Construction and application of Optimized Comprehensive Drought Index based on lag time: A case study in the middle reaches of Yellow River Basin, China

Drought is a complex and dynamic natural phenomenon. A single drought index can hardly reflect the multi-type char-acteristics of drought, and comprehensive drought indices that incorporate data from multiple sources have been pro-posed recently. In this study, an Optimized Comprehensive Drought Index (OCDI) was constructed by taking into account the lag time of meteorological drought, agricultural drought and hydrological drought. The Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Water Storage Deficit Index (WSDI) represented the three types of droughts, respectively. Specifically, we used the Solar-induced Chlorophyll Fluorescence (SIF) to characterize the vegetation condition instead of the Normalized Difference Vegetation Index (NDVI). The application results of the proposed drought index in the middle reaches of Yellow River basin (MRYRB) showed that the lag time of different types of drought indices had seasonal differences, with a shorter lag time in summer (0-4 months) and a longer lag time in winter and spring (> 4 months). For typical drought events, the drought intensity and duration identified by OCDI were compatible with the drought evolution characteristics and consistent with the historical records, therefore, OCDI is more suitable for drought monitoring in the study area. Based on the monitoring results of the OCDI, the average number of droughts in the MRYRB was 16 times, with a duration of 2.8 months and an average drought intensity of 0.28 (at moderate drought grade). Drought times and intensity were higher in the northwestern part of the study area, and spring was a high-frequency period for drought occurrences.

Automated summary

In this study, an Optimized Comprehensive Drought Index (OCDI) was constructed by considering the lag time of meteorological drought, agricultural drought, and hydrological drought. The application results showed that OCDI was more suitable for drought monitoring in the study area.