Spatiotemporal Dynamics and Explanatory Factors of Ecological Quality in the Baihetan Reservoir Drawdown Zone (2016–2025): An Expert-Guided PCA-Based Assessment Approach

As the world’s second-largest hydropower station, the reservoir drawdown zone of Baihetan Hydropower Station faces severe ecological disturbance from periodic water level fluctuations; exploring its ecological impact patterns is critical for global reservoir drawdown zone ecological restoration and assessment. Taking the drawdown zone of Baihetan Hydropower Station as the study area, an expert-guided PCA-based assessment framework is proposed: 13 key ecological indicators were screened through expert consultation to ensure ecological relevance and data reliability, followed by objective Principal Component Analysis (PCA) for indicator decorrelation, dimensionality reduction, and comprehensive scoring. Combined with spatiotemporal hot–cold spot and overlay analysis, spatially explicit ecological assessment maps were generated using multi-temporal remote sensing images (covering low-water exposure (July flood season), post-flood impoundment (November), and high-water stabilization (December) periods), spanning a continuous decade from 2016 to 2025 to construct a complete 10-year spatiotemporal cube, which include a 5 km buffer along the mainstream of the Jinsha River. Main results: (1) After the 2021 commissioning, comprehensive ecological quality declined overall, with weakened seasonal ecosystem responses, significant homogenization, and an oscillating cold spot-dominated pattern without stable high-quality hot spots. (2) Marked longitudinal differentiation existed: downstream had better, more stable ecological quality, while upstream showed declining quality and greater hot–cold spot variation associated with reservoir operation and anthropogenic disturbances. (3) Spatiotemporal active points only aggregated briefly in November, indicating autumn–winter impoundment inhibited ecological activity. (4) The first principal component explained 85.52% of variance, with VIIRS nighttime lights, wetness and NDVI as the dominant contributing indicators. The temporal changes reported here are associations with the commissioning of the hydropower station and are not presented as demonstrated causal effects. This study provides a transferable framework for the ecological assessment of hydropower-driven vulnerable areas worldwide.