Abstract: Investigating the spatiotemporal heterogeneity of inundation dynamics in floodplain lakes and its impact on hydrological drought quantification is of great significance for enhancing the management practices of floodplain lake ecosystems and the ability to defend against flood and drought disasters. In this study, multi-source remote sensing data and image fusion technology were employed to construct continuous high-spatiotemporal-resolution inundation data in the Poyang Lake from 2000 to 2023, thereby revealing the spatiotemporal heterogeneity characteristics of the lake inundation dynamics. Subsequently, drawing on the principle of the Standardized Precipitation Index (SPI), a standardized hydrological drought index based on the lake inundation area was proposed, and based on this, the change characteristics of hydrological drought in Poyang Lake were analyzed. The results show that: ① The spatiotemporal heterogeneity of inundation dynamics in the Poyang Lake is prominent. The inundation area in the main lake region and the peripheral dished lake region exhibits not only asynchronous intra-annual fluctuations, but also opposite inter-annual change trend. ② Hydrological drought index calculated from water level observations at specific hydro-stations has substantial uncertainties when quantifying the overall hydrological drought of the Poyang Lake, whereas the calculated hydrological drought index based on lake inundation area is more deterministic and scientific validity. ③ The hydrological drought in Poyang Lake displays complexity in both seasonal distribution and spatial pattern. Extreme droughts mainly occur from April to October within a year, and are more likely to occur in the main lake region. The combination of remote-sensing big data and image fusion technology can achieve a refined quantitative analysis of hydrological drought in large floodplain lakes, and promote the protection and utilization of lake resources as well as the prevention and control of flood and drought disasters.