## 5 Conclusions
Furthermore, enhancing water utilization efficiency within agricultural areas and implementing water-conserving irrigation practices are strategic measures aimed at mitigating the detrimental impacts of flash droughts on crop health and productivity. **Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/atmos15080886/s1](https://www.mdpi.com/article/10.3390/atmos15080886/s1)]([https://www.mdpi.com/article/10.3390/atmos15080886/s1](https://www.mdpi.com/article/10.3390/atmos15080886/s1)), Figure S1. (a) Correlation coefficients between daily SM of 0-10 cm for SMCII.0 and daily SM of 0-7 cm for ERA5, (b) correlation coefficients between daily SM of 0-30 cm for SMCII.0 and daily SM of 0-28 cm for ERA5, and (c) Correlation coefficients between daily SM of 0-100 cm for SMCII.0 and daily SM of 0-100 cm for ERA5; Figure S2. Spatial trends of (a,b) CSIF, (c,d) GOSIF, and (e,f) GPP during 2001-2020. Significance tests were conducted using \(p<0.1\); Figure S3. Annual changes in area proportions of flash droughts based on (a) ERA5 with 0-28 cm SM and based on (b) SMCII.0 with 0-30 cm SM; Figure S4. The area (grid) proportions of flash droughts based on 0-28 cm SM of ERA5 data during 1981\(-\)2020; Figure S5. Response frequency of CSIF, GOSIF, and GPP to Case 1, Case 2, and Case 4 flash droughts in the main southern agricultural areas of China during 2001\(-\)2020; Figure S6. The same as Figure S5 but for the response time; Figure S7. Temporal evolution of CSIF, GOSIF, and GPP during flash droughts for (a) total, (b) Case 1, (c) Case 2, and (d) Case 4 events in the UYR during 2001\(-\)2020. In each subplot, the left \(y\)-axis of represents the SM percentile, whereas the right \(y\)-axis denotes the standardized anomalies of the vegetation indices. Lines indicate the median values, and shading denotes the interquartile range. Additionally, the total number of flash drought events at the grid scale is labeled as \"\(n\)\"; Figure S8. The same as Figure S7, but for the MYR; Figure S9. The same as Figure S7, but for the SCR; Figure S11. Temporal evolution of (a) P-PET, (b) T\({}_{\text{max}}\), (c) VPD, (d) CSIF, (e) GOSIF, and (f) GPP during 2019 flash droughtsin the main southern agricultural areas of China. In each subplot, the left \(y\)-axis of represents the SM percentile, whereas the right \(y\)-axis denotes the standardized anomalies of the vegetation indices. Lines indicate the median values, and shading denotes the interquartile range. A total of 727 grids had a flash drought start in the 42 nd pentad of 2019. POY: pentad of year. Conceptualization, Y.Z. ; methodology, Y.Z., F.L. and T.L. ; software, Y.Z. and F.L. ; validation, F.L. and Y.Z. ; formal analysis, Y.Z. and F.L. ; investigation, F.L. and T.L. ; data curation, Y.Z. and T.L. ; writing--original draft preparation, Y.Z. ; writing--review and editing, Y.Z. and C.C. ; visualization, F.L. and Z.L. ; supervision, C.C. ; funding acquisition, Y.Z. All authors have read and agreed to the published version of the manuscript. This study was jointly supported by the MOE (Ministry of Education in China) Project of Humanities and Social Sciences (19 YJCZH259), and the National Natural Science Foundation of China (41907384), and the Qinglan Project funded by universities in Jiangsu Province (2023). Not applicable. The data that support our research findings are available from the corresponding author on request. The data are not publicly available due to privacy. We are very grateful to the anonymous reviewers for their constructive comments and thoughtful suggestions. The authors declare no conflict of interest.