Accuracy Evaluation of Standardized Precipitation Index (SPI) Estimation under Conventional Assumption in Yeşilırmak, Kızılırmak, and Konya Closed Basins, Turkey

IF 2.1 4区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
M. A. Hinis, Mehmet Selim Geyikli
{"title":"Accuracy Evaluation of Standardized Precipitation Index (SPI) Estimation under Conventional Assumption in Yeşilırmak, Kızılırmak, and Konya Closed Basins, Turkey","authors":"M. A. Hinis, Mehmet Selim Geyikli","doi":"10.1155/2023/5142965","DOIUrl":null,"url":null,"abstract":"The doubt in the calculation algorithm of the standardized precipitation index (SPI), which is widely preferred in the evaluation and monitoring of drought, still remains up-to-date because its calculation process is performed in the form of standardization or normalization with a default probability distribution. Therefore, the success of this index is directly affected by the choice of the probability distribution model. This study is based on the effect of three different parameter estimation methods on the calculation process, as well as the comparison of the SPI results calculated based on the default Gamma distribution and the distribution with the best ability to represent the 3-and 12-month consecutive summed rainfall data among the 15 candidate distributions namely Gamma (GAM), Generalized Extreme Value (GEV), Pearson Type III (P III), Log Pearson Type III (LP III), two-parameter Lognormal (LN2), three-parameter Lognormal (LN3), Generalized Logistic (GLOG), Extreme Value Type I (EVI), Generalized Pareto (GPAR), Weilbul (W), Normal (N), Exponential (EXP), Logistic (LOG), four-parameter Wakeby (WK4), and five-parameter Wakeby (WK5) distributions. Approximately 68.4% and 18.4% of the 3-month data considered had the best fit to the Weibull and Pearson III distribution, while approximately 24% and 18% of the 12-month data had the best fit to the Weibull and Logistic distribution. On the other hand, it was found that the default Gamma distribution calculated the extreme drought categories significantly more than the best-fit distribution model. In terms of parameter estimation methods, L-moments for 3-month series and maximum likelihood approaches for 12-month series were most dominant.","PeriodicalId":7353,"journal":{"name":"Advances in Meteorology","volume":" ","pages":""},"PeriodicalIF":2.1000,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Meteorology","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1155/2023/5142965","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 1

Abstract

The doubt in the calculation algorithm of the standardized precipitation index (SPI), which is widely preferred in the evaluation and monitoring of drought, still remains up-to-date because its calculation process is performed in the form of standardization or normalization with a default probability distribution. Therefore, the success of this index is directly affected by the choice of the probability distribution model. This study is based on the effect of three different parameter estimation methods on the calculation process, as well as the comparison of the SPI results calculated based on the default Gamma distribution and the distribution with the best ability to represent the 3-and 12-month consecutive summed rainfall data among the 15 candidate distributions namely Gamma (GAM), Generalized Extreme Value (GEV), Pearson Type III (P III), Log Pearson Type III (LP III), two-parameter Lognormal (LN2), three-parameter Lognormal (LN3), Generalized Logistic (GLOG), Extreme Value Type I (EVI), Generalized Pareto (GPAR), Weilbul (W), Normal (N), Exponential (EXP), Logistic (LOG), four-parameter Wakeby (WK4), and five-parameter Wakeby (WK5) distributions. Approximately 68.4% and 18.4% of the 3-month data considered had the best fit to the Weibull and Pearson III distribution, while approximately 24% and 18% of the 12-month data had the best fit to the Weibull and Logistic distribution. On the other hand, it was found that the default Gamma distribution calculated the extreme drought categories significantly more than the best-fit distribution model. In terms of parameter estimation methods, L-moments for 3-month series and maximum likelihood approaches for 12-month series were most dominant.
土耳其Yeşilırmak、Kızılırmak和Konya闭流域常规假设下的标准化降水指数(SPI)估算精度评价
在干旱评价和监测中被广泛采用的标准化降水指数(SPI)的计算算法仍然存在疑问,因为其计算过程以标准化或归一化的形式进行,具有默认概率分布。因此,该指标的成功与否直接影响到概率分布模型的选择。本研究基于三种不同参数估计方法对计算过程的影响,以及在Gamma (GAM)、Generalized Extreme Value (GEV)、Pearson Type III (P III)、Log Pearson Type III (LP III)、双参数Lognormal (LN2)、Gamma (GAM)和Gamma (gv) 15种候选分布中,基于默认Gamma分布和最能代表3个月和12个月连续降水求和数据的分布计算SPI结果的比较。三参数Lognormal (LN3)、Generalized Logistic (GLOG)、Extreme Value Type I (EVI)、Generalized Pareto (GPAR)、Weilbul (W)、Normal (N)、Exponential (EXP)、Logistic (LOG)、四参数Wakeby (WK4)和五参数Wakeby (WK5)分布。大约68.4%和18.4%的3个月数据最适合Weibull和Pearson III分布,而大约24%和18%的12个月数据最适合Weibull和Logistic分布。另一方面,发现默认Gamma分布对极端干旱类别的计算量显著高于最佳拟合分布模型。在参数估计方法方面,3个月序列的l -矩法和12个月序列的最大似然法占主导地位。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Advances in Meteorology
Advances in Meteorology 地学天文-气象与大气科学
CiteScore
5.30
自引率
3.40%
发文量
80
审稿时长
>12 weeks
期刊介绍: Advances in Meteorology is a peer-reviewed, Open Access journal that publishes original research articles as well as review articles in all areas of meteorology and climatology. Topics covered include, but are not limited to, forecasting techniques and applications, meteorological modeling, data analysis, atmospheric chemistry and physics, climate change, satellite meteorology, marine meteorology, and forest meteorology.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信