干旱区生态环境知识资源中心(Arid): Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the US Southern Great Plains

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DOI	10.1016/j.envsoft.2019.04.001
	Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the US Southern Great Plains
	Chen, Y.1; Marek, G. W.2; Marek, T. H.3; Gowda, P. H.4; Xue, Q.; Moorhead, J. E.2; Brauer, D. K.2; Srinivasan, R.1; Heflin, K. R.3
通讯作者	Chen, Y.
来源期刊	ENVIRONMENTAL MODELLING & SOFTWARE
ISSN	1364-8152
EISSN	1873-6726
出版年	2019
卷号	118 页码:23-34
英文摘要	Modeling alternative irrigation strategies can be a cost-effective and time-saving approach to field-based experiments. However, the efficacy of irrigation scheduling algorithms should be verified using field data from multiple locations. In this study, an auto-irrigation algorithm recently developed for Soil and Water Assessment Tool (SWAT) was further evaluated using irrigation data for corn (Zea mays L.) grown at six research sites across the Southern Great Plains. Simulated monthly irrigation, based on the management allowed depletion (MAD) of plant available soil water, was compared to measured data for irrigation applied in accordance with crop water requirement guidelines outlined by the Food and Agriculture Organization Irrigation and Drainage Paper 56. Overall, results indicated the MAD algorithm simulated monthly field-based irrigation amounts well (NashSutcliffe efficiency; NSE > 0.56). Comparisons revealed the MAD algorithm outperformed the plant water demand and soil water content approaches in SWAT, which tended to underestimate and overestimate irrigations, respectively.
英文关键词	FAO-56 Irrigation algorithm Management allowed depletion Corn Semi-arid region Groundwater
类型	Article
语种	英语
国家	USA
收录类别	SCI-E
WOS记录号	WOS:000469933100003
WOS关键词	TEXAS HIGH-PLAINS ; SUBSURFACE DRIP IRRIGATION ; YIELD RESPONSE ; WATER-USE ; DEFICIT IRRIGATION ; USE EFFICIENCY ; MODEL ; MANAGEMENT ; EVAPOTRANSPIRATION ; MAIZE
WOS类目	Computer Science, Interdisciplinary Applications ; Engineering, Environmental ; Environmental Sciences ; Water Resources
WOS研究方向	Computer Science ; Engineering ; Environmental Sciences & Ecology ; Water Resources
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/215460
作者单位	1.Texas A&M Univ, Dept Ecosyst Sci & Management, 2138 TAMU, College Stn, TX 77845 USA; 2.USDA ARS Conservat & Prod Res Lab, 300 Simmons Rd,Unit 10, Bushland, TX 79012 USA; 3.Texas A&M AgriLife Res, Texas A&M AgriLife Res & Extens Ctr, 6500 Amarillo Blvd W, Amarillo, TX 79106 USA; 4.USDA ARS Grazinglands Res Lab, 7207 West Cheyenne St, El Reno, OK 73036 USA
推荐引用方式 GB/T 7714	Chen, Y.,Marek, G. W.,Marek, T. H.,et al. Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the US Southern Great Plains[J],2019,118:23-34.
APA	Chen, Y..,Marek, G. W..,Marek, T. H..,Gowda, P. H..,Xue, Q..,...&Heflin, K. R..(2019).Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the US Southern Great Plains.ENVIRONMENTAL MODELLING & SOFTWARE,118,23-34.
MLA	Chen, Y.,et al."Multisite evaluation of an improved SWAT irrigation scheduling algorithm for corn (Zea mays L.) production in the US Southern Great Plains".ENVIRONMENTAL MODELLING & SOFTWARE 118(2019):23-34.