Adapting the temperature-fluorescence dryness index as a functional ecological indicator for tracking agroecosystem drought in China's winter wheat regions

Abstract

Accurate agroecosystem drought monitoring of winter wheat is essential for ensuring food security in China. The traditional Temperature Vegetation Dryness Index (TVDI) relies on structural reflectance metrics and can be affected by delayed vegetation responses and canopy saturation. The study adapted the Temperature-Fluorescence Dryness Index (TFDI), which integrates land surface temperature and solar-induced chlorophyll fluorescence, for drought monitoring across China's major winter-wheat regions during 2003–2022. After accounting for temporal autocorrelation and controlling the false discovery rate (FDR), TFDI increased the spatial coverage of significant negative correlations with SMCI1.0 soil moisture at 0–10 cm and 10–20 cm by 14.05 and 13.32 percentage points, respectively, relative to TVDI. However, this overall soil-moisture advantage did not extend to NASAR, where TVDI showed stronger associations in both evaluated layers. Coupling with meteorological drought was scale dependent: TFDI retained broader FDR-significant coverage at SPI-1 and SPI-3, but paired correlation magnitudes were comparable at SPI-1 and only modestly stronger at SPI-3; neither index retained FDR-significant coverage at SPI-6. Trend analysis of the annual March–May TFDI series indicated a mean Sen slope of 0.0092 yr − 1, with FDR-significant positive TFDI trends (drying) across 40.37% of the persistent winter-wheat domain. Drying was concentrated in the Huang–Huai–Hai Plain, Middle–Lower Yangtze Plain, Loess Plateau, and Sichuan Basin. Explanatory modeling identified a north–south contrast in environmental associations with TFDI trends: atmospheric evaporative-demand variables had greater model-attributed importance in northern regions, whereas precipitation had greater importance in southern regions. These results support the large-scale application of TFDI as a physiologically informed indicator of agroecosystem drought while defining the statistical and spatial boundaries of its advantage.