Journal
WATER
Volume 13, Issue 19, Pages -Publisher
MDPI
DOI: 10.3390/w13192777
Keywords
drought monitoring; northeastern China; passive microwave remote sensing; Pearson correlation analysis; soil moisture
Categories
Funding
- Philosophy and Social Science planning project of Guangdong Province [GD21YYJ15]
- Special Fund for Research on Public Interests, Ministry of Water Resources [201401036]
- Guangdong-Hong Kong Joint Laboratory for Water Security [2020B1212030005]
- Guangdong Provincial Water Science and Technology Innovation Foundation [2017-13]
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Drought is a costly disaster in China and globally, especially in the important grain-producing region of Northeastern China. The study found that the SMOS-SM product effectively monitored drought patterns in this area, showing high correlation with in situ meteorological indices. The spatial distribution of drought was successfully captured using maps based on SMOS-SM and in situ indices, indicating the potential for enhanced monitoring capacity with additional field information.
Drought is the costliest disaster around the world and in China as well. Northeastern China is one of China's most important major grain producing areas. Frequent droughts have harmed the agriculture of this region and further threatened national food security. Therefore, the timely and effective monitoring of drought is extremely important. In this study, the passive microwave remote sensing soil moisture data, i.e., the SMOS soil moisture (SMOS-SM) product, was compared to several in situ meteorological indices through Pearson correlation analysis to assess the performance of SMOS-SM in monitoring drought in northeastern China. Then, maps based on SMOS-SM and in situ indices were created for July from 2010 to 2015 to identify the spatial pattern of drought distributions. Our results showed that the SMOS-SM product had relatively high correlation with in situ indices, especially SPI and SPEI values of a nine-month scale for the growing season. The drought patterns shown on maps generated from SPI-9, SPEI-9 and sc-PDSI were also successfully captured using the SMOS-SM product. We found that the SMOS-SM product effectively monitored drought patterns in northeastern China, and this capacity would be enhanced when field capacity information became available.
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