Multifactor Prediction of the Water Richness of Coal Roof Aquifers Based on the Combination Weighting Method and TOPSIS Model: A Case Study in the Changcheng No. 1 Coal Mine

Abstract

Identifying the water richness of coal roof aquifers is an important and difficult goal of hydrogeological research to prevent and control roof water disasters. To evaluate the water richness of roof sandstone aquifers of the No. 1 coal seam in the Changcheng No. 1 coal mine, a multifactor prediction method based on the fuzzy Delphi analytic hierarchy process (FDAHP), entropy weight method (EWM), sum of squared deviations (SSD), and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was proposed. Multisource geological data, including sandstone thickness, burial depth, lithological composition index, core recovery, fault scale index, fault intersections and endpoint density, and fold fractal dimension, were chosen as the primary indicators for evaluating the water richness of roof sandstone aquifers. The FDAHP and EWM were used to scientifically determine the subjective and objective weight vectors of these seven main factors, and the SSD was used to determine the optimal combination weights based on the objective and subjective weight vectors. On this basis, the water richness index (WRI) model was developed using the TOPSIS method to rank the water richness of samples in the study area. A water richness zoning map was created using the WRI values, revealing three zones: the weak water richness zone, moderate water richness zone, and strong water richness zone. Additionally, the map was refined by incorporating hydrogeologic data collected during mining operations, including pumping tests and actual water inrushes from roadways and working faces. It is believed that the proposed WRI model is effective for predicting the water richness of the roof sandstone aquifers of the No. 1 coal seam in the Changcheng No. 1 coal mine based on the engineering practice data used to validate the WRI model.

Water-richness evaluation method and application of clastic rock aquifer in mining seam roof

“…With increasing coal seam thickness, the caving zone expands, leading to a corresponding increase in the development of the water-conducting fractured zone. Proportion coefficient of hard rock lithology ( b ) 15 . This factor can replace the two influencing factors of the uniaxial compressive strength and structural type of the roof combination rock layer, reflecting the strength type and lithology combination of the coal seam roof.…”

“…Proportion coefficient of hard rock lithology ( b ) 15 . This factor can replace the two influencing factors of the uniaxial compressive strength and structural type of the roof combination rock layer, reflecting the strength type and lithology combination of the coal seam roof.…”

“…Wang et al 14 also used AHP to establish an evaluation system and conducted water-richness zoning in the study area, providing scientific guidance for the prevention and control of water disasters in mining areas. Qiu et al 15 successfully applied Fuzzy Delphi Analytic Hierarchy Process (FDAHP) combined with entropy weight method, introducing the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to construct an aquifer richness evaluation model. In another study area, Qiu et al 5 combined FDAHP with grey correlation analysis to establish a water-richness zoning model with high accuracy.…”

Analysis of Potential Water Inflow Rates at an Underground Coal Mine Using a WOA-CNN-SVM Approach

“…The thickness of the aquifer is the basis for determining the strength of water yield and is also a direct influence [5]. The greater the thickness of the aquifer, the stronger the water yield.…”

“…With the increasing mining scale and intensity, the problem of coal seam roof water disasters has become increasingly prominent, which seriously threatens the safe mining of coal mines, resulting in surface subsidence and affecting the stability of buildings [3,4]. However, the water yield of aquifers directly affects the occurrence and frequency of water inflow [5]. Moreover, due to the influence of coal seam mining, the water yield of aquifers changes dynamically, and the borehole data are scarce and cannot be characterized globally in space [6].…”