Quantitative analysis of vegetation drought propagation process and uncertainty in the Yellow River Basin

Abstract

Understanding the full propagation process of drought, from meteorological drought (MD) to vegetation drought (VD), could promote drought monitoring and early warning in the ecosystems. This study characterized MD, soil moisture drought (SD), and VD and their propagations using the Standardized Precipitation Evapotranspiration Index (SPEI), the Soil Moisture Anomaly Percentage Index (SMAPI), and the Vegetation Health Index (VHI) to enhance understanding of the drought hazard in the Yellow River Basin (YRB), China. Drought events, duration, magnitude, intensity, and interval were identified from these time series via the run theory and percentile thresholds. The relationships between MD, SD, and VD were examined by cross-correlating the SPEI, SMAPI, and VHI. Finally, the effects of climate and grid properties on drought characteristics and propagations were investigated. The results showed that the upland had a low risk for all droughts, while the midland had a low risk for MD and a high risk for SD, and the lowland had a high risk for MD in the YRB. For the full-time data, the lowland had the strongest correlations and shortest time lags, while the upland had the weakest correlations and longest time lags for full propagation from MD to SD to VD. However, seasonality and multi-threshold characteristics in extreme drought dominated the propagation process of VD. For monthly data, midland showed the strongest correlations and shortest time lags in summer, while lowland showed the strongest correlations and shortest time lags in other seasons for full propagation of VD. For multi-threshold data, the 0–30th percentile had stronger correlations and shorter time lags for full propagation of VD. Meteorology showed a stronger correlation with all drought characteristics and drought propagation than soil properties and land use. These findings provide valuable insights for enhancing the vegetation aspects of drought monitoring and early warning in the YRB.