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Remote Sensing for Natural Resources    2022, Vol. 34 Issue (1) : 151-157     DOI: 10.6046/zrzyyg.2021074
A study on the characteristics and model of drought in Xinjiang based on multi-source data
QIN Dahui1(), YANG Ling1, CHEN Lunchao1, DUAN Yunfei1, JIA Hongliang1, LI Zhenpei1, MA Jianqin2
1. School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China
2. School of Water Conservancy, North China University of Water Conservancy and Hydroelectric Power, Zhengzhou 450046, China
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An improved and comprehensive drought monitoring model was developed in this study. Given multi-genetic types such as the interaction of atmospheric precipitation, vegetation growth, and elevation, multiple data sources were selected for the model, including EOS-MODIS data, TRMM precipitation data, and the region SRTM-DEM(digital elevation model) data from 2001 to 2019 in Xinjiang. The parameters including precipitation concentration index (PCI), temperature and vegetation drought index (TVDI), and DEM were calculated, and the principal component analysis (PCA) method was employed to establish the model. Then, the model was used to analyze the spatio-temporal characteristics of drought in the study area. The analytical results show that the annual occurrence frequency of drought in the study area from 2001 to 2019 was high in the middle part and low in the surrounding areas. In addition, drought struck 47.7% of the study area, and the occurrence frequency of drought reached 60% in 32.3% of the drought regions. Meanwhile, drought was concentrated in the Tarim and Turpan basins. The changing trends of drought in the study area differed greatly. For the linear regression slope of drought from March and September, the absolute values of the positive slope were far greater than those of the negative slope. Based on this, it can be predicted that the drought in the study area mainly included spring and summer droughts in 2020.

Keywords drought monitoring      multi-source data      principal component analysis      spatio-temporal evolution      trend analysis     
ZTFLH:  TP79  
Issue Date: 14 March 2022
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Dahui QIN
Lunchao CHEN
Yunfei DUAN
Hongliang JIA
Zhenpei LI
Jianqin MA
Cite this article:   
Dahui QIN,Ling YANG,Lunchao CHEN, et al. A study on the characteristics and model of drought in Xinjiang based on multi-source data[J]. Remote Sensing for Natural Resources, 2022, 34(1): 151-157.
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Fig.1  Distribution of meteorological stations in the study area
Fig.2  Flow chart for the model constructing
无旱 - 0.5 0.4
轻度干旱 ( - 1.0 , - 0.5 ) ( 0.3,0.4 )
中度干旱 ( - 1.5 , - 1.0 ] ( 0.2,0.3 ]
重度干旱 [ - 2.0 , - 1.5 ] [ 0.1,0.2 ]
极度干旱 < - 2.0 < 0.1
Tab.1  Classification of drought levels
月份 相关性系数 月份 相关性系数
1月 0.49 7月 0.73
2月 0.51 8月 0.74
3月 0.66 9月 0.70
4月 0.66 10月 0.64
5月 0.70 11月 0.58
6月 0.70 12月 0.18
Tab.2  The coefficient of correlation between SDMI and SPEI
Fig.3  Drought frequency distribution in the study area
Fig.4  Drought frequency of meteorological station
Fig.5  Drought frequency of inter-monthly
Fig.6  Seasonal drought distribution of the study area
Fig.7  Statistical characteristics of linear regression slope from January to December
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