Ecological Health Assessment of the Yuejiang River in Sichuan Province Based on the PCA–Entropy Weight Method

Vollständiger Abstract

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River-health assessment in small rural watersheds requires the integration of multiple environmental indicators, yet correlated variables may be repeatedly represented when they are weighted independently. This study evaluated the ecological health of the Yuejiang River in Dongpo District, Meishan City, Sichuan Province, for 2011, 2018, and 2024 using a principal component analysis (PCA)–entropy weighting framework. Fourteen effective indicators represented riparian habitat, climate–hydrology, water environment, human disturbance, and water quality. Water-quality data for 2011 and 2018 were treated as monitored regional background conditions, whereas continuous reach-scale observations were unavailable for 2024 and scenario-constrained regional background inputs were therefore used. PCA retained four components that explained 95.94% of the total variance, and the resulting combined weights were used to calculate the River Health Index (RHI). Mean RHI values increased from 0.290 in 2011 to 0.578 in 2018 and 0.634 in 2024. In 2024, 83.92% of the mapped assessment area was classified as Good and 16.08% as Moderate. High PCA loadings and combined weights are interpreted as statistical contributions within the assessment framework, rather than as evidence of direct ecological causation. The results support temporal comparison and identification of relatively weak reaches, while the 2024 findings should be interpreted as conditional on the adopted water-quality background scenario.