干旱区生态环境知识资源中心(Arid): A Model-Based Real-Time Decision Support System for Irrigation Scheduling to Improve Water Productivity

Arid

DOI	10.3390/agronomy9110686
	A Model-Based Real-Time Decision Support System for Irrigation Scheduling to Improve Water Productivity
	Chen, Xiaoping 1,2,3,4; Qi, Zhiming 1,2,4; Gui, Dongwei 1,2; Gu, Zhe 5; Ma, Liwang 6; Zeng, Fanjiang1,2 ; Li, Lanhai 1; Sima, Matthew W.7
通讯作者	Qi, Zhiming
来源期刊	AGRONOMY-BASEL
EISSN	2073-4395
出版年	2019
卷号	9 期号:11
英文摘要	A precisely timed irrigation schedule to match crop water demand is vital to improving water use efficiency in arid farmland. In this study, a real-time irrigation-scheduling infrastructure, Decision Support System for Irrigation Scheduling (DSSIS), based on water stresses predicted by an agro-hydrological model, was constructed and evaluated. The DSSIS employed the Root Zone Water Quality Model (RZWQM2) to predict crop water stresses and soil water content, which were used to trigger irrigation and calculate irrigation amount, respectively, along with forecasted rainfall. The new DSSIS was evaluated through a cotton field experiment in Xinjiang, China in 2016 and 2017. Three irrigation scheduling methods (DSSIS-based (D), soil moisture sensor-based (S), and conventional experience-based (E)), factorially combined with two irrigation rates (full irrigation (FI), and deficit irrigation (DI, 75% of FI)) were compared. The DSSIS significantly increased water productivity (WP) by 26% and 65.7%, compared to sensor-based and experience-based irrigation scheduling methods (p < 0.05), respectively. No significant difference was observed in WP between full and deficit irrigation treatments. In addition, the DSSIS showed economic advantage over sensor- and experience-based methods. Our results suggested that DSSIS is a promising tool for irrigation scheduling.
英文关键词	irrigation decision support system agro-hydrological model RZWQM2 water stress weather forecast
类型	Article
语种	英语
国家	Peoples R China ; Canada ; USA
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000502264700020
WOS关键词	DRIP IRRIGATION ; CANOPY TEMPERATURE ; USE EFFICIENCY ; HYBRID MODEL ; STRESS INDEX ; MAIZE ; RZWQM ; FIELD ; STRATEGIES ; COTTON
WOS类目	Agronomy ; Plant Sciences
WOS研究方向	Agriculture ; Plant Sciences
EI主题词	2019-11-01
来源机构	中国科学院新疆生态与地理研究所 ; 河海大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/310529
作者单位	1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Desert & Oasis Ecol, Urumqi 830011, Peoples R China; 2.Cele Natl Stn Observat & Res Desert Grassland Eco, Cele 848300, Peoples R China; 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 4.McGill Univ, Dept Bioresource Engn, Ste Anne De Bellevue, PQ H9X 3V9, Canada; 5.Hohai Univ, Coll Agr Engn, 1 Xikang Rd, Nanjing 210098, Jiangsu, Peoples R China; 6.USDA ARS, Rangeland Resources & Syst Res Unit, Ft Collins, CO 80526 USA; 7.Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA
推荐引用方式 GB/T 7714	Chen, Xiaoping,Qi, Zhiming,Gui, Dongwei,et al. A Model-Based Real-Time Decision Support System for Irrigation Scheduling to Improve Water Productivity[J]. 中国科学院新疆生态与地理研究所, 河海大学,2019,9(11).
APA	Chen, Xiaoping.,Qi, Zhiming.,Gui, Dongwei.,Gu, Zhe.,Ma, Liwang.,...&Sima, Matthew W..(2019).A Model-Based Real-Time Decision Support System for Irrigation Scheduling to Improve Water Productivity.AGRONOMY-BASEL,9(11).
MLA	Chen, Xiaoping,et al."A Model-Based Real-Time Decision Support System for Irrigation Scheduling to Improve Water Productivity".AGRONOMY-BASEL 9.11(2019).