Modelling the Effects of Meteorological Factors on Maximum Rainfall Intensities Using Exponentiated Standardized Half Logistic Distribution

B. F. Sasanya, P. O. Awodutire, O. G. Ufuoma and O. S. Balogun

Journal of Applied Mathematics, 2022, vol. 2022, issue 1

Abstract: Rainfall intensity prediction or forecast is vital in designing hydraulic structures and flood and erosion control structures. In this work, meteorological data were obtained from the National Aeronautics and Space Administration’s (NASA) website. Models estimating maximum rainfall intensities were derived, and some meteorological factors’ effects on the models were tested. The meteorological factors considered include annual relative humidity averages, specific humidity, temperature range at 2 m, maximum temperature, and minimum temperature. This research was aimed at developing a model for estimating maximum rainfall intensities, and the effects of various meteorological factors on the models were investigated. The exponentiated standardized half logistic distribution (ESLD) was used to model the effects of the factors and return periods on 35 years’ (1984–2018) annual maxima monthly rainfall intensities for Port Harcourt metropolis, Nigeria. The model parameters were estimated using the maximum likelihood estimation method. Compared with the results from the five standard distributions, three criteria were used to determine the best‐performed distribution. These indicated that the ESLD performed considerably better than the other five compared distributions. Only the return period had significant effects on the model for the rainfall intensity prediction since p

Date: 2022
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https://doi.org/10.1155/2022/3250954

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2022:y:2022:i:1:n:3250954

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