[Applicability and application of multiple drought indices to water deficit of staple crops in China].

In the context of global climate change, the increasing frequency, scale, and intensity of droughts severely threaten food security of China. We established two drought indices (crop evapotranspiration-effective preci-pitation index (CEEP) and water deficit index (WDI)) based on meteorological parameters and crop growth-related data during growing season. The performance of those two indices was compared with that of four widely used ones, i.e., percentage of precipitation anomaly (PA), moisture index (MI), standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI). We further used the six indices to analyze the characteristics of typical drought events in the winter wheat region of North China and the spring maize region of Northeast China, as well as the spatiotemporal variations of droughts from 1979 to 2018. The results showed that CEEP and WDI effectively captured crop water scarcity and drought characteristics, and WDI was identified as the optimal drought index in more than one-third of provinces, mainly concentrated in Northeast and North China. In terms of temporal variation, based on the WDI, there was no significant trend of drought events in the winter wheat region in North China and the spring maize region in Northeast China. In terms of spatial variation, the performance of the drought indices differed. In the winter wheat zone of North China, PA, MI, and SPI detected more wetting characteristics, while SPEI, CEEP, and WDI detected more drying characteristics. In the spring maize zone of Northeast China, the indices performed more consistency, with wetting trends observed in Suihua, Daqing, and Hegang while drying trends in western part of Jilin and Liaoning, southern Liaoning, western Heilongjiang, and southern Sanjiang Plain. WDI was suitable for crop water deficit analysis in Northeast and North China and could accurately reflect the spatial distribution of drying or wetting trends, which would provide support for water resource management and decision-making in agricultural production.