Developing integrated ecological indicators for hydropower efficiency: a centralized DEA approach incorporating water resource reallocation and nonseparable variables

Effective water reallocation is essential for sustaining performance in centralized hydroelectric systems under increasing climate variability. However, most prior DEA-based assessments emphasize plant-level efficiency and assume separable inputs and outputs, which limits their value for system-wide water–energy planning under centralized governance. To address this gap, this study develops a centralized data envelopment analysis (DEA) model. The model constructs integrated ecological indicators that treat water inputs and electricity outputs as nonseparable. The unique contribution of this framework lies in its ability to capture the joint production of water and energy. It provides system-level indicators that link seasonal water reallocation strategies to electricity generation performance. The model supports water resource reallocation planning by maximizing system-wide water–energy efficiency under centralized management. It is applied to 23 hydroelectric systems in Taiwan across three seasonal scenarios—wet, dry, and annual—to evaluate spatial and temporal efficiency adjustments. The results show that optimal water reallocation increases electricity output by 1.83% during the wet season and limits output losses to 4.12% during the dry season. Over the full year, the model improves overall system efficiency, reducing total discharge volume by 1.05% and increasing effective storage by 3.13%. These findings show that indicator-based evaluation can support centralized water–energy planning across seasons. The resulting indicators are intended to inform ecological resource management, including seasonal storage–release balance and scenario-based downstream-release considerations. • Integrated ecological indicators are developed for hydropower system efficiency. • A centralized DEA model with nonseparable variables is proposed. • Seasonal reallocation of water resources is analyzed across 23 hydropower systems. • Indicators reflect the water–energy nexus under centralized planning scenarios. • Optimal reallocation limits electricity output losses to 4.1% during the dry season.