Knowledge Resource Center for Ecological Environment in Arid Area
DOI | 10.2480/agrmet.D-18-00011 |
Determining agricultural drought for spring wheat with statistical models in a semi-arid climate | |
Zhao, Funian1,2,3; Lei, Jun4; Wang, Runyuan1; Wang, Heling1; Zhang, Kai1; Yu, Qiang5,6 | |
通讯作者 | Zhao, Funian |
来源期刊 | JOURNAL OF AGRICULTURAL METEOROLOGY
![]() |
ISSN | 0021-8588 |
EISSN | 1881-0136 |
出版年 | 2018 |
卷号 | 74期号:4页码:162-172 |
英文摘要 | Agricultural drought frequently occurs and results in major grain yield loss in semi-arid climate region, but determining it is difficult. This study was conducted to determine agricultural drought for spring wheat (Triticum aestivum L.) in the western Loess Plateau of China. Several statistical models were established and evaluated by long-term data, including soil water in soil layer of 50 cm depth at sowing day, air temperature, precipitation, pan evaporation during spring wheat growing season, and two groups of spring wheat yield (one from field experiments during 1987-2011 and the other from statistical Bureau during 1980-2013). Even though each of water supply factors, precipitation during growing season and the soil water at sowing day, could separately explain no more than 30% variation of the yield, both of them could explain > 55% yield variation under dry condition. Average air temperature and precipitation during growing season that displayed two apparent yield categories (drought and normal) could be used to determine agricultural drought by pattern recognition when years with the soil water at sowing day of > 98.4 mm were eliminated. Based on long-term meteorological data and the relationship between soil water at sowing day and yield under different growing season moisture conditions, the probability of agricultural drought occurrence in Dingxi for spring wheat was speculated, which nearly corresponds with the observational data during 1980-2013. |
英文关键词 | Pattern recognition Precipitation Regression analysis Soil water content Yield |
类型 | Article |
语种 | 英语 |
国家 | Peoples R China |
收录类别 | SCI-E |
WOS记录号 | WOS:000447068400004 |
WOS关键词 | STANDARDIZED PRECIPITATION INDEX ; LOESS PLATEAU ; WINTER-WHEAT ; YIELD VARIABILITY ; WATER-CONTENT ; CROP YIELDS ; CHINA ; IRRIGATION ; MANAGEMENT ; IMPACT |
WOS类目 | Agriculture, Multidisciplinary ; Meteorology & Atmospheric Sciences |
WOS研究方向 | Agriculture ; Meteorology & Atmospheric Sciences |
来源机构 | 中国科学院地理科学与资源研究所 ; 西北农林科技大学 |
资源类型 | 期刊论文 |
条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/210429 |
作者单位 | 1.China Meteorol Adm, Lanzhou Inst Arid Meteorol, Key Lab Arid Climate Change & Disaster Reduct CMA, Key Lab Arid Climat Change & Disaster Reduct Gans, Lanzhou 730020, Gansu, 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.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 4.Dingxi Meteorol Bur, Dingxi 743000, Peoples R China; 5.Northwest A&F Univ, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China; 6.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, Funian,Lei, Jun,Wang, Runyuan,et al. Determining agricultural drought for spring wheat with statistical models in a semi-arid climate[J]. 中国科学院地理科学与资源研究所, 西北农林科技大学,2018,74(4):162-172. |
APA | Zhao, Funian,Lei, Jun,Wang, Runyuan,Wang, Heling,Zhang, Kai,&Yu, Qiang.(2018).Determining agricultural drought for spring wheat with statistical models in a semi-arid climate.JOURNAL OF AGRICULTURAL METEOROLOGY,74(4),162-172. |
MLA | Zhao, Funian,et al."Determining agricultural drought for spring wheat with statistical models in a semi-arid climate".JOURNAL OF AGRICULTURAL METEOROLOGY 74.4(2018):162-172. |
条目包含的文件 | 条目无相关文件。 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。