In this study, two hybrid residual deep learning models coupled with physical knowledge are proposed for improving daily transpiration (Ec) estimation. A Hybrid-Physics-Data-Residual Learning (HPDRL) model is constructed by mixing a Hybrid-Physics-Data (HPD) model with a Physics-based Residual Learning (PRL) model. To this purpose, the HPD model is first formed by adding a complementary physical variable (EcPHY), which is generated by a recently presented physics-based Ec model (hereafter "BTA-& psi;"), to a deep learning (DL) model along with driving variables to regress Ec. Then, the PRL mod...
