Statistical distribution of rainfall in Uttarakhand, India

Kumar, Vishal; Shanu,; Jahangeer,

doi:10.1007/s13201-017-0586-5

Cited by 51 publications

(23 citation statements)

References 18 publications

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“…They concluded that the gamma distribution provided a better result for the hourly rainfall data. On the other hand, Kumar et al [2] conducted in Uttarakhand, India showed different results. The best-fit distribution is applied, with the comparison performed based on the goodness-of-fit test.…”

Section: Introductionmentioning

confidence: 95%

Statistical modelling of extreme rainfall in Peninsular Malaysia

2021

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Flash floods are known as one of the common natural disasters that cost over billions of Ringgit Malaysia throughout history. Academically, an extreme rainfall model is effective in modelling to predict and prevent the occurrence of flash floods. This paper compares four probability distributions, namely, exponential distribution, generalized extreme value distribution, gamma distribution, and Weibull distribution, with the rainfall data of 10 stations in peninsular Malaysia. The period of the data is from 1975 to 2008. The comparison is based on the descriptive and predictive analytics of the models. The determination of the most effective model is through Kolmogorov-Smirnov, Anderson-Darling, and chi-square test. The result shows that generalized extreme value is the most preferred extreme rainfall model for the rainfall cases in Peninsular Malaysia.

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Section: Introductionmentioning

confidence: 95%

Statistical modelling of extreme rainfall in Peninsular Malaysia

2021

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“…To this end, they fitted seven distribution families (normal, two‐ and three‐parameter log‐normal, two‐ and three‐parameter gamma, Weibull and log‐Pearson Type III) to rainfall time series and the performance of these distributions was compared by a chi‐squared (χ 2 ) test. It was observed that although the selected distributions varied from month to month, annual rainfall was well fitted by the normal distribution (see also Mohamed and Samir ; and Kumar and Shanu ).…”

Section: Introductionmentioning

confidence: 96%

Mapping spatial variability of annual rainfall under different return periods in Turkey: The application of various distribution functions and model selection techniques

Tosunoğlu

Gürbüz

2019

Meteorological Applications

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The objectives of the paper are to determine the best‐fitted probability distribution functions for annual rainfall in Turkey and to provide more accurate estimates of rainfall quantiles under different return periods. To achieve these aims, 10 popular and widely used probability distributions: gamma, generalized extreme value, Gumbel, normal, logistic, log‐logistic, two‐parameter log‐normal, three‐parameter log‐normal, Pearson type III and Weibull, are considered for modelling annual rainfall data covering the period 1975–2014 from 155 gauge stations uniformly distributed across Turkey. Unlike previous studies, the performances of the candidate probability distributions were evaluated by various model selection techniques: Akaike information criterion (AIC), Bayesian information criterion (BIC), Anderson–Darling (AD) criterion, the Cramér–von Mises test (CvM) and the Kolmogorov–Smirnov test (KS). According to the ranking‐based scoring evaluation, the gamma, log‐logistic, two‐parameter log‐normal, normal and Weibull distributions, which show the best fit for 78% of the data series, were mainly found to be the most suitable distributions. T year (25, 50 and 100) rainfall quantiles were then estimated using the best‐fitted distributions. Finally, the universal Kriging method, which is an effective interpolation method, was used to map the estimated rainfall quantiles.

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“…Rainfall was a basic fundamental input into most hydrologic processes specifically in the case of runoff generated sediments (Kumar 2017). Because rain is a naturally occurring phenomenon, which makes it a randomly occurring event, or an unpredictable phenomenon regarding its parameters such as intensity uniformity, duration, and drop size.…”

Section: Introductionmentioning

confidence: 99%

Sediment Outflow under Simulated Rainfall Conditions with Varying Geotechnical Properties

Joshi

Kumar

Singh

et al. 2020

J. Hazard. Toxic Radioact. Waste

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The vulnerability of soil toward erosion might be reduced by having a good vegetative cover over the soil surface, slope improvement, and improving soil properties so that it is not easily detached and transported. However, the establishment of proper vegetative cover is a long process because it takes time for seeds to germinate and attain maturity. As an alternative approach, if soil resistance was increased by increasing the shear strength of soil against erosive forces offered by eroding agents, the soil system would become capable of withstanding the detachment of its particles on the digitalcommons.unl.edu

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Statistical distribution of rainfall in Uttarakhand, India

Cited by 51 publications

References 18 publications

Statistical modelling of extreme rainfall in Peninsular Malaysia

Statistical modelling of extreme rainfall in Peninsular Malaysia

Mapping spatial variability of annual rainfall under different return periods in Turkey: The application of various distribution functions and model selection techniques

Sediment Outflow under Simulated Rainfall Conditions with Varying Geotechnical Properties

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