利用指数化标准化半Logistic分布模拟气象因子对最大降雨强度的影响

B. Sasanya, P. Awodutire, O. Ufuoma, O. S. Balogun
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引用次数: 0

摘要

降雨强度预测或预报在水工构筑物和防汛防蚀构筑物设计中具有重要意义。在这项工作中,气象数据来自美国国家航空航天局(NASA)的网站。建立了最大降水强度估算模型,并对气象因素对模型的影响进行了验证。气象因素包括年平均相对湿度、比湿度、2米温度范围、最高温度和最低温度。本研究旨在建立一个估算最大降雨强度的模型,并探讨了各种气象因素对模型的影响。采用指数化标准化半logistic分布(ESLD)模型对尼日利亚哈科特港市区35年(1984-2018)年最大月降水强度的影响进行了模拟。采用极大似然估计法对模型参数进行估计。与五个标准分布的结果进行比较,使用三个标准来确定表现最佳的分布。这些表明,ESLD的表现明显好于其他五个比较分布。只有回归期对模型的降雨强度预测有显著影响(p < 0.05),气象因子的影响不显著。
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Modelling the Effects of Meteorological Factors on Maximum Rainfall Intensities Using Exponentiated Standardized Half Logistic Distribution
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 < 0.05 , while the effects of the meteorological factors are insignificant.
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