Abstract
Explicit identification of hydrochemical processes and their controlling factors within groundwater systems is critical for the sustainable utilization of water resources in coastal urban areas. This study was undertaken in the North Coastal Region of Jiaozhou Bay (NCRJB), located in the eastern part of Shandong Province, China, an area grappling with significant issues of groundwater quality degradation and water scarcity. A total of 105 groundwater samples and 34 surface water samples, collected from 2020 to 2024, were analyzed and studied using various hydrogeological tools, multivariate statistical analyses, and water quality assessment methods. These include the Piper diagram, hydrochemical facies evolution diagram (HFE-D), Principal Components Analysis (PCA), correlation analysis, stable isotope analysis, Water Quality Index (WQI), and USSL diagrams. The results indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, exhibiting high Total Dissolved Solids (TDS) and Electrical Conductivity (EC) values, characteristics that render them poor to unsuitable for drinking and irrigation purposes. The fracture groundwater is predominantly of the Ca-Na-Cl mixed type, with average suitability for irrigation and a limited proportion (22.5%) deemed suitable for drinking. Seawater intrusion, primarily through the surface water system, and the impact of human activities were identified as the predominant controlling factors con-tributing to the degradation of the local groundwater environment. Field empirical investigations further validated the results derived from hydrogeological assessments, multivariate statistical analyses, and isotopic approaches. The long-term shifts in hydrochemical properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and show a certain degree of mitigation during the wet season. This study highlights that field investigations, in conjunction with hydrochemical tools, multivariate statistical analyses, and stable isotope analysis, can successfully furnish reliable insights into the predominant mechanisms governing regional groundwater evolution within the context of long-term and intricate envi-ronmental settings.
Similar content being viewed by others
Introduction
Groundwater is a pivotal freshwater resource for coastal communities, providing essential sustenance for a variety of critical applications1,2. It is indispensable for supplying potable water, fulfilling the industrial and domestic needs of urbanized regions, and for irrigating agricultural lands, particularly in areas where surface water resources are scarce or insufficient3. The reliance on groundwater in these diverse contexts underscores its fundamental role in maintaining ecological balance and supporting the socio-economic framework of coastal regions4,5.
In many coastal areas, the demand for water often exceeds supply, leading to what is termed quantity-induced water scarcity6. This situation arises from a combination of factors, including climate change, population growth, economic development, and agricultural practices that are intensive in their water use7,8. Coastal regions are increasingly facing the critical challenge of water scarcity, an issue that is characterized by both a dearth of water resources and a decline in water quality9,10. In the context of ongoing population growth and aggregation in these areas, the problem has become a focal point of concern for local authorities11. Consequently, elucidating the geochemical mechanisms that govern the transformation and quality of groundwater is crucial for the sustainable stewardship of water resources within the coastal area.
Scholars from around the world have conducted extensive studies focused on the identification and quantification of coastal aquifer groundwater systems. Some researchers have employed a variety of traditional and innovative methodologies, including Piper diagrams, modified Piper diagrams, Durov diagrams, Gibbs diagrams, ion ratio diagrams, Hydrogeological Facies Evolution diagram(HFE-D), and hydrogeochemical simulation techniques, to qualitatively analyze the hydrochemical characteristics and genesis of groundwater12,13,14,15,16. Concurrently, Multivariate Statistical Analysis (MVSA) methods, such as Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), Factor Analysis (FA), and correlation analysis, constitute a valuable approach that can potentially serve this purpose17,18,19,20. These methods are adept at uncovering the intrinsic relationships and structures among various groundwater indicator variables, facilitating the clustering of water samples with similar characteristics into homogeneous groups. Moreover, stable isotopes serve as an effective tool for identifying complex hydrochemical processes21,22,23. Additionally, methods such as Water Quality Index (WQI), Fuzzy Comprehensive Evaluation, and Health Risk Weight Method (HRWM) have been extensively utilized by researchers for quantitative assessment of groundwater quality24,25,26. These methodologies aid in elucidating the spatial and temporal variability of groundwater quality, determining primary hydrochemistry processes, and qualitatively or quantitatively assessing their temporal evolution. In recent years, the combined application and mutual validation of these methods have emerged as a focal point in current research on groundwater hydrochemistry and hydrogeology. Nevertheless, previous studies predominantly concentrated on singular groundwater systems when assessing the quality of groundwater in coastal regions, thereby overlooking the potential interconnections with local surface water bodies. Groundwater sampling was often confined to specific historical time frames, resulting in a lack of continuity in groundwater quality data. This lack of continuity hinders the assessment of the impact of temporal progression and seasonal variations on the local groundwater system. Moreover, the scarcity of systematic and extensive field investigations in prior research has led to conclusions that are less substantiated and robustly supported. The above issues may hinder researchers from clearly elucidating the hydrochemistry characteristics and genesis of groundwater in certain regions.
The north coastal region of the Jiaozhou Bay (NCRJB) in China is densely populated and economically advanced, with groundwater serving as a primary water source for agricultural and industrial production in the area. Moreover, this region also plays a pivotal role as the main water supply area for Qingdao City27. Previous works have been concentrated in the more densely populated southern coastal areas of Qingdao city, particularly in the Laoshan District, with several case studies and reports available28,29,30. There is insufficient research available on the hydrochemistry properties, causal mechanisms and quality of different types of groundwater in NCRJB. Considering the limitations of previous studies and the necessity of conducting surveys in the NCRJB area, the specific objectives of this research are: (a) to assess the spatiotemporal and seasonal variations of water quality parameters in the surface and groundwater systems of the NCRJB region, (b) to analyze whether the surface and groundwater in the study area are suitable for drinking and irrigation, (c) to describe the characteristics of groundwater quality and investigate the main hydrogeological and chemical processes affecting the groundwater chemistry, (d) to reveal the main factors leading to the degradation of local groundwater quality and propose countermeasures and suggestions. It is worth noting that this study marks the first comprehensive exploration of these severe issues within the NCRJB area. Our research findings will assist relevant government regulatory agencies, policymakers, water resource managers, and other stakeholders in formulating effective management plans to achieve sustainable economic and social development in the local area. In addition, the significance of this study extends well beyond the geographical confines of NCRJB. The comprehensive assessment framework and insights gained from our research can also provide scientific reference for water resource evaluation and management in similar coastal areas around the world.
Materials and methods
Overview of the study area
NCRJB has an area of 78 km2 bounded by east longitude 120° 11′ to 120° 19′ and north latitude 36° 14′ to 36° 19′ (Fig. 1a). Jiaozhou Bay (JZB), a partially enclosed estuary situated in the southern region of the Shandong Peninsula in Northeast China, has undergone substantial changes due to natural events and a variety of human activities over the past 70 years27. The primary currents in Jiaozhou Bay are tidal, fluctuating daily. The average tidal level in this region ranges from − 0.30 to 2.47 m, with a maximum tidal range of up to 4.61 m. Local climate is characterized northern temperate monsoon continental climate, where seasonal.
(a) Geographical location of NCRJB and its sampling locations. (b) The first author of this paper took water samples from groundwater observation wells. (c) The first and fifth authors collected surface water samples from the Xiangmao River at point SWD06. (d) The first author interviewed residents and collecting evidence.
changes and the ebb and flow of winds are more pronounced, with mean air temperature of 12.1 °C and a multi-year average relative humidity of 72%. The average annual in the last 10 years rainfall is 698.9 mm, with the majority rainfall concentrated in July and August. The average monthly rainfall during these two months amounts to 391.5 mm in last five years. The average evaporation in recent years is approximately 1014 mm. The entire study area encompasses urban areas, villages, farmland, forests, and industrial parks. The urban centers and industrial parks are primarily concentrated in the central and eastern regions of the study area, while the rural areas, farmland, and forests are predominantly located in the western, northern, and southern regions.
Overall, the landforms of this area can be categorized into two distinct groups based on their genesis and morphological characteristics: erosional mound landforms and accumulative plain landforms. The erosional mound landform area is primarily found in the northwest and southeast regions of the study area (Fig. 2a). The elevation of the erosional mound landforms ranges from 34.6 to 4.8 m, with slopes between 11 and 22‰. The accumulative plain landform area exhibits a generally flat topography, with ground elevations ranging from 5.0 to 1.30 m and slopes varying from 1 to 3‰. In contrast, fracture groundwater and pore groundwater are the main types present in these two landscapes, respectively. The geology of NCRJB can be divided into three distinct vertical stratigraphic units. These units, from top to bottom, are as follows: (1) Quaternary Holocene sediments; (2) Late Pleistocene sediments; and (3) Mesoproterozoic basement rocks.
The Quaternary Holocene sediments in this region are located between elevations of + 16 to − 17 m and contain anthropogenic land fill or cultivated soil, silty sand, silty clay, and medium to coarse sand. The Quaternary porous aquifer is primarily constituted by a single or dual-layered structure, comprising an upper unconfined aquifer and a semi-confined lower aquifer. These are separated by discontinuous clay layers that are interspersed within the sand and silt lenses. Most units of Quaternary Holocene sediments can form major aquifers, except for silty clay with poor permeability. In the Erosion mound landform region, highly weathered basalt, andesite, and breccia, along with the jointed fissure zones and tectonic fractures present in moderate to weak weathering, collectively form the principal aquifer within the bedrock. The groundwater level contour map and a typical hydrogeological cross-section of the NCRJB area are presented in Fig. 2b,c, respectively. It is noteworthy that Fig. 2b reveals the presence of groundwater cone of depression in densely populated areas located in the southeastern part of the study region, which is likely attributed to the large-scale human-induced water pumping and drainage activities during construction projects in recent years.
The surface water network in NCRJB is relatively well developed and consisting mainly of natural rivers and artificially modified water systems. The larger rivers include the Xiangmao River and the Hongjiang River, while the major man-made water systems include the Hulu River, the Nanwei River and Haiyue Lake, among others. The local government is situated on an elliptical man-made landscaped island, the Intelligence Island, which is surrounded by the man-made water system, the Hulu River. All the aforementioned natural rivers are part to the coastal water system and discharge into Jiaozhou Bay. The flow of these rivers is clearly influenced by precipitation and anthropogenic hydraulic regulation, exhibiting seasonal variations. The plain’s aquifer is recharged by atmospheric precipitation, nearby surface water bodies and groundwater runoff from bedrock areas, and it is primarily discharged through evaporation in shallow aquifers, groundwater extraction and pumping for residential life and urban construction and operation. According to available data and our investigations, the local groundwater usage is ranked from highest to lowest as follows: agricultural irrigation, industrial production, potable water supply, and urban landscaping purposes. Furthermore, the unauthorized extraction and utilization of groundwater within the study area are relatively common practices.
Sample collection and processing
The sample collection and chemical analyses of water for this study were sourced from four rounds carried out from 2020 to 2024 within the program named “Qingdao Urban Geological Survey Project”. Four rounds of intensive and regular sample collection were conducted in August 2020, January 2021, August 2023 and January 2024, respectively. The focus was on all newly established monitoring wells (Fig. 1b), major rivers (Fig. 1c), surface water bodies, and seawater of JZB, but also samples from private household wells (Fig. 1d), municipal department wells, and smaller business wells, as well as drinking water production companies, were taken. The pore aquifer groundwater samples were collected from wells with a depth range of approximately 10–28 m, while fractured aquifer samples were obtained from wells with depths ranging approximately from 15 to 70 m. Additional water samples were irregularly collected for experimental analyses when significant short-term fluctuations in the conductivity readings of groundwater monitoring wells were observed, in order to validate the accuracy of monitoring data.
Prior to the collection of groundwater samples, field personnel pre-pump the boreholes or wells to ensure that the water samples collected accurately reflect the actual conditions of the groundwater. Water samples were gathered in 500 mL polyethylene plastic drums, with the sampling bottles thoroughly washed at least three times with water from the target water body prior to filling. For turbid groundwater samples, the laboratory employs a standardized pretreatment procedure to process the samples, including coagulation and sedimentation, centrifugation, and filtration, to clarify the specimens. In addition, onsite measurements of crucial physicochemical parameters, including temperature, pH, and electrical conductivity (EC), were efficiently conducted using a multi-parameter portable meter (HANNA HI 98130), facilitating subsequent laboratory tests.
The chemical analysis of water was conducted by the Experimental Testing Centre of the No.4 institute of geological and mineral survey, Shandong Province, China. The major ions, such as K+, Na+, Ca2+, Mg2+, Cl−, NO3− and SO42−, were analyzed using ion chromatography; HCO3− was determined by titration; and total dissolved solids (TDS) were measured using the gravimetric method. Stable isotope analysis (δ2H and δ18O) was performed in Beat Laboratory in Miami, Florida, USA, using a mass spectrometer. All values are referenced to Vienna Standard Mean Ocean Water (VSMOW) standards and the analytical deviation reproducibility of ± 0.1‰ for δ18O and ± 1‰ for δ2H. A total of 114 hydrochemistry samples and 25 isotopic samples, comprising 105 groundwater samples, 28 surface water samples (mainly collected from rivers, ponds, lakes within the study area) and 6 seawater samples (collected near the coastline of Jiaozhou Bay), have been comprehensively interpreted based on the test results.
Multivariate statistical analysis (MVSA)
Principal components analysis (PCA)
PCA is a sophisticated method for identifying multiple influencing factors. It simplifies and reduces the dimensionality of a large set of variables by transforming them into a smaller number of uncorrelated variables, known as principal components (PC), through linear combinations and orthogonal transformations based on standardized data6,31. The aim of PCA is to better elucidate the variation within these variables by converting a multitude of interrelated variables into a smaller number of independent variables32,33. The representation of the principal components is as follows:
where a is the component loading, z is the component score, x is the measured value of a variable, i is the component number, j is the sample number, and m is the total number of variables.
Correlation matrix analysis
The Pearson correlation coefficient matrix is a statistical tool that measures the strength and direction of the linear relationships between pairs of variables. It is a fundamental concept in data analysis and is widely used across various fields, such as earth sciences, engineering, and technology34,35,36. In this paper, it is used to analyse the strength of correlation between major ion concentrations, physicochemical indicators of water samples in the study area with each other. The correlation was calculated using the following formula 2:
where P is Pearson correlation coefficient, \({\text{X}}_{\text{i}}\) and \({\text{Y}}_{\text{i}}\) are variables in X and Y, respectively; \(\stackrel{-}{\text{X}}\) and \(\stackrel{-}{\text{Y}}\) are the mean values of variables X and Y, respectively.
Hydrogeological facies evolution diagram (HFE-D)
HFE-D is a sophisticated graphical tool utilized for the meticulous analysis of seawater intrusion, developed by Elena Giménez37 and employed by several authors38,39,40. It serves as a pivotal instrument in assessing the state of coastal aquifers, particularly during seawater intrusion and freshening phases.
The ordinates of HFE-D depict the percentages of anions, with the percentage of chloride serving as an indicator of sea water and the percentage of bicarbonate or sulfate (dependent on the anion predominantly present in fresh water) characterizing the recharge water. Notably, the percentages of SO4 and HCO3 are not aggregated but are represented by selecting the ion with the higher percentage. For instance, the Na- HCO3 / SO4 facies encompasses both the Na-HCO3 and Na-SO4 facies. In cases where water from both facies is present, the sample is represented by the percentage of bicarbonate (if %HCO3 > %SO4) or sulfate (if %SO4 > %HCO3), as indicated in the center of the diagram using distinct symbols. The aforementioned criteria also apply to the abscissa axis, which represents cations such as Na, K, Ca, and Mg. Consequently, the diagram offers a representation of four heterotopic facies out of a potential 16: Na–Cl (representative of seawater), Ca–HCO3 (indicative of natural freshwater), Ca–Cl (signifying salinized water with reverse exchange), and Na–HCO3 (denoting salinized water with direct exchange).
The two fundamental phases encompassed within this framework are freshening (FW) and intrusion (SW), bifurcated by the conservative mixing line (CML), which divides the HFE-D into two distinct sections. Water samples situated above and to the left of the CML represent the freshening phase, whereas those positioned below and to the right of the CML correspond to the intrusion phase4. Distinct sub-stages pertaining to both the freshwater and intrusion phases can be discerned based on the chemical composition of the sampled waters. These sub-stages, include freshening sub-stages (f1, f2, f3, f4, and FW, representing the various stages from the commencement to the conclusion of the freshening process) and intrusion sub-stages (i1, i2, i3, i4, and SW, indicating the various stages from the initiation to the termination of the intrusion process), collectively contribute to elucidating the salinization dynamics of the groundwater samples4,41.
Utilizing Excel 2016 and Origin 2021, we conducted a descriptive statistical analysis of the hydrochemistry parameters. This analysis included the generation of boxplots, Piper trilinear diagrams, Principal Component Analysis (PCA) charts, correlation coefficient matrix visualizations, and Hydrogeological Facies Evolution Diagrams (HFE-D).
Water quality assessment
Understanding the spatial distribution of water quality is essential for the effective management of groundwater resources. Water Quality Index (WQI) maps offer a valuable tool for this purpose, presenting information that is readily interpretable by both researchers and policymakers42. In the present study, we computed the WQI of by comparing the concentrations of its constituent chemical elements with the World Health Organization’s (WHO) recommended standards43,44, and subsequently assessed the potability of the groundwater.
The determination of the WQI was conducted through a systematic approach encompassing several sequential steps. The inaugural step entailed the assignment of weights to each parameter, commensurate with its relative importance, with values ranging from 1 to 5. These weights are delineated in Table 1, drawing on the outcomes of preceding research. In the subsequent step, the relative weight (Wi) of each parameter is ascertained by employing Eq. (3):
where wi is the weight of each parameter, n is the number of parameters, and Wi is the relative weight.
The third step in the methodology involves calculating the quality rating scale (qi) for each parameter, as per the guidelines of the World Health Organization (WHO), utilizing Eq. (4):
where qi is the quality ranking, Ci is the concentration of each chemical parameter in mg/L, and Si is the WHO standard of each chemical parameter in mg/L.
Based on the computed values of the Water Quality Index (WQI), water quality was categorized into five distinct classes: excellent, good, poor, very poor, and unsuitable for human consumption45. Subsequently, ArcGIS version 10.8 software was employed to delineate a WQI zoning map for the study area.
Additionally, the agricultural suitability of both surface and groundwater in the study area for irrigation purposes was evaluated using the United States Salinity Laboratory (USSL) diagram. Where the sodium adsorption ratio (SAR) was calculated according to Eq. (6):
where c(Na), c(Ca), and c(Mg) are the concentrations of Na+ ions, Mg2+ ions, and Ca2+ ions, respectively, all in meq/L.
Field survey
In this study, we have attached great importance to field investigations, and devoted considerable effort and resources to ensure their thoroughness and accuracy. During the specific field investigations from 2020 to 2024, with the primary workload completed in 2020 and 2024, the following information was critically examined and recorded: (a) factors pertaining to the extraction and utilization of surface and groundwater, including agricultural irrigation, aquaculture, water consumption for residents, industry, municipal use, and engineering construction activities; (b) local water conservancy facilities and specific management measures that impact surface water and groundwater; (c) Other existing and historical evidence that aids in better understanding of the groundwater characteristics in NCRJB. Over 500 field photographs, 70 survey records, and 30 interviews with informed individuals were collected during the fieldwork (see Fig. 1d). These materials have significant reference value for verifying the analyses and conclusions related to water chemistry patterns in NCRJB.
Results
Chemical composition statistics of surface water bodies and groundwater in NCRJB
General hydrogeochemistry
The pivotal ion concentrations, pertinent physical parameters and sampling altitude, as measured from pore groundwater, fracture groundwater, and surface water specimens, across the periods during 2020–2021 and 2023–2024, are meticulously delineated in Table 2. The box plots serve as a valuable tool for enhancing the description and visualization of these characteristics and variations (Fig. 3). The collected samples, encompassing three distinct types, exhibit an average altitude that varies between 1.46 and 9.63 m, implying a subtle elevation variance between the groundwater and surface water systems within the study area. Remarkably, the minimum collection altitudes for pore water samples during the rainy and dry seasons are recorded at − 2.08 and − 4.23 m, respectively, which are significantly below the mean sampling altitude and sea level elevation. Such pronounced deviations may be ascribed to the formation of groundwater funnel areas48, likely a consequence of excessive groundwater extraction in localized areas. The median pH values for pore aquifer samples, fractured aquifer samples, and surface water were 8.50–8.60, 7.30–7.65, and 7.60, respectively. These data indicate that the groundwater in the fractured aquifer and surface water in the study area exhibit a weakly alkaline to neutral nature, whereas the pH values in the porous aquifer are significantly higher than those of the former two. Moreover, the pH values of all type samples collected during the dry season tend to be higher than those collected in the wet season. The plausible explanation for this pronounced difference lies in the shallow burial depth of the porous aquifers within the study area, typically ranging from 2 to 30 m below the surface. This shallow depth renders them highly susceptible to the influence of human activities, encompassing land use, agricultural production, aquaculture, and wastewater discharge.
The extent of data dispersion can be determined by examining the standard deviation (SD) and coefficient of variation (CV)49. Table 2 and Fig. 3 demonstrate that the primary ions, TDS, and EC in the three distinct types of water samples exhibit significant dispersion across the sampling region. The magnitude of variability among the aforementioned indicators is greatest for pore water, followed by surface water, and lowest for fracture water. Notably, the influence of seasonal variations on this variability remains insignificant. In this investigation, the coefficient of variation for ions such as NO3−, Ca2+, and Mg2+ is the highest, with values exceeding 0.9. In contrast, the coefficient of variation for TDS and EC ranged from 0.598 to 0.954. Generally, groundwater major anions concentration in pore groundwater and surface water were in the order of Cl− > SO42− > HCO3− > NO3−, and Cl− > HCO3− > SO42− > NO3− for fracture groundwater. Correspondingly, the average order of major cations in surface water and pore groundwater was Na+ > Mg2+ > Ca2+ > K+, whereas in fissure groundwater, the average order is Ca2+ > Na+ > Mg2+ > K+. The median concentrations of Cl−, SO42−, Na+, and Mg2+ in pore groundwater during the dry season were 1.46, 1.11, 1.50, and 1.64 times higher, respectively, than those observed in the rainy season. Consequently, the dry season water samples tended to exhibit higher EC and TDS values compared to the wet season. Similarly, fractured acquire samples exhibited comparable characteristics. Conversely, the concentrations of NO3−, HCO3−, and K+ ions in majority of groundwater samples during the dry season were lower than those in the wet season, with the NO3− concentration of fractured acquire samples in the dry season being particularly low. Given that these three ions contribute relatively minor proportions to the overall composition of the water samples, they did not significantly influence the seasonal variation trends of TDS and EC.
Piper diagram and hydrochemistry facies classification
The Piper trilinear diagram is capable of reflecting the variations in the major ionic composition and the hydrochemical characteristics of groundwater, which can be employed to delineate hydrochemical types50. The data pertaining to the major anions and cations, derived from chemical analyses, are depicted on the Piper diagram for the wet season of 2020, the dry season of 2021, the wet season of 2023, and the dry season of 2024 (Fig. 4). For cations, all surface water and pore groundwater samples are plotted in the Na-type region of the lower left triangle, while most fracture groundwater samples are plotted in the Ca-type region. This indicates a significant preponderance of alkali metal elements (Na⁺ and K⁺) over alkaline earth metal elements (Ca2⁺ and Mg2⁺) in the analyzed samples, particularly in surface water and pore groundwater. In the lower right triangle of the Piper diagram, where anions are plotted, all surface water samples and a majority of pore groundwater samples are concentrated in the Cl⁻ region on the right side. Chloride emerges as the dominant ion in the aforesaid samples, with the concentration of strong acid ions (Cl⁻ + SO₄2⁻) significantly exceeding that of weak acid ions (HCO3⁻). Conversely, anions in the fracture groundwater samples are predominantly located in the center of the triangle, indicating no dominant type, while a few are situated in the chloride region on the right side of the triangle. Notably, during the dry season, the anion distribution in the fracture groundwater exhibited a tendency to skew towards the Cl⁻ axis.
According to the classification criteria adopted by Bauer51, groundwater and surface water in the study area can be classified into the four following types: Na–Cl, Ca–Cl, Ca–HCO3 and mixed water types. Although there are certain variations in the concentrations of ions between the dry and wet seasons, these fluctuations do not significantly impact the hydrochemical classification of the samples. The hydrochemical typing of the samples is predominantly determined by the type of water sample. A substantial majority of the fracture groundwater samples, 65.85%, are classified as mixed types, followed by 21.95% characterized by the Ca–Cl type, and a minor proportion, 9.76%, as Na–Cl type. Notably, only the sample SW55, which is the farthest from the coastline (approximately 7.4 km from the coast), is categorized as Ca–HCO3 type. In contrast, both the pore groundwater and surface water samples are exclusively of the Na–Cl type. The HCO3–Ca type is a predominant feature of freshwater, while the Cl–Na type characterizes seawater. Mixed water samples, on the other hand, represent the transition between freshwater and saline water52. Given the significant proportion of Cl⁻ in most groundwater samples in this region, all surface water and pore groundwater samples fall into the Cl–Na type category, indicating a potential severe seawater intrusion in the study area. Furthermore, it is likely that a considerable portion of the bedrock fracture groundwater in the region is in a transitional phase between fresh and saline water. Specifically, during the wet season, samples from the fractured aquifer tend more towards the Ca–Cl type, while in the dry season, they lean more towards a mixture of Na–Cl and Ca–Cl types. This likely correlates with the seasonal variation in seawater intrusion, being less pronounced during the wet season and more pronounced during the dry season.
In addition, the Piper diagram also presents the sample mineralization grouping results of the samples in the form of a bubble chart. The mineralization degree of the fractured groundwater is relatively low, generally not exceeding 3000 mg/L, with the most falling within the range of 500 to 1500 mg/L. In contrast, the mineralization of surface and pore groundwater exhibits considerable variability, with the majority of samples surpassing 3000 mg/L and some even exceeding the mineralization level of seawater. This finding also serves as evidence of severe seawater intrusion in NCRJB.
Multivariate statistical analysis (MVSA)
Principal components analysis (PCA)
PCA was conducted on a dataset that included 12 parameters from 87 groundwater and 23 surface water samples. To determine the number of significant principal components (PCs) for interpretation, the Kaiser criterion was applied53. PCs with a combined explained variance of at least 70% and an eigenvalue exceeding one were selected. The analysis revealed three PCs, which collectively explaining 80.11% of the total variance, thus effectively reducing the dataset’s dimensionality. Figure 5a,b present the factor loadings, eigenvalues, and percentage variations of the PCs. To establish clear relationships between the factors and the hydrochemical data, only absolute factor loadings of ≥ ± 0.35 were deemed to indicate moderate to strong correlations40.
The TDS, EC, Cl−, Na+, and Mg2+ concentrations were included in Principal Component 1 (PC1), which had the highest factor loading (7.040) and explained 58.66% of the total sample variance. PC1 showed positive loadings in the range of 0.367–0.373, with the three highest ranked factors being EC (0.373), TDS (0.372) and Cl− (0.371). In addition, Na+ (0.367) and Mg2+ (0.363) also showed moderate positive loadings. Although their loading values were not exceptionally high, their proximity suggests that the component represents the water’s salinity, potentially indicating the influence of seawater intrusion in the study area. Consequently, Factor 1 can be defined as the saltwater intrusion factor54.
Principal Component 2 (PC2) included NO3− (0.552) and SE (0.463) showing high positive factor loadings, while pH (− 0.584) with high negative factor loading. PC 2 accounted for 13.11% of the total variance, reflecting the combined influence of pH, human activities, and sampling elevation on water quality evolution. This factor characterizes the impact of anthropogenic activities, such as agricultural fertilization14, on the water samples in the study area. Water samples collected at higher elevations may exhibit higher concentrations of NO3−, reflecting the influence of these activities on water quality.
Principal Component 3 (PC3) consisting of HCO3− (0.721) and NO3− (0.513) showed strong positive loadings and accounted for 8.34% of the total variance. This factor represents a natural process of infiltration of recharge water into the groundwater system, where water–rock interaction occurs and ultimately releases HCO3− into the groundwater55. It is noteworthy that the NO3− ion demonstrates a significant positive correlation, suggesting that regions with intense recharge activities of underground aquifers, such as those from rainfall, are often accompanied by high-intensity human agricultural activities.
Figure 5c exhibits the three-dimensional PCA score plots, encompassing PC1, PC2, and PC3. In contrast to the two-dimensional representations, the integration of the third principal component potentially enhances the discrimination capabilities among samples, offering a more comprehensive visualization of the data’s inherent structure56. Fracture groundwater samples are mainly located in the third and sixth quadrant, while surface water samples are mostly located in the fourth and eighth quadrants. The pore groundwater samples exhibit a higher degree of dispersion; however, the majority cluster within the first and fifth quadrants. The observed parameters and their combinations could potentially be attributed to diverse dynamic hydrogeochemical processes occurring in the region, encompassing factors like seawater intrusion, recharge mechanisms, and water–rock interactions, among others.
Correlation analysis
The Pearson correlation matrix was utilized to further evaluate the relationships between various water chemistry variables and parameters of water samples within the study area. Within the correlation coefficient matrix, the correlation coefficient r spans the interval from − 1 to 1, indicating the degree of association between paired variables. An absolute value of r (|r|) that approaches unity signifies a progressively stronger relationship between the elements in question. Correlations among water quality indicators are considered strong when the absolute value of the correlation coefficient, |r|, lies between 0.8 and 1, indicating a positive association. When |r| is within the range of 0.4 to 0.8, the correlation is moderate, suggesting a less pronounced but still significant association. Conversely, a correlation is deemed weak when |r| is between 0 and 0.428.
Figure 6a delineates the correlation analysis results for pore groundwater. The TDS exhibited a strong to moderate order of correlation with the cations, where sodium (Na+) demonstrated the highest degree of association, followed successively by magnesium (Mg2+), potassium (K+), and calcium (Ca2+), with correlation coefficients of 0.99, 0.97, 0.70, and 0.40, respectively. In contrast, the correlation between TDS and the anions was most pronounced with chloride (Cl−), followed by sulfate (SO42−) and NO3−, with corresponding correlation coefficients of 1.00, 0.85 and 0.30, respectively. This suggests that Na+ and Cl− are the primary determinants influencing TDS, serving as the controlling factors for the widespread salinization of pore groundwater in this region. The pairs of Na+–Cl−, Na+–SO42−, Cl−–SO42−, Mg2+–SO42−, Mg2+–Cl− and Na+–Mg2+, exhibit significant positive correlations, with all their correlation coefficients exceeding 0.80, indicating a common aqueous salt origin between these ionic species57.
The TDS of fracture groundwater showed a descending order of correlation with the cations, with Mg2+ exhibiting the strongest association (r = 0.94), followed in sequence by Na+ (r = 0.91), K+ (r = 0.82), and Ca2+ (r = 0.69), as depicted in Fig. 6b. Cl− and SO42− were identified as the anions most closely related to TDS, with correlation coefficients of 0.95 and 0.86, respectively, exhibiting a similar trend observed in pore groundwater. Notably, HCO3− demonstrated a moderate positive correlation with TDS, as well as the major anions and cations, displaying the highest positive correlation coefficient of 0.70 with Ca2⁺. This strongly suggests water–rock interactions during the percolation of groundwater through bedrock. In contrast, a moderate negative correlation was observed between HCO3− and TDS, Na⁺, and Cl− in pore groundwater samples, with correlation coefficients of − 0.44, − 0.43, and − 0.44, respectively. These findings imply that the influx of freshwater, potentially derived from bedrock areas, is a pivotal element in the attenuation of groundwater salinization.
The results of the correlation coefficients for various parameters in 26 surface water and 2 seawater samples are presented in Fig. 6c. The order of correlation with TDS for cations was Na+ (r = 1.00) > Mg2+ (r = 0.98) > K+ (r = 0.89) > Ca2+ (r = 0.81), while for anions, it was Cl− (r = 1.00) > SO42− (r = 0.98) > NO3− (r = 0.17) > HCO3− (r = − 0.18). Collectively, these features were broadly similar to those observed in the pore groundwater. It is noteworthy that the elevation at which the surface water samples were collected (SE) exhibited a moderate negative correlation with TDS, EC, and the major ions. Specifically, the correlation coefficients between SE and TDS, Na+ and Cl− were − 0.47, − 0.48, and − 0.48, respectively. This indicates that surface waters at lower elevations were prone to higher levels of mineralization and salinity. Additionally, the correlations between pH and both TDS and EC were nearly moderate, with correlation coefficients of 0.36 and 0.35, respectively. However, this trend was not mirrored in the groundwater, which exhibited only weak correlations among SE, pH, and other parameters.
Comparing the correlation coefficient matrices of different sample groups presented in Fig. 6 yielded further valuable insights. The correlation coefficients for Na+ and Cl− were highest in surface water, with r = 1, followed by those in pore groundwater (r = 0.98) and fracture groundwater (r = 0.92). In light of this, we propose a hypothesis that the ordering of these correlation coefficients may indicate potential pathways of seawater intrusion, such that surface water may infiltrate into pore water, thereby affecting fracture groundwater. This inference awaits support from additional evidence, including isotopic signatures and field investigations28,58. NO3− was not distinctly related to any other hydrogeochemical variables, invariably pointing towards the influence of widespread anthropogenic activities on the water quality59,60,61. The correlation coefficient between K+ and Cl− in fracture groundwater (r = 0.84) was significantly higher than that in pore groundwater (r = 0.69). This discrepancy hints at the possibility of more intensive use of potassium fertilizers in the bedrock region, which is a sign of more pronounced agricultural activities62.
Stable isotopic signatures
The isotopic signatures of hydrogen and oxygen in precipitation, serving as pivotal indicators of hydrological phenomena, are commonly employed to pinpoint probable zones of groundwater recharge and to assess the origins and sinks of contaminants within the groundwater system63. The stable isotope values of mixed seawater, sampled from JZB inshore, varied from − 54.53 to − 30.36‰ in δ2H and from − 7.24 to − 3.91‰ in δ18O. In contrast, seawater samples collected from the central region of Jiaozhou Bay exhibited values of -19.89‰ for δ2H and − 2.24‰ for δ18O64. The above values are all lower than those of the δ2H and δ18O values of standard seawater (both being 0), suggesting that these seawater samples, collected from the coastal line of Jiaozhou Bay have been influenced by the mixing of river recharge17. The isotopic compositions of δ2H and δ18O in the pore groundwater samples range from − 53.48 to − 10.29‰ and − 7.62 to − 0.80‰, with mean values of − 36.51 and − 4.75‰, respectively. In contrast, the δ2H values in the fracture groundwater samples span from − 62.82 to − 48.25‰, averaging at − 54.67‰, while δ18O values fall between − 8.70 and − 6.63‰, with a mean value of − 7.53‰. Notably, the δ2H and δ18O values exhibit a significant degree of variability, particularly in the pore groundwater samples. It is noteworthy that the δ2H and δ18O values of the samples display a considerable degree of variability, particularly among the pore groundwater samples, despite the fact that they were all sampled during the rainy season of 2020.
There is an absence of long-term monitoring data for stable isotopes in precipitation in NCRJB. Our research selects the atmospheric precipitation line from the Dagu River Basin22, which is located about 15 km from the center of the study area, to represent the local meteoric water line (LMWL) for NCRJB:
while the global meteoric water line (GMWL) is shown in Eq. (8) 65:
The locations of all surface and groundwater samples situated in close proximity to the right-hand side of the GMWL and LMWL (Fig. 7), indicating that they predominantly originate from precipitation infiltration and have been subject to a degree of evaporation during their runoff process. The SWD13 sample, situated near the seawater samples from Jiaozhou Bay, as seen in Fig. 7a, suggesting that the downstream region of the Hongjiang River may be influenced by seawater mixing. This potential influence can be attributed to seawater intrusion resulting from tidal actions or other factors. In Fig. 7b, samples M1 and M14 exhibit lower δ2H and δ18O values and are positioned closely, showing fissure aquifers water in their vicinity receive stable and short-path atmospheric precipitation recharge. Advancing upward along the GMWL and LMWL, a mixing zone is observable, composed of fracture groundwater samples represented by M3 and M12, as well as pore groundwater samples such as M7, M8, and M9. In terms of geospatial distribution, the sampling locations for these specimens are not far apart, and most of them are situated around the junction zone between the pore aquifer and the bedrock fissure aquifer. This distribution signifies the existence of hydraulic connectivity between the two aquifers. Both the groundwater flow and recharge occurring between two aquifers, as well as seawater intrusion driven by hydraulic forces, may potentially result in the exchange of groundwater between these aquifers, subsequently leading to the formation of the aforementioned mixing zone. The final observation pertains to the distribution zone of pore groundwater comprising samples such as M2, M6, and M21. Notably, the samples located in this region exhibit a considerable deviation below the GMWL, showing a significantly lower deuterium excess value compared to the GMWL (10‰). Furthermore, samples M6, M10, and M13 are positioned close to standard seawater. Hence, we believe that intense evaporation and the seawater influence play a crucial role in the hydrochemical evolution of pore groundwater in the NCRJB, based on the above findings66.
δ2H versus δ18O for water samples in NCRJB: (a) surface water and inshore mixed seawater of JZB; (b) pore groundwater and fracture groundwater. Note: the date of sample JZB4 was cited from Chen et al.64.
Water quality assessment
Groundwater evaluation for drinking purposes
The WQI classification scheme proposed by Sahu and Sikdar67 was utilized to delineate the threshold values deemed acceptable for potable purposes. As shown in Table 3, this classification system categorizes water quality into the following five tiers: excellent (WQI < 50), good (50 ≤ WQI < 100), poor water (100 ≤ WQI < 200), very poor (200 ≤ WQI < 300), and unsuitable for drinking (WQI ≥ 300).
In the study area, the WQI values for pore groundwater range from 220.50 to 5929.91, with an average value of 1986.95. All samples of pore groundwater were categorized as “very poor” or "unsuitable for drinking" accounting for 10.64% and 89.36% of the samples, respectively. This signifies a severe degree of salinization in pore groundwater, rendering almost all of it unfit for human drinking purposes. In contrast, the WQI scores for fracture groundwater varied between 47.59 and 446.83, averaging 151.66, indicating a significantly better water quality compared to pore groundwater. Nevertheless, it is regrettable to note that the proportion of samples classified as “excellent” and “good” was relatively small, comprising 2.5% and 20% of the total fracture groundwater samples. Additionally, 12.5% and 5.0% of the samples were classified as “very poor” and "unsuitable for drinking". This indicates that fracture groundwater has also been impacted by factors such as water–rock interaction and groundwater salinization, or faces a potential risk of severe pollution.
The spatial maps derived from the WQI values can offer a comprehensive and holistic perspective on the understanding of the spatial distribution and variability of groundwater quality across NCRJB. Considering the considerable variation in the WQI values of groundwater within the study area, the spatial WQI maps depicting four different years have been systematically classified into seven distinct regions: WQI < 50, 50 ≤ WQI < 100, 100 ≤ WQI < 200, 200 ≤ WQI < 300, 300 ≤ WQI < 500, 500 ≤ WQI < 1000, and WQI ≥ 1000. This stratification can facilitate a detailed analysis and interpretation of the spatial patterns and gradients in WQI value.
As evident from Fig. 8, the groundwater quality in the eastern and southwestern regions of the study area is exceedingly poor, with WQI values generally exceeding 1000, regardless of whether it is the wet or dry season. Specifically, during January to February of the dry season in 2021, WQI values surpassed 500 in most areas, with the exception of a few regions in the southern and western parts of NCRJB. It is noteworthy that this dire situation appears to have been significantly alleviated during the wet season of 2023, with areas with WQI values above 1000 reduced by more than half compared to the 2021 wet season. Additionally, there has been a remarkable increase in the number of areas with WQI values below 100. On all four maps, these regions are predominantly located in the western and northern areas, that are farther from the coastline of Jiaozhou Bay, as well as in the higher-lying central and southern regions. Areas closer proximity to the coastline or at lower elevations tend to exhibit higher WQI values and poorer groundwater quality. By synthesizing the available data, we have compelling reasons for suspecting that that seawater intrusion is likely responsible for the observed spatial distribution pattern of WQI values.
Water evaluation for agricultural irrigation purposes
The irrigation system plays a pivotal role in determining the quantity and intensity of crop production, with a profound reliance on groundwater and surface sources68. More significantly, the quality and mineral composition of this irrigation water significantly impact both the soil and plant health69. To elucidate the suitability of surface water and groundwater for agricultural irrigation in NCRJB, both the EC and sodium adsorption ratio (SAR) parameters were employed to construct USSL diagram70, as depicted in Fig. 9 for wet and dry season.
USSL diagram is delineated into a 4 × 4 grid based on the SAR and EC values. EC values, indicative of the water salinity hazard for crops, are categorized into four sub-regions: low salinity (C1, EC < 250 μS/cm), medium salinity (C2, 250 μS/cm ≤ EC < 750 μS/cm), high salinity (C3, 750 μS/cm ≤ EC < 2250 μS/cm), and very high salinity (C4, EC ≥ 2250 μS/cm). The SAR values, which reflect the potential water sodium (alkali) risk to crops, are similarly classified into four sub-regions: low sodium (S1, SAR < 10), medium sodium (S2, 10 ≤ SAR < 18), high sodium (S3, 18 ≤ SAR < 26), and very high sodium (S4, SAR ≥ 26). As illustrated in Fig. 9a, during the wet season, 75 percent of the fractured groundwater is situated within the field C3S1. This classification designates a water category characterized by high salinity yet low sodium content, which renders it suitable for irrigation across a wide range of soil types, owing to the negligible risk posed by exchangeable sodium. However, considering the osmotic effects and the potential impact of elevated salinity on crop health and the likelihood of nutrient disorders, it is advisable to utilize this type of water primarily for well-drained soils or irrigating crops with moderate salt tolerance71. Furthermore, 16.67% of the fissured groundwater is categorized within the C4S1 zone, while 4.16% is distributed across both the C4S2 and C3S2 zones. These types of water are not suitable for the practice of irrigated agriculture.
The majority of pore groundwater and surface water samples, characterized by their high Electric Conductivity (EC) values and elevated sodium (Na+) ion concentrations, are classified within the C4S3 and C4S4 zones, irrespective of the wet or dry season. At identical locations, the irrigation suitability of these water samples during the wet season was slightly enhanced compared to the dry season; particularly for surface water, approximately 60% of samples are situated in the C4S2–C4S3 zones during the wet season, whereas this proportion drops to 22.2% in the dry season. This discrepancy may be attributed to the pronounced dilution effect characteristic of frequent rainfall during the wet season72. Despite the dilution effects of rainfall, the unsuitable nature of pore groundwater and surface water in this region remains unchanged. Especially during the dry season, the near-totality of pore groundwater samples is found within the C4S4 zone, which is indicative of their very poor suitability for irrigation.
Discussion
Assessment of seawater intrusion based on HFE-D
As mentioned earlier, the main factor contributing to degradation of groundwater quality in NCRJB is likely to be the mixing of fresh and saline water caused by seawater intrusion. However, Piper diagrams do not permit detailed assessment and sequence of facies during the intrusion process55,73. The Hydrogeological facies evolution diagrams (HFE-D), originally conceptualized and further elaborated by Giménez‐Forcada4,37, present a novel graphical perspective that facilitates the scrutiny of hydrogeochemical transitions within coastal aquifers, particularly those undergoing recurrent cycles of freshwater influx and salinization. Hence, we have employed the HFE-D to provide a more comprehensive understanding of the mechanisms and dynamics underlying seawater intrusion in NCRJB.
The groundwater and surface samples, collected during both wet and dry seasons, are illustrated in Fig. 10 according to various zones within the HFED, while Tables 4 and 5 statistic the percentages of hydrochemistry facies and sub stage identified in each sampling set. Based on the sub-stages defined by the HFE-D framework, the data were converted into zoning maps utilizing the inverse distance weighted (IDW) interpolation method provided by ArcGIS. Figure 11 illustrates the spatiotemporal variations of desalination and intrusion conditions in the NCRJB region across four sampling time points. For pore groundwater taken during the wet season, as seen in Fig. 10a, four hydrochemical facies are recognized, 29.2% corresponding to freshening stages and 70.8% to facies of the intrusion stages. The largest percentage (66.67%) is represented by the i4 + SW sub-stage, followed by 20.83% of the samples in the f1 phase of initial freshening. This result reveals that the pore groundwater aquifer in NCRJB has suffered significant and extensive salinization. In Fig. 10a, the M9 site, located approximately 150 m away from the Xiangmao River, has captured our attention. Pore groundwater collected in M9 was observed to be in the advanced freshening stages f2 and f3 during the wet seasons of 2020 and 2023, respectively. This may be attributed to the abundant flow of the Xiangmao River during the wet season, which has likely contributed to the advancement of the freshening efforts. Driven by concentration gradient effect, Na+ and Cl− diffused from the groundwater with higher concentration at site M9 to the surface water of Xiangmao River with lower concentration.
Correspondingly, the fracture groundwater samples collected during the rainy season exhibited a more diverse array of hydrochemical facies: a total of seven chemical phases were confirmed, with 41.7% of the samples in the freshening stage and 58.3% in the intrusion stage. When the bedrock fissure aquifer is filled with fresh Ca-HCO3 water (represented by the SWD55 sample, which is furthest from the coastline), the water increasingly progresses through substage i1, represented Ca-MixHCO3 facies of the distal intrusion (represented by samples M1, M12, M14, M17). Subsequently, the water transitioned to the ‘i2’ substage (represented by samples SW09, SW10, M20). As reverse cation exchange continues, the water evolves into the i3 substage (No samples are located within this specified region i3, although samples SWD09, SWD10, and SWD47 are situated in proximity to the boundary between i2 and i3. These intrusion phases observed in HFE-D, denoted an escalation in Total Dissolved Solids (TDS) as Ca2+ and Mg2+ are progressively replaced by Na+ and K+ in the groundwater, a consequence of the indirect cation exchange mechanism74,75. The hydrogeochemical Piper diagrams and statistical outcomes presented in Section "Results" also corroborate the perspectives. Together these data imply that fracture groundwater from NCRJB evolves from Ca-HCO3 mixed type waters in the northwest and south to more Na-rich waters in the east.
During the dry season, the proportion of pore and fracture groundwater samples in the intrusion stage reached 82.61% and 81.25%, respectively, marking an increase of 11.81% and 22.91% compared to the wet season ratios. Seawater intrusion appears to have advanced further, particularly in the case of fractured aquifers. For instance, 43.75% and 6.25% of the samples are in the i3 and i4 substages, significantly exceeding the proportions of those in the i1 (18.75%) and i2 (6.25%) substages. Additionally, fracture groundwater sampling points that were in the i1 stage during the rainy season have progressed to the mid-stages of seawater influence, i2 and i3, during the dry season (as exemplified by samples M12, M14, M17). The spatial distribution map of HFE diagram sub-stages reveals that during the dry season, the eastern and southern regions adjacent to Jiaozhou Bay are in the intrusion stages, which is particularly evident in the dry season of 2024. Concurrently, the hydrochemical facies begin to evolve from the Ca-Mix-HCO3 facies through the Ca-Mix-Cl facies towards the Ca–Cl facies., which can also be corroborated by the Piper diagram. This comparison emphasizes that the chronic progression of hydrochemistry indicators predominantly ascended an ascent during the dry season and descended during the wet season, thereby reflecting the impacts of rainfall infiltration and evaporative processes76,77. Notably, this trend is particularly evident in the Na and Cl ions, which are indicative of seawater intrusion. These findings can also be substantiated by the results of descriptive statistics analysis and Piper tri-line diagram in Section "Chemical composition statistics of surface water bodies and groundwater in NCRJB".
Contrasting with the patterns identified in the groundwater samples, the full complement of 26 surface water samples was classified within the Na-Cl facies, demonstrates an absence of pronounced seasonal variation. This outcome aligns with the categorizations delineated by the Piper diagram presented in Fig. 4. Most of surface water samples were proximate to the conservative mixing line, suggesting a potential blending of seawater and freshwater55. With majority of the 26 surface water samples collected during the rainy season, the copious rainfall and substantial surface runoff tended to drive these samples towards the freshening phase. More precisely, these samples are predominantly situated in the vicinity of, yet above (to the left of), the conservative mixing line in Fig. 10c. This distribution may be attributed to the fact that majority of the surface water samples were collected during the rainy season, where the confluence of substantial rainfall and surface runoff exerts a combined influence, steering these samples towards a phase of dilution and freshening. However, the actual efficacy of these processes is limited, with only the SWD07 and SWD39 samples advancing to the initial freshening substage f1, while the SWD35 sample is positioned at the threshold between f1 and the i4 (seawater) stage. All three of the mentioned above samples were collected during the rainy season, and the sampling sites are all located at the positions furthest from the coastline within their respective surface water bodies (SWD35 is located in the upper reaches of the Xiangmao River, SWD39 in the mid-upper reaches of the Hongjiang River, and SWD07 in the upstream headwater area of the Hulu River. These findings suggest that surface water is likely the principal conduit for seawater intrusion. In section "Correlation analysis", it was discovered that the correlation coefficients for Na+ and Cl− ions were most pronounced in surface water, reaching an r-value of 1, surpassing those found in pore groundwater (r = 0.98) and fracture groundwater (r = 0.92). In conclusion, seawater intrusion is highly likely to have penetrated the NCRJB region through the surface water network, progressing from downstream to midstream and upstream areas, with this process being especially pronounced during the dry season. Both natural and anthropogenic factors may have contributed to this issue as driving forces.
Further findings from site investigations of seawater intrusion
Field investigations are of paramount importance in the fields of aquatic environmental and pollution research, including the study of seawater intrusion. They play a crucial role in identifying the sources of pollutants, tracking the vectors of environmental degradation, and assessing the impact of both anthropogenic and natural processes on groundwater systems79. Furthermore, the empirical evidence garnered from field studies is instrumental in refining predictive models, crafting informed policy, and underpinning the development of targeted remediation. In this study, we devoted considerable time and effort to conducting field investigations having three primary objectives: (a) to gather further evidence and data regarding seawater intrusion and the degradation of groundwater quality in the NCRJB area; (b) to explore and analyze the underlying causes of the degradation of groundwater quality in NCRJB, thereby validating the rationality of our research inferences and conclusions; (c) to provide a basis for the formulation of policies and measures for local water environmental protection. Prior to systematic field investigations, we initially collected and analyzed local remote sensing and topographic map data.
The estuarine regions of the main rivers in the study area, where they flow into the Jiaozhou Bay, were prioritized for field investigation. At the estuary of the Xiangmao River (Fig. 12a), a dam with a width of approximately 138 m was constructed by the local government in 2011, primarily for flood relief purposes in the upstream area of the river. During two field surveys conducted in August 2020 and February 2021, we observed that the water level within the dam at the Xiangmao River was about 1.7 m and 1.4 m higher than that of the seawater in the Jiaozhou Bay. Notably, despite the dry season with scarce rainfall, the water volume downstream of the Xiangmao River remained abundant, exhibiting no significant variation compared to the rainy season, which piqued our interest. Subsequently, we collected samples from both the river water within the dam and the seawater outside the dam and conducted on-site measurements, finding that the EC values of the two were quite similar; especially in the dry season, the electrical conductivity of the samples within the dam was only about 15% lower than that of the samples outside the dam. Field personnel reported that when the water level of the Xiangmao River is low during the dry season, the field personnel were instructed to open the sluice gates during the high tide in Jiaozhou Bay, allowing the seawater to flow back into the Xiangmao River to replenish its water volume. Although the mixed saline water has limited usage, it can still provide water for landscape maintenance during the dry season. Additionally, this measure further enhances the attractiveness of local urban landscapes, contributing to the city’s image and real estate sales. This assertion was subsequently validated in the investigation conducted on the tributaries of the Xiangmao River (Fig. 12d). Field personnel, driven by convenience and the desire to economize on water usage costs, have been extracting surface water directly from the river’s tributaries for irrigation purposes in the adjacent landscaping operations. This finding from our field investigation regarding the anthropogenic introduction of seawater was unexpected. Correspondingly, the situation of Hongjiang River is not optimistic. Within the scope of this research, we did not find hydraulic structures designed to prevent seawater intrusion through the river channel. Despite the presence of numerous highway bridges spanning the river, they are devoid of any accompanying hydraulic facilities. We consistently documented instances of seawater making incursions into the channel of the Hongjiang River during our field investigations course, propelled by forces of tidal activity (Fig. 12b). This recurrent observation underscores the dynamic interplay between tidal fluctuations and the river’s vulnerability to seawater intrusion. This finding can account for the transition in water type of the fissured groundwater samples observed in the Piper diagram during the dry season, from a Ca–Cl type to a mixed Na–Ca–Cl type. In addition, this finding may also corroborate the recharge relationship between surface water, seawater and groundwater revealed by the isotopic analyses in Sect. "Stable isotopic signatures".
Location and summary of key field empirical investigation points related to seawater intrusion: (a) artificial introduction of seawater; (b) lack of water infrastructure to prevent seawater intrusion; (c) utilization of high-salinity surface water mixed with seawater for aquaculture; (d) widespread extraction of surface water for irrigation of landscaped green spaces; (e) alarming large-scale extraction and discharge of groundwater associated with construction projects; (f) unregulated extraction of groundwater for agricultural production.
As we ventured upstream along the surface water bodies towards the inland areas more crucial evidence were identified. Along the rivers that flow into the Haiyue Lake, we discovered dozens of shrimp ponds. These ponds vary in size from several hundred to several thousand square meters, with depths typically ranging from 0.8 to 4.0 m, and are primarily used for the cultivation of prawns, oysters, and fish. As depicted in Fig. 12c, these shrimp ponds are constructed adjacent to the surface water systems flowing towards Jiaozhou Bay, typically elevated by 0.5–1.5 m above them. We consulted with local shrimp farmers and learned that the ponds require stringent water quality and salinity management to optimize shrimp growth and disease prevention. The local surface water bodies that feed into Jiaozhou Bay serve as their primary source for the purpose of obtaining fresh, high-salinity water and discharging waste. They employ various methods, including water pumps for extraction, and the production and storage of saline water, ensure a year-round supply of fresh brackish surface water mixed with seawater. In theoretical terms, shrimp ponds act as repositories of saline water that overlay arable land. The denser pond water can permeate the soil strata and mingle with the fresher groundwater beneath. Furthermore, shrimp ponds may alter the properties of the coastal groundwater associated seepage. This phenomenon has come to light as a previously underappreciated factor exacerbating groundwater salinization9. Furthermore, significant differences in pH values among various sample groups were observed in Section "General hydrogeochemistry". The widespread presence of shrimp ponds, both currently and historically, may also be a crucial factor contributing to the higher pH values in the pore aquifer. This is because an alkaline aquaculture environment is more conducive to the reproduction and growth of fish and shrimp. Considering environmental preservation, the local government has recently refrained from endorsing and imposed restrictions on such inefficient aquaculture methods. Nonetheless, our investigation has alarmingly revealed that the phenomenon of private shrimp ponds is still prevalent in the central and southern regions of the study area.
Our field investigation also exposed the profound impact of construction projects and agricultural production on the local groundwater environment. Numerous ongoing construction projects were observed in the eastern and central parts of the study area. These construction projects inevitably involve excavation of foundation pits and reduction of groundwater levels at the site (Fig. 12e), due to the demand for underground space. Alarmingly, the groundwater extracted from the pits has been mostly discharged directly into the stormwater and sewage pipes, eventually flowing into the ocean. This could partially explain the formation of groundwater funnel areas in the eastern part of the study area48. Finally, we observed a prevalence of unauthorized construction of motorized wells in the bedrock fissure groundwater region of the surveyed area (Fig. 12f). These wells typically range in size diameter from 30 to 50 cm, with depths varying from tens to hundreds of meters. Despite the limitations on the suitability of groundwater for drinking and irrigation use as outlined in Section "Water quality assessment", residents remain enthusiastic about setting up private motorized wells. A concerning aspect is the absence of regulatory oversight in the construction of these wells and the ensuing unregulated tapping of groundwater resources, which may precipitate a series of complications, such as groundwater contamination and the escalation of water scarcity80. Furthermore, we observed that local farmers frequently employ potassium fertilizers and manure in their farmland. The resulting pollution is likely the underlying cause for the marked difference in K+ and NO3− ion concentrations observed in the fractured groundwater samples compared to those in other groups. In summary, the issues and evidence uncovered through our field investigation undoubtedly exacerbate the strain on local groundwater resources, further intensifying the severity of seawater intrusion.
Identified environmental problems and recommendations for countermeasures
In summary, natural factors such as the coastal environment, seasonal precipitation-evaporation dynamics, and water–rock interactions play a pivotal role in driving the local hydrogeochemical processes. Conversely, the complex array of anthropogenic activities involving multiple factors, including agricultural production, aquaculture, urban maintenance, large-scale construction projects, and the absence of water management oversight, have led to the severe issue of groundwater salinization. All the hydrogeochemistry evidence and insights obtained from general hydrogeochemical analysis, MSVA, isotopic analysis, and field investigations in this study have been integrated into the model presented in Fig. 13. This comprehensive model will aid local governments and management agencies in gaining a clearer understanding of the escalating deterioration of the groundwater conditions in the area.
NCRJB exhibits intricate geographical and socio-economic dynamics, ranging from urban residential sectors to aquaculture, industrial, and agricultural zones, extending from coastal belts to inland expanses. In pursuit of sustainable development for NCRJB, it is imperative to devise and propose pertinent policy directives tailored to local administrators and residents. The immediate priority is to effectively block the inflow of seawater from Jiaozhou Bay into the inland areas along the surface water systems. The deliberate introduction of seawater into the downstream dam of the Xiangmao River must be strictly prohibited, despite the potential shortage of urban landscape water that may arise from this measure. Alternative solutions such as adopting sponge city transformation in the built-up areas and constructing water storage facilities in the undeveloped regions should be considered81. Furthermore, it is recommended that a hydraulic facility be planned and constructed in the downstream region of the Hongjiang River, to address the situation where seawater intrudes inland during high tide.
Secondly, targeted measures should be taken to address environmental issues stemming from aquaculture and agricultural production. For local governments, guiding the scattered individual farmers to establish cooperative alliances may be highly necessary. The purpose of this initiative is to employ advanced and efficient aquaculture technologies for the preparation of high-salinity brackish water and the centralized treatment of production wastewater, ultimately achieving the goal of strictly controlling the unauthorized extraction of seawater and the discharge of sewage through surface water systems. Furthermore, the indiscriminate exploitation and inefficient use of groundwater undoubtedly exacerbate the hazard of seawater intrusion. Therefore, the act of arbitrarily drilling wells to extract groundwater must be prohibited. Moreover, it is essential to institute integrated management for surface water and groundwater, with rational planning of water resource use and control over the use of nitrogen fertilizers and manure that pollute the environment. For groundwater that has undergone high salinity salinization, freshwater replacement remediation measures can be adopted. The extracted saline groundwater, once treated, can find versatile applications, including irrigation of salt-tolerant crops, industrial production processes, and the exploitation of saline water resources. This approach not only addresses the issue of saline groundwater but also fosters sustainable water utilization practices.
Ultimately, there is a pressing need for local authorities to enhance investments in water environmental regular monitoring and sampling analysis. This is not only essential for the scientific management of local water resources but also provides a basis for future governance of seawater intrusion disasters. Although more than 16 groundwater monitoring stations have been established, there are no surface water monitoring stations in place. Given the close relationship between surface water and groundwater, it is highly necessary to establish surface water monitoring stations as soon as possible. Notably, the eastern region of the study area faces a severe degree of groundwater salinization, with some groundwater exceeding seawater salinity, likely due to the combined effect of long-term and complex factors. Pending further in-depth investigations into groundwater salinization and the implementation of effective management measures, it is advisable to restrict large-scale engineering projects, aquaculture, and agricultural activities in this region to prevent further deterioration of the groundwater environment.
Conclusions
In the present study, a comprehensive approach, integrating hydrogeological assessments, multivariate statistical analyses, and field-based empirical studies, was utilized to delineate the spatial distribution of water chemistry and identify the key determinants within the NCRJB. The statistical results of the chemical composition indicated that all surface water and pore groundwater samples were categorized as Na-Cl type, with a general cation abundance order of Na+ > Mg2+ > Ca2+ > K+, and the anions were predominantly present in the sequence of Cl− > SO42− > HCO3− > NO3−. Accordingly, the majority of the fractured groundwater samples (65.85%) were classified as mixed types, with the dominant ion order being Ca2+ > Na+ > Mg2+ > K+ for cations and Cl− > HCO3− > SO42− > NO3− for anions. Furthermore, PCA had uncovered three principal components within the composition of surface and groundwater samples in the study area: the first component, accounting for 58.66% of the variance, indicated the influence of seawater intrusion; the second component, contributing 13.11% of the variance, reflected the impact of anthropogenic activities; and the third component, with a variance value of 8.34%, was primarily driven by the infiltration of recharge water and water–rock interactions. Insights can be inferred into the progression of seawater intrusion from surface water through porous aquifer and ultimately into the fractured aquifer, by analyzing the correlation coefficient matrices of samples from different groups. The examination of the stable isotopes δ2H and δ18O had furnished compelling evidence that both evaporation and seawater intrusion were pivotal in shaping the hydrochemistry evolution of the groundwater within the NCRJB area. The HFE diagrams illustrated the distinct compositional stages of the freshwater phase and the seawater intrusion phase within the coastal aquifer, further corroborating the occurrence of seawater intrusion in the study area. Indeed, during the wet season, 70.8% of the pore groundwater samples and 58.3% of the fractured groundwater samples were identified as being in the seawater intrusion phase. These percentages escalated to 82.61% and 81.25% respectively during the dry season. Field empirical investigations unveiled the profound impact of anthropogenic factors such as urban construction and agricultural production on the local groundwater environment, and further validate the results derived from hydrogeological, multivariate statistical analyses and isotopic approach.
As far as the suitability of groundwater for drinking purposes is concerned, calculated results and spatial distribution maps for WQI revealed that pore aquifer of NCRJB ranged from “very poor” to "unfit for drinking", while only 22.5% of the samples in the fractured aquifer fall within the “excellent” or “good” categories. The USSL diagrams have shown the pore groundwater and surface water in the NCRJB region exhibit poor suitability for irrigation purposes, due to the elevated EC values. Our findings highlighted that the long-term shifts in hydrochemistry properties, along with the latent threat of seawater intrusion, exhibit an upward trend during the dry season and a certain degree of mitigation during the rainy season. This dynamic pattern distinctly points to the pronounced impact of precipitation infiltration and evaporation processes. The outcomes and local environmental strategies presented in our study are of paramount importance to local government agencies, water resource managers, residents, and other stakeholders. They can use this information to formulate better plans for the sustainable management of the vital groundwater resources in the NCRJB region, in light of climate change, human activities, and urban development. The comprehensive approach holds significant potential, with a particular emphasis on the crucial role of empirical investigation, making it amenable to broader application in other coastal areas of China and beyond.
Moving forward, we intend to continuously collect and analyze additional samples, and gather experimental data on groundwater and surface water over the past 10–20 years, with the aim of better revealing the historical progression of groundwater chemical evolution. This work will also contribute to elucidating the historical reasons behind the observed salinization of groundwater in the eastern part of the study area, where salinity levels are found to exceed those of seawater. Additionally, we will develop a three-dimensional geological model for seawater intrusion in the study region, which includes an enhanced evaluation model and a predictive model. These models aim to further elucidate the primary factors that will drive the chemical evolution of groundwater in the NCRJB area in the future.
Data availability
Data will be made available on request, further inquiries can be directed to the corresponding author.
References
Jaramillo, F. & Destouni, G. Local flow regulation and irrigation raise global human water consumption and footprint. Science 350, 1248–1251 (2015).
Destouni, G. & Prieto, C. Robust assessment of uncertain freshwater changes: The case of greece with large irrigation—and climate-driven runoff decrease. Water 10, 1645 (2018).
Castelletti, A. et al. Model Predictive Control of water resources systems: A review and research agenda. Annu. Rev. Control 55, 442–465 (2023).
Giménez-Forcada, E. Use of the Hydrochemical Facies Diagram (HFE-D) for the evaluation of salinization by seawater intrusion in the coastal Oropesa Plain: Comparative analysis with the coastal Vinaroz Plain Spain. HydroResearch 2, 76–84 (2019).
Kim, C. S., Kim, J., Lim, H., Jeong, Y. & Park, K. S. Coastal water quality modeling in Tidal lake: Revisited with groundwater intrusion. J. Coast. Res. 75, 1342–1346 (2016).
Jung, H., Ha, K., Koh, D.-C., Kim, Y. & Lee, J. Statistical analysis relating variations in groundwater level to droughts on Jeju Island Korea. J. Hydrol. Region. Stud. 36, 100879 (2021).
Zhang, X., Qi, L., Li, W., Hu, B. X. & Dai, Z. Bacterial community variations with salinity in the saltwater-intruded estuarine aquifer. Sci. Total Environ. 755, 142423 (2021).
Abd-Elaty, I. & Zelenakova, M. Saltwater intrusion management in shallow and deep coastal aquifers for high aridity regions. J. Hydrol. Region. Stud. 40, 101026 (2022).
Hou, Y. et al. Impacts of coastal shrimp ponds on saltwater intrusion and submarine groundwater discharge. Water Resour. Res. 58 (2022).
Tang, G. et al. A new idea for predicting and managing seawater intrusion in coastal channels of the Pearl River China. J. Hydrol. 590, 125454 (2020).
Rudnik, G., Rabinovich, A., Siebner, H., Katz, Y. & Kurtzman, D. Exploring predictive uncertainty at a double‐source managed aquifer recharge site via stochastic modeling. Water Resour. Res. 58, (2022).
Weymer, B. A. et al. The coastal transition zone is an underexplored frontier in hydrology and geoscience. Commun. Earth Environ. 3, 323 (2022).
Thabrez, M. & Parimalarenganayaki, S. Assessment of hydrogeochemical characteristics and seawater intrusion in coastal parts of Mangaluru City, Karnataka India. Water Air Soil Pollut. 234, 251 (2023).
Landar, A. Q., Jahangir, T. M., Khuhawar, M. Y., Lanjwani, M. F. & Khuhawar, F. Y. Evaluation of water quality of groundwater of Sanghar District, Sindh, Pakistan: chemical and multivariate analysis. Water 16, 856 (2024).
Xaza, A., Mapoma, H. W. T., Abiye, T. A., Clarke, S. & Kanyerere, T. Investigating seawater intrusion in Republic of South Africa’s Heuningnes, Cape Agulhas using hydrogeochemistry and seawater fraction techniques. Water 15, 2141 (2023).
Choi, H. et al. Assessment of spatio-temporal variations in groundwater quality for the groundwater-dependent Maltese islands. J. Hydrol. Region. Stud. 54, 101875 (2024).
Khangembam, S. & Singh, K. K. Evaluation of hydrochemical facies along the flow path and geomorphic surfaces in a Quaternary Alluvial plain of Barak Valley of Northeast India. Arab. J. Geosci. 14, 1348 (2021).
Yang, F. et al. Hydrochemical characteristics and functions of groundwater in southern Laizhou Bay based on the multivariate statistical analysis approach. Estuarine Coast. Shelf Sci. 250, 107153 (2021).
Kazapoe, R. W., Addai, M. O., Amuah, E. E. Y. & Dankwa, P. Hydrogeochemical characterization of groundwater in the Wassa Amenfi East and Prestea-Huni Valley areas of southern Ghana using GIS-based and multivariate statistical techniques. Sustain. Water Resour. Manag. 9, 141 (2023).
Manu, E., De Lucia, M. & Kühn, M. Hydrochemical characterization of surface water and groundwater in the crystalline basement aquifer system in the Pra Basin (Ghana). Water 15, 1325 (2023).
Xie, R. C. et al. Isotopic evidence for complex biogeochemical cycling of Cd in the eastern tropical South Pacific. Earth Planet. Sci. Lett. 512, 134–146 (2019).
Yin, Z., Luo, Q., Wu, J., Xu, S. & Wu, J. Identification of the long-term variations of groundwater and their governing factors based on hydrochemical and isotopic data in a river basin. J. Hydrol. 592, 125604 (2021).
Liu, X., Xiang, W., Song, J. & Si, B. Spatial variations in groundwater hydrochemistry, sources, and controls across catchments on Chinese Loess Plateau. J. Hydrol. Region. Stud. 53, 101791 (2024).
Varol, S. & Davraz, A. Evaluation of the groundwater quality with WQI (Water Quality Index) and multivariate analysis: A case study of the Tefenni plain (Burdur/Turkey). Environ. Earth Sci. 73, 1725–1744 (2015).
Idowu, T. E. et al. Integrated seawater intrusion and groundwater quality assessment of a coastal aquifer: GALDIT, geospatial and analytical approaches. Environ. Sci. Pollut. Res. 29, 36699–36720 (2022).
Nong, X., Shao, D., Zhong, H. & Liang, J. Evaluation of water quality in the South-to-North Water Diversion Project of China using the water quality index (WQI) method. Water Res. 178, 115781 (2020).
Zhang, D. et al. Global sensitivity analysis on a numerical model of seawater intrusion and its implications for coastal aquifer management: a case study in Dagu River Basin, Jiaozhou Bay China. Hydrogeol. J. 28, 2543–2557 (2020).
Gang, S., Jia, T., Deng, Y., Xing, L. & Gao, S. Hydrochemical characteristics and formation mechanism of groundwater in Qingdao City, Shandong Province China. Water 15, 1348 (2023).
Han, B. et al. Spatial distribution, source analysis, and ecological risk assessment of polycyclic aromatic hydrocarbons (PAHs) in the sediments from rivers emptying into Jiaozhou Bay China. Mar. Pollut. Bull. 168, 112394 (2021).
Ning, Z., Lin, M., Zhang, Y., Zhang, X. & Kong, X. Distribution of potential geological hazards and control factors in Qingdao offshore China. China Geol. 2, 40–48 (2019).
Ayach, M. et al. Groundwaters in the Auvergne-Rhône-Alpes Region, France: Grouping homogeneous groundwater bodies for optimized monitoring and protection. Water 16, 869 (2024).
Liu, Y. et al. Groundwater chemical characteristics and circulation mode in the Suixiao coal-mining district. QJEGH 53, 227–235 (2020).
Patel, D., Pamidimukkala, P. & Chakraborty, D. Groundwater quality evaluation of Narmada district, Gujarat using principal component analysis. Groundw. Sustain. Dev. 24, 101050 (2024).
Li, Z., Gao, X. & Lu, D. Correlation analysis and statistical assessment of early hydration characteristics and compressive strength for multi-composite cement paste. Constr. Build. Mater. 310, 125260 (2021).
Sadeghi, B. Chatterjee Correlation Coefficient: A robust alternative for classic correlation methods in geochemical studies- (including “TripleCpy” Python package). Ore Geol. Rev. 146, 104954 (2022).
Zhang, L. & Wang, L. Optimization of site investigation program for reliability assessment of undrained slope using Spearman rank correlation coefficient. Comput. Geotech. 155, 105208 (2023).
Giménez-Forcada, E. Dynamic of sea water interface using hydrochemical facies evolution diagram. Groundwater 48, 212–216 (2010).
Hamma, B. et al. Hydrochemical assessment of groundwater using multivariate statistical methods and water quality indices (WQIs). Appl. Water Sci. 14, 33 (2024).
Bahir, M., Ouazar, D., Ouhamdouch, S. & Zouari, K. Assessment of groundwater mineralization of alluvial coastal aquifer of essaouira basin (Morocco) using the hydrochemical facies evolution diagram (HFE-Diagram). Groundw. Sustain. Dev. 11, 100487 (2020).
Onwe, I. M., Eyankware, M. O., Obasi, P. N. & Ifeanyichukwu, K. A. Hydrochemical and statistical approaches in the evaluation of groundwater quality for drinking and irrigation uses around around Ezzangbo-Ngbo area Southeastern Nigeria. Model. Earth Syst. Environ. 9, 413–429 (2023).
Parisi, A., Alfio, M. R., Balacco, G., Güler, C. & Fidelibus, M. D. Analyzing spatial and temporal evolution of groundwater salinization through multivariate statistical analysis and hydrogeochemical facies evolution-diagram. Sci. Total Environ. 862, 160697 (2023).
Condon, L. E. et al. Global groundwater modeling and monitoring: opportunities and challenges. Water Resour. Res. 57, (2021).
WHO. Guidelines for drinking-water quality: fourth edition incorporating the first addendum (2017).
WHO. Hardness in Drinking-water: Background document for development of WHO Guidelines for Drinking-water Quality (2011).
Krishna Kumar, S., Logeshkumaran, A., Magesh, N. S., Godson, P. S. & Chandrasekar, N. Hydro-geochemistry and application of water quality index (WQI) for groundwater quality assessment, Anna Nagar, part of Chennai City, Tamil Nadu, India. Appl. Water Sci. 5, 335–343 (2015).
Shao, Y. et al. Hydrochemical characteristics and quality evaluation of irrigation and drinking water in Bangong co lake watershed in northwest Tibetan plateau. Water 15, 2655 (2023).
Diédhiou, M. et al. Hydrogeochemical appraisal of groundwater quality and its suitability for drinking and irrigation purposes in the west central Senegal. Water 15, 1772 (2023).
Chen, J., Yan, B., Xu, T. & Xia, F. Hydrochemical evolution characteristics and mechanism of groundwater funnel areas under artificial governance in Hengshui City North China. Ecol. Indic. 148, 110059 (2023).
Aladejana, J. A., Kalin, R. M., Sentenac, P. & Hassan, I. Groundwater quality index as a hydrochemical tool for monitoring saltwater intrusion into coastal freshwater aquifer of Eastern Dahomey Basin Southwestern Nigeria. Groundw. Sustain. Dev. 13, 100568 (2021).
Piper, A. M. A graphic procedure in the geochemical interpretation of water-analyses. Neurochem. Int. 6, 27–39 (1984).
Bauer, J. et al. Geochemistry and evolution of groundwater resources in the context of salinization and freshening in the southernmost Mekong Delta Vietnam. J. Hydrol. Region. Stud. 40, 101010 (2022).
Han, D., Post, V. E. A. & Song, X. Groundwater salinization processes and reversibility of seawater intrusion in coastal carbonate aquifers. J. Hydrol. 531, 1067–1080 (2015).
Kaiser, H. F. The application of electronic computers to factor analysis. Educ. Psychol. Meas. 20, 141–151 (1960).
Ahmed, A. H., Rayaleh, W. E., Zghibi, A. & Ouddane, B. Assessment of chemical quality of groundwater in coastal volcano-sedimentary aquifer of Djibouti, Horn of Africa. J. Afr. Earth Sci. 131, 284–300 (2017).
Sae-Ju, J., Chotpantarat, S. & Thitimakorn, T. Hydrochemical, geophysical and multivariate statistical investigation of the seawater intrusion in the coastal aquifer at Phetchaburi Province Thailand. J. Asian Earth Sci. 191, 104165 (2020).
Ilić, M. et al. Legume Fingerprinting through lipid composition: utilizing GC/MS with multivariate statistics. Foods 12, 4420 (2023).
Shin, K., Koh, D.-C., Jung, H. & Lee, J. The Hydrogeochemical Characteristics of Groundwater Subjected to Seawater Intrusion in the Archipelago Korea. Water 12, 1542 (2020).
Ahmed, A. T. & Askri, B. Seawater intrusion impacts on the water quality of the groundwater on the northwest coast of Oman. Water Environ. Res. 88, 732–740 (2016).
Wang, S. et al. Groundwater hydrochemical signatures, nitrate sources, and potential health risks in a typical karst catchment of North China using hydrochemistry and multiple stable isotopes. Environ. Geochem. Health 46, 173 (2024).
Wang, S. et al. Hydrochemical evolution characteristics, controlling factors, and high nitrate hazards of shallow groundwater in a typical agricultural area of Nansi Lake Basin North China. Environ. Res. 223, 115430 (2023).
Schmidt, C. E., Robinson, R. S., Fields, L. & Nixon, S. W. Changes to nitrate isotopic composition of wastewater treatment effluent and rivers after upgrades to tertiary treatment in the Narragansett Bay watershed. RI. Mar. Pollut. Bull. 104, 61–69 (2016).
Al Rawashdeh, R. World peak potash: An analytical study. Resour. Policy 69, 101834 (2020).
Han, D. M., Song, X. F., Currell, M. J., Yang, J. L. & Xiao, G. Q. Chemical and isotopic constraints on evolution of groundwater salinization in the coastal plain aquifer of Laizhou Bay China. J. Hydrol. 508, 12–27 (2014).
Chen, G. et al. Elucidating the pollution sources and groundwater evolution in typical seawater intrusion areas using hydrochemical and environmental stable isotope technique: A case study for Shandong province China. Lithosphere 2021, 4227303 (2021).
Craig, H. Isotopic variations in meteoric waters. Science 133, 1702–1703 (1961).
Gomes, O. V. O. et al. Origin of salinity and hydrogeochemical features of porous aquifers from northeastern Guanabara Bay, Rio de Janeiro, SE - Brazil. J. Hydrol. Region. Stud. 22, 100601 (2019).
Sahu, P. & Sikdar, P. K. Hydrochemical framework of the aquifer in and around East Kolkata Wetlands, West Bengal India. Environ. Geol. 55, 823–835 (2008).
Su, Y., Chen, X., Li, Y. & Wang, Y. The robustness mechanism of the rural social-ecological system in response to the impact of urbanization——Evidence from irrigation commons in China. World Dev. 178, 106565 (2024).
Ghosh, A. & Bera, B. Hydrogeochemical assessment of groundwater quality for drinking and irrigation applying groundwater quality index (GWQI) and irrigation water quality index (IWQI). Groundw. Sustain. Dev. 22, 100958 (2023).
US Salinity Laboratory Staff (USSLS). Diagnosis and improvement of saline and alkali soils. US Department of Agriculture Handbook 60, 160 (1954).
Adimalla, N., Li, P. & Venkatayogi, S. hydrogeochemical evaluation of groundwater quality for drinking and irrigation purposes and integrated interpretation with water quality index studies. Environ. Process. 5, 363–383 (2018).
Xiao, J., Jin, Z. & Wang, J. Assessment of the hydrogeochemistry and groundwater quality of the Tarim river basin in an extreme arid region NW China. Environ. Manag. 53, 135–146 (2014).
Ghosh, S. & Jha, M. K. Hydrogeochemical characterization of groundwater and critical assessment of its quality in a coastal basin. Environ. Dev. Sustain. https://doi.org/10.1007/s10668-023-03874-x (2023).
Abu Salem, H. S., Gemail, K. S., Junakova, N., Ibrahim, A. & Nosair, A. M. An integrated approach for deciphering hydrogeochemical processes during seawater intrusion in coastal aquifers. Water 14, 1165 (2022).
Jena, M. R., Tripathy, J. K., Sahoo, D. & Sahu, P. Geochemical Evaluation of Groundwater Quality in the Coastal Aquifers of Kujang Block, Jagatsinghpur District, Eastern Odisha India. Water Air Soil Pollut. 235, 349 (2024).
Selvakumar, S. et al. Hydrogeochemical processes controlling the groundwater salinity in the coastal aquifers of Southern Tamil Nadu India. Marine Pollut. Bull. 174, 113264 (2022).
Sarker, Md. M. R. et al. Groundwater salinization and freshening processes in coastal aquifers from southwest Bangladesh. Sci. Total Environ. 779, 146339 (2021).
Giménez-Forcada, E. Space/time development of seawater intrusion: A study case in Vinaroz coastal plain (Eastern Spain) using HFE-Diagram, and spatial distribution of hydrochemical facies. J. Hydrol. 517, 617–627 (2014).
Syeed, M. M. M. et al. Surface water quality profiling using the water quality index, pollution index and statistical methods: A critical review. Environ. Sustain. Indic. 18, 100247 (2023).
Lyra, A. & Loukas, A. Simulation and evaluation of water resources management scenarios under climate change for adaptive management of coastal agricultural watersheds. Water Resour. Manage https://doi.org/10.1007/s11269-022-03392-x (2022).
He, C. et al. Future global urban water scarcity and potential solutions. Nat. Commun. 12, 4667 (2021).
Acknowledgements
This work was funded by the Project Qingdao Urban Geological Survey (grant No. ZFCG2019001542), Higher Education Research Planning Project of China Association of Higher Education (grant No. CX230303), the Doctoral Research Initial Foundation of Weifang University (grant No. 2022BS34). We would like to acknowledge Ruifang Xie and Lixin Qu, School of Oceanography, Shanghai Jiao Tong University, for their writing and technical help. In particular, we also appreciate the editor and anonymous reviewers for providing numerous comments and suggestions, which helped improve this manuscript.
Funding
This work was funded by the Project Qingdao Urban Geological Survey (grant No. ZFCG2019001542), Higher Education Research Planning Project of China Association of Higher Education (grant No. CX230303), the Doctoral Research Initial Foundation of Weifang University (grant No. 2022BS34).
Author information
Authors and Affiliations
Contributions
Dong Ji: writing—original draft, methodology, investigation, funding acquisition. Jian Ma: methodology, conceptualization, investigation, validation, software. Junzhuo Xue: methodology, investigation, supervision, data curation. Xinghui Wu: writing—review and editing, supervision, methodology. Zeyong Wang: methodology, investigation, data curation. Shuai Wei: data curation, software.
Corresponding authors
Ethics declarations
Competing interests
The authors declare no competing interests.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.
About this article
Cite this article
Ji, D., Ma, J., Xue, J. et al. Identifying groundwater characteristics and controlling factors in Jiaozhou Bay’s northern coastal region, China: a combined approach of multivariate statistics, isotope analysis, and field empirical investigations. Sci Rep 14, 23856 (2024). https://doi.org/10.1038/s41598-024-75425-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/s41598-024-75425-x