This study produced the parameter maps of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall generation model across South Korea and developed and validated the web application that automates the process of rainfall generation based on the produced parameter maps. To achieve this purpose, three deferent sets of parameters of the MBLRP model were estimated at 62 ground gage locations in South Korea depending on the distinct purpose of the synthetic rainfall time series to be used in hydrologic modeling (i.e. flood modeling, runoff modeling, and general purpose). The estimated parameters were spatially interpolated using the Ordinary Kriging method to produce the parameter maps across South Korea. Then, a web application has been developed to automate the process of synthetic rainfall generation based on the parameter maps. For validation, the synthetic rainfall time series has been created using the web application and then various rainfall statistics including mean, variance, autocorrelation, probability of zero rainfall, extreme rainfall, extreme flood, and runoff depth were calculated, then these values were compared to the ones based on the observed rainfall time series. The mean, variance, autocorrelation, and probability of zero rainfall of the synthetic rainfall were similar to the ones of the observed rainfall while the extreme rainfall and extreme flood value were smaller than the ones derived from the observed rainfall by the degree of 16%-40%. Lastly, the web application developed in this study automates the entire process of synthetic rainfall generation, so we expect the application to be used in a variety of hydrologic analysis needing rainfall data.