引用本文:陈岩,童国平,王蕾.淮河流域农业灰水足迹效率的时空分布与驱动模式[J].水资源保护,2020,36(6):60-66DOI:10.3880/j.issn.1004-6933.2020.06.010
CHEN Yan,TONG Guoping,WANG Lei.Spatial-temporal distribution and driving models of agricultural grey water footprint efficiency in the Huai River Basin[J].Water Resources Protection,2020,36(6):60-66.
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淮河流域农业灰水足迹效率的时空分布与驱动模式
陈岩1,2, 童国平1, 王蕾3
1.南京林业大学经济管理学院, 江苏 南京 210037;2.南京林业大学生态文明与乡村振兴研究中心, 江苏 南京 210037;3.南京信息工程大学教师发展与教学评估中心, 江苏 南京 210044
摘要:运用灰水足迹效率测算模型对淮河流域35个地级市的农业灰水足迹效率进行了测度和时空分布研究,采用Kaya恒等式和LMDI分解模型将农业灰水足迹效率驱动因素分解为农业经济效应、化肥强度效应、灰水产出规模效应、农业环境效应和耕地资源效应等5个因素,并对淮河流域各地级市农业灰水足迹效率的驱动模式进行了分类。结果表明:2000—2015年,淮河流域35个地级市的农业灰水足迹效率都有显著的提升,从各省分布情况来看,山东省的农业灰水足迹效率最高,其次是安徽省和江苏省,河南省最低;农业灰水足迹效率驱动因素中,农业经济效应、灰水产出规模效应和耕地资源效应为正向效应,化肥强度效应和农业环境效应为负向效应,其中农业经济效应是提升农业灰水足迹效率最关键的驱动因素;淮河流域35个地级市的农业灰水足迹效率的驱动模式可以划分为农业经济效应单因素驱动模式I、灰水规模产出效应单因素驱动模式Ⅱ、双因素驱动模式Ⅲ和三因素驱动模式Ⅳ共4类,对于不同驱动模式的地区需要采取不同的治理措施。
关键词:  农业灰水足迹  灰水足迹效率  驱动模式  淮河流域
DOI:10.3880/j.issn.1004-6933.2020.06.010
基金项目:教育部人文社科基金(20YJA630006);国家自然科学基金青年科学基金(71403122);江苏省自然科学基金青年项目(BK20140980)
Spatial-temporal distribution and driving models of agricultural grey water footprint efficiency in the Huai River Basin
CHEN Yan1,2, TONG Guoping1, WANG Lei3
1.College of Economics and Management, Nanjing Forestry University, Nanjing 210037, China;2.Research Center of Ecological Civilization and Rural Revitalization, Nanjing Forestry University, Nanjing 210037, China;3.Teachers and Teaching Development Center, Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract:The spatial and temporal distribution of agricultural gray water footprint efficiency of 35 prefecture-level cities in Huai River Basin was studied by using the gray water footprint efficiency calculating model. Kaya identity and LMDI model were employed to decompose the driving factors of agricultural grey water footprint efficiency into five aspects: agricultural economic effect, fertilizer intensity effect, gray water output scale effect, agricultural environmental effect, and cultivated land resource effect. A classification study of driving models of agricultural gray water footprint efficiency in every city in Huai River Basin was conducted. The results show that the agricultural gray water footprint efficiency of 35 prefecture-level cities in Huai River Basin has been significantly improved during 2000-2015. According to the distribution of each province, the agricultural gray water footprint efficiency of Shandong Province is the highest, followed by Anhui Province and Jiangsu Province, with Henan Province being the lowest. Among the driving factors of agricultural gray water footprint efficiency, agricultural economic effect, gray water output scale effect and cultivated land resource effect are positive, while chemical fertilizer intensity effect and agricultural environment effect are negative. Among them, agricultural economic effect is the most critical driving factor to improve the efficiency of agricultural gray water footprint. The driving models of agricultural gray water footprint efficiency of 35 prefecture-level cities in Huai River Basin can be divided into 4 categories: single-factor driving model I dominated by agricultural economic effect, single-factor driving model II dominated by gray water scale output effect, two-factor driving model III and three-factor driving model IV. Different governance measures should be taken in regions with different driving models.
Key words:  agricultural grey water footprint  efficiency of grey water footprint  driving model  Huai River Basin

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