LÜ Yinfeng, ZHOU Jiayi, SUN Peng, ZHANG Qiang, MA Zice, ZOU Yifan, BIAN Yaojin, LIU Ruilin. Spatial-temporal characteristics and possible impacts of drought in Hengduan Mountain: a TVDI study[J]. Journal of Beijing Normal University(Natural Science), 2022, 58(6): 926-935. DOI: 10.12202/j.0476-0301.2021301
Citation: LÜ Yinfeng, ZHOU Jiayi, SUN Peng, ZHANG Qiang, MA Zice, ZOU Yifan, BIAN Yaojin, LIU Ruilin. Spatial-temporal characteristics and possible impacts of drought in Hengduan Mountain: a TVDI study[J]. Journal of Beijing Normal University(Natural Science), 2022, 58(6): 926-935. DOI: 10.12202/j.0476-0301.2021301

Spatial-temporal characteristics and possible impacts of drought in Hengduan Mountain: a TVDI study

  • Drought in Hengduan Mountain from 2001 to 2019 was studied.Comparison was made between two temperature vegetation dryness index (TVDI), calculated from enhanced vegetation index (EVI) and normalized difference vegetation index (NDVI), and crop water stress index (CWSI), calculated from potential evapotranspiration (PET) and actual evapotranspiration (ET).Theil-Sen trend analysis and Mann-Kendall test were used to study spatial distribution, temporal variation and space-time evolution of drought.Meteorological data were correlated.EVI-based TVDI was found more suited for drought research.Ts-EVI characteristic space constructed from MODIS EVI and land surface temperature (LST) products showed an annual drought decrease in the study period, average annual drought was found higher in the south and lower in the north.Severe drought occurred mainly in Panzhihua, in hot and humid areas.In the north, concentration was noted in vicinity of the three rivers (Lancang River, Nujiang River and Jinsha River) and Hongyuan Grassland.The most severe drought occurred in summer, and drought increased significantly during transition from spring to summer.Significant correlation was found between drought and sunshine duration, but weak or no correlation between drought, precipitation and humidity respectively.Meteorological conditions could be used to predict disaster to facilitate disaster prevention and mitigation.
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