰). In contrast, Trent River waters exhibited more irregular in-stream Cu isotope patterns (δ65Cu from −0.75 ‰ to +0.21 ‰), beyond the variability in Cu isotope signatures observed for adjacent agricultural soils (δ65Cu between −0.26 ‰ and +0.30 ‰) and lacking spatial correlation, reflective of the more diffuse sourcing and entwined endmember contributions to Cu loads in this catchment. This work shows that metal stable isotopes may improve our understanding of the sources and baseline dynamics of metals, even in large river systems.

A comprehensive overview of groundwater salinization and recharge processes in a semi-arid coastal aquifer (Essaouira, Morocco)

Study regionThe downstream part of the Essaouira basin, Morocco, Northwestern Africa. Study focusThis study combines multivariate statistical analyses, stable isotopes, hydrogeochemical, hydrogeological, geological and remotely sensed data to gain a better understanding of the hydrological and groundwater salinization processes in a coastal aquifer. Hydrogeochemical data from 223 samples as well as stable isotope data collected during 10 sampling campaigns between 1990 and 2020 were compiled and subjected to a comprehensive analysis. Groundwater recharge obtained from the stable isotope approach was checked using a water balance method based on remote sensing data of actual evapotranspiration. New hydrological insights for the regionSeawater intrusion was detected only for the period of 2009–2020, nearby the ocean, whereas hyper-salinity due to evaporite dissolution occurred throughout the entire period (1990–2020) primarily in the southern part of the aquifer. Additionally, the isotopic mass balance model shows that aquifer recharge from the Ksob river area is mainly located in the northeastern region. Furthermore, based on average values of stable isotopes of rainfall and groundwater, preliminary results show that only months of November, December and January with rainfall higher than 54 mm contribute to groundwater recharge. The water balance approach confirmed these results, but also revealed a lower recharge in February, with a monthly average precipitation of 46 mm. The outcomes of this research enabled the construction of a comprehensive conceptual 3D model of the Essaouira coastal aquifer. The insights from this research are important to guide measures for sustainable water resources management.

Characteristics and evolution of karst collapse columns in the Huainan coalfield

Karst collapse columns (KCCs) seriously affect the mining safety of deep coal seams. This study systematically summarizes and analyzes the development of KCCs, and classifies the different development stage to identify their development stages and evolutionary process in the Huainan coalfield. The evolution models for KCC development are given, combining with the exploration strata data from boreholes, the groundwater flow data of regional field, the hydrogeochemical data from the relative aquifers of KCC, and the hydrodynamic parameters. The results show that first types of KCCs are discovered in Liuzhuang and the Pansan mine, which is broken and disorganized, with a high degree of filling and cementation, and with the low permeability and velocity, and lower storage capacity. The KCCs in the Xieqiao and Zhangji mine have various morphologies and size differences. Their internal rocks are broken and semi-cemented, with a coefficient of permeability between 0.2 and 0.5 m/d and a specific discharge between 0.1 and 0.2 L/s•m. The KCCs are located in the cone of depression and are part of a sink area with moderate water-richness, where upper and lower aquifers have close hydraulic connections with mixed water quality. The internal core of the KCCs in the Gubei Mine is close to the center of the cone of depression which is highly broken and disorganized, with a high permeability, and a specific discharge more than 1.5 L/s•m. The intensity of runoff increases as its vertical depth also increases, especially the local areas are a higher hydraulic conductivity. Based on comprehensive hydrogeological characteristics, the KCCs development is divided into three stages: growing stage, declining stage, and dead stage. According to their characteristics of different stages, a series of evolutionary processes are established. Combining the sedimentological, karstological, and hydrogeological theories, some measures have been taken for prevention and control of mine water hazard in the various developmental stages. Hence, this research not only provides a new classified approach for KCC stages, but also an essential reference for a better understanding the mechanism of water inrush of KCCs in Northern China.

Using continuous electrical conductivity measurements to derive major solute concentrations in karst systems

AbstractHydrochemical data of karst springs provide valuable insights into the internal hydrodynamical functioning of karst systems and support model structure identification. However, the collection of high‐frequency time series of major solute species is limited by analysis costs. In this study, we develop a method to retrieve the individual solute concentration time series and their uncertainty at high temporal resolution for karst springs by using continuous observations of electrical conductivity () and low‐frequency ionic measurements. Due to the large ion content and non‐negligible concentrations of aqueous complexes in karst systems, the concentration of each solute species occurring as free ion and as part of aqueous complexes are computed separately. The concentration of species occurring as free ions are computed considering their contributions to the total , whereas the concentration of the species as part of complexes are obtained from speciation calculations. The pivotal role of the complexation processes for the reconstruction of solute concentration time series starting from the signal is investigated in two karstic catchments with different geologies and temporal resolution of the available hydrochemical datasets, that is the Kerschbaum dolostone system in Austria and the Baget limestone system in France. The results show that complexation processes are significant and should be considered for the estimation of the total solute concentration in case of SO4, Ca, Mg and HCO3. The signal of a karst spring can be used to interpolate and quantify the dynamics of those solutes characterized by large contribution (approximately >6%) to the total and low relative variability, that is HCO3, Ca and Mg. Moreover, the presented method can be used to estimate concentrations of solutes when applied to karst systems with stationary and hydrogeochemical homogeneous contributing area. On the contrary, the method is affected by large uncertainty in case of dynamic systems characterized by varying contributions of water from different geological areas. This study aims to contribute to the problem of hydrogeochemical data availability and to support future works on karst systems conceptualization.

4D interpretation of time-lapse electrical resistivity monitoring data to identify preferential flow path in a landfill, South Korea.

Monitoring the leakage of leachate from a landfill is critical in preventing possible contamination in the surrounding area. Time-lapse (TL) electrical resistivity tomography (ERT) has been performed along eleven survey lines at four different time points in a landfill in Korea. The TL data sets were interpreted using an in-house 4D inversion algorithm. Changes in 4D inversion results were analyzed in order to interpret a leachate-contaminant region. Since the rainy season started during obtaining TL ERT data sets, the effects of precipitation on TL ERT data are also analyzed. Changes in electrical resistivity (ER) showed that precipitation increases ER of contaminant zones. As hydrogeochemical data offer contamination information in some areas where boreholes are located, these are helpful to interpret and compare with ERT inversion results to evaluate the extent of the contaminated plume. We also classified soil textures from particle size analysis on soil samples and analyzed electrical conductivity (EC) and dissolved oxygen (DO) using groundwater samples obtained from observation wells in the survey site. The information on soil structure as well as the results of 4D inversion provided insight into the location of a preferential flow path.