## 1 Introduction  
Drought is one of the most destructive natural disasters. It has brought huge adverse effects to human social life, industrial and agricultural production and the ecological environment [1]. Global warming and increasing human activities have resulted in the increased number and severity of droughs all over the world year by year [2]. There are four main types of droughs, namely agricultural drought, meteorological drought, socio-economic drought and hydrological drought [3, 4], causing a comprehensive effect on the environment and society in the evolution of drought. Therefore, accurate monitoring and prevention of drought is of great significance to the development of human society. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) missions have been implemented successively. Their main goal is to detect the Earth's time-variable gravity field in the medium and long wavelength parts [5]. The GRACE time-variable gravity field model has played an extremely important role in hydrological applications [6; 7; 8]. The basin area and runoff of the Amazon River is the largest in the world. The famous Amazon Rainforest is located in this basin, which covers an area of 5.5 million km\({}^{2}\), spans eight countries and occupies 1/3 of the world's rainforest area and 20% of the world's forest area [9]. It has a huge influence on regional precipitation (PPT), runoff, evapotranspiration (ET) and even the global climate [10]. The Amazon River basin (ARB) plays an important role in global water vapor exchange [11], and it is also an important composition of the global water cycle and terrestrial ecosystems [12; 13]. Extreme climate has caused frequent droughts in the ARB [4]. Therefore, the ARB drought assessment aids the research on regional and global climate change. Many scholars have detected and analyzed the ARB droughts by using GRACE data. For instance, [PERSON] et al. [14] quantified the 2005 extreme drought event in the ARB using GRACE monthly gravity solutions, and the results were verified by PPT data and water level data. [PERSON] et al. [15] used GRACE satellites to detect the same drought in the ARB, and found that the water storage was 70% lower than the average level in previous years. [PERSON] et al. [16] reproduced the transition process from the 2010 extreme drought to the 2012 flood by comparing GRACE terrestrial water storage change (TWSC) data with PPT data. The GRACE TWSC and PPT data had the same spatial and temporal distribution and variation. [PERSON] et al. [13] investigated the interannual and interdecadal GRACE TWSC from 1980 to 2015. They found that the droughts have occurred frequently since 2010, and their severity was getting worse. [PERSON] et al. [17] conducted a quantitative assessment of the drought characteristics from 2003 to 2013 based on GRACE-derived water storage deficit, and the results were consistent with meteorological drought data. However, in the applications of satellite gravimetry data, there is an 11-month data gap between GRACE and GRACE-FO missions, which inevitably caused a discontinuity in drought research of ARB [18; 19]. Since the Swarm mission period just covers the above gap, its satellites are equipped with gravity detection equipment, such as accelerometer, Global Navigation Satellite System receiver, etc. [20; 21]. Many scholars have discussed the possibility of using the Swarm model to detect time variable gravity signals. The results indicate that the time variable gravity signals of Swarm model are mainly concentrated in the long wave part, and the Swarm model has the possibility of monitoring the regional TWSC [22; 23; 24; 25]. Some scholars used the Swarm model to detect TWSC and droughts in the ARB [19; 25; 26], and the main purpose of their studies is to use the Swarm model to fill the gap between GRACE and GRACE-FO missions.