Mixture models of probability distributions applied to rainfall in the state of Pernambuco, Brazil

IF 0.6 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Acta Scientiarum-technology Pub Date : 2023-04-28 DOI:10.4025/actascitechnol.v45i1.60621
L. D. Silva, Edgo Jackson Pinto Santiago, Frank Gomes-Silva, Antonio Samuel Alves da Silva, R. Menezes
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Abstract

The Brazilian semi-arid region is recurrently affected by the scarcity of water that marks the landscape as it prints periods of severe drought. Therefore, rainfall in this region greatly influences plant growth in regional hydrological processes that affect droughts or floods. It is of practical interest to assess how changes in rainfall patterns occur to anticipate hydrological dynamics. However, this is not easy as climate change reshapes global hydrology. Thus, assertive forecasting has become rare and imputed estimates of a reasonable degree of uncertainty. The objective of this work was to verify from the mixture of exponential, gamma, beta, log-normal, Weibull, normal, log-logistic, and exponentiated log-logistic distributions, which best fits the monthly rainfall of the state of Pernambuco, Brazil. The data used came from 133 monthly rainfall series (1950 to 2012) distributed over the state of Pernambuco. The Maximum Likelihood Method estimated all parameters. The Kolmogorov-Smirnov adherence test was applied at 5% probability to assess the adjustments. The least rejected distributions in the adherence test were Weibull, gamma, and beta; October presented the smallest number of distributions considered adequate to model monthly rainfall. More than 99% of the rain gauge stations had some adequate probabilistic distribution to model monthly rainfall in March. For most months, except for March, the Weibull distribution was the most suitable for modeling the monthly rainfall in the vast majority of rain gauge stations of Pernambuco.
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混合概率分布模型应用于巴西伯南布哥州的降雨
巴西半干旱地区经常受到缺水的影响,这标志着该地区出现了严重干旱时期。因此,在影响干旱或洪水的区域水文过程中,该地区的降雨对植物生长有很大的影响。评估降雨模式的变化如何发生以预测水文动力学是有实际意义的。然而,这并不容易,因为气候变化重塑了全球水文。因此,武断的预测已变得罕见,并对合理程度的不确定性进行了估算。这项工作的目的是从指数分布、伽马分布、beta分布、对数正态分布、威布尔分布、正态分布、对数逻辑分布和指数对数逻辑分布的混合中验证最适合巴西伯南布哥州的月降雨量。使用的数据来自分布在伯南布哥州的133个月降雨系列(1950年至2012年)。最大似然法估计所有参数。以5%的概率应用Kolmogorov-Smirnov依从性检验来评估调整。依从性测试中拒绝率最低的分布是Weibull、gamma和beta;10月是被认为足以模拟月降雨量的分布最少的月份。超过99%的雨量站有足够的概率分布来模拟三月的月雨量。除3月份外,绝大多数月份,威布尔分布最适合模拟伯南布哥省绝大多数雨量站的月降雨量。
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来源期刊
Acta Scientiarum-technology
Acta Scientiarum-technology 综合性期刊-综合性期刊
CiteScore
1.40
自引率
12.50%
发文量
60
审稿时长
6-12 weeks
期刊介绍: The journal publishes original articles in all areas of Technology, including: Engineerings, Physics, Chemistry, Mathematics, Statistics, Geosciences and Computation Sciences. To establish the public inscription of knowledge and its preservation; To publish results of research comprising ideas and new scientific suggestions; To publicize worldwide information and knowledge produced by the scientific community; To speech the process of scientific communication in Technology.
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