Application of the Improved Knothe Time Function Model in the Prediction of Ground Mining Subsidence: A Case Study from Heze City, Shandong Province, China

Abstract

Taking into account the inadequacy of the Knothe time function model to predict the dynamic surface subsidence caused by underground mining, a new hypothesis is proposed, and the improved Knothe time function model is established. Theoretical analysis shows the improved model agrees well with surface subsidence dynamic change, velocity change, and acceleration change rules. Combined with field measured data, the probability integral method, dual-medium method, and least square method are adopted to determine the time influence parameter C and the model order n. Based on monitoring data from four monitoring stations in the Guotun coal mine subsidence basin strike main profile from Heze city, Shandong Province, China, the accuracies of the Knothe time function and improved model are compared and analyzed. Results show the improved model can accurately describe the dynamic surface subsidence process and subsidence velocity with mining time. The average relative standard error between the predicted and measured values is only 4.8%—far lower than the Knothe time function model is 23%, verifying the improved model’s accuracy and reliability.