Evaluating the Impact of Daily Net Radiation Models on Grass and Alfalfa-Reference Evapotranspiration Using the Penman-Monteith Equation in a Subhumid and Semiarid Climate

摘要

Net radiation (R_n) is the main driving force of evapotranspiration (ET) and is a key input variable to the Penman-type combination and energy balance equations. However, R_n is not commonly measured. This paper analyzes the impact of 19 net radiation models that differ in model structure and intricacy on estimated grass and alfalfa-reference ET (ET_o and ET_r, respectively) and investigates how climate, season and cloud cover influence the impact of the R_n models on ET_o and ET_r. Datasets from two locations (Clay Center, Nebraska, subhumid; and Davis, California, a Mediterranean-type semiarid climate) were used. R_n values computed from the 19 models were used in the standardized ASCE-EWRI Penman-Monteith equation to estimate ET_o and ET_r on a daily time step. The influence of seasons on the estimation of R_n and on estimated ET_o and ET_r was investigated in winter (November-March) and summer (May-September) months. To analyze the influence of clouds on the impact of R_n models, relative shortwave radiation (R_(rs)) was used as a means to express the cloudiness of the days as: O≤R_(rs)≤0.35 for completely cloudy days; 0.35 ≤R_(rs)≤ 0.70 for partially cloudy days; and 0.70 < R_(rs)≤1.0 for clear sky days. The performances of R_n models showed variations at the same location and between the locations for the same model based on methods used to calculate various model parameters. The most significant impact of R_n on estimated ET_o and ET_r was related to the methods used to calculate atmospheric emissivity (e) rather than methods used to calculate clear sky solar radiation (R_(so)) or cloud adjustment factor (f). R_n models that used average air temperature to compute e and an estimated f resulted in good performances at both locations. Empirical models that assumed f= 1.0 showed poor to average performances at both locations. While model performances varied based on methods used to calculate R_(so), f, and ε, there were significant seasonal variations in performances of models that calculated e as a function of actual vapor pressure of the air (e_a). The seasonal variations in performances of these models were greater under subhumid climate at Clay Center than in semiarid climate at Davis, Calif. The models that calculated e as a function of e_a performed better under completely cloudy days than on other days, more so at Clay Center. Methods used to calculate e have a significant impact on the R_n model performance, especially in unstable climatic conditions such as at Clay Center where there are frequent and rapid changes in climatic variables in a given day and throughout the year. The results of this study can be used as a reference tool to provide practical information on which method to select based on the data availability for reliable estimates of daily R_n relative to the ASCE-EWRI R_n method in subhumid and semiarid climates similar to Clay Center, Neb. and Davis, Calif.