In mining areas with high groundwater levels, intensive coal mining has led to the accumulation of substantial surface water and significant alterations in regional landscape patterns. Reconstructing the ecological security pattern (ESP) has emerged as a critical focus for ecological restoration in coal mining subsidence areas with high groundwater levels. This study employed the patch-generating land use simulation (PLUS) model to predict the landscape evolution trend of the study area in 2032 under three scenarios, combining environmental characteristics and disturbance features of coal mining subsidence areas with high groundwater levels. In order to determine the differences in ecological network changes within the study area under various development scenarios, morphological spatial pattern analysis (MSPA) and landscape connectivity analysis were employed to identify ecological source areas and establish ecological corridors using circuit theory. Based on the simulation results of the optimal development scenario, potential ecological pinch points and ecological barrier points were further identified. The findings indicate that: (1) land use changes predominantly occur in urban fringe areas and coal mining subsidence areas. In the land reclamation (LR) scenario, the reduction in cultivated land area is minimal, whereas in the economic development (ED) scenario, construction land exhibits a marked increasing trend. Under the natural development (ND) scenario, forest land and water expand most significantly, thereby maximizing ecological space. (2) Under the ND scenario, the number and distribution of ecological source areas and ecological corridors reach their peak, leading to an enhanced ecological network structure that positively contributes to corridor improvement. (3) By comparing the ESP in the ND scenario in 2032 with that in 2022, the number and area of ecological barrier points increase substantially while the number and area of ecological pinch points decrease. These areas should be prioritized for ecological protection and restoration. Based on the scenario simulation results, this study proposes a planning objective for a “one axis, four belts, and four zones” ESP, along with corresponding strategies for ecological protection and restoration. This research provides a crucial foundation for decision-making in enhancing territorial space planning in coal mining subsidence areas with high groundwater levels.

Mineral resource extraction and urban expansion in resource-based cities have progressively degraded regional ecosystems, leading to increasingly fragmented ecological patterns. Ecological network resilience plays a critical role in maintaining regional ecological stability. In this study, we integrated landscape ecology and systems science to develop a network model and assess the resilience of ecological networks in the coal mining subsidence area with high groundwater levels. This study employed morphological spatial pattern analysis (MSPA) and circuit theory to construct the ecological network. A cascading failure model was further applied to simulate network dynamics under three attack strategies. Based on a comparative analysis of these strategies, we introduce the concept of “dangerous nodes” to identify priority conservation areas. The research results show that 101 ecological source areas and 255 ecological corridors were identified in the study area. Topologically, its ecological network is characterized by a small number of core nodes and a large number of secondary nodes. When the adjustable parameter is $\alpha <1.2$, targeting low-degree nodes may inflict more severe damage on the network. When $\alpha >1.2$, attacks against nodes with a high-degree or high betweenness centrality may have significant cascading failure implications. Our results show that the network’s critical threshold $T_c$ depends on the number of dangerous nodes in the attack set. The distribution of these nodes differs substantially between low-degree attacks and those targeting high-degree or high betweenness centrality nodes. These findings advance ecological network optimization and provide practical guidance for ecosystem conservation and restoration in resource-based cities.