Drought index revisited to assess its response to vegetation in different agro-climatic zones

A combination of in-situ climatic variables and remote sensing data could provide dynamic information that facilitates to get effective dryness or wetness situations for planetary ecosystems. Thus, the traditional stan-dardized precipitation evapotranspiration index (SPEI) was revisited by drought index (DI) using satellite soil moisture data and land surface evapotranspiration from Penman-Monteith-Leuning Version 2 (PML_V2) datasets to assess the dryness over 2417 station's grid points in China. DI was compared with the self-calibrating Palmer drought severity index (scPDSI), SPEI and composite drought index (CDI) for three major land cover classes (croplands, grasslands, and forests) area. The independent evaluation was carried out using sun-induced chlo-rophyll fluorescence (vegetation photosynthesis), and normalized difference vegetation index datasets including crop yield. Results exhibited that DI performance was comparable with CDI than scPDSI and SPEI to capture the impact of drought on vegetation photosynthesis. Vegetation productivity assessed by NDVI was significantly affected by dryness in the northern and southern part of China using DI, CDI and scPDSI and compared to SPEI. DI displayed a positive correlation with wheat, maize, and rice yield. Revisited drought index showed significant results for vegetation productivity but still necessitate future work to improve DI for agricultural drought research.

Automated summary

A combination of in-situ climatic variables and remote sensing data is used to assess the dryness of planetary ecosystems. The drought index (DI) is compared with other indices for different land cover classes in China, showing comparable performance in capturing the impact of drought on vegetation photosynthesis. DI is also positively correlated with crop yield.