Applied research on summer soil moisture monitoring models based on Suomi NPP/VIIRS in the eastern agricultural region of Qinghai Province
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DOI:10.7606/j.issn.1000-7601.2023.04.31
Key Words: Suomi NPP  soil moisture  TVDI  NDWI  VCI
Author NameAffiliation
LI Suyun Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
CHEN Guoqian Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
ZHU Cunxiong Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
QIAO Bin Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
SHI Feifei Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
CAO Xiaoyun Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
ZHOU Bingrong Qinghai Province Institute of Meteorological Sciences, Xining, Qinghai 810001, China
Qinghai Province Key Laboratory of Disaster Prevention and Mitigation, Xining, Qinghai 810001, China 
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Abstract:
      Soil moisture is a most important index to measure the degree of drought and continues to bea major scientific problem for effective monitoring and early warning about soil moisture for all walks of life. The normalized difference water index, vegetation condition index and temperature-vegetation dryness index were calculated based on Suomi NPP/VIIRS to construct three soil moisture monitoring models in the eastern agricultural region of Qinghai Province.Models were tested using continuous field fixed-point observation data and site observation data, and application tests were performed in the summer drought of 2017. The results showed that the TVDI model was the best (RMSE was 4.4%), the VCI model was the second (RMSE was 4.7%) and the NDWI model was the worst (RMSE was 5.2%) in the back-generation test during 2012-2016. When the three models applied to the field survey points in Huzhu County of Qinghai Province using the remote sensing inspection during 2018 to 2020, TVDI model performed best (RMSE was 3.8%), VCI model took the second place (RMSE was 5.0%)and NDWI model was the worst (RMSE was 8.8%).The drought distribution range retrieved by TVDI model was consistent with the actual occurrence and development and mitigation process.The changes of drought mitigation or relief period were not reflectedby VCI model in drought distribution and the drought area retrieved by NDWI model was smaller in the summer drought of 2017.