Abstract
Roof water inrush is a major hazard threatening coal mine safety. This paper addresses the risk of roof water inrush during mining in the shallow-buried Jurassic coalfield of Northern Shaanxi, taking the Guojiawan Coal Mine as a case study. A systematic framework of “identification of main controlling factors–coupling of subjective and objective weighting–GIS-based spatial evaluation” is proposed. An integrated weighting system combining the Fuzzy Analytic Hierarchy Process (FAHP) and the Coefficient of Variation (CV) method is innovatively adopted. Four weight optimization models, including Linear Weighted Method, Multiplicative Synthesis Normalization Method, Minimum Information Entropy Method, and Game Theory Method, are introduced to evaluate 10 main controlling factors, including the fault strength index and sand–mud ratio. The results indicate that the GIS-based vulnerability evaluation model using the Multiplicative Synthesis Normalization Method achieves the highest accuracy, with a Spearman correlation coefficient of 0.9961. This model effectively enables five-level risk zoning and accurately identifies high-risk areas. The evaluation system and zoning results developed in this paper can provide a direct scientific basis for the design of water prevention engineering and precise countermeasures in the Guojiawan Coal Mine and other mining areas with similar geological conditions.