Responses of the Remote Sensing Drought Index with Soil Information to Meteorological and Agricultural Droughts in Southeastern Tibet

Ziyu Wang; Zegen Wang; Junnan Xiong; Wen He; Zhiwei Yong; Xin Wang

doi:10.3390/rs14236125

Remote Sensing (Dec 2022)

Responses of the Remote Sensing Drought Index with Soil Information to Meteorological and Agricultural Droughts in Southeastern Tibet

Ziyu Wang,
Zegen Wang,
Junnan Xiong,
Wen He,
Zhiwei Yong,
Xin Wang

Affiliations

Ziyu Wang: School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China
Zegen Wang: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
Junnan Xiong: School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China
Wen He: Institute for Disaster Management and Reconstruction, Sichuan University-Hongkong Polytechnic University, Chengdu 610207, China
Zhiwei Yong: School of Geoscience and Technology, Southwest Petroleum University, Chengdu 610500, China
Xin Wang: School of Civil Engineering and Geomatics, Southwest Petroleum University, Chengdu 610500, China

DOI: https://doi.org/10.3390/rs14236125
Journal volume & issue: Vol. 14, no. 23
p. 6125

Abstract

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The Temperature–Vegetation–Precipitation–Drought Index (TVPDI) has a good performance in drought monitoring in China. However, different regions have different responses to droughts due to terrain differences. In southeastern Tibet, the drought monitoring capacity of some drought indices without soil information has to be assessed on account of the poor sensitivity between temperature and soil humidity. Therefore, soil moisture was added to calculate a new drought index based on TVPDI in southeastern Tibet, named the Temperature–Vegetation–Soil-Moisture–Precipitation–Drought Index (TVMPDI). Then, the TVMPDI was validated by using the Standardized Precipitation Evapotranspiration Index (SPEI) and other remote sensing drought indices, including the Vegetation Health Index (VHI) and Scale Drought Conditions Index (SDCI), during the growing seasons of 2003–2018. The Standardized Precipitation Index (SPI) and SPEI were used to represent meteorological drought and Gross Primary Productivity (GPP) was used to represent agricultural drought. The relation between TVMPDI and these drought indices was compared. Finally, the time trends of TVMPDI were also analyzed. The relation coefficients of TVMPDI and SPEI were above 0.5. The correlations between TVMPDI and drought indices, including the Vegetation Health Index (VHI) and Scale Drought Conditions Index (SDCI), also had a good performance. The correlation between the meteorological drought indices (SPI and SPEI) and TVMPDI were not as good as for the TVPDI, but the temporal correlation between the TVMPDI and GPP was greater than that between the TVPDI and GPP. This indicates that the TVMPDI is more suitable for monitoring agricultural drought than the TVPDI. In addition, historical drought monitoring had values that were consistent with those of the actual situation. The trend of the TVMPDI showed that drought in the study area was alleviated from 2003 to 2018. Furthermore, GPP was negatively correlated with SPEI (r = −0.4) and positively correlated with Soil Moisture (SM) drought index (TVMPDI, SMCI) (r = 0.4) in the eastern part of the study area, which suggests that SM, rather than precipitation, could promote the growth of vegetation in the region. A correct understanding of the role of soil information in drought comprehensive indices may monitor meteorological drought and agricultural drought more accurately.

Published in Remote Sensing

ISSN: 2072-4292 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Science
Website: http://www.mdpi.com/journal/remotesensing/

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