Mine Water Production, Treatment, and Utilization in the Yellow River Basin: Spatial Patterns and Sustainable Transformation Pathways

Abstract

The Yellow River Basin faces high-intensity coal resource development and severe water scarcity. This makes the treatment and use of mine water a critical factor constraining both coal industry development and ecological security for the region. This study uses kernel density estimation and the Standard Deviational Ellipse model to identify the spatial pattern of mine water production. It also combines bibliometric analysis and field investigations to assess research progress and current practice for mine water treatment and use in the basin. Results show that mine water production displays strong spatial clustering, with the center of gravity shifting northward. Research is moving from an engineering-focused stage to a theory-oriented one, emphasizing systematic optimization and sustainable use. Current practices still struggle with non-standardized data, uneven treatment quality, and incomplete management systems. This research underscores the importance of improving the region’s integrated management of mine water and proposes shifting mine water from an environmental burden to a resource asset.

1. Introduction

The Yellow River Basin (natural hydrological scale), often referred to as an “Energy Basin,” is a vital, energy-rich region and a major coal production area in China [1,2]. At the same time, it has one of the most fragile ecological environments, suffering from severe water scarcity [3,4]. The per capita water resource availability in the basin is only 905 m³, approximately one-third of the national average. Although the basin accounts for 12% of the national population and 17% of the country’s arable land, it contains only 2.6% of China’s total water resources. This results in a strong conflict between water supply and demand. [5]. Recently, large-scale coal resource development in the basin has made mine water [6]—a byproduct of coal mining—a key factor affecting both the water resource balance and regional ecological security [7]. Mine water treatment capacity in the Yellow River Basin has increased significantly with policy support, but the overall reuse rate remains low [8]. Additionally, direct production still occurs in some mining areas, especially in coal mines where resources are nearly depleted, which increases water environment risk [9].

With the development of the coal industry, the spatial production pattern of mine water in the Yellow River Basin is undergoing significant changes [10]. The generation of mine water is closely linked to coal mining. As a result, its spatial production pattern depends on the layout and intensity of coal mining areas [11]. China is continuously optimizing its coal production capacity layout [12] and building large-scale coal bases at an accelerating pace. Development is relying more on these Large Coal Bases and National Planned Coal Mining Areas. This change guides coal development to concentrate in the middle and upper reaches of the Yellow River Basin [13]. Resource endowments are superior here. Mining conditions are favorable, and production costs are low [14]. As a result, mine water production is highly concentrated in key coal-producing areas. This places unprecedented pressure on regional water resources and the environment. At the same time, China is placing greater emphasis on ecological civilization and stricter environmental protection. As a result, policies such as the Outline of the Plan for Ecological Protection and High-Quality Development of the Yellow River Basin have been published. These documents propose higher standards and clearer requirements for mine water treatment by coal enterprises [15]. Many coal bases in the Yellow River Basin (natural hydrological scale) are located in ecologically vulnerable areas in the middle reaches [16]. The basin faces serious ecological issues. These include severe groundwater over-extraction in some regions [17], surface water function degradation [18], insufficient ecological base flow [19], and the failure of many river sections to meet water quality standards [20]. These issues are most severe in coal-intensive areas like Shanxi and Northern Shaanxi. They have become major factors disturbing the health of the basin’s aquatic ecosystem [21,22]. Meanwhile, mine water in the basin has high reuse value. With appropriate treatment, it can be used for mining industry purposes, agricultural irrigation, or ecological replenishment [23]. However, high technical thresholds and operating costs, along with a lack of unified reuse standards, mean the actual reuse rate remains far below expectations [24].

Researchers have widely studied mine water treatment technology, reuse models, and water quality evolution. However, several gaps persist. Most studies focus on single mining areas or specific technologies, relying either on detailed micro-scale hydrogeological models or aggregated local statistical data. There is a lack of systematic analysis of mine water production patterns at a macro-scale. Moreover, the aggregated mine water data are often inconsistent with the current status of coal development, while the computational demands of micro-scale modeling make it difficult to apply such approaches at the basin scale. This paper analyzes the spatial pattern of mine water production in the Yellow River Basin based on the spatial distribution of coal mining areas. Using bibliometric analysis and field surveys, it reviews research progress in mine water treatment and utilization in the Yellow River Basin from 2011 to 2024. Finally, this study offers an outlook on future research in mine water treatment and utilization in the basin, aiming to support coordinated ecological protection and coal industry development.

2. Materials and Methods

2.1. Site Description

The Yellow River Basin (natural hydrological scale) spans about 1900 km from west to east and is one of the major river basins in China. It originates from the Bayan Har Mountains in Qinghai Province. The river flows through four major natural geographic regions: the Qinghai-Tibet Plateau, the Inner Mongolia Plateau, the Loess Plateau, and the North China Plain. It involves nine provinces and autonomous regions: Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan, and Shandong [25]. This study selects these nine provinces (regions) as the research object, based on the natural scope of the Yellow River Basin. This choice also considers the direct link between the basin and these administrative regions in terms of resource development, ecological protection, and economic growth. The demarcation points for the upper, middle, and lower reaches reference the standards set by the Yellow River Basin Flood Control Plan. Specifically, it uses Hekou Town and Taohuayu [26] as boundaries. In this paper, the “Yellow River Basin” refers to two spatial scales. First, the “Yellow River Basin Area” at the natural hydrological scale includes the main river, its tributaries, and endorheic areas, thus covering the full catchment area. Second, the “Nine Provinces (Regions) along the Yellow River” at the administrative scale refers to the provinces (regions) traversed by the river and its major tributaries: Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan, and Shandong (see Figure 1). This study considers both the natural basin and administrative divisions. Unless otherwise stated, “Yellow River Basin” mainly means these nine provinces (regions) along the river.

2.2. Data Sources and Pre-Processing

2.2.1. Coal Production and Mine Water Production

Coal production data for each province within the Yellow River Basin from 2011 to 2024 were obtained from the China Statistical Yearbook and China Production Safety Yearbook. Because direct statistical data on mine water production are incomplete, it was necessary to estimate the total mine water production ($P_{\mathrm{mine} \mathrm{water}}$) in each province. This study utilizes coal production data to estimate mine water production using a commonly employed top-down estimation method [27,28]. This estimation was carried out using the following relationship:

$$P_{\mathrm{mine} \mathrm{water}}=P_{\mathrm{coal}}\times C_{\mathrm{water} \mathrm{rich}}$$

(1)

where P_coal represents the annual raw coal production (10⁸ t) and $C_{\mathrm{water} \mathrm{rich}}$ represents the average water-rich coefficient for coal mines in each province. Considering the national mine water statistics from the National Mine Safety Administration, the current status of coal development [29,30], and the drainage effects of active, suspended, and abandoned mines, the provincial average water-rich coefficients in the Yellow River Basin were obtained from previously published studies on regional mine water resources (

Table 1. The average water-rich coefficient for coal mines in each province of the Yellow River Basin (data from [8]).

Provinces (Autonomous Regions)	Average Water-Rich Coefficient
Henan	3.75
Sichuan	3.02
Shandong	1.85
Qinghai	0.84
Ningxia	0.76
Gansu	0.74
Shaanxi	0.64
Shanxi	0.41
Inner Mongolia	0.24

). It should be noted that the empirical nature of the $C_{\mathrm{water} \mathrm{rich}}$ coefficient introduces uncertainties into the estimation of mine water production. These uncertainties mainly arise from the spatial heterogeneity of hydrogeological conditions across mining areas, as well as the necessity of aggregating site-specific data into provincial averages. Although such errors may propagate into the calculated $P_{\mathrm{mine} \mathrm{water}}$, the method remains suitable for macro-scale analysis of spatiotemporal trends across the Yellow River Basin, given that constructing a precise hydrogeological model is impractical at this scale.

2.2.2. Large Coal Base and National Planned Coal Mining Area Location

Determining the precise geographical locations of Large Coal Bases and National Coal Planning Mining Areas is key to studying the spatial production characteristics of mine water in the Yellow River Basin. This study strictly extracts and locates these positions using official, authoritative data. First, the names and administrative information of Large Coal Bases are obtained from the 13th Five-Year Plan for Coal Industry Development [31]. Textual descriptions of national planned mining areas (coal) come from the National Mineral Resources Plan (2016–2020) [32]. The original data are mostly unstructured text. To address this, the Gaode Map platform is used for geocoding. Through the service interface, the extracted names of bases and mining areas are converted into longitude and latitude in the CGJ-02 coordinate system. Next, to enable spatial overlay analysis in a geographic information system, the longitude and latitude data are imported into the ArcGIS 10.2 software. Here, the necessary coordinate system corrections and transformations are performed. The data are then projected onto a unified geographic coordinate system. Finally, they are output as point features, which is the most suitable representation for precisely modeling the spatial location of these coal production areas in macro-scale analysis. To validate the positional accuracy of the geocoding, the resulting point elements were visually verified by overlaying them onto high-resolution satellite imagery (e.g., Google Earth). This process confirmed that all geocoded coordinates align correctly with the known geographical extents of the respective coal bases and mining areas, ensuring sufficient accuracy for macro-scale spatial analysis.

2.2.3. Bibliometric Metadata (CNKI)

The scientific literature of this paper is from the China National Knowledge Infrastructure (CNKI) database. A search was conducted using themes such as “Mine water treatment”, “Mine water utilization”, “Mine water governance”, and “Mine water Reuse and purification”, with “All” selected as the citation index. The time range was from 1 January 2011, to 10 November 2025. A combined search yielded 1760 results. To ensure the reliability of the analysis results, the literature with low relevance to the research topic, research subjects not within the scope of the provinces involved in the Yellow River Basin, and no author records, as well as data contents such as newspapers, conferences, standards, and achievements, are excluded through manual intensive reading. This manual screening followed a strict, predefined protocol. To ensure maximum inter-rater reliability, the entire set of 892 articles was independently screened by two additional researchers. Any discrepancies in the exclusion decisions were resolved through discussion and consensus to ensure consistency, thus validating the integrity of the final literature set. The 892 valid publications selected were exported in the “RefWorks” format.

2.3. Analytical Methods

2.3.1. Kernel Density Estimation

Kernel Density Estimation (KDE), which reflects the probability of point features occurring at different spatial locations [33], is widely applied in the visualization and detection of spatial point patterns [34]. This study utilizes kernel density analysis to investigate the spatial distribution characteristics and agglomeration of the National Planned Coal Minng Areas within the Yellow River Basin. Its calculation formula is as follows:

$$f(x)={\displaystyle \frac{1}{nh}}{\displaystyle \sum _{i=1}^{n}K\left(\frac{x-x_i}{h}\right)}$$

(2)

where $x$ represents the point location coordinates of the National Coal Planning Area $i$ ($i$ = 1, 2, …, n), $n$ represents the number of distributed mining area points, $h$ represents the search radius for kernel density calculation, $K$ represents the kernel function. The search radius ($h$) was determined using the widely recognized Silverman’s empirical rule, which automatically estimates the optimal bandwidth based on the standard deviation and sample size of the point data. In this analysis, the calculated value of $h$ was 208.8 km.

2.3.2. Center of Gravity Transfer Model

The Standard Deviational Ellipse (SDE) is a widely used spatial analysis method. Its key elements are the center, azimuthal angle, and the standard deviations along the major and minor axes. SDE effectively reveals the central tendency, dispersion, and directionality of geographic data [35,36]. This study conducted a statistical analysis on the spatial locations of the National Planned Coal Mining Areas in each province. The mean center was calculated for each province to identify the coal mining center. The research period was divided into three intervals: H1 (2011–2015), H2 (2016–2020), and H3 (2021–2024). For each interval, mine water production data from all provinces were statistically computed. The results were then integrated into a GIS platform for spatial analysis. The SDE model was then used to quantify the spatio-temporal evolution of mine water generation patterns in the Yellow River Basin. The formulas are:

Azimuth:

$$\tan \theta ={\displaystyle \frac{\left({\displaystyle \sum _{i=1}^n{W}_i^2{\tilde{X}}_i^2-}{\displaystyle \sum _{i=1}^n{W}_i^2{\tilde{Y}}_i^2}\right)+\sqrt{{\left({\displaystyle \sum _{i=1}^n{W}_i^2{\tilde{X}}_i^2-}{\displaystyle \sum _{i=1}^n{W}_i^2{\tilde{Y}}_i^2}\right)}^2+4{\displaystyle \sum _{i=1}^n{W}_i^2{\tilde{X}}_i^2{\tilde{Y}}_i^2}}}{2{\displaystyle \sum _{\mathrm{i}=1}^n{W}_i^2{\tilde{X}}_i\widetilde{Y_i}}}}$$

(3)

Standard deviation of the x-axis:

$${\sigma }_x=\sqrt{{\displaystyle \frac{{\displaystyle \sum _{i=1}^n{\left(W_i{\tilde{X}}_i\cos \theta -W_i{\tilde{Y}}_i\sin \theta \right)}^2}}{{\displaystyle \sum _{i=1}^n{W}_i^2}}}}$$

(4)

Standard deviation of the y-axis:

$${\sigma }_y=\sqrt{{\displaystyle \frac{{\displaystyle \sum _{i=1}^n{\left(W_i{\tilde{X}}_i\sin \theta -W_i{\tilde{Y}}_i\cos \theta \right)}^2}}{{\displaystyle \sum _{i=1}^n{W}_i^2}}}}$$

(5)

Mean center:

$$X_w={\displaystyle \frac{{\displaystyle \sum _{i=1}^n{W}_i\times X_i}}{{\displaystyle \sum _{i=n}^n{W}_i}}},Y_w={\displaystyle \frac{{\displaystyle \sum _{i=1}^n{W}_i\times Y_i}}{{\displaystyle \sum _{i=n}^n{W}_i}}}$$

(6)

where $\theta$ represents the azimuth of the ellipse, which is the angle formed by rotating clockwise from due North to the long axis of the ellipse, ${\sigma }_x$ and ${\sigma }_y$ represent the standard deviations along the x-axis and y-axis, respectively, $(X_i, Y_i)$ represents the center coordinates of coal mining for province, $({\tilde{X}}_i, {\tilde{Y}}_i)$ represents the relative coordinates of each point (province’s centroid) relative to the regional center of gravity, $(X_w, Y_w)$ represents the center coordinates of mine water production in the Yellow River Basin, $W_i$ represents the weight, which in this paper is the value of mine water production for each province. In the temporal evolution analysis, the calculation of SDE used mine water production for each period (H1, H2, H3) as weights, without normalizing across periods. This approach was deliberately chosen to ensure that changes in the size, shape, and central location of the SDE reflect not only the relative spatial structure of production but also the significant influence of absolute mine water production over time. To further assess the statistical significance of centroid shifts across consecutive periods, a Weighted Perturbation Bootstrap resampling method was employed. In this approach, the mine water production weights were treated as composite variables ($P_{\mathrm{mine} \mathrm{water}}\times C_{\mathrm{water} \mathrm{rich}}$), and lognormal multiplicative noise was applied for repeated resampling (B = 5000) to account for inherent measurement errors and random fluctuations in the weighted production data. A new centroid was computed for each resample, generating an empirical distribution of centroid differences. Statistical significance was evaluated by examining whether the 95% Bootstrap confidence interval of the centroid shift included zero, ensuring a robust and distribution-free inference of temporal centroid migration. All spatial computations were performed in ArcGIS 10.2, and the Bootstrap resampling analysis was conducted in Python 3.11.

2.3.3. Scientometric Analysis by CiteSpace

Firstly, through literature review and technical analysis, a total of 892 relevant documents were systematically sorted and comprehensively analyzed. According to the differences in research content and purpose, the literature achievements are classified into two categories: one category is applied research literature, mainly focusing on practical aspects such as mining area governance, equipment application, and process flow; another category is theoretical analysis literature, mainly involving theoretical explorations such as experimental testing, characteristic mechanisms, and development directions. On this basis, the CiteSpace 6.4.R1 software was used to conduct visual analyses, including keyword co-occurrence and keyword clustering, of the 892 aforementioned publications [37,38]. The study period was defined as January 2011 to November 2025, with a one-year time slice. The analysis was conducted using keyword nodes. To improve the clarity and interpretability of the network, a hybrid pruning strategy was applied for optimization, combining the Pathfinder and Pruning Sliced Networks. Additionally, a knowledge graph in the field of mine water treatment and utilization in the Yellow River Basin was constructed. This will reveal the research hotspots, overall development trends, and evolution characteristics in this field and summarize the key research topics and their main contents.

2.4. Design of Case Study and Field Investigation

The purpose of the field investigation was to understand the actual operational status of mine water treatment and utilization in the Yellow River Basin and to further supplement the frontline data and genuine feedback that are difficult to obtain through bibliometric analysis alone. To complement the spatial and scientific-bibliometric analysis, a field survey was designed to acquire firsthand data on the practices of mine water production, treatment, and utilization in the Yellow River Basin. Between 2023 and 2024, the author’s team conducted on-site investigations across 412 active coal mines in the Yellow River Basin. The focus was primarily on hydrogeological types, mine water inflow volumes, mine water quality types, treatment and utilization processes, and operational management mechanisms. The 412 coal mines surveyed were selected using a stratified sampling approach based on geographic distribution (covering the main coal-producing provinces of the Yellow River Basin) and mine scale (with priority given to large- and medium-sized active mines). This sample represents approximately 27% of all registered active coal mines in the Yellow River Basin (estimated total 1500), ensuring representativeness in both spatial distribution and operational characteristics. The field investigation aimed to ascertain regional disparities and deficiencies in mine water treatment and utilization across different mining areas, providing empirical insights for the subsequent discussion of future management pathways.

3. Results and Discussion

3.1. Regional Spatial Context of Mine Water Production in the Yellow River Basin

Since the Chinese government promulgated the 12th Five-Year Plan (2011–2015), the development of China’s coal industry has been stable. Raw coal production has generally shown an upward trend. Coal resource exploitation in the Yellow River Basin has continued to intensify (Figure 2a), and its coal production accounts for approximately 80% of the national total. The provinces of Shanxi, Inner Mongolia, and Shaanxi constitute the core of coal supply (Figure 2b). They are the main drivers for regional coal output growth. Shanxi, a traditional coal-producing province, has significantly increased its output proportion. During the 14th Five-Year Plan period, Shanxi surpassed Inner Mongolia to become the leading coal supplier in the Yellow River Basin. This was due to continuous advancements in resource integration and the deployment of advanced production capacity. Inner Mongolia has consistently maintained a high level of output, supported by large energy bases. Shaanxi, relying on the resource advantages in its northern region (Shaanbei), has seen its coal output rise steadily. This has continuously strengthened its regional influence. Overall, coal development in the Yellow River Basin shows a trend of concentration in areas with comparative advantages and large-scale development.

3.2. Spatial–Temporal Characteristics and Evolution of Mine Water Production

The Yellow River Basin, as a vital coal-producing region, contains nine Large Coal Bases, including Huanglong, Ningdong, Jinbei, Jindong, Jinzhong, Shanbei, Shendong, Henan, and Luxi. It has become a crucial supporting area within the national coal resource supply system. From the perspective of the spatial distribution of coal development areas, there are 162 National Planned Coal Mining Areas across the country. Of these, 101 mining areas, accounting for 61.1%, are located in the Yellow River Basin, forming a vital bearing area for national coal resource security and energy output. If we further focus on the scope of the Yellow River Basin Area (natural hydrological scale) (see Figure 3), we find that there are 57 mining areas, accounting for 35.2% of the national total. These mining areas are primarily concentrated in the upper and middle reaches of the Yellow River Basin (natural hydrological scale).

The spatial distribution density pattern of mining areas in the Yellow River Basin was obtained using the Kernel Density Analysis (KDE) tool (Figure 4a). The results show that the distribution of mining areas in the Yellow River Basin exhibits a clear spatial agglomeration characteristic. The kernel density values range from 0 to 1.94, with the overall distribution pattern characterized by a central concentration and dispersion in the two wings. In terms of distribution density, the dense mining areas are mainly concentrated within the Yellow River Basin area (natural hydrological scale), particularly forming a distinct high-value core cluster at the junction area of Central Shanxi, Northern Shaanxi, and Southwestern Inner Mongolia, where the kernel density is significantly higher than in surrounding regions. Secondly, local sub-high-value areas also appear in regions such as north-central Henan and western Shandong, forming several localized secondary centers of gravity for agglomeration. The overall distribution shows a “core-periphery” diffusion pattern, decreasing from the center of the middle reaches of the Yellow River towards the upper and lower reaches.

The centroid of mine-water production shifted consistently and significantly northward over the entire period (2011–2024). The statistical analysis confirms that the longitudinal (east–west) displacement was non-significant across all transitions.

Table 2. Standard deviation elliptic parameters of mine water production layout.

	Period	Longitude of the Center of Gravity/(E)	Latitude of the Center of Gravity/(N)	Long Axis/km	Short Axis/km	Azimuth/(°)	95% Confidence Interval (CI) of the Shift (ΔX/ΔY)
Mine water production	H1	111°49′	35°55′	656.21	362.16	27.80
	H2	111°58′	36°32′	575.37	342.80	24.28	ΔX: [−0.127,0.476]° ΔY: [0.337,1.043]° *
	H3	111°52′	37°8′	514.96	323.47	20.58	ΔX: [−0.398,0.133]° ΔY: [0.201,0.835]° *

* Statistically significant (p < 0.05).

shows that the azimuth angle of the SDE for mine-water production in the Yellow River Basin ranges from 20.58° to 27.80° across the three periods. This reflects a northeast-southwest orientation near the middle reaches of the Yellow River. The angle decreases gradually from H1 to H3 but remains generally stable. Both the long and short semi-axis lengths decrease over time. This suggests weaker directionality and reduced spatial dispersion of mine water production. The trend points to an increasing concentration of mine water production.

In summary, the spatial pattern of mine water production in the Yellow River Basin exhibits pronounced spatial clustering and clear evolutionary trends, with the production center shifting northward overall and becoming increasingly concentrated. This result aligns with existing studies on the spatiotemporal evolution of the coal production pattern [39,40], further demonstrating that mine water production is largely influenced by the layout of coal mining activities. Mine water production in the Yellow River Basin (natural hydrological scale) will further concentrate in the Jiziwan region of the Yellow River [41], which hosts numerous coal production enterprises and development mining areas. This area of concentration highly overlaps geographically with ecologically vulnerable zones, making it the dominant region for mine water production in the Yellow River Basin. This spatial structural feature, characterized by “dense mining areas, high production volume, and significant water pressure,” dictates the systemic nature and complexity of the mine water problem in the Yellow River Basin, and constitutes the fundamental context for mine water resource utilization and ecological protection within the basin.

3.3. Evolution and Frontier Hotspots of Mine Water Treatment and Utilization Research

3.3.1. Analysis of Annual Publication Trends

This study statistically analyzed publication trends related to mine water treatment and utilization in the Yellow River Basin from 2011 to 2025 (Figure 5). Research activity has remained relatively active since 2011, reaching a peak of 91 publications in 2021. However, the overall trend shows notable fluctuations: after peaking at 91 papers in 2021, the annual output declined to 43 in 2024 and rebounded to 55 in 2025. The recent decline is attributable to major structural shifts in the field, which is further supported by the literature classification results (Figure 6). Research on mine water treatment and utilization in the Yellow River Basin can be divided into two stages: Applied Research Stage (2011–2016): During this period, applied studies outnumbered theoretical ones. Research primarily focused on addressing practical challenges in mine water treatment, with particular emphasis on engineering practices and technological applications. Theoretical Deepening Stage (2017–2025): In 2017, the proportion of theoretical publications exceeded 50% for the first time, and this proportion continued to increase thereafter (reaching 58% by 2025). Studies increasingly emphasized mechanism exploration and the development of theoretical frameworks. The decline in applied research (the blue portions in Figure 6) and the reduction in total publications after 2021 (Figure 5) reflect a shift in the maturity of the field. As research priorities move toward theoretical deepening, many conventional engineering cases and application-oriented studies are likely being consolidated, leading to a temporary decrease in total publications and a reduction in the share of applied research. This indicates that the field is becoming more mature, transitioning from an earlier phase dominated by applied case studies to one where deeper theoretical integration and mechanism-based research are prioritized.

3.3.2. Key Research Directions

The keywords are the highly condensed topics of the research in the paper. The keywords are statistically analyzed by using the keyword co-occurrence function in Citespace. Considering that “mine water” is a core keyword, it is meaningless for the analysis of the research content and was therefore eliminated. The co-occurrence analysis results of the screened literature are shown in Figure 7. In terms of overall frequency, “Coal Mine” is the most frequently mentioned keyword (75 times), reflecting that the research on mine water treatment in the Yellow River Basin is highly focused on the coal industry scenario. “Comprehensive Utilization” and “Water Treatment” ranked second and third with 61 and 55 times, respectively, indicating that the utilization of mine water resources and pollution control are the core research topics. The frequency of the terms “Reverse Osmosis” and “Advanced Treatment” appearing 52 and 35 times, respectively, indicates that advanced membrane treatment technologies remain one of the mainstream technical paths at present. In the direction of “Resource Utilization”, keywords such as “High Mineralization”, “Mine Wastewater”, and “Reuse” frequently appear, highlighting the need to address the complexity of water quality. The total frequency of the keywords related to “Coagulation Technology” exceeding 30 times indicates that the removal of suspended solids in mine water remains an important issue that must be addressed. “Energy conservation and emission reduction” has been a research hotspot guided by policies, with the keyword frequency exceeding 20 times in total, reflecting the guiding role of the green development concept in the direction of mine water treatment. “Optimization” has become an important keyword for enhancing the system’s operational efficiency and improving processes, covering multiple sub-items such as “Optimized Design” and “Optimized Configuration”. Overall, the high-frequency aggregation of keywords indicates that current research mainly focuses on improving water treatment technology, exploring resource utilization paths, and developing green and low-carbon strategies in the context of coal mines. This provides a clear research foundation and development direction for the subsequent integration and promotion of mine water treatment and comprehensive utilization technologies.

Based on keyword co-occurrence, CiteSpace’s clustering algorithm was applied to generate keyword clusters, from which the top 10 clusters were extracted. The final results are shown in Figure 8. The 10 clusters are as follows: #0 Mine water, #1 Coal mine, #2 Water treatment, #3 Coagulation, #4 Comprehensive utilization, #5 Underground reservoir, #6 Reverse osmosis, #7 Process flow, #8 Treatment, and #9 Energy conservation and emission reduction. The clustering modularity index (Q) of cluster analysis is 0.621. If it is greater than 0.3, it indicates that the network structure obtained by division is significant. The clustering profile index (S) is 0.903. If it is greater than 0.7, it indicates that the clustering results are efficient and reasonable. Both suggest that the results of the clustering analysis in this paper are convincing [42]. Meanwhile, partial overlaps among some clusters indicate a close interconnection between the research themes represented by different clusters. The results of keyword cluster analysis show that the research content related to mine water treatment and utilization in the Yellow River Basin mainly focuses on the following three aspects. (1) Research on Mine Water Treatment Technology and Process Optimization. This direction mainly focuses on the removal of suspended solids in mine water, the combined application of different treatment technologies, and the adaptability to the treatment of highly mineralized water bodies. The commonly used technologies at present are coagulation sedimentation, reverse osmosis, membrane separation, etc. In practical applications, they are gradually evolving towards high efficiency, low cost, and adaptability to complex water quality conditions. It is mainly reflected in cluster analysis of #2 (water treatment), #3 (coagulation), #6 (reverse osmosis), #7 (process flow), and #8 (treatment). (2) Exploration of the path for the utilization and comprehensive utilization of mine water resources. With the intensification of water shortage in the Yellow River Basin and the increasing requirements for ecological protection, the resource utilization of mine water has gradually become a research hotspot. The research focuses on the reuse of mine wastewater, the treatment standards, and matching technologies for different utilization scenarios (such as agricultural irrigation, industrial production, and ecological water replenishment), as well as the feasibility analysis of new utilization methods such as underground reservoirs. For instance, the recycling and reuse of mine wastewater, the construction and regulation and storage utilization of underground reservoirs, etc., reflect a transformation from single treatment to diversified utilization, mainly reflected in cluster analysis #4 (comprehensive utilization), #5 (underground reservoir), and #9 (energy conservation and emission reduction). (3) Research on regional management and practical applications centered on coal mines. This research category focuses on coal mining enterprises as the core units to explore management models and policy practices related to mine water discharge, treatment, and utilization. It emphasizes the optimization of mine water treatment systems, engineering applications of drainage reuse, and the green transition of coal mines under policy incentives. Through case studies of representative coal mines, these studies summarize regional experiences and limitations in mine water management and utilization, providing scientific support for coordinated water resource management at the regional level. This research focus is mainly reflected in clusters #0 (mine water) and #1 (coal mine).

3.4. Case Study Analysis and Identification of Treatment and Utilization Shortcomings

The survey results indicate that, in the current research phase, difficulties and non-standard practices persist in the statistical reporting of coal mine water utilization data. Mine water has inherent spatial dispersion. It also shows significant temporal fluctuations and marked differences in quality. These problems worsen due to the lack of unified standards for data collection and reporting across departments and enterprises. As a result, it is difficult to precisely quantify key data, such as the destination and volume of mine water utilization. Large modern coal enterprises have generally built relatively complete treatment systems. These use combined processes like coagulation-sedimentation, filtration, and membrane treatment. Some enterprises have introduced new technologies, such as magnetic separation, high-efficiency cyclonic purification, and mine water recharge or re-injection. In contrast, small and medium-sized or resource-depleted mining areas face major issues. These include outdated treatment facilities, difficult operation and maintenance, low mine water reuse rates, and singular usage purposes. Unstable water quality, high treatment costs, and the lack of proper management mechanisms further constrain re-use. Thus, most coal mines still mainly use mine water for underground dust suppression and surface greening within the mining area. Few mines achieve ecological replenishment or industrial reuse. Mine water resources are not being effectively utilized. Large coal mining enterprises have set up comprehensive water resource management systems. They have also started to explore digital platforms for online monitoring and remote regulation. In contrast, smaller mines still use manual, experience-based management practices. In some areas, statistical records are inaccurate, or mine water types are not clearly classified. This fails to meet the requirements of modern mine water management.

4. Outlook and Future Trends

This study reviews the characteristics of coal development and mine water production in the Yellow River Basin, as well as research hotspots in mine water treatment and utilization. Based on the theoretical framework of the mine water full life cycle—source reduction, harmless treatment during processes, resource recovery at tail end, and recharge at terminals [43]—it proposes the development of an integrated, efficient, and intelligent system for mine water treatment and utilization. Future directions are outlined in three aspects: optimization of technological pathways, expansion of resource utilization, and establishment of coordination mechanisms (Figure 9).

4.1. Optimization of Technical Paths for Mine Water Treatment and Utilization

As ecological protection and high-quality development in the Yellow River Basin receive increasing attention, mine water treatment technologies need to advance toward greater integration, efficiency, and intelligence. (1) Diversified combinations: Due to the complex quality of mine water, single treatment technologies often exhibit limitations such as low removal efficiency, poor stability, or high operational costs, making them insufficient to meet reclaimed water standards or ensure stable system performance [44,45]. Process optimization and the coupling of treatment units enhance both adaptability and overall system efficiency. For example, combined processes such as “coagulation–ultrafiltration–reverse osmosis” have achieved strong performance in practice [46,47], providing reliable water quality. Therefore, diversified combined processes are expected to become the mainstream development trend. (2) Specialized Process Advancement: Treatment methods for mine water with high mineral content, high suspended solids, or special chemical constituents continue to be actively investigated. As ecological requirements increase, low-energy consumption processes have become a primary research focus. Examples include super-magnetic separation [48], underground coal-mine reservoirs [49], and mine water recharge or reinjection technologies [50,51]. The development and refinement of these emerging processes can reduce resource consumption while improving recovery efficiency. (3) Application of Intelligent Systems: Intelligent monitoring is essential in the Yellow River Basin, where water treatment needs are both concentrated and geographically dispersed. Several coal mines have adopted cloud-based systems for digital operation and maintenance. These systems enable closed-loop management—from data acquisition and transmission to analysis and feedback—thereby enhancing facility efficiency. The application of intelligent systems provides reliable data and technical support for regional water resource allocation and ecological restoration. Through sensors, data acquisition, and intelligent algorithms, mine water treatment facilities can be managed with greater precision, reducing human error and improving automation and safety.

4.2. Expansion of the Utilization Path of Mine Water Resources

Given the current conditions of mine water production in the Yellow River Basin, promoting the comprehensive utilization of mine water is an inevitable pathway for achieving sustainable development in the coal industry. Mine water possesses “resource attributes” [52]. For example, low-mineralized mine water can be directly used for coal production and underground dust suppression, while treated mine water that meets relevant standards can be supplied for industrial use, agriculture, and even ecological restoration [53,54,55]. In addition, mine water contains substantial thermal energy potential, and mine-water heat pump technologies enable stable and efficient thermal recovery [56]. Looking ahead, it is necessary to establish a diversified and multi-tiered utilization foundation that enables mine water to serve production, industry, agriculture, culture, domestic needs, and ecosystem functions. Achieving “resource recovery at tail end” requires the expansion and integration of multiple utilization modes and the advancement of cascade utilization. The development of comprehensive utilization pathways must align with the inherent resource attributes of mine water and support the optimization of regional water balance and ecological demand.

4.3. Construction of Regional Coordination Mechanism

Currently, it is necessary to promote the upgrading of mine water treatment and utilization models in the Yellow River Basin from single-mine management to regional coordination. This involves constructing a regional coordination mechanism led by the government, implemented by enterprises, supported by scientific research, and with public participation, to enhance the mine water full life cycle treatment and utilization capacity. In the coal-intensive middle reaches of the Yellow River Basin, pursuing centralized mine water treatment and regional sharing, along with regional energy base construction, should improve resource utilization efficiency and economic feasibility. Furthermore, it is essential to strengthen the standardization and institutionalization of technical standards, operational norms, and regulatory mechanisms, providing support for achieving high-quality green development in the Yellow River Basin’s coal industry. Although some mining areas have explored certain reuse practices, the overall utilization level of mine water within the basin remains low, facing multiple obstacles such as unclear water volume statistics, insufficient application and promotion, high treatment costs, and unstable usage. The future approach should comprehensively consider social, economic, and environmental benefits, establish a differentiated water quality utilization standard system, and push for the implementation of fiscal and policy incentive mechanisms. Based on the standard of ecological protection and high-quality development of the coal industry in the Yellow River Basin, this will construct a systematic pathway for the transformation of mine water from an environmental burden to a valuable resource asset.

5. Conclusions

(1) The mine water production pattern in the Yellow River Basin exhibits significant spatial agglomeration and an evolutionary trend, with the center of gravity of production generally shifting towards the northward and the production pattern concentrating. This spatial characteristic of “dense mining areas, high production volume, and significant water pressure” has become the fundamental context for mine water treatment and utilization in the Yellow River Basin.

(2) Based on the bibliometric analysis, research on mine water treatment and utilization in China’s Yellow River Basin is transitioning from an application-oriented approach toward a phase of mechanistic deepening and systematic framework construction. The research focus is primarily on optimizing treatment processes, exploring pathways for resource utilization, and regional management models.

(3) The survey results show that large-scale coal mines have mature technology and management. Small-to-medium-sized and resource-depleted mining areas often have old equipment, basic management, and low resource use. In the Yellow River Basin, mine water treatment still faces high costs, changing water quality, and weak management. It is important to strengthen policy and adapt technology to improve water reuse.

(4) The following approaches are recommended to advance research and define regional coordination mechanisms for mine water management: Apply the “full life cycle” framework to integrate research and technology for mine water treatment and utilization in the Yellow River Basin. Emphasize diversified utilization, accelerate intelligent system development, and strengthen regional coordination. Design a systematic pathway to transform mine water in the Yellow River Basin from an environmental burden into a valuable resource asset.