APPLICATION OF MONTE CARLO SIMULATION TECHNIQUE IN DERIVATION OF RAINFALL TEMPORAL PATTERNS CASE STUDY: ZIDASHT WATERSHED, IRAN

The identification of rainfall temporal pattern is an essential task for hydrologists, climatologists as well as regional and local planners and managers. Monte Carlo simulation technique for flood estimation based on the principles of Joint Probability can employ many of the commonly adopted flood estimation models and design data. Design flood estimation is one of the major steps in the design and sizing of hydraulic structures and installations. When storage capacity is significant or return period of design flood is long, use of mathematical models is a common option for changing of the design rainfall to design flood. Design rainfall which cause to design flood must have some characteristics which one of them is distribution of rainfall during the rainy period which so-called design rainfall temporal pattern. Design rainfall temporal pattern is a major source of uncertainty in rainfall-based design flood estimation methods. In this study, Monte Carlo simulation technique which is based on the Joint Probability Approach, a holistic approach to design flood estimation that considers probability distributed inputs such as rainfall temporal pattern in rainfall-runoff modelling and model parameters, and their correlations, applied to determine probability-distributed rainfall temporal pattern in Zidasht watershed, Iran. Also, this is the first time that RORB model is used in Iran. In addition Joint Probability Approach and Monte Carlo simulation technique have not ever applied in Iran to extract rainfall temporal patterns.

Iran, Joint Probability Approach, Monte Carlo simulation technique, Rainfall Temporal Pattern, Zidasht watershed