Abstract: To obtain the contact parameters of livestock and poultry manure accurately and quickly, this study calibrated the contact parameters of pig manure by physical stacking test and simulation method. A stacking angle measurement test bench was designed, and the contour of the stacking slope was obtained by the image-digital simulation method, and a linear fitting was performed. Through the natural air-drying and the deionized water adjustment methods, the pig manure accumulation angle under different water content was measured, and a polynomial fitting model between the water content and the pig manure accumulation angle under different water contents was established. To obtain the actual stacking angle, the Hertz-Mindlin with JKR sphere bonding model was used, and the discrete element simulation of the physical stacking test was performed by EDEM2.7 Screening experiment design (Plackett-Burman Design, P-BD) was used to screen 10 initial parameters. It was found that JKR (Johnso-Kendall-Roberts) surface energy, particle-particle rolling friction coefficient, and particle-particle collision recovery coefficient had significant effects on the swine manure accumulation angle, and the other 7 factors had no significant effect on the accumulation angle. The best range of three significant influencing factors was determined by the steepest climbing test. The 7 non-significant influencing factors in this test were the intermediate values of the initial range, and the 3 significant parameters gradually were increased until the relative error between the simulated value and the physical test value reached the minimum. Based on the results of the response surface experiment design (Box-Behnken Design, B-BD), a quadratic polynomial model between the stacking angle and the three significant parameters was created. The analysis of the quadratic polynomial model variance showed that the model was meaningful. Under the condition that the model was significant and the miss-fit terms were not significant, the terms that did not significantly affect the results were removed, and the regression model was optimized to obtain a new quadratic polynomial regression model. The coefficient of variation of the optimized model dropped to 0.81%, indicating that the reliability of the model had been further increased. The determination coefficient R2 =0.994 1 and the correction determination coefficient R2adj=0.986 1 were both close to 1, indicating the model fitted better. The precision (precision) was 37.023, improved before optimization, which could be used to predict the particle accumulation angle. Through the optimization of the optimized quadratic polynomial regression model, the best parameter combination of 3 significant influencing factors were obtained. The results illustrated that the surface energy of JKR was 0.03 J/m2, the coefficient of rolling friction between pig manure and pig manure was 0.27, and the coefficient of recovery of the collision between pig manure and pig manure particles was 0.54. The discrete element stacking test simulation was carried out based on the calibrated optimal values of the discrete element parameters of pig manure, and the error between the simulated stacking angle result and the actual test result was 4.27%, which showed that the calibration results were credible. The results could provide a reference for the selection and calibration of discrete element model parameters to other agricultural livestock and poultry manure.