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Monitoring and predicting drought based on multiple indicators in an arid area, China

  • Wang, Yunqian
  • Yang, Jing
  • Chen, Yaning
  • Su, Zhicheng
  • Li, Baofu
  • Guo, Hao
  • De Maeyer, Philippe
Publication Date
Jan 01, 2020
DOI: 10.3390/rs12142298
Ghent University Institutional Archive
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Droughts are one of the costliest natural disasters. Reliable drought monitoring and prediction are valuable for drought relief management. This study monitors and predicts droughts in Xinjiang, an arid area in China, based on the three drought indicators, i.e., the Standardized Precipitation Index (SPI), the Standardized Soil Moisture Index (SSMI) and the Multivariate Standardized Drought Index (MSDI). Results indicate that although these three indicators could capture severe historical drought events in the study area, the spatial coverage, persistence and severity of the droughts would vary regarding different indicators. The MSDI could best describe the overall drought conditions by incorporating the characteristics of the SPI and SSMI. For the drought prediction, the predictive skill of all indicators gradually decayed with the increasing lead time. Specifically, the SPI only showed the predictive skill at a 1-month lead time, the MSDI performed best in capturing droughts at 1- to 2-month lead times and the SSMI was accurate up to a 3-month lead time owing to its high persistence. These findings might provide scientific support for the local drought management.

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