ISWC OpenIR  > 水保所科研产出--SCI  > 2018--SCI
Quantitative study of the crop production water footprint using the SWAT model
Xiaobo Luan1; Pute Wu1,3; Shikun Sun2,3; Yubao Wang2,3; Xuerui Gao3; Wu, PT; Sun, SK (reprint author), Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China.
SubtypeArticle
2018
Source PublicationECOLOGICAL INDICATORS
ISSN1470-160X
description.correspondentemailgjzwpt@vip.sina.com ; sksun@nwafu.edu.cn
Volume89Pages:1-10
AbstractAssessment of the water use efficiency is the key to effectively manage agricultural water resource. The water footprint is a new index for water use evaluation, and its quantification is a precondition for assessment of the agricultural water use efficiency. Due to the shortage of water footprint calculation methods and computational module defects, this study aims to establish a method for calculating the water footprint of crop production based on hydrological processes. In this study, the field-scale water footprints of wheat, corn and sunflower were calculated using the SWAT model in the Hetao irrigation district (HID), China. The results showed that the average total water footprints of wheat, corn and sunflower were 1.036 m(3)/kg, 0.774 m(3)/kg and 1.510 m(3)/kg, respectively. Additionally, the proportions of green water footprints in wheat, corn and sunflower were 22.3%, 26.1% and 29.4%, respectively. Water footprint calculations based on the SWAT model can reflect the spatial differences of water footprints during the process of crop production. The overall distribution pattern of the green, blue and total water footprints for the three crops demonstrated that high values were in the east part of the HID, followed by the west and the central areas. The SWAT-based water footprint offers high spatial resolution and is effective in exploring the spatial heterogeneity of crop water footprints.
KeywordSwat Hydrologic Process Water Footprint Water Use Evaluation Hetao Irrigation District
Subject AreaBiodiversity & Conservation ; Environmental Sciences & Ecology
DOI10.1016/j.ecolind.2018.01.046
Indexed BySCI
Publication PlacePO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
Language英语
WOS IDWOS:000430760900001
PublisherELSEVIER SCIENCE BV
Funding OrganizationNational Natural Science Foundation of China [51409218, 51609063] ; National Natural Science Foundation of China [51409218, 51609063] ; National Key Research and Development Program of China [2016YFC0400201] ; National Key Research and Development Program of China [2016YFC0400201] ; Natural Science Basic Research Plan, Shaanxi Province of China [2016JQ5092] ; Natural Science Basic Research Plan, Shaanxi Province of China [2016JQ5092] ; Science and Technology Integrated Innovation Project, Shaanxi Province of China [2016KTZDNY-01-01] ; Science and Technology Integrated Innovation Project, Shaanxi Province of China [2016KTZDNY-01-01]
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Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.iswc.ac.cn/handle/361005/8243
Collection水保所科研产出--SCI_2018--SCI
Corresponding AuthorWu, PT; Sun, SK (reprint author), Chinese Acad Sci & Minist Water Resources, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China.
Affiliation1.Univ Chinese Acad Sci, Inst Soil & Water Conservat, Yangling 712100, Shaanxi, Peoples R China
2.Northwest A&F Univ, Key Lab Agr Soil & Water Engn Arid & Semiarid A, Minist Educ, Yangling 712100, Shaanxi, Peoples R China
3.Northwest A&F Univ, Inst Water Saving Agr Arid Reg China, Yangling 712100, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Xiaobo Luan,Pute Wu,Shikun Sun,et al. Quantitative study of the crop production water footprint using the SWAT model[J]. ECOLOGICAL INDICATORS,2018,89:1-10.
APA Xiaobo Luan.,Pute Wu.,Shikun Sun.,Yubao Wang.,Xuerui Gao.,...&Sun, SK .(2018).Quantitative study of the crop production water footprint using the SWAT model.ECOLOGICAL INDICATORS,89,1-10.
MLA Xiaobo Luan,et al."Quantitative study of the crop production water footprint using the SWAT model".ECOLOGICAL INDICATORS 89(2018):1-10.
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