Assessing the soil moisture drought index for agricultural drought monitoring based on green vegetation fraction retrieval methods

被引:6
|
作者
Wu, Rongjun [1 ]
Li, Qi [2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Jiangsu Key Lab Agr Meteorol, Nanjing 210044, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Coll Appl Meteorol, Nanjing 210044, Peoples R China
基金
中国国家自然科学基金;
关键词
Agricultural drought; Root zone soil moisture; Global drought monitoring; Green vegetation fraction;
D O I
10.1007/s11069-021-04693-x
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Soil moisture in root zone soil layers is one of the most important indicators of agricultural drought. Thus, monitoring agricultural drought requires not only knowledge of rainfall anomaly but also quantification of soil moisture. In this study, the effects of various methods of quantifying the green vegetation fraction green vegetation fraction (GVF) on the land-surface-model (LSM)-based soil moisture drought index (SMDI) were assessed using the harvest area data of the World Meteorological Organization together with the widely used vegetation health index and drought severity index. GVF data used in this study include monthly climatological GVF, weekly advanced very high-resolution radiometer (AVHRR)-normalized difference vegetation index-based and 8-daily moderate-resolution imaging spectroradiometer (MODIS) leaf area index (LAI)-based GVF. The results show that SMDI is optimized when using the near-real-time GVF and that LAI-based GVF increases the accuracy of SMDI when monitoring early agricultural drought. The study shows that we can be confident in the accuracy of signals of emerging drought, particularly during the rapid onset of drought.
引用
收藏
页码:499 / 518
页数:20
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