干旱区生态环境知识资源中心(Arid): Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation

Arid

DOI	10.3390/atmos11040389
	Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation
	Armanuos, Asaad M.1; Al-Ansari, Nadhir 2; Yaseen, Zaher Mundher 3
通讯作者	Yaseen, Zaher Mundher
来源期刊	ATMOSPHERE
EISSN	2073-4433
出版年	2020
卷号	11 期号:4
英文摘要	The results of metrological, hydrological, and environmental data analyses are mainly dependent on the reliable estimation of missing data. In this study, 21 classical methods were evaluated to determine the best method for infilling the missing precipitation data in Ethiopia. The monthly data collected from 15 different stations over 34 years from 1980 to 2013 were considered. Homogeneity and trend tests were performed to check the data. The results of the different methods were compared using the mean absolute error (MAE), root-mean-square error (RMSE), coefficient of efficiency (CE), similarity index (S-index), skill score (SS), and Pearson correlation coefficient (r(Pearson)). The results of this paper confirmed that the normal ratio (NR), multiple linear regression (MLR), inverse distance weighting (IDW), correlation coefficient weighting (CCW), and arithmetic average (AA) methods are the most reliable methods of those studied. The NR method provides the most accurate estimations with r(Pearson) of 0.945, mean absolute error of 22.90 mm, RMSE of 33.695 mm, similarity index of 0.999, CE index of 0.998, and skill score of 0.998. When comparing the observed results and the estimated results from the NR, MLR, IDW, CCW, and AA methods, the MAE and RMSE were found to be low, and high values of CE, S-index, SS, and r(Pearson) were achieved. On the other hand, using the closet station (CS), UK traditional, linear regression (LR), expectation maximization (EM), and multiple imputations (MI) methods gave the lowest accuracy, with MAE and RMSE values varying from 30.424 to 47.641 mm and from 49.564 to 58.765 mm, respectively. The results of this study suggest that the recommended methods are applicable for different types of climatic data in Ethiopia and arid regions in other countries around the world.
英文关键词	Nile Basin missing data estimation precipitation Ethiopia classical methods
类型	Article
语种	英语
国家	Egypt ; Sweden ; Vietnam
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000539492200076
WOS关键词	TIME-SERIES ; SPATIAL INTERPOLATION ; WEIGHTING METHODS ; IMPUTATION ; RAINFALL ; MODEL ; TEMPERATURE ; RECORDS ; VALUES
WOS类目	Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向	Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/319424
作者单位	1.Tanta Univ, Fac Engn, Irrigat & Hydraul Engn Dept, Civil Engn Dept, Tanta 31511, Egypt; 2.Lulea Univ Technol, Civil Environm & Nat Resources Engn, S-97187 Lulea, Sweden; 3.Ton Duc Thang Univ, Fac Civil Engn, Sustainable Dev Civil Engn Res Grp, Ho Chi Minh City 758307, Vietnam
推荐引用方式 GB/T 7714	Armanuos, Asaad M.,Al-Ansari, Nadhir,Yaseen, Zaher Mundher. Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation[J],2020,11(4).
APA	Armanuos, Asaad M.,Al-Ansari, Nadhir,&Yaseen, Zaher Mundher.(2020).Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation.ATMOSPHERE,11(4).
MLA	Armanuos, Asaad M.,et al."Cross Assessment of Twenty-One Different Methods for Missing Precipitation Data Estimation".ATMOSPHERE 11.4(2020).