A thermal infrared remote sensing approach for groundwater discharge detection: a case study with SDGSAT-1 data in the Heihe River

River Groundwater Discharge (RGD) is a key component of the hydrological cycle in arid regions, influencing water allocation and ecosystem stability. However, reliably identifying RGD zones at regional scales with satellite thermal infrared remote sensing remains challenging due to limited spatial resolution and unstable detection methods. This study develops a Detection of River Groundwater Discharge (DRGD) approach for identifying potential RGD zones using 30 m high-resolution thermal infrared data from the SDGSAT-1 satellite. The DRGD approach consists of three modules. The first is the Land Surface Temperature (LST) retrieval module, in which LST is derived from SDGSAT-1 data using a split-window algorithm. The second module calculates the Thermal Anomaly Robustness Index (R) using a sliding-window technique constrained by land cover to quantify local thermal anomalies. The third module detects RGD zones by integrating LST, R, topographic wetness index, and normalized difference water index using the Dempster–Shafer evidence fusion technique. The DRGD approach is tested in the middle reaches of the Heihe River Basin. Results show that SDGSAT-1 LST is consistent with MODIS products, with R2>0.81 and RMSE <1.75 K. A comparison with Landsat 8 LST indicates that SDGSAT-1 preserves finer river-scale thermal variability and more localized low temperature signals. R effectively highlights cooling effects associated with RGD. The multi-source evidence fusion module identified 207 RGD pixels in the study area, achieving a spatial agreement rate of 94.1%, indicating the potential locations of the RGD zones. This study demonstrates the potential of thermal infrared remote sensing for detecting RGD in arid regions. The proposed approach offers a reliable framework supporting hydrological modeling, groundwater assessment, and watershed ecological management.