Stochastic Generation of Storm Pattern

Lack of storm patterns (storm hyetograph) in many catchments is an important issue in hydrological analysis. So, in many studies various methods are developed to generate storm pattern. There are uncertainties in generated storm patterns due to uncertainty of generating method (model uncertainty) and uncertainty of the variables affecting the storm patterns such as the total depth of rainfall, rainfall duration and dimensionless hyetograph (inherent uncertainty). This study developed the Rain Data Processor (RDP) and the Rain Pattern Generator (RPG) models to generate storm patterns based on Mass curve method with considering inherent and model uncertainty in ungauge catchments by using the Monte Carlo simulation and Bootstrap resampling. Methodology of this study is applied in Iran (Seymareh catchment). According to the statistics of generated peak intensity by the RPG model; there is an acceptable agreement between observed and generated hyetographs. Also, the RPG model is more accurate than triangular hyetograph model in generation of storm pattern.