Halimah Tun Satdiah, - and Rado Yendra, - and Muhammad Marizal, - and Ari Pani Desvina, - and RAHMADENI, - The Effect of Simulation Storm Amount Hourly Rainfall Based on Increase Various Rates Parameters to Mean and Maximum by Using Best Distribution Model.

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Abstract

Flood events are very difficult to predict early, this is because the value of the amount of rainfall that occurs for each month in the next few years cannot be properly estimated, of course, will result in difficulty estimating the strength of the dam in holding back the flow rate water, in addition to the difficulty in estimating the size of the ditch as a rain reservoir for the next few years. This event will continue to occur every year along with an increased amount of rainfall. Amount rainfall variables can be determined using short-scale rainfall such as hourly obtained using storm theory. This study focuses on using hourly rainfall data to be modeled using several probability distribution models such as Gamma, Weibull, and Log Normal. Once the best model can be determined, the parameters will be modified by increasing every 10% so that it reaches 50% and using the quantile function the Amount of rainfall data simulation based on parameter modification will be carried out and the two characteristics of the simulated data such as the mean and maximum amount values will be compared to show the effect of increasing storm amount rainfall. In this study, it was found that the log-normal distribution model was the best and an increase in parameter values would affect the increase in the mean and maximum amount of rainfall for each year. Keywords - Amount Storm, Storm Theory, Gamma, Weibull, Log Normal, Quantile Function.

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