# MCPSHA: A New Tool for Probabilistic Seismic Hazard Analysis Based on Monte Carlo Simulation
## 1 Introduction
The intensity exceedance probability is calculated using the extreme value distribution, and the final expression is thoroughly considered by taking into account various factors such as the potential source and its magnitude upper limit, as well as the temporal and spatial distribution unevenness of seismic activity. Using hypothetical conditions to reduce the mathematical expressions of the model may result in large deviations in the calculation results, especially in high intensity, and addressing the problem of the uncertainty of various factors caused by model simplification is also challenging. As a result, understanding how to build the resulting occurrence probability of the intensity model is critical for the study of earthquake loss assessment. The data required for a seismic hazard assessment using traditional probabilistic seismic hazard assessment methods (PSHA) can also be used for probabilistic hazard analysis using Monte Carlo simulation methods [21; 22; 23]. Monte Carlo simulation methods stand out due to their exceptional flexibility and transparency, proficient handling of parameter uncertainties, and implementing complex seismic activity models [24]. [PERSON] [25] systematically explores random factors in seismic risk assessment for structures using the Monte Carlo method, examining the randomization of crucial parameters in numerical simulations and employing asymptotic distributions of extremes to enhance the reliability of estimates, particularly in the context of rare seismic events with multiple response re strictions. [PERSON] and [PERSON] [26] employ a CIS-based Monte Carlo simulation to assess the impact of random perturbations in earthquake ground shaking intensity zone boundaries and consider sensitivity to intensity estimation errors, revealing that variations within a 1560 m corridor have minimal effect on property loss estimates, while a five percent error in ground shaking intensities leads to an 11 to 15 percent error in property loss estimates, demonstrating the use of GIS to simulate error propagation and identify strategic error reductions in risk assessments. Numerous established software packages exist [24; 27; 28; 29]. These approaches rely on Monte Carlo simulations for hazard calculation and have found extensive application in various seismic risk assessments [22; 30; 31]. Nevertheless, the package software may not be suitable for the Chinese area. CPSHA (China Probability Sessmic Hazard Assessment) is a modified PSHA method that has advantages in characterizing the non-uniform spatial distribution of intraplate earthquakes in China [32; 33]. The effect of the Monte Carlo method with CPSHA is unknown on the resulting probabilistic results in China. To fill this gap, we present an exploration of the framework for Chinese probabilistic seismic hazard analysis utilizing the Monte Carlo approach (MCPSHA) implemented in MATLAB. This approach allows for the determination of earthquake intensity, occurrence, and exceedance probabilities. The three integral components of MCPSHA, namely the seismic source model, earthquake recurrence model, and ground motion attenuation model, are comprehensively addressed. The Baoji area is selected as the research site. To assess the compatibility of our proposed method with conventional approaches, seismic hazard maps (with a 10 percent probability of exceedance in 50 years) are computed on a 0.05-degree grid using both our program and a classic seismic hazard assessment program (Cornell-McGuire approach). Furthermore, the occurrence and extreme probability of VI, VII, and VIII seismic intensities over 50 years are calculated and analyzed. The development of the framework and the results derived from MCPSHA serve as a benchmark for comprehensive seismic hazard and seismic risk analysis.