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Remote Sensing Technology and Application  2019, Vol. 34 Issue (4): 865-873    DOI: 10.11873/j.issn.1004-0323.2019.4.0865
    
Evaluation of Drought Indices of Metrology, Hydrology and Agriculture over the Continental United States
Zhanpeng Wang1(),Lisheng Song1(),Ziyan Lan2,Menying Yang1,Dan Lu1
1. Chongqing Engineering Research Center for Remote Sensing Big Data Application, School of Geographical Sciences, Southwest University, Chongqing 400715, China
2. Hanhong College, Southwest University, Chongqing 400715, China
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Abstract  

Droughts are one of the more normally natural hazards on a year-to-year basis. And the drought are significant and widespread, affecting economic development, agriculture and people health at any one time. There are various drought indexes have been developed to monitor this hazard which arise precipitation decrease, soil moisture deficit and vegetation stress. However, single drought index cannot consider all of these anomaly to warn and monitor the drought. In this study, remote sensing based data including GLDAS climate data involve precipitation and soil moisture, GLEAM ET and GRACE dataset simulated terrestrial water storage are used to calculate multiple drought indicators including SPI, SMI, ESI and TWSC. These drought indicators refer to anomaly of precipitation, soil moisture and vegetation water supply, and terrestrial water storage change, respectively. Then they were used combined and compared to track the droughts events in United State of American. The results showed that all the drought indexes performed reliable and consistent with each other well, with correlation coefficient value greater than 0.7. However, the ESI performed more reliable, which can reflect the plant water stress under dry condition, additionally, it can be computed in combined with satellite observed data with high spatial resolution to monitor the drought conditions from field scale to global scale. The vegetation have divergent responses to the meteorological, hydrological and droughts except under grassland. The differences between the three drought indexes increase along with the elevated aboveground biomass. Therefore, the land surface vegetation covered conditions involve canopy structure and feedback between plants and climate, which relevant in a drought monitor is often a curial consideration in determining the application of drought indexes.

Key words:  Drought indexes      ESI      SPI      SMI     
Received:  11 May 2018      Published:  16 October 2019
ZTFLH:  Q948  
Corresponding Authors:  Lisheng Song     E-mail:  wangzp0825@email.swu.edu.cn;songls@swu.edu.cn
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Zhanpeng Wang
Lisheng Song
Ziyan Lan
Menying Yang
Dan Lu

Cite this article: 

Zhanpeng Wang,Lisheng Song,Ziyan Lan,Menying Yang,Dan Lu. Evaluation of Drought Indices of Metrology, Hydrology and Agriculture over the Continental United States. Remote Sensing Technology and Application, 2019, 34(4): 865-873.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2019.4.0865     OR     http://www.rsta.ac.cn/EN/Y2019/V34/I4/865

Fig. 1  The landuse map of the Continental United States
SMI-1SMI-3ESI-3TWSC
SPI-6Pearson 相关性0.591 6**0.714 5**0.694 9**0.253 2
显著性(双侧)0000.001 5
SMI-1Pearson 相关性0.869 9**0.634 7**0.167 2
显著性(双侧)000.038 2
SMI-3Pearson 相关性0.771 0**0.223 7**
显著性(双侧)00.005 3
ESI-3Pearson 相关性0.273 8**
显著性(双侧)0.000 6
注:**. 在 0.01 水平(双侧)上显著相关
Table 1  The coefficient between the main indexes’ average value
Fig. 2  The comparison of ESI、SPI、SMI and grace-TWSC in drought monitoring
Fig. 3  Coefficient of temporal correlation between the monthly maps of these drought indexes from 2003~2015
Fig. 4  The comparison of ESI、SPI and SMI for monitoring drought under different underlaying surface
耕地裸地林地灌木草地
SPI-6与ESI-3相关性0.29950.80280.59080.86580.8173
SPI-6与SMI-3相关性0.61830.79030.67360.80970.7017
ESI-3与SMI-3相关性0.53460.86640.62760.89630.8450
Table 2  The coefficient between the drought indexes
Fig. 5  The comparative analysis of drought formation process in 2012
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