Local Water Inrush Risk Assessment Method Based on Moving Window and Its Application in the Liangshuijing Mining Area

Abstract

Most of the existing coal mine water inrush risk assessment methods are global assessment methods, which have the following problems: they ignore the difference in importance of the evaluation indicators at different locations in the study area and assign the same weight value; the area of the danger zone in the evaluation results is thus too large. The evaluation results improve the prediction accuracy by reducing the safe zone area. To address the aforementioned issues, this study employs a local analysis method based on a moving circular window, taking into account the spatial heterogeneity of criterion indicators in the decision-making process. By traversing each position of the raster with a circular moving window, the method performs local standardization and calculates local weights of indicators within the local window range. Based on the obtained maps of locally standardized evaluation criteria and local weights, a local water inrush risk assessment model is established using Geographic Information Systems (ArcGIS), considering the differences in the importance of evaluation indicators within the study area. Taking the Liangshuijing mining area as an example, both global and local evaluation models were employed to assess its water inrush risk. The evaluation results obtained from these two models were compared and validated against geological survey data and historical water inrush points. The comparative analysis between the two methods reveals that the local evaluation model demonstrates higher accuracy. It offers a more precise delineation of the distribution of water inrush risk zones, which better corresponds to the actual conditions within the mine. The localized water inrush risk assessment method proposed in this paper breaks away from the traditional approach of uniformly weighting evaluation indicators across the entire area, offering a novel method for assessing water inrush risk.