## 5 Conclusions  
In this study, we analyzed the characteristics of drought in Northeast China and the response of vegetation to drought using the SPI derived from high-precision daily precipitation data. The conclusions drawn are as follows:  
1. The SPI-30 index is most sensitive to drought identification. In terms of drought characteristics, the Liaohe Plain, Sanjiang Plain, and Songnen Plain experienced the most frequent, severe, and prolonged droughs in 2009 and 2011, with less severe droughs in 2018 and 2021. These findings correlate with the trends in total annual precipitation across the three plains. Spatially, drought trends were more pronounced in the northern part of the Northeast region, while drought conditions eased in the central and southern parts. 2. From the perspective of different land use types, grasslands exhibit greater overall changes and are more sensitive to drought, while wetlands show relatively slower changes and weaker responses to drought. In comparison, dry cropland and grasslands collectively experience a slightly more severe state of drought, whereas woodlands and wetlands are less severely affected. 3. Since 2008, vegetation in Northeast China has exhibited a significant greening trend. During the crop growth period, the vegetation cover of the three plains (Liaohe Plain, Sanjiang Plain, and Songnen Plain) has shown a significant increasing trend, with R\({}^{2}\) values of 0.78, 0.62, and 0.59, respectively. The correlation between the SPI and NDVI was stronger during the crop growth period. Specifically, the correlation was most significant between grassland and dry cropland and slightly weaker between woodland and wetland, and the most significant correlation was observed between the SPI and NDVI with a one-month lag. The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/su17125288/s1](https://www.mdpi.com/article/10.3390/su17125288/s1)]([https://www.mdpi.com/article/10.3390/su17125288/s1](https://www.mdpi.com/article/10.3390/su17125288/s1)), Figure S1: Run Theory concepts; Figure S2: Accuracy validation of meteorological sites and satellite precipitation data (a,b) for CLM3.5 and ERA5 daily precipitation data and (c,d) for CLM3.5 and ERA5 monthly precipitation data; Figure S3: Changes in drought duration at different time scales and trends in precipitation for the three plains, 2008-2023. (a) Liaohe Plain, (b) Sanjiang Plain, and (c) Songnen Plain; Figure S4: Spatial trends in drought duration at 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China, 2008-2023; Figure S5: Changes in drought intensity at different time scales and trends in precipitation for the three plains, 2008-2023. (a) Liaohe Plain, (b) Sanjiang Plain, and (c) Songnen Plain; Figure S6: Spatial trends in drought intensity at 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China, 2008-2023; Figure S7: Changes in drought severity at different time scales and trends in precipitation in the three plains, 2008-2023. (a) Liaohe Plain, (b) Sanjiang Plain, and (c) Songnen Plain; Figure S8: Spatial trends in drought severity at 30-, 60-, 90-, 180-, 270-, and 360-day time scales in Northeast China, 2008-2023; Figure S9: (a) Trends in average NDVI time per year, 2008-2023; (b) spatial trends in NDVI in the Northeast from 2008 to 2023, with the upper-right plot representing the percentage of raster trends, with positive trends in blue and negative trends in red; (c-e), temporal trends in NDVI for Liaohe Plain, Sanjiang Plain, and Songnen Plain, respectively. **Author Contributions: Writing--original draft, methodology, data curation, Y.Z. ; writing--review and editing, Y.L. ; software, J.S. ; writing--review and editing, Y.S. ; writing--review and editing, methodology, software, data curation, L.C. ; data curation, C.P., Y.W. ([PERSON]) and M.D. ; writing--review and editing, Y.W. ([PERSON]). All authors have read and agreed to the published version of the manuscript.