干旱区生态环境知识资源中心(Arid): Comparison of the performance of leaf wetness duration models for rainfed jujube (Ziziphus jujubaMill.) plantations in the loess hilly region of China using machine learning

Arid

DOI	10.1002/eco.2237
	Comparison of the performance of leaf wetness duration models for rainfed jujube (Ziziphus jujubaMill.) plantations in the loess hilly region of China using machine learning
	Gao, Zhiyong; Shi, Wenjuan; Wang, Xing; Cao, Bing; Wang, Youke
通讯作者	Shi, WJ
来源期刊	ECOHYDROLOGY
ISSN	1936-0584
EISSN	1936-0592
出版年	2020
卷号	13 期号:7
英文摘要	Leaf wetness duration (LWD) affects the ability of tree canopy to regulate eco-hydrological processes. Jujube (Ziziphus jujubaMill.) is one of the main plants with significant impact on water cycle process and flux characteristics in the Loess Plateau region of China. However, little is known about LWD in rainfed jujube plantations in the loess hilly region of China. For the causes of leaf wetness in rainfed jujube plantations, dew-only, rain and the combined scenario were investigated in terms of LWD and meteorological variables for the 2012, 2013, 2017 and 2018 jujube growing seasons. The results were as follows: The leaf wetness events occurred frequently, and the days of leaf wetness driven by dew-only and rain accounted for 88.3% of the total number of days in a regular jujube growing season. LWD driven by dew-only was significantly lower than that driven by rain (p< 0.05). The correlation between LWD and meteorological factors varied with different scenarios. In dew-only scenario, the four calibrated models (RH, DPD, CART and NN) accurately predicted LWD. In rain scenario, only the calibrated NN model performed well. In the combined scenario, the calibrated RH, CART and NN empirical models performed nearly equally; all well estimated LWD. On the basis of accuracy, practicability and variable count, the calibrated RH, NN and RH models for dew-only, rain and the combined scenario can reliably estimate LWD in rainfed jujube plantations in the loess hilly region of China.
英文关键词	empirical model leaf wetness duration loess hilly region machine learning rainfed jujube plantation
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000558394900001
WOS关键词	MILL. PLANTATIONS ; DEW FORMATION ; RELATIVE-HUMIDITY ; NEURAL-NETWORK ; WATER ; DESERT ; EVAPOTRANSPIRATION ; VALIDATION ; PLATEAU ; AIR
WOS类目	Ecology ; Environmental Sciences ; Water Resources
WOS研究方向	Environmental Sciences & Ecology ; 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/2XILL650/325549
作者单位	[Gao, Zhiyong; Shi, Wenjuan] Xian Univ Technol, State Key Lab Eco Hydraul, Xian 710048, Peoples R China; [Wang, Xing; Cao, Bing] Ningxia Univ, Sch Agr, Yinchuan 750021, Ningxia, Peoples R China; [Wang, Youke] Northwest A&F Univ, Coll Water Resources & Architectural Engn, Yangling, Shaanxi, Peoples R China; [Wang, Youke] Chinese Acad Sci, Res Ctr Soil & Water Conservat & Ecol Environm, Yangling, Shaanxi, Peoples R China; [Wang, Youke] Minist Educ, Yangling, Shaanxi, Peoples R China
推荐引用方式 GB/T 7714	Gao, Zhiyong,Shi, Wenjuan,Wang, Xing,et al. Comparison of the performance of leaf wetness duration models for rainfed jujube (Ziziphus jujubaMill.) plantations in the loess hilly region of China using machine learning[J]. 西北农林科技大学,2020,13(7).
APA	Gao, Zhiyong,Shi, Wenjuan,Wang, Xing,Cao, Bing,&Wang, Youke.(2020).Comparison of the performance of leaf wetness duration models for rainfed jujube (Ziziphus jujubaMill.) plantations in the loess hilly region of China using machine learning.ECOHYDROLOGY,13(7).
MLA	Gao, Zhiyong,et al."Comparison of the performance of leaf wetness duration models for rainfed jujube (Ziziphus jujubaMill.) plantations in the loess hilly region of China using machine learning".ECOHYDROLOGY 13.7(2020).