Spatial Heterogeneity in the Response of Winter Wheat Yield to Meteorological Dryness/Wetness Variations in Henan Province, China

被引:1
|
作者
Li, Cheng [1 ]
Gu, Yuli [1 ]
Xu, Hui [2 ]
Huang, Jin [3 ]
Liu, Bo [4 ]
Chun, Kwok Pan [5 ]
Octavianti, Thanti [5 ]
机构
[1] Yangzhou Univ, Sch Plant Protect, Dept Ecol, Joint Int Res Lab Agr & Agriprod Safety,Minist Edu, Yangzhou 225009, Peoples R China
[2] Nanjing Municipal Acad Ecol & Environm Protect Sci, Nanjing 210013, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Sch Ecol & Appl Meteorol, Nanjing 210044, Peoples R China
[4] Yangzhou Univ, Coll Hydraul Sci & Engn, Yangzhou 225009, Peoples R China
[5] Univ West England, CATE Sch Architecture & Environm, Bristol BS16 1QY, England
来源
AGRONOMY-BASEL | 2024年 / 14卷 / 04期
基金
中国国家自然科学基金;
关键词
winter wheat yield; meteorological dryness/wetness features; spatial differences; Henan province; LONG-TERM PRECIPITATION; CLIMATE INDEXES; TIME-SERIES; DROUGHT; VARIABILITY; REGRESSION; DYNAMICS; REGION; BASIN; WIND;
D O I
10.3390/agronomy14040817
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Knowledge of the responses of winter wheat yield to meteorological dryness/wetness variations is crucial for reducing yield losses in Henan province, China's largest winter wheat production region, under the background of climate change. Data on climate, yield and atmospheric circulation indices were collected from 1987 to 2017, and monthly self-calibrating Palmer drought severity index (sc-PDSI) values were calculated during the winter wheat growing season. The main results were as follows: (1) Henan could be partitioned into four sub-regions, namely, western, central-western, central-northern and eastern regions, based on the evolution characteristics of the time series of winter wheat yield in 17 cities during the period of 1988-2017. Among them, winter wheat yield was high and stable in the central-northern and eastern regions, with a remarkable increasing trend (p < 0.05). (2) The sc-PDSI in February had significantly positive impacts on climate-driven winter wheat yield in the western and central-western regions (p < 0.05), while the sc-PDSI in December and the sc-PDSI in May had significantly negative impacts on climate-driven winter wheat yield in the central-northern and eastern regions, respectively (p < 0.05). (3) There were time-lag relationships between the sc-PDSI for a specific month and the atmospheric circulation indices in the four sub-regions. Furthermore, we constructed multifactorial models based on selected atmospheric circulation indices, and they had the ability to simulate the sc-PDSI for a specific month in the four sub-regions. These findings will provide scientific references for meteorological dryness/wetness monitoring and risk assessments of winter wheat production.
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页数:15
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