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Remote Sensing
Volume 13
Issue 19
10.3390/rs13193858
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Article

Monitoring Meteorological Drought in Southern China Using Remote Sensing Data

by
Li Liu
1,2,3,
Ran Huang
4,
Jiefeng Cheng
5,
Weiwei Liu
6,
Yan Chen
1,2,3,
Qi Shao
1,2,3,
Dingding Duan
7,
Pengliang Wei
1,2,3,
Yuanyuan Chen
8 and
Jingfeng Huang
1,2,3,*
1
Institute of Applied Remote Sensing and Information Technology, Zhejiang University, Hangzhou 310058, China
2
Key Laboratory of Agricultural Remote Sensing and Information Systems, Zhejiang University, Hangzhou 310058, China
3
Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Natural Resources and Environmental Science, Zhejiang University, Hangzhou 310058, China
4
School of Automation, Hangzhou Dianzi University, Hangzhou 310018, China
5
Zhejiang Geopher Spatial Planning Technology Co., Ltd., Hangzhou 310000, China
6
Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China
7
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
8
College of Environment, Zhejiang University of Technology, Hangzhou 310000, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2021, 13(19), 3858; https://doi.org/10.3390/rs13193858
Submission received: 11 August 2021 / Revised: 23 September 2021 / Accepted: 24 September 2021 / Published: 27 September 2021
(This article belongs to the Topic Climate Change and Environmental Sustainability)
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Abstract

Severe meteorological drought is generally considered to lead to crop damage and loss. In this study, we created a new standard value by averaging the values distributed in the middle 30–70% instead of the traditional mean value, and we proposed a new index calculation method named Normalized Indices (NI) for meteorological drought monitoring after normalized processing. The TRMM-derived precipitation data, GLDAS-derived soil moisture data, and MODIS-derived vegetation condition data from 2003 to 2019 were used, and we compared the NI with commonly used Condition Indices (CI) and Anomalies Percentage (AP). Taking the mid-to-lower reaches of the Yangtze River (MLRYR) as an example, the drought monitoring results for paddy rice and winter wheat showed that (1) NI can monitor well the relative changes in real precipitation/soil moisture/vegetation conditions in both arid and humid regions, while meteorological drought was overestimated with CI and AP, and (2) due to the monitoring results of NI, the well-known drought event that occurred in the MLRYR from August to October 2019 had a much less severe impact on vegetation than expected. In contrast, precipitation deficiency induced an increase in sunshine and adequate heat resources, which improved crop growth in 78.8% of the area. This study discusses some restrictions of CI and AP and suggests that the new NI index calculation provides better meteorological drought monitoring in the MLRYR, thus offering a new approach for future drought monitoring studies.
Keywords: meteorological drought; drought impact; paddy rice; winter wheat meteorological drought; drought impact; paddy rice; winter wheat
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MDPI and ACS Style

Liu, L.; Huang, R.; Cheng, J.; Liu, W.; Chen, Y.; Shao, Q.; Duan, D.; Wei, P.; Chen, Y.; Huang, J. Monitoring Meteorological Drought in Southern China Using Remote Sensing Data. Remote Sens. 2021, 13, 3858. https://doi.org/10.3390/rs13193858

AMA Style

Liu L, Huang R, Cheng J, Liu W, Chen Y, Shao Q, Duan D, Wei P, Chen Y, Huang J. Monitoring Meteorological Drought in Southern China Using Remote Sensing Data. Remote Sensing. 2021; 13(19):3858. https://doi.org/10.3390/rs13193858

Chicago/Turabian Style

Liu, Li, Ran Huang, Jiefeng Cheng, Weiwei Liu, Yan Chen, Qi Shao, Dingding Duan, Pengliang Wei, Yuanyuan Chen, and Jingfeng Huang. 2021. "Monitoring Meteorological Drought in Southern China Using Remote Sensing Data" Remote Sensing 13, no. 19: 3858. https://doi.org/10.3390/rs13193858

APA Style

Liu, L., Huang, R., Cheng, J., Liu, W., Chen, Y., Shao, Q., Duan, D., Wei, P., Chen, Y., & Huang, J. (2021). Monitoring Meteorological Drought in Southern China Using Remote Sensing Data. Remote Sensing, 13(19), 3858. https://doi.org/10.3390/rs13193858

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