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<p>Drought is a complex process resulting from the interaction of atmospheric, surface, and subsurface conditions, whereas most existing drought indices are designed to monitor only a single type of drought. In this study, a new comprehensive drought index, the Standardized Precipitation Vegetation Soil Moisture Drought Index (SPVSDI), was developed for China by integrating precipitation, enhanced vegetation index, and soil moisture information. The index was established in two steps. First, a composite wetness indicator (PVSDI) was constructed using a three-dimensional spatial distance model. Second, PVSDI was transformed into a standardized drought index through Gamma distribution fitting and probabilistic normalization. The results showed that PVSDI was significantly correlated with TVPDI, with correlation coefficients ranging from − 0.79 to 0.97, and moderate to high positive correlations were observed in nearly two-thirds of China. Compared with SPEI9 and scPDSI, SPVSDI reproduced similar drought evolution patterns while providing clearer delineation of drought extent and a more detailed characterization of drought fluctuations. From 2001 to 2021, more than half of China experienced 14 to 20 drought events, mainly in the eastern and southeastern regions, whereas the NCP and parts of the QTP experienced fewer drought events but markedly longer duration and higher intensity. At the regional scale, the NCP and the QTP exhibited intensifying drought trends, whereas the HHHP and the SBSR generally showed wetting trends. Seasonal analysis further indicated that drought in northwestern China was more persistent throughout the four seasons, whereas eastern and southern China displayed stronger seasonality. Overall, SPVSDI effectively captured the spatio-temporal characteristics of comprehensive drought in China and provides a useful tool for drought monitoring, early warning, and regional drought management.</p>

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Spatio-Temporal Assessment of Drought Based on Multiple Datasets From Atmosphere-Surface-Subsurface Perspective

  • 期刊论文

  • 发表日期：

    2026年5月16日

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  • Peng. Yan,
  • Wei. Wei,
  • Liang. Zhou,
  • JiPing. Wang,
  • BinBin. Xie,
  • JunJu. Zhou,
  • Dibo. Chen

摘要

Drought is a complex process resulting from the interaction of atmospheric, surface, and subsurface conditions, whereas most existing drought indices are designed to monitor only a single type of drought. In this study, a new comprehensive drought index, the Standardized Precipitation Vegetation Soil Moisture Drought Index (SPVSDI), was developed for China by integrating precipitation, enhanced vegetation index, and soil moisture information. The index was established in two steps. First, a composite wetness indicator (PVSDI) was constructed using a three-dimensional spatial distance model. Second, PVSDI was transformed into a standardized drought index through Gamma distribution fitting and probabilistic normalization. The results showed that PVSDI was significantly correlated with TVPDI, with correlation coefficients ranging from − 0.79 to 0.97, and moderate to high positive correlations were observed in nearly two-thirds of China. Compared with SPEI9 and scPDSI, SPVSDI reproduced similar drought evolution patterns while providing clearer delineation of drought extent and a more detailed characterization of drought fluctuations. From 2001 to 2021, more than half of China experienced 14 to 20 drought events, mainly in the eastern and southeastern regions, whereas the NCP and parts of the QTP experienced fewer drought events but markedly longer duration and higher intensity. At the regional scale, the NCP and the QTP exhibited intensifying drought trends, whereas the HHHP and the SBSR generally showed wetting trends. Seasonal analysis further indicated that drought in northwestern China was more persistent throughout the four seasons, whereas eastern and southern China displayed stronger seasonality. Overall, SPVSDI effectively captured the spatio-temporal characteristics of comprehensive drought in China and provides a useful tool for drought monitoring, early warning, and regional drought management.