While traditional mine hydrogeology focuses on preventing water inrush to protect underground workings, this study establishes a novel evaluation framework aimed at protecting valuable, high-temperature geothermal water resources during deep coal extraction in coal–water dual-resource mines. We selected seven key indicator factors to quantify the disturbance intensity of mining to the overlying geothermal reservoir aquifer, and applied fuzzy variable set theory to evaluate the disturbance level and delineate disturbance zones to investigate the Tongzhe Coalfield area in the eastern Henan Plain of China. The results show that zones of stronger disturbance associated with the extraction of the main coal seam are concentrated in the northern, northeastern, and southwestern parts of the study area. Area statistics indicate that high disturbance zones account for 5.0% of the study area, relatively high disturbance zones for 30.6%, moderate disturbance zones for 32.6%, relatively low disturbance zones for 22.1%, and low disturbance zones for 9.7%. In total, zones at moderate disturbance or above represent 68.2%, suggesting that appropriate mining methods are required during extraction of the main coal seam to mitigate mining induced disturbance to the roof geothermal aquifer. These results provide a scientific basis for selecting mining practices that protect water resources in coal–water dual-resource mining areas.

Grouting to seal the recharge channels of water-bearing aquifers is an effective method for reducing mine water inflow. Evaluating effectiveness and establishing a hierarchical classification system are crucial for assessing project quality. Taking the grouting seal project of the Cambrian limestone aquifer recharge channels at Mine No.7 in the Pingdingshan Coalfield as a case study, this paper first comprehensively evaluates the grouting seal effectiveness based on the difference in dynamic water recharge to goaf before and after grouting, derived from long-term pumping test data. Further, six indicator factors-grout volume, grout volume per unit time, grout volume per unit thickness, final borehole pressure, penetration depth into Cambrian limestone, and variation in rock mechanical strength-were selected. Weights for these factors were determined by integrating the Analytic Hierarchy Process, entropy weight method, and composite weighting method. The TOPSIS model was applied to classify and rank the grouting seal effectiveness in six recharge channels. Results indicate that post-grouting water recharge from goaf decreased by 240.78 m(3)/h during dry season and 878.57 m(3)/h during wet season, confirming high-quality grouting seal. The grouting seal quality of the six recharge channels was ranked from highest to lowest as follows: NO.3 > NO.2 > NO.6 > NO.1 > NO.5 > NO.4. The evaluation results corresponded with the actual karst fissure development and distribution of goaf in the exposed recharge channels.

To calculate the hydrogeological parameters of the Cambrian thick limestone aquifer beneath the coal seam floor in the newly developed Xiadian coalfield, North China, a multi-borehole, high-discharge, long-duration water release test was conducted in underground tunnels at depths exceeding 800 m. This test overcame the limitations of conventional pumping, water pressure, and tracer tests, which are constrained by discharge capacity, test scale, and applicability, and enabled long-term observation of hydraulic responses in a deep confined aquifer. During the test, the maximum total water release rate reached 393.14 m3/h, with a duration of 508.17 h. The maximum groundwater drawdown in the Cambrian limestone aquifer was 127.46 m. Using the unsteady-state Jacob formula, a superposition model was developed to relate drawdown to flow rate. This model allowed the calculation of the aquifer’s transmissivity coefficient, storage coefficient, discharge per unit drawdown, and specific capacity. As the result shows: (1) The multi-borehole, long-duration water release test effectively stimulates the aquifer’s groundwater flow field, overcoming the limitations of surface small-flow tests. (2) The drawdown-flow relationship model accounts for the hydraulic interference among multiple release points, and the derived hydrogeological parameters align with field observations. These findings provide a reliable technical basis for parameter acquisition and inversion in deep (>800 m) high-pressure confined aquifers, and for developing drainage and depressurization strategies in similar deep coal mines.

To overcome the rapid expansion of the drawdown cone, severe inter-well interference, and high operating costs caused by independent geothermal well operation, this study investigated the coordinated optimal scheduling of geothermal water extraction. Fifteen geothermal production wells in the main urban area of Kaifeng City were selected as the study case. The intake intervals of these wells are located at depths of 1020 to 1330 m. Based on the exploitable yield of the geothermal reservoir, user water demand, and well layout, a management model for coordinated scheduling was developed. Design drawdown, water demand, and heating capacity were used as constraints. The objectives were to minimize operating cost, nodal drawdown, and drawdown interference between wells. The results from several optimization algorithms show that the improved Cheetah Optimization Algorithm converged faster and produced more consistent solutions. Compared with the preoptimization scheme, the optimized scheme reduced total operating cost by 31.64%, total drawdown in the study area by 69.5%, and the sum of inter-well drawdown interference by 34.7%. This study provides useful support for selecting efficient optimization algorithms and offers a basis for the scientific development, utilization, and protection of geothermal water resources.

A burnt rock aquifer threatens the safe mining of underlying coal seams. Understanding the height and evolution mechanisms of the water-conducting fractured zone (WFZ) is critical for preventing water inrush disasters and protecting water resources. Focusing on the S1233 panel at the Ningtiaota Coal Mine, where an overlying burnt rock aquifer jeopardizes mining safety, this study comprehensively estimates the WFZ height under completed extraction conditions using empirical and theoretical methods. With two theoretical methods applied based on the key stratum theory, the predicted WFZ height indicated that mining of the S1233 panel had a serious risk of water inrush. Then, a similar material model was established. The characteristics of strata failure, movement, and fracture evolution during working face advancement were systematically analyzed through experimental results. In addition, a critical threshold for water inrush disasters was determined by coupling the relationship between the advance distance and aquifer pressure. Finally, specific water hazard control measures were proposed based on the evolution features of water-conducting fractures. The results of this study provide valuable insights for roof water hazard management in coal mines.

While single-phase immersion cooling (SPIC) is effective for high-density data centers, its implementation is hindered by the computational intractability of full-scale computational fluid dynamics (CFD) simulations for multi-server tanks, alongside an incomplete theoretical basis for optimal flow distribution. To address these issues, this study develops an optimal control framework combining the field synergy theory, entransy dissipation extremum principle, and Lyapunov theory. This synergistic approach enables the optimal control of SPIC terminal systems, achieving superior heat transfer performance coupled with significant energy savings. Guided by the field synergy principle and entransy dissipation theory, flow field optimization of the simplified server model reveals that maximizing coolant impingement on the heating surfaces is crucial. Moreover, the optimal flow rate allocation among servers in symmetric immersion tanks with uniform server structures is analytically formulated to maximize heat transfer efficiency. To overcome the prohibitive computational costs of full-scale CFD simulations, fluid-thermal network (FTN) models are proposed by integrating porous media and thermal resistance network theories. Results demonstrate that the steady-state FTN model predicts the temperatures of all chips with high efficiency and accuracy, reducing computational overhead by over 60% compared to full-scale CFD while facilitating accelerated convergence. Furthermore, the transient FTN model unveils critical dynamic response characteristics. Finally, by coupling the transient FTN model with Lyapunov stability theory, a robust control framework is developed, successfully achieving precise chip temperature regulation under variable power conditions.

In the process of deep coal resource mining,the coal seam floor is subjected to significant water pressure,and the water hazard risk from the underlying aquifer is particularly prominent.The composite strata between the coal seam and the main water-threatening aquifer are characterized by highly complex structures,significant spatial heterogeneity in thickness,and substantial differences in water-bearing properties among different lithological sections.Therefore,the quantitative evaluation of their overall water-barrier performance has become a key link and core scientific issue for the proactive and precise prevention and control of coal seam floor water hazards.Tra-ditional evaluation methods mainly focus on macroscopic geological characteristics and are unable to fully characterize the water-con-trolling effect of the internal microstructure of rock strata.Therefore,a more refined and comprehensive evaluation system is urgently needed.In this study,macro-micro dual-scale indicators were integrated.Fault complexity,effective aquiclude thickness,mass ratio coef-ficient,composite compressive strength,plastic-to-brittle rock thickness ratio,and core recovery rate were selected as macroscopic indicat-ors,while composite area porosity and composite pore volume ratio were selected as microscopic indicators,thereby constructing a com-prehensive evaluation index system.Based on the subjective and objective weights obtained by integrating the G1 method and the Criteria Importance Through Intercriteria Correlation(CRITIC)method using game theory,the constructed normal cloud model was applied to quantitatively evaluate the water-barrier capacity of composite strata.Meanwhile,the water-barrier performance of the mining area was compared and analyzed under the macroscopic single-scale framework and the macro-micro dual-scale framework.The results show that fault complexity and pore-structure parameters account for significant proportions in the index system,confirming that fault structures and the degree of microfracture development are the dominant factors controlling the water-barrier performance of such composite strata.The comprehensive evaluation based on the normal cloud model indicates that the overall water-barrier capacity of the floor composite strata in the study area is relatively weak.Compared with the traditional single macroscopic-scale evaluation,the dual-scale evaluation incorporat-ing microscopic indicators can more accurately capture the water-controlling effect of internal microstructural defects in rock strata,and the evaluation results are highly consistent with the known fault distribution and actual mining conditions of working faces.By introdu-cing microscopic indicators,namely composite area porosity and composite pore volume ratio,a macro-micro dual-scale evaluation index system based on multi-factor integration was established.The reliability of the proposed model and evaluation results was further verified through comparison with known fault distribution and working-face mining conditions.The research results not only deepen the under-standing of the water-barrier mechanism of complex rock strata,but also provide a quantitative evaluation tool for mine water hazard pre-vention and control under similar geological conditions.

The geological conditions of North China-type coalfields are complex, where tectonic cutting of coal seam floors creates numerous water-conducting channels. Moreover, the exploration and identification of water-conducting channels has always been a key challenge in water hazard prevention and control. Based on the ground multi-branch directional drilling for advanced geological exploration, a novel water-conducting channels identification framework that synergistically integrates process analysis with fuzzy comprehensive evaluation has been constructed. Firstly, during advanced geological exploration, drilling time logging, drilling fluid consumption, γ logging, rock debris logging, water pressure test, and injectability were selected as evaluation indicators for identifying water-conducting channels, and they were respectively quantified as average drilling rate, drilling fluid consumption, γ value, non-limestone proportion, unit injection volume, and grouting volume. Subsequently, the over-standard weighting method was employed to determine the weights of the indicators, and based on fuzzy theory and the maximum membership principle, a three-tier quantitative assessment was conducted to evaluate the water-conducting potential of the sampling points. Finally, the fuzzy comprehensive evaluation was applied to assess the water conductivity of 10 locations in the 17051 working face of Guhanshan Mine. The results revealed high water-conducting potential at 8 locations and low risk at 2 locations. Building on these findings, the specific location of a water-conducting channel was successfully pinpointed through engineering validation. The spatial consistency between this identified channel and the water inrush risk zoning map generated by the vulnerability index method confirmed the practicality and scientific validity of the advanced detection and evaluation technology. In summary, this technology establishes a dual-phase identification framework integrating quantitative classification with systematic evaluation, achieving a great improvement in recognition accuracy for water-conducting channels within coal seam floor formations compared to conventional methods.

Scientific evaluation of pre-grouting effectiveness in coal seam floors is crucial for preventing water inrush. This study proposes a quantitative evaluation model based on a combination of the Analytic Hierarchy Process (AHP), the CRITIC method, and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). Applied to the Zhaogu No.1 coal mine, the model used five key construction parameters to assess the horizontal pre-grouting project. The results revealed that the grouting effect was 31.48% excellent, 48.48% good, and 20.04% qualified. The model's reliability was validated by its strong consistency with post-grouting field tests, including transient electromagnetic (TEM) surveys, water-level monitoring, and water inflow data. The proposed methodology provides a reliable tool for the quantitative assessment and optimization of floor grouting projects.

A novel interpretable intelligent water source identification model, integrating gradient boosting decision trees (GBDT) with SHapley Additive exPlanations (SHAP), has been developed to enhance safety in coal mining operations. To mitigate the impact of outliers on model accuracy during training, box plots and multivariate distribution matrix plots were employed to detect and subsequently remove outlier data from the sample. The processed dataset was subsequently subjected to training via GBDT, culminating in the development of a definitive classification model predicated on the gradient of residuals. The model’s hyperparameters, encompassing the number of trees, tree depth, and learning rate, were meticulously optimized through a random search algorithm to augment the model’s predictive performance. Utilizing the measured data from water samples collected in the Pingdingshan Coalfield, cross-validation was performed, yielding a maximum precision of 0.857 and an average precision of 0.602. Upon the application of the optimized GBDT model to the classification of 24 unknown water samples, the model achieved a high accuracy rate of 95.8

Studying the distribution characteristics and genetic mechanisms of fluoride in geothermal water has significant importance for the utilization and treatment of geothermal water. To investigate the fluoride distribution characteristics and formation mechanisms in the geothermal water of the Lushan Hot Spring, this study focuses on the water and rock properties in the geothermal area of Lushan County, Henan Province. A total of 22 water samples (including surface water, groundwater, and geothermal water) and 15 rock samples were collected for ion content analysis, rock sample testing, and morphological extraction. Using tools such as the Piper trilinear diagram, Gibbs diagram, and scanning electron microscopy analysis of the rock samples, the distribution of fluoride content in the rock samples and their primary host media and forms are clarified, and the formation mechanism of high-fluoride geothermal water is investigated. The results show that the average fluoride ion content in the surface water and geothermal water in the study area is 0.51 mg/L and 14.48 mg/L, respectively, and the water chemical type is predominantly HCO3-Na. The pH values of the water samples range from 7.77 to 9.08, all of which are weakly alkaline. There is a significant positive correlation between fluoride ion concentration and temperature, indicating that higher temperatures facilitate the accumulation of fluoride ions. Due to water-rock interactions, fluoride ions in geothermal water mainly originate from the dissolution and release of fluoride-containing minerals such as fluorapatite and mica. The fluoride content in the rock samples ranges from 114 to 1445 mg/kg, exhibiting an enrichment pattern in the study area. The mineral composition of the rock samples includes quartz, potassium feldspar, plagioclase, mica, and clay minerals such as chlorite, with fluorapatite, mica, and clay minerals being the primary carriers of fluoride. Furthermore, the fluoride content in the geothermal water is directly influenced by its form, which determines the ease of fluoride release from the rocks. There are significant differences in fluoride content among the various forms, with residual fluoride being the dominant form, accounting for over 99 %. The fluoride ions in geothermal water primarily originate from watersoluble fluoride and ion-exchangeable fluoride. The distribution of fluoride in various forms decreases from residual F > water-soluble F > organically bound F > exchangeable F > Fe/Mn-bound F.

The conclusion that the column vector of the phase space after reconstruction of the mine water inflow sequence has a clear geological meaning is proposed and verified by an example, and then a prediction model of the mine water inflow coupled with chaos theory and artificial neural network is established. The delay time τ is determined by the mutual information method, and the embedded dimension m is determined by Cao method, and the phase space reconstruction of the water inflow sequence is carried out. Regression analysis and Pearson correlation test are used to analyze the correlation between the elements in each column of phase space and the main controlling factors of water inflow. The chaos theory is coupled with Elman neural network (ENN), and the Chaos-ENN water inflow prediction model is established; The gradient prediction method is used to verify the model. Four evaluation indexes are used to evaluate the prediction results. The results show that the embedding dimension of phase space is equal to the number of main control factors of mine water inflow. The column vector of the phase space is linearly related to the mined out area, the development length, and the water level of the three main aquifers. The prediction accuracy of Chaos-ENN model is 97.91

Over the past half-century, field tests for enhanced geothermal system (EGS) worldwide have revealed the significant risks associated with the development of low porosity and low permeability hot dry rock (HDR) reservoirs. In view of the transmission and traceability of production uncertainty, the realization of stochastic characterization of permeability distributions and the corresponding output simulation preview can provide a general and objective evaluation of EGS production under the current permeability enhancement technology. Based on the Monte Carlo method, a traversal simulation of geothermal energy extraction is conducted to achieve a predictive analysis of thermal energy production under the same enhanced permeability conditions. Firstly, the overall decreasing trend of permeability is determined based on the magnitude and expansion range of permeability enhancement in artificial reservoirs, and the turning bands method (TBM) is used to generate random distributions, superimposing decreasing trends and random distributions to construct permeability distribution samples with overall determinism and local randomness. Secondly, a multiphysics coupling model is established, and geothermal extraction simulations are conducted on the constructed permeability distribution samples under unified initial and boundary conditions. Finally, the production evaluation indicators for each sample are derived from the numerical simulation results, and the distribution characteristics of the production indicators are analyzed. Based on statistical analysis of the production indicators, this paper highlights that enough flux which can sweep adequate stimulated reservoir volume (SRV) is the key to different production patterns. When setting the critical values of 20 kg/s of production flow and a service life of 15 years, the failure rate of samples is approximately 1/4. This indicates that, even under conditions of maximum permeability enhancement by 5 orders of magnitude and an expansion range of 350 m, the EGS system still faces significant production capacity risks. The two key points for effectively constructing EGS artificial reservoirs are the effective connection of enough high-permeability domains and the avoidance of dominant seepage channels. That is, the development of HDR requires reservoir enhancement technologies with higher controllable technique. Thus, under the current technological conditions, a conservative and cautious attitude should be maintained towards the decision of EGS construction.

Groundwater fluoride vulnerability assessment is a critical tool for identifying pollution risks, as it objectively reveals the mechanisms of fluoride enrichment and its spatial heterogeneity. To quantify fluoride contamination vulnerability in the semi-arid region of Fuxin, China, this study enhances the traditional DRASTIC framework by incorporating land use and the topographic wetness index, forming the DRASTIC-LT index system. Hydrogeological parameters calibrated using MODFLOW provide feedback for refining input factors, and machine learning algorithms-including Random Forest, eXtreme Gradient Boosting, and Support Vector Machine-are applied to predict the spatial distribution of groundwater vulnerability. The results indicate that the revised indicator system can accurately reflect the impact on fluoride vulnerability. The correlation coefficients of the indicators are all less than 0.7, demonstrating the validity of the indicator system. Among the models, XGBoost performed the best, with a Mean Absolute Error of 0.099. The cumulative contribution of net recharge and groundwater depth exceeds 70 %, making them the primary influencing factors. The vulnerability in the northwest of the study area is significantly higher than in the southeast, showing a gradual distribution without abrupt changes. The areas of very high and high vulnerability are mainly distributed in patches around Minzhu Village and Hanjiadian. Due to the high permeability of the aquifer, weak groundwater flow conditions, large net recharge, low vegetation cover, and significant water-rock interactions in these areas, they are identified as key areas for prevention and control. It is recommended to implement zonal management, enhance comprehensive monitoring and pollution control in high vulnerability areas, optimize water resource management in medium vulnerability areas, and maintain the ecosystems in low vulnerability areas to effectively reduce groundwater pollution risks and ensure sustainable use of water resources. The optimized groundwater fluoride vulnerability model proposed in this study can be effectively applied to semi-arid regions, providing a scientific basis for groundwater pollution risk management. (c) 2025 COSPAR. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Identifying the sources of mine water gushing is fundamental for preventing water hazards in coal mining areas,enhan-cing the economic efficiency and effectiveness of prevention measures.Taking a mining area in the southern margin of Ordos Basin as the research area,11 mine water samples were collected before and after the mine water gushing events.Hydrogeological compre-hensive analysis was employed to preliminarily identify the water sources,and a mathematical model was developed using ground-water chemical compositions.The sources of water gushing were quantitatively analyzed using statistical methods such as cluster analysis,factor analysis,multiple regression analysis,and canonical correlation analysis,the analysis results are mutually verified with the actual exploration results.The main sources of water gushing in the study area include Zhiluo Formation water,Luohe Formation water,and Quaternary water.Among these,Luohe Formation water and Quaternary water were primarily recharged by surface water,which infiltrated the mine through fractures.Cluster analysis showed that the first inrush water sample was grouped with Zhiluo Formation water,Quaternary water,and surface water,while goaf water formed a separate cluster.The chemical com-positions of the second and third gushing water samples were similar to those of goaf water,the mass concentration of sulfate ions(SO42-)and magnesium ions(Mg2+)is higher.Factor analysis revealed that Zhiluo Formation water and goaf water contributed signi-ficantly to the water gushing,with contribution rates of 0.989 and 0.988,respectively.Multiple regression analysis indicated that sur-face water and Quaternary water had the most significant impacts on water gushing.Canonical correlation analysis further confirmed the strong relationship between gushing water samples and surface water or Quaternary water with regression coefficients of 2.764 and-3.169,respectively.The main sources of water gushing in the study area were identified as surface water,Quaternary water,and Zhiluo Formation water,with the findings highly consistent with actual exploration results.Therefore,integrating multivariate statistical analysis techniques can achieve quantitative identification of water gushing sources.

To improve the production capacity of fractured reservoirs in the Matouying Uplift Area, the physical composite stimulation is proposed, and its effect is analyzed and verified based on numerical simulation methods of finite- discrete element and thermo-hydro-mechanical coupling theories. Results show that the artificial cracks generated by the on-site fracturing connect natural fractures to some extent, the large fractures generated by the secondary fracturing can promote the connection between injection and production wells, the micro-cracks generated by the blasting based on on-site fracturing increase both the crack density and crack coverage area, and adopting the physical composite stimulation can generate a dense network of main and branch cracks. After the mining of 40 a, the thermal mining rate of the original reservoir is 15.24 %, while those of reservoirs with the on-site fracturing, the secondary fracturing, the blasting based on on-site fracturing and the physical composite stimulation are 23.02 %, 27.69 %- 29.86 %, 26.80 %- 48.47 % and 79.85 %, respectively. The optimal displacement of hydraulic fracturing and peak pressure of liquid explosives is 5.07 m3/min and 800 MPa. Although the physical composite stimulation is very beneficial for the mining of hot dry rock, technical breakthroughs are still needed in areas such as the perfusion method, detonation way, and high-temperature stability of liquid explosives. This study can support the theoretical and technological development of hot dry rock reservoir stimulation.

The karst groundwater of Cambrian limestone may become an important water source for industry and agriculture in the Pingdingshan area,and is also a potential threat to mining safety.Therefore,to find out the origin,flow paths,and hydrogeochemical processes of karst groundwater beneath the Pingdingshan coalfield,a total of 16 water samples were collected.Our findings confirmed that the karst groundwater is mainly recharged by precipitation.The precipitation can directly supply the deep aquifer of the karst water system through the southwest limestone outcrops,and this area mostly includes the southern part of mines No.11,No.9,and the hidden outcrops in the southern part of mine No.2.What is more,the areas adjacent to the synclinal axis,including mines No.10,No.12,and No.8,may be the main discharge areas.A mixing model of 87Sr/86Sr and Sr showed that in the southwest Pingdingshan coalfield,the proportion of precipitation decreased gradually from the recharge area to the discharge area,ranging from 89.1％to 17.1％.Besides,the northeast Pingdingshan coalfield is another recharge area for the whole karst system,thus,the infiltrating groundwater will indirectly supply the deep aquifer through Quaternary deposition near the mine No.13.Our research results can provide theoretical support for the prevention and control of groundwater disasters and the development and utilization of regional groundwater resources in the coalfield in Northern China.

The rock mass of coal seam floor plays a crucial role in blocking the uplift and runoff of the underlying confined water in the course of mining under water pressure. Accurately assessing its water resistance performance, which is influenced by numerous factors, is important for preventing accidents caused by inrushing water. This study focuses on a coal mine in the Ningwu coalfield in North China. We establish an evaluation system for the water resistance performance of coal seam floor rock mass, using indices including rock mass thickness, lithological combination characteristics, rock mass quality, structure complexity and bedding plane count. A variable weight-normal cloud (VW-NC) model is formulated to quantitatively evaluate the water resistance performance of the coal seam floor rock mass. Comparative analysis with actual mining conditions and other models reveals that the VW-NC model provides the most precise and accurate results. The study finds that the primary influencing factors on the water resistance performance are weak structural planes, including faults, joints, and bedding planes. The proportions of strong, relatively strong, relatively weak, and weak zones in research area are 20.41%, 59.88%, 12.38%, and 7.33%, respectively.

The emergence of large-scale time-series data and advancements in computational power have opened new avenues for analyzing the spatiotemporal evolution of groundwater chemistry, water quality, and human health risks. This paper utilizes hydrogeochemical methods to elucidate the controlling factors of water chemical components based on the test results of 124 groundwater samples collected from 31 monitoring wells in Fuxin City, Liaoning Province, China, from 2018 to 2021. By integrating the Random Forest and Enhanced Water Quality Index methods for water quality assessment and employing the Human Health Risk Assessment (HHRA) model to analyze human health risks, our findings indicate that the groundwater is mildly alkaline, with SO4·Cl–Ca·Mg and HCO3–Ca·Mg as the dominant hydrochemical types, primarily derived from the dissolution of carbonate and silicate minerals such as dolomite, limestone, and andesite, and cation exchange reactions. The EI_RF water quality evaluation model reveals that the overall water quality in the study area is poor, with Class I and II water quality zones mainly located in the northeastern and central parts of the study area, showing a gradual transition from Class I and II in the northeast to Classes IV and V in the southwest, significantly influenced by NO3−, TH, TDS, and SO42−. The HHRA model results indicate that the potential non-carcinogenic risk of groundwater nitrates has a severe impact on infants, with the spatial distribution being low in the northeast and high in the southwest. Due to industrial activities, agricultural practices, and population growth, certain areas in developing countries such as China and India exhibit nitrate concentrations significantly higher than those in most international regions, highlighting global environmental and public health challenges. This underscores the importance of enhancing groundwater monitoring and implementing measures to mitigate pollution. These research outcomes hold significant implications for the government in formulating rational protection and management measures to ensure the sustainable utilization of groundwater resources.