Uncertainty analysis of evapotranspiration models is essential in hydrological modeling, particularly given the limited use of process-based models and ensemble algorithms for evapotranspiration estimation. In this study, the performance and uncertainty in two simplified process-based models (BTA and BTA-theta), and three classical ensemble algorithms (adaptive boosting, random forest, and extreme gradient boosting) in estimating evapotranspiration are assessed across various ecosystems. The results show that: (a) the BTA-theta model outperforms the BTA model across all ecosystems, and the int...
