Since Eqs. (1)–(4) present significant nonlinear parameter-effects (PE), the bias measures should be used to identify parameters that are responsible for the nonlinear behavior (% bias > 1%). The largest bias is given by Eq. (3) (Chung–Pfost). Another important result is that the inclusion of a third parameter (c) in the Henderson equation, which originated the Henderson–Thompson equation, implies significant nonlinear behavior. Since this parameter is empirical, a reparameterization could be considered in order to