A quantitative framework for evaluating overburden disturbance and surface subsidence induced by coal seam mining

Abstract Coal seam mining inevitably causes varying degrees of disturbance to the overlying strata and surface environment, necessitating the establishment of a scientific and systematic quantitative assessment framework for overburden disturbance. This study introduces a comprehensive methodology for assessing the impacts of mining activities on overburden strata. A theoretical model was developed to calculate the subsidence of a target rock stratum (TRS) during multi-panel mining, and an efficient computational tool was implemented using MATLAB. Key factors influencing TRS subsidence distribution were analyzed. The results indicate that mining height, loess thickness, and roof strata collapse angle positively correlate with TRS subsidence, while the distance between the coal seam and TRS, TRS thickness, and TRS elastic modulus exhibit negative correlations. Adjusting coal pillar width was shown to optimize the location of max-subsidence. Response surface methodology (RSM) was applied to explore the interactions among factors, revealing additive effects between positive-positive and negative-negative factors and attenuating effects between positive–negative factors. By integrating RSM, gray relational analysis, and normalization sensitivity analysis, the relative importance of influencing factors was quantified. A fuzzy comprehensive evaluation method was employed to establish a quantitative model for evaluating overburden disturbance. A disturbance index ( φ ) was introduced as a metric, with a threshold ( φ > 3.0) defined to identify significant surface deformation. The reliability of the proposed model was validated using geological borehole data and GNSS-measured surface subsidence from the No. 6105 panel of the Hongshuliang Coal Mine, achieving high predictive accuracy with an average absolute error of less than 0.085 after normalization. The analysis treated the uppermost bedrock in the study area as the TRS and provided a robust evaluation of post-mining surface disturbance. This study delivers a generalized assessment framework for predicting surface subsidence, and supporting the preliminary assessment of ascending mining feasibility and aquifer disturbance. The proposed system offers valuable insights for optimizing mining plans, managing mine-induced pressure, and protecting surface ecosystems.