High-resolution spatiotemporal precipitation data are critical for accurate hydrological simulations. This paper presents stochastic simulations of the hourly precipitation processes at 142 meteorological stations across the Huang-Huai-Hai Plain

using a Hyetos stochastic precipitation model that couples the Bartlett-Lewis rectangular pulse model with a daily precipitation adjustment algorithm. This model is evaluated comprehensively on its performance using metrics such as basic statistical characteristics

extreme precipitation indices

and intra-day wet-dry characteristics. Results reveal the model accurately simulates the means and standard deviations of hourly precipitation but underestimates its skewness coefficients. While it captures the intensity and frequency indices of certain extreme precipitation events

it underestimates the annual maximum 1-hour precipitation and extreme precipitation intensities. Its biases are evident in simulating intra-day wet-dry characteristics

particularly for those long-duration events. The findings would be useful to precipitation-runoff simulations in the study region.