## 6 Discussion  
We used GRACE and Swarm satellites to monitor the droughts in the ARB between 2003 and 2020 and quantified the characteristics of these droughts. However, due to the limitation of Satellite-to-Satellite Tacking in the high-low model, the Swarm model has greater errors than the GRACE model [19]. The uncertainty of TWSC results from the Swarm model in the basin is a hot spot for scientists in the world. [PERSON] et al. [60] computed the long-term trend changes of TWSC in the ARB from December 2013 to June 2017. The results show that the TWSC results from the GRACE and Swarm models have the same change trend, and the long-term change trends of the two models are close. Additionally, there is a strong correlation between TWSC results from GRACE and Swarm models (93.55%). The cycle repetition time and periodic repetition ratio of TWSC from the two models are 3.5 years and 100%, respectively. The results indicate that the Swarm model  
Figure 12: The correlation coefficients and delay months between GRACE/Swarm-DSI and PPT anomaly, ET anomaly in the ARB (The correlation coefficient results have passed the 95% confidence level).  
Figure 13: The long-term trend changes and acceleration of GRACE/Swarm-DSI in the ARB during 2003–2020 (The maximum correlation coefficient results in (**a**) have passed the 95% confidence level).  
is fully suitable for hydrological research in the ARB. [PERSON] et al. [19] also used the GRACE and Swarm models to calculate TWSC results in the ARB from December 2013 to May 2020. They found that the TWSC results from two models have good spatiotemporal consistency. [PERSON] et al. [25] suggested that the TWSC time series in the ARB from Swarm and GRACE/GRACE-FO are very close, and the correlation between the two series is 0.95. Therefore, it is feasible that GRACE, GRACE-FO and Swarm data were combined to construct a combined drought index to characterize droughts in the ARB.  
Regarding the causes of drought in the ARB, [PERSON] et al. [56] explained that the three severe drought events in the ARB in 2005, 2010 and 2015 were mainly caused by extreme climate. The severely sufficient PPT in most regions of ARB during 2005 and 2015 aggravated the drought severity. It is consistent with our results that PPT is the most important factor affecting drought events. However, although the frequency of droughts in the ARB has increased since 2000, there is a wetter trend in this region [13; 61]. Only in the southeast ARB is there a significant negative change trend (Figure 9a), and the trend may be due to the influence of extreme drought in the northeast of Brazil [62; 63]. In addition to climate change, human activity also has an influence on the formation of drought in the ARB. [PERSON] et al. [64] indicated that deforestation is an important cause of the runoff change in the ARB. The runoff changes directly affected the soil moisture, and the soil water deficit led to the occurrence of drought [29]. However, it is difficult to assess the human-induced TWSC. Therefore, how to obtain the long-term time series of human-induced TWSC with high temporal resolution is the key to studying the influence of human activity on the drought.