## 2 Materials and Methods
### Data  
#### 2.2.1 Precipitation and Satellite Images  
The precipitation data used as a reference in this study were obtained from Global Precipitation Measurement (GPM) version 6 dataset [45], which uses the Integrated Multi-satellite Retrievals for GPM (IMERG) algorithm at a spatial resolution of 0.1\({}^{\circ}\) (11 km). The precipitation product from GPM was improved after the calibration process for the study period from December 2021 to early February 2022. According to the rainfall time series as shown in Figure 2, the study period can be divided into two different periods (Figure 2): (1) the first period (22 December 2021-15 January 2022) as the preflooding period and (2) the second period (27 January 2022-2 February 2022) as the after-flooding period, which shows the destructive impacts from the consecutive rainfall events, especially the major event on 17 January to 22 January 2022. For the first period, there is an event (maximum hourly rate > 12 mm/h) on 31 December 2021 that could also induce extensive flooding in the study area.  
This study uses high-resolution products from Landsat-7/8/9 and Sentinel-1 and -2 for spatiotemporal analysis of the surface water areas. All the NASA Landsat-7/8/9 multispectral images provide visible and near-infrared (VNIR), shortwave infrared (SWIR), thermal infrared (TIR), and quality assessment (QA) bands. This study uses the Green and SWIR bands to calculate the modified normalized difference water index (mNDWI) [46] to identify the water surface from the land surface. It is noted that the \"strip\" issue in Landsat-7 data was not addressed due to higher cloud coverage. All of the mNDWI layer was processed to 30 m spatial resolution. The QA band removes low-quality observations such as clouds, cirrus, and cloud shadow to minimize their impacts on the water surface identification. The 30 m mNDWI was also calculated and processed from the Sentinel-2 images obtained from the European Space Agency (ESA) mission with two twin polar-orbiting satellites as a constellation (Sentinel-2A and Sentinel-2B), with a global 5-day revisit time.  
For the synthetic-aperture radar (SAR) images, we used Sentinel-1 ground-range-detected (S1_GRD) images at C-band (central frequency of 5.404 GHz) with a global 6- or 12-day revisit time. Sentinel-1 is a mission of ESA with twin satellites (Sentinel-1A and Sentinel-1B) as a constellation. In this study, we only use the vertical transmit, vertical receive (VV) backscatter data with 10 m spatial resolution, as suggested by [47; 48]. These data were preprocessed (e.g., thermal noise removal, radiometric calibration, and terrain correction) with the Sentinel-1 Toolbox and processed to 30 m resolution. The characteristics of the satellite images from Landsat-7/8/9 and Sentinel-1/2 are summarized in Table 1.  
Figure 2: Time series of the rainfall intensity and satellite-available dates (solid dots show the images with lower cloud coverage used in the study) in the study area (rainfall data source: GPM).  
As shown in Figure 2, a total of 10 satellite images were acquired at the following names and dates, respectively: Sentinel-1 (22 December 2021), Landsat-8 (24 December 2021), Sentinel-2 (26 December 2021), Landsat-9 (1 January 2022), Landsat-7 (1 January 2022), Sentinel-1 (3 January 2022), Sentinel-1 (3 January 2022), Sentinel-1 (3 January 2022), Sentinel-1 (27 January 2022), Sentinel-2 (30 January 2022), and Landsat-9 (2 February 2022).