The soil-water balance approach of irrigation scheduling is considered one of the most reliable and essential component of crop water management in modern-day agriculture. Irrigation scheduling using this approach employs the measurement of various parameters and the application of empirical equations for the computation of reference evapotranspiration (ET_o), determination of crop evapotranspiration (ET_c) and the subsequent development of crop coefficient (K_c).  The variation in environmental factors (particularly relating to weather and soil) across localities has necessitated the need for the determination of local variables for the computation of ET_o, ET_c, and K_c. Various ET_o estimation models have been proposed, among which is the generally accepted Standardized Reference Evapotranspiration Equation (SREE) developed by the ASCE. Owing to the complexity of the SREE and the huge dependence on a host of weather variables, it could be of interest to compare findings with other simpler ET_o models in a given locality. This study was aimed at estimating and comparing ET_o measured by the SREE and other simpler models (such as Turc, Priestley and Taylor, and Makkink), as well as the determination of ET_c (using cotton as a test crop) and the subsequent development of Kc for cotton crop. Weather parameters for the computation of ET_o were obtained from a standard weather station (with Bermuda grass surface), and ET_c was measured by the use of paired weighing lysimeters installed in a middle of a cotton field. Findings from this study and the application to irrigation scheduling for cotton in northeast Louisiana, mid south US, will be presented.