## 5 Conclusions  
This study presents the development and application of the VMFDI, a novel drought index designed to provide a high-spatial-resolution (1 km) and monthly temporal-scale monitoring of drought conditions in the Yellow River Basin. By integrating a three-dimensional spatial distance model with key drought-related factors (VPD, SM, and SIF), this study offers a comprehensive tool for assessing regional drought dynamics, particularly in agroecosystems. The key findings of this study are as follows: (1) The VMFDI demonstrates superior sensitivity and accuracy in detecting regional drought conditions compared to existing drought indices such as the SPEI, GRACE-DSI, and individual drought indicators (VPD, SM, and SIF). Its 1 km spatial resolution and monthly scale allow for a more detailed and timely monitoring of ecosystem drought, making it a valuable tool for both research and practical applications in drought risk management. (2) An analysis of the VMFDI series reveals significant spatiotemporal variability in drought severity across the Yellow River Basin from 2003 to 2020. Seasonal trends indicate that the basin experienced drier conditions in winter and wetter conditions in spring, summer, and autumn. The areas most affected by drought are in the middle and lower reaches of the river, with seasonal shifts in the drought center observed in Shaanxi and Gansu. These findings highlight the dynamic nature of drought in the region and the importance of localized monitoring. (3) In the agroecosystem, the VMFDI effectively captures the negative impacts of drought on plant productivity, including significant reductions in the NDVI, GPP, WUE, and LAI (_p_ < 0.05). The Liang-Kleeman information flow analysis reveals that the basin and agroecosystem experienced SM-induced drought and VPD-induced drought, respectively. This study also identifies critical VPD thresholds that trigger changes in crop responses, particularly in maize and wheat systems. This information is crucial for developing targeted drought mitigation strategies to minimize crop yield losses and realize water-saving in agricultural systems. Future research could focus on refining data downscaling methods and further validating the VMFDI across diverse regions and agroecosystems. Overall, the VMFDI represents a significant advancement in drought monitoring, offering a robust and high-resolution approach for understanding regional drought dynamics. And this study offers a framework for more precise drought risk assessment by identifying key drought drivers and response thresholds, which can inform the development of early warning systems, drought mitigation strategies, and water-saving agricultural practices.  
Conceptualization, C.D.; Data curation, L.Z., S.Y., J.G. and L.S.; Formal analysis, L.Z.; Funding acquisition, C.D. and T.X.; Methodology, C.D. and L.S.; Project administration, T.X.; Supervision, T.X. and H.J.K.; Validation, R.K.; Visualization, L.Z., S.Y. and J.G.; Writing--original draft, C.D.; Writing--review and editing, C.D., T.X., R.K. and H.J.K. All authors have read and agreed to the published version of the manuscript.  
This study was jointly supported by the National Natural Science Foundation of China (No. 42192534, 42301327) and the Key Research and Development Program of Shandong Province (No. 2021 ZDSYS01) and the China Postdoctoral Science Foundation (No. 2022M711929).  
The data that support the findings of this study are available from the corresponding author upon reasonable request.  
We thank the National Tibetan Plateau/Third Pole Environment Data Center ([[http://data.tpdc.ac.cn](http://data.tpdc.ac.cn)]([http://data.tpdc.ac.cn](http://data.tpdc.ac.cn))) (accessed on 14 May 2024)and [PERSON] and [PERSON] (2019) [48] for providing the datasets of VPD and SM and GOSIF, respectively. We also thank the anonymous reviewers and editors for their helpful comments and suggestions for the manuscript.  
The authors declare no conflicts of interest.