A novel comprehensive agricultural drought index reflecting time lag of soil moisture to meteorology: A case study in the Yangtze River basin, China

• Lag times of soil moisture to different meteorological factors were investigated. • A drought index reflecting time lag of soil moisture to meteorology was proposed. • The CADI was sensitive to capture agricultural drought in temporal and spatial. • The CADI can excellently identify summer drought during the growing season. Soil moisture related agriculture drought usually lags behind meteorological factors. In order to address such a hysteresis, the time lag of soil moisture to meteorological factors were initially investigated based on remote sensing products and meteorological observed data in Yangtze River basin. Soil moisture exhibited different lag times to meteorological factors in different climate regions. There is one month lagged in the northwest of the Yangtze River basin, while two months lagged in the middle and east. A novel Comprehensive Agricultural Drought Index (CADI) was then constructed to reflect the feedback of time lag effects in drought assessment, which comprehensively integrated the lagging times of soil moisture to precipitation and evapotranspiration. The CADI was negatively correlated with Standardized Precipitation Index (SPI), Standard Precipitation Evapotranspiration Index (SPEI), Vegetation Health Index (VHI) and Reconnaissance Drought Index (RDI), among which the SPEI-3 was most strongly correlated. Drought grades captured by CADI had significantly positive correlations to SPI, SPEI, VHI and RDI captured with correlation coefficients between 0.5 and 0.7. Moreover, the CADI was able to effectively monitor the annual and seasonal variations and spatial pattern of agricultural drought, particularly better identify summer droughts, from which the crop phenology related agriculture drought monitoring can benefit. The temporal variation trend of CADI also agreed to the crop drought-affected area. Therefore, the proposed CADI is superior to characterize agricultural drought by eliminating temporally asynchronous effects of meteorology and soil moisture on drought monitoring. It provides scientific support for hazard assessment and mitigation of regional drought management.