Vegetation is one of the most important indicators of climate change, as it can show regional change in the environment. Vegetation health is affected by various factors, including drought, which has cumulative and time-lag effects on vegetation response. However, the cumulative and time-lag effects of drought on different terrestrial vegetation in China are still unclear. To address this issue, this study examined the cumulative and time-lag effects of drought on vegetation from 2001 to 2020 using the Standardized Precipitation Evapotranspiration Index (SPEI) in the Global SPEI database and the Normalized Difference Vegetation Index (NDVI) in MOD13A3. Based on Sen-Median trend analysis and the Mann–Kendall test, the change trend and significance of the NDVI from 2001 to 2020 were explored. The Pearson correlation coefficient was used to analyze the correlation between the SPEI and NDVI at each cumulative scale and time-lag scale and to further analyze the cumulative and time-lag effects of drought on vegetation. The results show the following: (1) The NDVI value increased at a rate of 0.019/10 years, and the increased area of the NDVI accounted for 80.53% of mainland China, with a spatial trend of low values in the west and high values in the east. (2) The average SPEI cumulative time scale most relevant to the NDVI was 7.3 months, and the cumulative effect demonstrated a high correlation at the scale of 9–12 months and revealed different distributions in different areas. The cumulative effect was widely distributed at the 9-month scale, followed by the 12-month scale. The correlation coefficients of cumulative effects between the SPEI and NDVI for cropland, woodland and grassland peaked at 9 months. (3) The average SPEI time-lag scale for the NDVI was 6.9 months, and the time-lag effect had the highest correlation coefficient at the 7-month scale. The strongest time-lag effect for cropland and grassland was seen at 7 months, while the strongest time-lag effect for woodland was seen at 6 months. Woodland had a lower time-lag effect than grassland at different scales. The research results are significant for their use in aiding the scientific response to drought disasters and making decisions for climate change precautions.

Flash droughts (FDs) are rapid droughts that occur over a short period caused by severe heat waves and precipitation deficiency. FDs have critically increased impacts on agriculture and natural ecosystems. We used the standardized evaporative stress ratio (SESR) to identify FDs during the growing season in a historical simulation and under 4 future shared socio-economic pathway scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP5-8.5) of the CMIP6 model based on actual and potential evapotranspiration. Arid regions were classified based on the aridity index (AI), and the frequency, duration, and intensity of FDs were compared and analyzed for different arid regions under different future scenarios. The results showed significant regional differences in global FD events, where the frequency was 10~30%, and the duration was primarily 30~35 d in most areas. FD intensity was mainly moderate, and severe FDs and ranges of FDs under the 4 future scenarios were similar. In addition, the frequency and duration of FDs were slightly higher in humid regions under different scenarios. The proportion of different FD intensities in humid regions was much higher than in other arid regions. Finally, FD regions were divided into Governance, Concern, and Prevention Areas based on the overlayed FD characteristics under the 4 future scenarios, contributing to regionally varied approaches and solutions for the response and prevention of drought disasters.