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Hydrogeology and Regional Groundwater Flow
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Hydrogeology and Regional Groundwater Flow

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 November 2025 | Viewed by 3092

Special Issue Editors

Prof. Dr. Donglin Dong

E-Mail Website
Guest Editor
College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, China
Interests: hydrogeology; environment geology; application of GIS; abnormal groundwater dynamics assessment; water inrush assessment; mine water control; mine water environment
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wenjie Sun

E-Mail Website
Guest Editor
College of Geoscience and Surveying Engineering, China University of Mining & Technology, Beijing, China
Interests: hydrogeology; mine water environment; groundwater hydrochemistry; groundwater dynamics; hydrological modeling and GIS
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Francesco Fiorillo

E-Mail Website
Guest Editor
Department of Science and Technology, Università degli Studi del Sannio, Benevento, Italy
Interests: karst hydrogeology; landslide; geohydrology; extreme events; climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Hydrogeology and regional groundwater flow systems are critical to understanding water resource sustainability, contaminant transport, and ecosystem resilience. This Special Issue aims to advance interdisciplinary research on groundwater dynamics at regional scales, integrating field observations, numerical modeling, and innovative technologies. Topics of interest include, but are not limited to, the following:

  • Groundwater flow modeling: novel approaches for simulating regional aquifer systems, including machine learning applications and hybrid models.
  • Hydrogeochemical processes: interactions between groundwater and geological formations, contaminant fate, and remediation strategies.
  • Climate change impacts: effects of warming trends and extreme weather on groundwater recharge and availability, particularly in sensitive regions like arid zones and high-altitude catchments.
  • Sustainable management: policy frameworks, water–energy–food nexus, and adaptive strategies for groundwater depletion.
  • Emerging technologies: remote sensing, isotopic tracing, and big data analytics in hydrogeological studies.
  • Groundwater thematic research: evaluation, prediction, prevention, or control of water problems at mining operations or their impact on the environment.

This Special Issue welcomes original research articles, reviews, and case studies that address both theoretical advancements and practical solutions for groundwater challenges.

Prof. Dr. Donglin Dong
Prof. Dr. Wenjie Sun
Prof. Dr. Francesco Fiorillo
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • groundwater flow dynamics
  • aquifer characterization
  • hydrogeochemical modeling
  • climate–groundwater interactions
  • regional water security

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Published Papers (5 papers)

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Research

25 pages, 12502 KB  
Article
BiLSTM-VAE Anomaly Weighted Model for Risk-Graded Mine Water Inrush Early Warning
by Manyu Liang, Hui Yao, Shangxian Yin, Enke Hou, Huiqing Lian, Xiangxue Xia, Jinsui Wu and Bin Xu
Appl. Sci. 2025, 15(19), 10394; https://doi.org/10.3390/app151910394 - 25 Sep 2025
Viewed by 220
Abstract
A new cascaded model is proposed to improve the accuracy and early warning capability of predicting mine water inrush accidents. The model sequentially applies a Bidirectional Long Short-Term Memory Network (BiLSTM) and a Variational Autoencoder (VAE) to capture the spatio-temporal dependencies between borehole [...] Read more.
A new cascaded model is proposed to improve the accuracy and early warning capability of predicting mine water inrush accidents. The model sequentially applies a Bidirectional Long Short-Term Memory Network (BiLSTM) and a Variational Autoencoder (VAE) to capture the spatio-temporal dependencies between borehole water level data and water inrush events. First, the BiLSTM predicts borehole water levels, and the prediction errors are analyzed to summarize temporal patterns in water level fluctuations. Then, the VAE identifies anomalies in the predicted results. The spatial correlation between borehole water levels, induced by the cone of depression during water inrush, is quantified to assign weights to each borehole. A weighted comprehensive anomaly score is calculated for final prediction. In actual water inrush cases from Xin’an Coal Mine, the BiLSTM-VAE model triggered high-risk alerts 9 h and 30 min in advance, outperforming the conventional threshold-based method by approximately 6 h. Compared with other models, the BiLSTM-VAE demonstrates better timeliness and higher accuracy with lower false alarm rates in mine water inrush prediction. This framework extends the lead time for implementing safety measures and provides a data-driven approach to early warning systems for mine water inrush. Full article
(This article belongs to the Special Issue Hydrogeology and Regional Groundwater Flow)
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15 pages, 6226 KB  
Article
Investigation of Grout Anisotropic Propagation at Fracture Intersections Under Flowing Water
by Bangtao Sun, Dongli Li, Xuebin Liu, Qiquan Hu, Xiaoxiong Li, Xiangdong Meng and Wanghua Sui
Appl. Sci. 2025, 15(17), 9787; https://doi.org/10.3390/app15179787 - 6 Sep 2025
Viewed by 584
Abstract
Grout propagation is a critical aspect of fracture grouting. This study investigated grout propagation at fracture intersections under flowing conditions using a simplified two-dimensional (2D) fracture network. Transparent soil technology was employed to simulate the porous filling material within the fractures. The results [...] Read more.
Grout propagation is a critical aspect of fracture grouting. This study investigated grout propagation at fracture intersections under flowing conditions using a simplified two-dimensional (2D) fracture network. Transparent soil technology was employed to simulate the porous filling material within the fractures. The results showed that the penetration velocity of grout decreased significantly after passing through an intersection, and the velocity in the main fracture was consistently higher than that in the branch fractures. In the unfilled fracture network, the diffusion ratio between branch and main fractures ranged from 0.35 to 0.88, whereas after filling, it ranged from 0.71 to 0.86. For each intersection, the ratio of grout length in the downstream branch to that in the main fracture (RDM) was positively correlated with branch width. This trend was especially evident in unfilled fractures, whereas in filled fractures, the increase in RDM was much less pronounced. Regarding the upstream ratio (RUM), it was consistently lower than RDM. RUM increased with branch width in unfilled fractures but decreased in filled fractures. Additionally, higher fluid velocity amplified these anisotropic propagation behaviors. Based on the simplified filled fracture model, it was concluded that porous filling materials reduce permeability differences between fractures with different aperture widths. Furthermore, increased flow rate intensified the anisotropic diffusion of grout. This study provides valuable insight into the mechanism of anisotropic grout propagation and offers guidance for engineering grouting applications. Full article
(This article belongs to the Special Issue Hydrogeology and Regional Groundwater Flow)
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17 pages, 2779 KB  
Article
Mine Water Inflow Prediction Using a CEEMDAN-OVMD-Transformer Model
by Yang Li, Qiang Wu and Fangchao Lei
Appl. Sci. 2025, 15(17), 9710; https://doi.org/10.3390/app15179710 - 4 Sep 2025
Viewed by 636
Abstract
Coal is a vital part of China’s energy system, and accurately predicting mine water inflow is crucial for ensuring the safety and efficiency of coal mining. To enhance prediction accuracy, this study introduces a hybrid model—CEEMDAN-OVMD-Transformer—that combines Adaptive Noise Complete Ensemble Empirical Mode [...] Read more.
Coal is a vital part of China’s energy system, and accurately predicting mine water inflow is crucial for ensuring the safety and efficiency of coal mining. To enhance prediction accuracy, this study introduces a hybrid model—CEEMDAN-OVMD-Transformer—that combines Adaptive Noise Complete Ensemble Empirical Mode Decomposition (CEEMDAN), Optimal Variational Mode Decomposition (OVMD), and the Transformer architecture. This combined model is used to forecast water inflow at the Heidaigou Coal Mine. The experimental results show that the proposed model achieves excellent predictive accuracy, with a Mean Absolute Error (MAE) of 0.507, a Root Mean Square Error (RMSE) of 0.614, a Mean Absolute Percentage Error (MAPE) of 0.010, and a Coefficient of Determination (R2) of 0.948. Compared to the standalone Transformer model, the CEEMDAN-OVMD-Transformer model reduces the MAE by 34.50% and increases the R2 by approximately 3.04%, indicating a significant improvement in forecasting accuracy. The findings demonstrate that the CEEMDAN-OVMD-Transformer hybrid model can effectively reduce the complexity of high-frequency components in mine water inflow time series, thereby enhancing the stability and reliability of predictions. This research presents a new and effective approach for mine water inflow forecasting and offers valuable technical guidance for water hazard prevention and control in similar coal mining environments. Full article
(This article belongs to the Special Issue Hydrogeology and Regional Groundwater Flow)
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17 pages, 9898 KB  
Article
Comparative Study on Prediction Methods for Water Inflow in Regional High-Intensity Water Inrush Mine Clusters: A Case Study of Xiaozhuang Coal Mine
by Jia Ding, Shuning Dong, Xiaoming Guo and Bo Liu
Appl. Sci. 2025, 15(17), 9472; https://doi.org/10.3390/app15179472 - 28 Aug 2025
Viewed by 520
Abstract
To address the challenges of predicting high-intensity water inflow in regional mine clusters, this study evaluates the reliability of three methods—hydrogeological analogy, dynamic water inflow prediction models, and numerical simulations—based on geological and hydrogeological conditions as well as measured water inflow data from [...] Read more.
To address the challenges of predicting high-intensity water inflow in regional mine clusters, this study evaluates the reliability of three methods—hydrogeological analogy, dynamic water inflow prediction models, and numerical simulations—based on geological and hydrogeological conditions as well as measured water inflow data from the target mining area. The water inflow at various working faces of the target coal mine was back-calculated, and the reliability of the three methods was compared. The conclusions are as follows: (1) Under the hydrogeological conditions of high-intensity water inflow in regional mine clusters, the conventional hydrogeological analogy method exhibits high reliability in predicting water inflow at the first-mined working face, with a coefficient of determination (R2) as high as 0.95. However, its prediction error increases significantly for non-first-mined working faces, yielding R2 values of only 0.72–0.85. (2) Compared to the hydrogeological analogy method, the dynamic prediction model based on groundwater dynamics more accurately characterizes the lateral runoff recharge process of aquifers, significantly improving the prediction accuracy for non-first-mined working faces (R2 = 0.90–0.94). (3) The numerical simulation method for water inflow prediction demonstrates high reliability under various conditions, but its accuracy is highly dependent on model characterization and parameter calibration. Full article
(This article belongs to the Special Issue Hydrogeology and Regional Groundwater Flow)
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25 pages, 4997 KB  
Article
Application of Game Theory Weighting in Roof Water Inrush Risk Assessment: A Case Study of the Banji Coal Mine, China
by Yinghao Cheng, Xingshuo Xu, Peng Li, Xiaoshuai Guo, Wanghua Sui and Gailing Zhang
Appl. Sci. 2025, 15(16), 9197; https://doi.org/10.3390/app15169197 - 21 Aug 2025
Viewed by 452
Abstract
Mine roof water inrush represents a prevalent hazard in mining operations, characterized by its concealed onset, abrupt occurrence, and high destructiveness. Since mine water inrush is controlled by multiple factors, rigorous risk assessment in hydrogeologically complex coal mines is critically important for operational [...] Read more.
Mine roof water inrush represents a prevalent hazard in mining operations, characterized by its concealed onset, abrupt occurrence, and high destructiveness. Since mine water inrush is controlled by multiple factors, rigorous risk assessment in hydrogeologically complex coal mines is critically important for operational safety. This study focuses on the roof water inrush hazard in coal seams of the Banji coal mine, China. The conventional water-conducting fracture zone height estimation formula was calibrated through comparative analysis of empirical models and analogous field measurements. Eight principal controlling factors were systematically selected, with subjective and objective weights assigned using AHP and EWM, respectively. Game theory was subsequently implemented to compute optimal combined weights. Based on this, the vulnerability index model and fuzzy comprehensive evaluation model were constructed to assess the roof water inrush risk in the coal seams. The risk in the study area was classified into five levels: safe zone, relatively safe zone, transition zone, relatively hazardous zone, and hazardous zone. A zoning map of water inrush risk was generated using Geographic Information System (GIS) technology. The results show that the safe zone is located in the western part of the study area, while the hazardous and relatively hazardous zones are situated in the eastern part. Among the two models, the fuzzy comprehensive evaluation model aligns more closely with actual engineering practices and demonstrates better predictive performance. It provides a reliable evaluation and prediction model for addressing roof water hazards in the Banji coal seam. Full article
(This article belongs to the Special Issue Hydrogeology and Regional Groundwater Flow)
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