# The Influence of Glacier Mass Balance on River Runoff in the Typical Alpine Basin
## 2 Data and Methods
### Datasets  
Sentinel-1A satellite was launched on 3 April 2014. It is the first satellite developed by the European Commission and the European Space Agency for the Copernicus Global Earth Observation Project [47]. It is mainly used for marine environmental monitoring, Arctic sea ice monitoring, and surface deformation monitoring. It has four working modes, SM, IW, EW, and WV [48]. The spatial resolution of the satellite data is 5 m \(\times\) 20 m [49], the temporal resolution is 12 days, and the period can be shortened to 6 days with the  
Figure 1: Overview of the study area. co-operation of the double star. It provides a rich and effective data source for monitoring glacier elevation [50]. This paper uses Sentinel-1A data from 12 February and 24 February 2022, to obtain InSAR DEM. The NASA DEM was modified by the SRTM (Shuttle Radar Topography Mission) for processing, elevation controlling, gap filling, and merging with data from the original SRTM production to improve elevation accuracy and fill in missing elevation data [51]. The SRTM dataset is composed of two band DEMs, C-band (5.6 GHz) and X-band (9.7 GHz), with widths of 225 km and 50 km, respectively [52]. In this paper, C-band NASA DEM (resolution is 30 m) is used as the 2000 elevation reference DEM. Due to the reduced strip width and large data gaps in the X-band SRTM [53], only the X-band DEM (resolution is 30 m) is used in this paper as the base data for GSE change error correction. ALOS-PALSAR DEM has been used in the field of terrain analysis because of its high resolution, visualization of fine terrain, and low influence on surface cover [25]. It is currently the highest resolution and most widely distributed free DEM [54]. PALSAR has several observation modes, including FBS, FBD, and PLR [55]. In this paper, ALOS DEM (resolution is 12.5 m) is chosen as the reference DEM in 2009. Due to the complex topography and high altitude of the Tailan River, remote-sensing meteorological data have become the main source for obtaining climate data in this area. ERA5 (ECMWF Reanalysis v5) is published by the ECMWF (European Centre for Medium-Range Weather Forecasts) [56]. Its dataset has been recorded since 1981 and provides an accurate description of past climate [57], which can be used to study glacier change with climate response. GLDAS (Global Land Data Assimilation System) is a land surface model that provides 30 meteorological parameters including precipitation, temperature, soil moisture, and solar radiation [58]. It uses satellite data and ground-based observations to infer global land surface hydrological processes with a spatial resolution of 0.25\({}^{\circ}\). Due to the complex geographical location of the Tailan River basin, obtaining measured data is challenging. Therefore, this study utilizes GLDAS runoff data from 2000 to 2022 as an adjunct to investigate glacier runoff change patterns. The RGI 6.0 (Randolph Glacier Inventory 6.0) database, released in July 2017, was used in this paper for glacier profile confirmation and assisted estimation of glacier area in the study area [59]. Glacier thickness dataset version 3.1.0 was international standardized glacier thickness dataset. It was distributed by the World Glacier Monitoring Service on 6 October 2019, and collected from raw and remotely sensed observations by NASA's Operation IceBridge [60]. This paper uses the glacier thickness dataset in the study area for the removal of elevation change abnormal values. ICESat-2/ATLAS is a new generation of laser altimetry satellite launched by NASA after ICESat/GLAS. The laser footprint of ICESat-2 has a diameter of approximately 17 m with a spacing of 0.7 m. The horizontal accuracy is better than 6.5 m, and the nominal vertical accuracy is 0.1 m [23]. ICESat-2's mission includes precise measurements of terrain and vegetation canopy heights, achieving a surface accuracy of \(\pm\)13.8 m. Data collection is concentrated during the autumn and winter seasons when vegetation interference is minimal, ensuring the reliability of the data.