Spatio-Temporal Distribution Characteristics and Driving Factors of Main Grain Crop Water Productivity in the Yellow River Basin

被引:5
作者
Zhang, Yan [1 ]
Wang, Feiyu [2 ]
Du, Zhenjie [3 ]
Dou, Ming [4 ]
Liang, Zhijie [1 ]
Gao, Yun [3 ]
Li, Ping [1 ,3 ]
机构
[1] Chinese Acad Agr Sci, Farmland Irrigat Res Inst, Xinxiang 453002, Peoples R China
[2] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
[3] Minist Agr, Lab Qual & Safety Risk Assessment Agroprod Water E, Xinxiang 453002, Peoples R China
[4] Zhengzhou Univ, Sch Ecol & Environm, Zhengzhou 450001, Peoples R China
来源
PLANTS-BASEL | 2023年 / 12卷 / 03期
基金
中国国家自然科学基金;
关键词
water productivity; discrepancy characteristics; driving factors; contribution rate; Yellow River Basin; WINTER-WHEAT; IRRIGATION DISTRICT; YIELD; RICE; VARIABILITY; TRENDS;
D O I
10.3390/plants12030580
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
To reveal the relationship between agricultural water resource consumption and grain production in the Yellow River Basin, the irrigation water productivity (WPI), crop water productivity (WPC), total inflow water productivity (WPT), and eleven influencing factors were selected. The spatial and temporal distribution characteristics and driving factors of water productivity of the main crops in the Yellow River Basin were analyzed with the spatial autocorrelation analysis, grey correlation analysis, sensitivity analysis, and relative contribution rate. The results showed that the minimum mean values of WPI, WPC, and WPT were 0.22, 0.35, and 0.18 kg/m(3) in Qinghai, respectively, the maximum mean value of WPI was 2.11 kg/m(3) in Henan, and the maximum mean values of WPC and WPT were 0.71 and 0.61 kg/m(3) in Shandong, respectively. The changing trends in WPI and WPT in Qinghai and in WPC in Shandong were insignificant, whereas the WPI, WPC, and WPT in other provinces showed a significant increasing trend. Water productivity displayed a certain spatial clustering feature in the Yellow River Basin in different years, such as a high-high (H-H) aggregation in Henan in 2005, and an H-H aggregation in Shanxi in 2015 for WPI. The water productivity had a significant positive correlation with the consumption of chemical fertilizer with a 100% effective component (CFCEC), effective irrigated area (EIA), plastic film used for agriculture (PFUA), and total power of agricultural machinery (AMTP), while it had a significant negative correlation with the persons engaged in rural areas (PERA). There was a large grey correlation degree between the water productivity and the average annual precipitation (AAP), CFCEC, PFUA, consumption of chemical pesticides (CFC), and AMTP in the Yellow River Basin, but their sensitivity was relatively small. The main driving factors were EIA (8.98%), agricultural water (AW, 15.55%), AMTP (12.64%), CFCEC (12.06%), and CPC (9.77%) for WPI; AMTP (16.46%), CFCEC (13.25%), average annual evaporation (AAE, 12.94%), EIA (10.49%), and PERA (10.19%) for WPC; and EIA (14.26%), AMTP (13.38%), AAP (12.30%), CFCEC (10.49%), and PFUA (9.69%) for WPT in the Yellow River Basin. The results can provide support for improving the utilization efficiency of agricultural water resources, optimizing the allocation of water resources, and implementing high-quality agricultural developments in the Yellow River Basin.
引用
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页数:21
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