Currently, water inrush accidents in China’s coal mines are mainly under control, but occasionally, grave water inrush accidents still occur, causing significant casualties and economic losses. Existing studies have primarily focused on accident statistics, and the research on the trend of accident evolution is becoming obsolete to match the current context of coal resource development. This study analyzes the water inrush accidents in China’s coal mines between 2014 and 2022. It investigated the spatial and temporal distribution of accidents, the level of accidents, and the extent to which water prevention and control measures vary by zone in coal mines. The study results showed that from 2014 to 2022, water inrush accidents in coal mines exhibited a “decline-stability-fluctuation” stage change pattern. Additionally, the location of water inrush accidents has shifted westward. Paying particular attention to preventing and controlling water disasters in coal mines within the west development zone is crucial. The water disaster accidents in China’s coal mines have been effectively controlled, but the problem of unequal levels of preventing and controlling water disasters in coal mines persists. This study can provide a reference for the safe and efficient production of coal mines and the control of the number of deaths in mine water hazard accidents.

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.

The roof aquifer of the Jurassic coal seam is the primary source of water inrush in the Nalinhe Mining Area. It poses a severe threat to safe mining operations. Accurate prediction of its water richness is crucial for production safety. This study focuses on the Nalinhe No. 2 Coal Mine. Seven key controlling factors were selected as evaluation indicators, including aquifer thickness, burial depth, core recovery rate, the thickness ratio of brittle to plastic rock, fault scale density, fault fractal dimension, and the density of fault endpoints and intersections. A hybrid weighting strategy was applied in this study. This strategy integrates the Analytic Hierarchy Process (AHP) and the Entropy Weight Method (EWM) to assign scientific weights to the evaluation indices. A water richness evaluation model was subsequently developed based on matter-element extension theory. The model calculates the comprehensive correlation degree for each grid node and determines the corresponding water richness level. Zoning results were validated with unit inflow data from pumping test boreholes, mine inflow observations, and ground transient electromagnetic survey findings. The predicted water richness zones closely matched the measured hydrogeological data. These results demonstrate the scientific rigor and reliability of the matter-element extension model. The proposed model provides a novel approach for assessing water richness in coal seam roof aquifers.

The contradiction between water supply and spring preservation issues is becoming increasingly apparent as Lijiang City develops. An investigation into the dynamic variations in the discharge rate of Heilongtan Spring in Lijiang City and the response law between the water level of the spring and precipitation is crucial for safeguarding the landscape water of Heilongtan Spring. This study employed linear regression analysis, Mann–Kendall (MK) mutation test, wavelet analysis, and vector autoregression (VAR) to examine the fluctuating pattern of the Heilongtan Spring discharge and the response of the Heilongtan Spring water level to precipitation in Lijiang City. Furthermore, the study discussed the influence of human activities on the alteration of Heilongtan Spring. The results indicate that the mean discharge rate of Heilongtan Spring is 0.94 m³/s, with an annual variation of 0.05 m³/s. The time series analysis reveals that the variation pattern of Heilongtan Spring discharge aligns with the precipitation trend in Lijiang City. Nevertheless, there is a distinction between the timing of the Heilongtan Spring discharge station point and the precipitation mutation point in Lijiang City. The significant primary cycle of spring discharge change occurs every 18 months, with a cycle length of 12 months. The vector autoregression (VAR) model demonstrates a lagged relationship between the water level of Heilongtan Spring and the precipitation in Lijiang City. Specifically, the water level of Heilongtan Spring has a four-month lag response to precipitation variability in Lijiang City. The results can provide a beneficial reference for preserving spring water and managing regional water resources.