## 1 Introduction  
Strong ground motions induced by devastating large earthquakes will not only cause many casualties but also destroy human habitats and threaten the safety of major infrastructures [1, 2]. Thus, many countries have developed seismic codes to guide the earthquake-resistant design of various building structures [3, 4, 5, 6]. In particular, seismic hazard assessment of the engineering sites of major infrastructures is required since it is of great importance to the sustainable development of critical infrastructures such as nuclear power plants, reservoirs, and hydropower stations, especially for those located in seismically active regions. Deterministic seismic hazard analysis considers worst-case scenarios or the maximum credible earthquake to estimate the intensity of seismic ground motion distributions. The current approach to obtaining deterministic ground motion parameters is to employ only one set of modeling parameters for ground motion simulations or calculate average values by using ground motion prediction equations. However, it is difficult to obtain accurate ground motion simulation parameters, and ground motion prediction equations from both domestic and foreign sources lack near-field strong ground motion recordings [7, 8, 9, 10, 11, 12]. The reasonable evaluation of near-field ground motion parameters offers important engineering significance for seismic fortification, which has an effect on the evaluation of structural responses and the results of nonlinear analysis [13, 14, 15, 16]. Regionally adoptable ground motion simulation parameters are critical for obtaining reasonable simulation results. However, aleatory and epistemic uncertainties inevitably exist when determining these parameters; therefore, different researchers can obtain different ground motion simulation parameters for the same fault [17; 18]. Therefore, it is particularly important to consider the uncertainties of modeling parameters when calculating peak ground acceleration (PGA) and the response spectra of near-field large earthquakes when using ground motion simulations, considerations often overlooked in simulation work [19; 20]. Over the past two decades, the stochastic finite-fault method has been applied to the simulation of near-field ground motion parameters of large earthquakes, providing reliable ground motion predictions for areas that lack strong ground motion records [21; 22; 23; 24; 25; 26; 27; 28; 29]. This method can be used to effectively synthesize Fourier amplitude spectra, response spectra, and the time history of acceleration [30]. This method can also be used to analyze the effect of modeling parameter uncertainty on ground motion simulations [19; 20]. [PERSON] et al. [19] analyzed the applicability of the stochastic finite-fault method in near-field large earthquake simulations. Based on the parameters of uncertainty analysis, they established a comprehensive evaluation system for ground motion parameters and considered the influence of different seismogenic tectonics on a dam site. [PERSON] et al. [20] used the stochastic finite-fault method to consider the impact of the source, propagation path, and site conditions. They analyzed fault size, rupture velocity, shear wave velocity, stress drop, kappa value, and \(Q\) value and produced a corresponding range of values. In this study, based on a multi-scheme simulation and the stochastic finite-fault method, we focused on analyzing the impact of different source models, initial rupture points, and site locations on the simulation of near-field large earthquakes. The Tianshan orogenic belt is a compressiverogenic belt located within the Eurasian continent (Figure 1a). It is the result of the collision of the Indian and Eurasian plates during the Late Cenozoic [31; 32]. Previous geological and geodesy studies have shown that the northern and southern boundary fault zones of the Tianshan Mountains exhibit strong structural deformation [33; 34; 35; 36].