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DOI	10.1007/s00703-019-00685-6
	Modeling monthly rainfall data using zero-adjusted models in the semi-arid, arid and extra-arid regions
	Zamani, Hossein 1; Bazrafshan, Ommolbanin 2
通讯作者	Bazrafshan, Ommolbanin
来源期刊	METEOROLOGY AND ATMOSPHERIC PHYSICS
ISSN	0177-7971
EISSN	1436-5065
出版年	2020
卷号	132 期号:2 页码:239-253
英文摘要	Modeling rainfall data and analyzing precipitation variability are accurately critical for managing water resources. Generally, rainfall is one of the most important inputs in model fitting based on probability distribution functions. The probability functions provide the possibility of estimation rainfall variability within a specific range. But in many situations, especially in the low rainfall regions, there will be many zero rainfall values. In these cases, the common distributions applied in the literatures cannot be used for modeling those data since statistically they are defined on positive range values. To overcome this problem an edition on the common probability functions should be implemented. The aim of this study is to introduce the zero-adjusted models (ZAM) and then applying these models on monthly rainfall using 46 years of data from 25 stations in semi-arid, arid and extra-arid regions of Iran. The models that will be used through this study, are the zero-adjusted gamma (ZAGA), zero-adjusted Weibull (ZAWEI), zero-adjusted inverse Gaussian (ZAIG), zero-adjusted log-logistic (ZALL) and zero-adjusted log-normal (ZALN). For selecting the best fitted model some numerical validation methods such as the AIC, the BIC and the K-S test are used. Bedsides the numerical methods, some graphical aspects such as PDF, CDF, and Q-Q plots have been served. The results show that the ZAWEI model is suitable for the extra-arid regions, while the ZAGA model has a better performance in the semi-arid and arid regions. This study attempts to provide the technique of using ZA models for the rainfall data in the low-rainfall region and can be considered as a foundation of using these statistical models. The ZAMs can be applied to the rainfall data, and to classify (or cluster) the rainfall regimes, especially for the semi-arid, arid and extra-arid regions of Iran. Also, these probability models can be considered as decision-support tools for decision-makers to manage the water and agricultural resources as well as food reserves with assessing different scenarios in these regions.
类型	Article
语种	英语
国家	Iran
收录类别	SCI-E
WOS记录号	WOS:000520851500006
WOS关键词	PRECIPITATION ; TRENDS ; GENERATION
WOS类目	Meteorology & Atmospheric Sciences
WOS研究方向	Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/315164
作者单位	1.Univ Hormozgan, Dept Math & Stat, Fac Sci, POB 7916193145, Bandar Abbas, Iran; 2.Univ Hormozgan, Fac Agr & Nat Resources Engn, Dept Nat Resources Engn, POB 7916193145, Bandar Abbas, Iran
推荐引用方式 GB/T 7714	Zamani, Hossein,Bazrafshan, Ommolbanin. Modeling monthly rainfall data using zero-adjusted models in the semi-arid, arid and extra-arid regions[J],2020,132(2):239-253.
APA	Zamani, Hossein,&Bazrafshan, Ommolbanin.(2020).Modeling monthly rainfall data using zero-adjusted models in the semi-arid, arid and extra-arid regions.METEOROLOGY AND ATMOSPHERIC PHYSICS,132(2),239-253.
MLA	Zamani, Hossein,et al."Modeling monthly rainfall data using zero-adjusted models in the semi-arid, arid and extra-arid regions".METEOROLOGY AND ATMOSPHERIC PHYSICS 132.2(2020):239-253.