Development of Intensity Duration Frequency (IDF) Curves for Merawi Town, Ethiopia, Using Stationary Approach

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Date

2024-06

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Addis Ababa University

Abstract

Planning and management of water resources depend heavily on intensity duration frequency curves because they show the statistical relationship between rainfall frequency and intensity duration. This thesis used the universal extreme value stationary approach, which is implemented in the R statistical programming environment, to give a thorough examination into the development of rainfall intensity duration frequency curves. The study starts out by going over the theoretical understanding of the general extreme value model and how it is applied to the process of creating rainfall intensity duration frequency curves. Next, using specific packages and functions to effectively handle rainfall data, fit the general extreme value distribution, and produce the final intensity duration frequency curves; it explores the step-by-step implementation of the general extreme value stationary approach in R studio. For the duration of the observation periods, the stationary model takes constant parameters into consideration. Estimating the distribution parameters involved applying the maximum likelihood estimator method. Statistical programming software R-studio was utilized to compute the distribution parameters, intensity levels, and fit the GEV stationary model to sample rainfall data. For four neighboring rainfall sites, the National Meteorological Agency in Addis Ababa, Ethiopia, provided the necessary historical rainfall data. Various tests and trends using the rainfall data were looked at. The Man-Kendall trend test at each station's rainfall data showed no patterns. The stationary model was adopted for return levels estimation for all rainfall stations instead of the non-stationary model due to the lack of trend results. The distribution parameters of the parameter model were used to forecast the return levels for each return term of 2, 5, 10, 25, 50, and 100 years. Since the model did not exhibit time-varying variability, it was possible to derive maximum return level outputs directly from the general extreme value fitted to the maximum annual rainfall. The return levels were then plotted on the x-y axis and translated to rainfall intensity using a simple formula. In practice, longer return periods yielded higher values than shorter return periods when computing rainfall intensity. For instance, a 15-minute rainstorm stationary model with a 25-year return period produced an intensity of 178.28 mm/hr, while a 15-minute rainstorm with a 100-year return period produced 261.2 mm/hr of rainfall.

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Keywords

Stationary Model, Quantile Plot, R-studio, Merawi Town, Diagnostic Test

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