Groundwater distribution influenced by mining activities is hard to be tracked due to the lack of accurate and real-time monitoring data. To address the groundwater dynamic change data under the mining conditions of open-pit coal mines, a three-dimensional automatic observation network of groundwater was constructed, and this observation network takes open-pit as the center, showing a radioactive distribution, based on hydrogeological conditions, and observes different aquifers. The data was analyzed by integrating hydrology, mining activity, and meteorological data. Analytic hierarchy process was adopted to reveal the underground disturbance influencing factors, and suggestions for groundwater protection were given. The results show that the dynamic variations of the groundwater with time can be divided into 3 types (precipitation affected, unaffected type, and mining affected types). The drainage operation during the open-pit mining triggered the drop of groundwater level, resulting in a cone of depression. The maximum drawdown of the central groundwater level was 60 m. And the disturbance mainly occurred in the mining area where the maximum groundwater disturbance radius was 8 km. Artificial drainage was the main disturbance factor of groundwater, and the range of groundwater level drop within the disturbance radius was closely related to the distance from the open-pit coal mine and the drainage volume. The closer the distance to the mines and the higher the drainage volume led to the deeper the groundwater level drop. This study shows the importance of the three-dimensional observation network of groundwater and provides a good reference for groundwater resources protection and ecological restoration in open-pit coal mines.

Land surface temperature (LST) is a key indicator reflecting the ecological environmental disturbance caused by open-pit coal mining activities and determining the ecological status in alpine permafrost regions. Thus, it is crucial to study the spatiotemporal variations and influencing mechanisms of LST throughout all stages of small-scale mining–large-scale land surface damage–ecological restoration. Landsat imagery over nine periods was extracted from the growing seasons between 1990 and 2024. This study retrieved LST while simultaneously calculating albedo, soil moisture, and normalized difference vegetation index (NDVI) for each time phase. By integrating land use/cover (LUCC) data, the spatiotemporal evolution patterns of LST in the mining area throughout all stages were revealed. Based on the Geodetector method, an identification approach for factors influencing LST spatial differentiation was established. This approach was applicable to the entire process characterized by significant land type transitions. The results indicate that the spatiotemporal variations in LST were significantly correlated with land surface damage and restoration caused by human activities in the mining area. With the implementation of ecological restoration, high and ultra-high temperatures decreased by about 25.98% compared to the period when the surface damage was the most severe. The main influencing factors of LST differentiation were identified for different land use types, i.e., natural and restored meadows (soil wetness, albedo, and NDVI), mine pits (albedo, aspect, and elevation), and mining waste dumps (aspect and albedo before restoration; aspect and NDVI after restoration). This study can provide a reference for monitoring the ecological environment changes and ecological restoration of global coalfields with the same climatic characteristics.

In the context of extensive high-intensity mining in open-pit coal mines, the temporal and spatial changes of the groundwater level and the range of disturbance caused by the mining activities remain unclear, and the traditional hydrological observation methods are insufficient in obtaining accurate and real-time groundwater monitoring data under the open-pit mining conditions. To address these challenges, the construction of an automatic groundwater observation network to obtain long-term groundwater level dynamic monitoring data via wireless remote transmission, integrated with hydrological background value survey, open-pit coal mine production and drainage data, meteorological data, and hydrogeological data, will reveal the temporal and spatial change characteristics of groundwater under open-pit coal mining conditions and disturbances radius and area of influence on groundwater. The results show: 1) The drainage operation during the open-pit mining caused the drop of groundwater level and forming of a cone of depression, with maximum drawdown of the central groundwater level at 60 m. The disturbance mainly occurred in the mining area where the maximum groundwater disturbance radius was 8 km, and the disturbance area accounted for 66.7% of the mining area. and 10% of the hydrogeological units; 2) The range of groundwater level drop within the disturbance radius is closely related to the distance from the open-pit coal mine and the drainage volume. The closer the distance to the open-pit coal mine and the greater the drainage volume led to the greater the groundwater level drop; 3) The change characteristics of dynamic curve of groundwater can be divided into 3 types (weather-affected, unaffected and mining-affected). Therefore it is of great significance for groundwater resources protection and ecological restoration in open-pit coal mines to conduct automatic monitoring of groundwater, and study the influence of open-pit coal mining on groundwater by establishing a three-dimensional observation network of groundwater in open-pit mines.