期刊
REMOTE SENSING
卷 13, 期 18, 页码 -出版社
MDPI
DOI: 10.3390/rs13183748
关键词
drought; spatial and temporal pattern; Yellow River Basin; remote sensing drought index; air temperature; precipitation; soil moisture
类别
资金
- NationalNatural Science Foundation Project ofChina [32130066]
- Henan Provincial Department of Science and Technology Research Project [212102310019]
- Natural Science Foundation of Henan [202300410531]
- Youth Science Foundation Program of Henan Natural Science Foundation [202300410077]
- the major project of Collaborative Innovation Center on Yellow River Civilization jointly built by Henan Province andMinistry of Education [2020M19]
This study used remote sensing technology and meteorological data to analyze drought conditions in the Yellow River Basin. The results show that reconstructed temperature and vegetation indices can improve the accuracy of drought monitoring, different drought indices show consistency in spatial and temporal patterns but differences in some local areas, and drought level in the Yellow River Basin is highest in the northwest and lowest in the southwest and southeast, remaining stable from 2003 to 2019.
Drought is one of the most complex and least-understood environmental disasters that can trigger environmental, societal, and economic problems. To accurately assess the drought conditions in the Yellow River Basin, this study reconstructed the Land Surface Temperature (LST) using the Annual Temperature Cycle (ATC) model and the Normalized Difference Vegetation Index (NDVI). The Temperature Condition Index (TCI), Vegetation Condition Index (VCI), Vegetation Health Index (VHI), and Temperature-Vegetation Drought Index (TVDI), which are four typical remote sensing drought indices, were calculated. Then, the air temperature, precipitation, and soil moisture data were used to evaluate the applicability of each drought index to different land types. Finally, this study characterized the spatial and temporal patterns of drought in the Yellow River Basin from 2003 to 2019. The results show that: (1) Using the LST reconstructed by the ATC model to calculate the drought index can effectively improve the accuracy of drought monitoring. In most areas, the reconstructed TCI, VHI, and TVDI are more reliable for monitoring drought conditions than the unreconstructed VCI. (2) The four drought indices (TCI, VCI, VH, TVDI) represent the same temporal and spatial patterns throughout the study area. However, in some small areas, the temporal and spatial patterns represented by different drought indices are different. (3) In the Yellow River Basin, the drought level is highest in the northwest and lowest in the southwest and southeast. The dry conditions in the Yellow River Basin were stable from 2003 to 2019. The results in this paper provide a basis for better understanding and evaluating the drought conditions in the Yellow River Basin and can guide water resources management, agricultural production, and ecological protection of this area.
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