## 7 Conclusions  
To obtain the continuous long-term drought index series in the ARB, we combined GRACE, GRACE-FO and Swarm models to construct a set of 18-year uninterrupted TWSC-based drought index series (GRACE/Swarm-DSI). We used the GTCH and least square method to fused the TWSC results from six GRACE solutions to improve the reliability of GRACE TWSC results, and combined fused TWSC results and Swarm data to construct GRACE/Swarm-DSI in our study. Subsequently, we used the correlation coefficients and NSEs between GRACE/Swarm-DSI and four drought indices to measure the reliability of GRACE/Swarm-DSI, and GRACE/Swarm-DSI was used to detect and characterize the drought events in the ARB during 2003 and 2020. The results show that GRACE/Swarm-DSI has the good consistent with SCPDSI, SPEI-3, SPEI-6, SPEI-12, and there are 11 drought events in the ARB during the study period. Among these drought events, the drought event from November 2015 to December 2016 is the most severe, covering 66.56% of the entire basin area and the drought severity is \(-\)9.63. PPT is the main factor affecting drought disasters, while ET only plays an auxiliary role, and the response time of GRACE/Swarm-DSI to PPT is about 1-2 months in most regions of ARB.  
Our results indicate that Swarm data have the potential to monitor and characterize the droughts in the ARB. They provide a certain reference for filling the gap between GRACE and GRACE-FO missions in the hydrological research.  
Conceptualization, L.C.; methodology, L.C. and X.W.; validation, L.C. and Z.H.; formal analysis, M.Y. and X.L.; investigation, L.C.; resources, C.Y.; data curation, M.Y.; writing--original draft preparation, L.C. and C.Y.; writing--review and editing, X.W. and C.Y.; supervision, M.Y.; funding acquisition, Z.H. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (42004013), Guangdong Basic and Applied Basic Research Foundation (2022A1515010469), Guangzhou Science and Technology Project (202102020526), State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project (SKLGP2021Z022); the Sichuan Provincial Science and Technology Department Project (2020Y0115).  
Data Availability Statement: GRACE RL06 data from CSR, GFZ, JPL, and ITSG and Swarm data from COST-G: [[http://icgem.gfz-potsdam.de/series](http://icgem.gfz-potsdam.de/series)]([http://icgem.gfz-potsdam.de/series](http://icgem.gfz-potsdam.de/series)) (accessed on 10 April 2022); GPCC precipitation data: [[https://psl.noaa.gov/thredds/catalog/Datasets/gproc/catalog.html](https://psl.noaa.gov/thredds/catalog/Datasets/gproc/catalog.html)]([https://psl.noaa.gov/thredds/catalog/Datasets/gproc/catalog.html](https://psl.noaa.gov/thredds/catalog/Datasets/gproc/catalog.html)) (accessed on 10 April 2022); ET gridded data: s[[ftp://hydras.ugent.be](ftp://hydras.ugent.be)]([ftp://hydras.ugent.be](ftp://hydras.ugent.be)) (accessed on 10 April 2022); SPEI data: ([[http://spei.csic.es/](http://spei.csic.es/)]([http://spei.csic.es/](http://spei.csic.es/))) (accessed on 10 April 2022); SCPDSI data: [[https://crudata.uea.ac.uk/cru/data/drought/](https://crudata.uea.ac.uk/cru/data/drought/)]([https://crudata.uea.ac.uk/cru/data/drought/](https://crudata.uea.ac.uk/cru/data/drought/)) (accessed on 10 April 2022).  
We are grateful to CSR, GFZ, JPL and ITSG for providing the GRACE solutions; to COST-G and ASU for providing the Swarm solutions; to the Goddard Space Flight Center for providing the GLDAS-2.1 data; to the GPCC for providing the precipitation products; to the Climatic Research Unit at university of East Anglia for providing SCPDSI data, to Vicente-Serrano S.M. and Begueria S for providing SPEI database and to the Global Land Evaporation Amsterdam Model for providing the ET data.  
The authors declare no conflict of interest.