## 6 Conclusions  
This study assessed the vegetation vulnerability for the base period (2010-2019), near future period (2020-2059), and distinct future period (2060-2099) in the MRB, and then analyzed the transition of the vegetation vulnerability of different periods by stochastic matrix to point out the high vegetation vulnerability areas. The conclusions are as follows:  
1. The vegetation vulnerability in MRB for the base period showed a decreasing trend from east to west. The high-high cluster had high vulnerability, and the low-low cluster had low vulnerability.
2. For the near future period and distinct future period, vegetation vulnerability was highest upstream, followed by the downstream, and the lowest midstream. The vegetation vulnerability showed a high-high cluster in the east, and a low-low cluster in the midstream and downstream.
3. The upstream of the MRB will experience the highest vegetation vulnerability increase due to intense human activity and less protection. The vegetation vulnerability decreased only under the SSP1-2.6, therefore, the MRB should control population growth, actively respond to climate change, and take the sustainable development path with low-emission to promote the sustainable vegetation in the MRB.  
[PERSON] and [PERSON] designed the paper. [PERSON] conducted the data processing and statistical analysis and wrote the paper. [PERSON] and [PERSON] made great efforts in writing and figure optimization. All the authors contributed to the paper revision. All authors have read and agreed to the published version of the manuscript.  
This research was funded by a project commissioned by the National Key R&D Program of China \"Integrated Management for Sustainable Utilization of Water Resources in East Africa Great Lakes Basins\" (No. 2018 YFE0105900).  
The ERA5-Land monthly averaged data from 2010 to 2019 are from the European Centre for Medium-Range Weather Forecasts ([[https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5](https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5)]([https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5](https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5)), accessed on 10 February 2023). The CMIP6 data are also from the European Centre for Medium-Range Weather Forecasts ([[https://cds.climate.opernicus.eu/cdsapp#](https://cds.climate.opernicus.eu/cdsapp#)]([https://cds.climate.opernicus.eu/cdsapp#](https://cds.climate.opernicus.eu/cdsapp#))!/dataset/projections-cmip6?tab=form, accessed on 13 February 2023). The STRM data are from the Shuttle Radar Topography Mission ([[http://srtm.csi.cgi.org](http://srtm.csi.cgi.org)]([http://srtm.csi.cgi.org](http://srtm.csi.cgi.org)), accessed on 20 February 2023). The land use data are from Land Use Harmonization 2 ([[https://luh.umd.edu/data.shtml](https://luh.umd.edu/data.shtml)]([https://luh.umd.edu/data.shtml](https://luh.umd.edu/data.shtml)), accessed on 3 March 2023). The population data are from WorldPop ([[https://hub.worldpop.org/project/categories?id=18](https://hub.worldpop.org/project/categories?id=18)]([https://hub.worldpop.org/project/categories?id=18](https://hub.worldpop.org/project/categories?id=18)), accessed on 6 March 2023) and Our World in Data ([[https://ourworldindata.org/population-growth](https://ourworldindata.org/population-growth)]([https://ourworldindata.org/population-growth](https://ourworldindata.org/population-growth)), accessed on 6 March 2023). The vegetation ecological water demand data are from the article [25].  
The authors would like to thank the European Centre for Medium-Range Weather Forecasts and NASA for their valuable data.  
The authors declare no conflicts of interest.