干旱区生态环境知识资源中心(Arid): A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China

Arid

DOI	10.1016/j.agwat.2020.106594
	A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China
	Yan, Shicheng; Wu, Lifeng; Fan, Junliang; Zhang, Fucang; Zou, Yufeng; Wu, You
通讯作者	Fan, JL (corresponding author), Northwest A&F Univ, Key Lab Agr Soil & Water Engn Arid & Semiarid Are, Minist Educ, Yangling 712100, Shaanxi, Peoples R China.
来源期刊	AGRICULTURAL WATER MANAGEMENT
ISSN	0378-3774
EISSN	1873-2283
出版年	2021
卷号	244
英文摘要	The information of reference evapotranspiration (ET0) is vital for optimizing irrigation scheduling, planning water resources and assessing hydrological drought. However, accurate estimation of ET0 is difficult if long-term or complete climatic variables are unavailable, especially in developing countries like China. This study proposed a novel hybrid extreme gradient boosting (XGB) model with the whale optimization algorithm (WOA) to estimate daily ET0 at four stations in the arid region and four stations in the humid region of China. Particularly, its performances were evaluated under the local and three external scenarios with seven incomplete combinations of maximum and minimum temperatures (T-max and T-min), relative humidity (RH), wind speed (U-2), relative sunshine duration (n/N) and extra-terrestrial radiation (R-a) for the period 1966-2015. The results showed that U-2 was the most influencing variable for daily ET0 estimation in the arid region, followed by n/N and RH, while n/N was more important than RH and U-2 in the humid region. Locally trained and tested WOA-XGB models greatly outperformed their corresponding simplified FAO-56 PM models, with the average decrease in root mean square error (RMSE) by 40.1% and 38.9% in the arid and humid regions, respectively. Compared with local WOA-XGB models, the prediction accuracy of externally trained WOA-XGB models with local or external testing data decreased by 18.1% or 69.9% in the arid region, and 16.8% or 67.9% in the humid region, respectively. However, external WOA-XGB models with synthetic testing data from the target and adjacent stations overall improved the prediction accuracy of local WOA-XGB models by 5.7% and 9.6% in the arid and humid regions, respectively. The results indicated that external WOA-XGB models with local testing data produced acceptable daily ET0 estimates. However, when synthetic data were employed during testing, external WOA-XGB models gave excellent daily ET0 estimates, which were comparable to or even better than local WOA-XGB models. This is a promising strategy that allows more accurate estimation of daily ET0 when lack of long-term historical or complete recent data.
英文关键词	Reference evapotranspiration Extreme gradient boosting Whale optimization algorithm Cross station FAO-56 Penman-Monteith
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000603305400001
WOS关键词	MONTEITH REFERENCE EVAPOTRANSPIRATION ; REFERENCE CROP EVAPOTRANSPIRATION ; PENMAN-MONTEITH ; LIMITED DATA ; HARGREAVES-SAMANI ; NEURAL-NETWORKS ; RANDOM FORESTS ; MISSING DATA ; OPTIMIZATION ; ALTERNATIVES
WOS类目	Agronomy ; Water Resources
WOS研究方向	Agriculture ; Water Resources
来源机构	西北农林科技大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/347654
作者单位	[Yan, Shicheng; Wu, Lifeng; Fan, Junliang; Zhang, Fucang; Zou, Yufeng; Wu, You] Northwest A&F Univ, Key Lab Agr Soil & Water Engn Arid & Semiarid Are, Minist Educ, Yangling 712100, Shaanxi, Peoples R China; [Wu, Lifeng] Nanchang Inst Technol, Sch Hydraul & Ecol Engn, Nanchang 330099, Jiangxi, Peoples R China
推荐引用方式 GB/T 7714	Yan, Shicheng,Wu, Lifeng,Fan, Junliang,et al. A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China[J]. 西北农林科技大学,2021,244.
APA	Yan, Shicheng,Wu, Lifeng,Fan, Junliang,Zhang, Fucang,Zou, Yufeng,&Wu, You.(2021).A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China.AGRICULTURAL WATER MANAGEMENT,244.
MLA	Yan, Shicheng,et al."A novel hybrid WOA-XGB model for estimating daily reference evapotranspiration using local and external meteorological data: Applications in arid and humid regions of China".AGRICULTURAL WATER MANAGEMENT 244(2021).