Surface subsidence, a major geological hazard induced by mining activities, severely compromises the sustainable economic development of mining areas and the safety and stability of residents’ livelihoods. Consequently, long-term and effective monitoring and prediction of mining areas are essential. Aiming to identify the key characteristic of narrow and elongated mining areas—where the strike length is significantly greater than the dip length—this study proposes a surface subsidence monitoring method integrating Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) and the Improved Probability Integral Method (IPIM). Specifically, this method utilizes SBAS-InSAR technology to acquire cumulative subsidence results of low-gradient deformation zones in mining areas. To address the issue of excessively fast edge convergence in traditional Probability Integral Method (PIM) applications for narrow and elongated mining areas, the traditional PIM is adjusted by modifying the dip-direction influence radius parameter; this adjustment alters the shape of the dip-direction subsidence curve at the edge of the subsidence basin, thereby resolving the convergence problem. Meanwhile, based on the InSAR deformation gradient theory, the subsidence edge and subsidence center are identified, and the corresponding threshold is determined. The results of SBAS-InSAR and IPIM are then fused via the inverse distance squared weighting (IDSW) method to eliminate discontinuous boundaries in fused results and obtain complete surface subsidence data of the mining area. Taking the 31109-1 working face of the Lijiahao Coal Mine as the study area, 14 scenes of Sentinel-1A imagery and field leveling data of the working face were used to validate the feasibility and accuracy of the proposed method. The results indicate that a distinct rectangular subsidence basin was formed in the working face during the monitoring period. The maximum subsidence measured by the integrated method is 3453 mm, and the location, subsidence curve, and variation trend of the monitored subsidence basin are basically consistent with actual mining conditions. The maximum relative errors of subsidence in the strike and dip directions are 5.2% and 4.1%, respectively. This method can effectively compensate for the limitations of SBAS-InSAR and PIM when applied individually to surface subsidence monitoring in narrow and elongated mining areas, enabling the acquisition of refined subsidence information for the entire mining basin. The research results provide a scientific basis for subsidence monitoring and early warning, disaster prevention and mitigation, and the rational development and utilization of resources in mining areas.

Accurate quantification of groundwater evapotranspiration (ET_g) is essential for reliable water resource assessment. Existing methods for estimating ET_g from water table fluctuation largely rely on one-dimensional simplifications that neglect transient groundwater flow. However, in areas with shallow water table and topographic relief, where transient groundwater flow often occurs, the validity and accuracy of this simplification remain inadequately evaluated. In this study, we used HYDRUS-2D to construct a 50 m-long sandy hillslope with a 0.05 gradient to investigate ET_g based on the water table fluctuation (WTF) method under transient groundwater flow conditions. The results indicate that periodic evapotranspiration generates water table fluctuations along the hillslope that exhibit amplitude attenuation and temporal phase lag, features not captured by 1D models. Ignoring transient groundwater flow leads to a systematic underestimation of ET_g by up to 85% in sandy soil near the topographic lows. Furthermore, we found that both the decoupling depth and the extinction depth are significantly amplified by lateral groundwater flow, by up to 66% and 51%, respectively, compared with 1D estimates derived from the Shah method. These findings highlight the importance of incorporating transient flow processes into ET_g estimation to improve the accuracy of water balance assessments and ecohydrological predictions, particularly in areas with shallow water tables and topographic relief.