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Drought is the most widespread and destructive hazard in arid and semiarid regions, with behaviors that become more complicated under climate change. To provide an overall view of drought conditions across the Loess Plateau of China, two multiscalar drought indices, the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), were used to identify the regional spatiotemporal characteristics of drought conditions from 1957 to 2012. Climatic data from 54 meteorological stations across the region were used to calculate the SPI and SPEI time series at 1-, 3-, 6-, 12- and 24-month time scales. Subregions with independent drought characteristics and the corresponding representative meteorological stations were identified by principal component analysis to facilitate regional drought monitoring. A temporal trend of drought severity over a 12-month time scale, as detected by the Mann-Kendall test, was mapped for the entire region. The intensity of the increasing trend of drought severity based on the SPEI was weaker than that based on the SPI. The area with a significant increasing trend of drought severity based on the SPEI was only found in the southwest of the region and was much smaller than that based on the SPI. The temporal behavior of drought frequency from January to December differed over different time scales and levels of drought severity. The regional distributions of the drought frequency were mapped for different months. Generally, the drought frequency spatially decreased from southeast to northwest and was higher in the middle of the winter, late spring and early summer. While the drought-hit area also changed with time, it was generally within the central and northwest areas of the region. Drought behaviors identified by the SPI and SPEI also changed with different time scales. Clear differences were also found among the drought characteristics identified by SPI, SPEI and the self-calibrated Palmer Drought Severity Index. The SPEI is considered as a robust index for regional drought monitoring and analysis under global climate change scenarios because of its multiscalar nature, simple form, low data requirement, and ability to identify the effects of temperature on drought conditions. (C) 2016 Elsevier B.V. All rights reserved.