Cascade hydropower alters river hydrological regimes and threatens aquatic ecosystems, calling for robust ecological risk assessment (ERA). Conventional assessments often rigidly apply the full five-layer Driving Force–Pressure–State–Impact–Response framework, leading to indicator redundancy and unbalanced weighting. Single weighting methods also fail to reconcile expert judgment with data variability. To address these issues, we developed a three-layer (target–element–indicator) evaluation system embedding DPSIR logic without its full structure, focusing on hydrological regime, water environmental quality, and aquatic ecology with ten indicators. We used an improved group AHP-CRITIC coupling method for weighting: AHP aggregates expert judgments via geometric mean, and CRITIC integrates data variability and inter-indicator conflict. Multi-attribute utility theory normalized indicators into a unified security index, applied to four cascade stations in the middle Jinsha River using 66-year (1953–2018) hydrological and seven-year (2013–2019) in situ monitoring data. The evaluation obtained a comprehensive index of 0.71 to 0.74, which is generally safe. River connectivity loss was the primary limiting factor. Hydrological alteration was mild overall with a value of 0.139, while extreme flow decline rate variation reached a high level of 0.83. Weekly regulated stations achieved over 97% ecological flow guarantee, which is much higher than daily regulated stations. This streamlined framework improves interpretability for cascade basins and supports sustainable watershed management.