Abstract

Net radiation Rn is the main driving force of evapotranspiration ET and is a key input variable to the Penman-type combination and energy balance equations. However, Rn 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 ETo and ETr, respectively and investi- gates how climate, season and cloud cover influence the impact of the Rn models on ETo and ETr. Datasets from two locations Clay Center, Nebraska, subhumid; and Davis, California, a Mediterranean-type semiarid climate were used. Rn values computed from the 19 models were used in the standardized ASCE-EWRI Penman-Monteith equation to estimate ETo and ETr on a daily time step. The influence of seasons on the estimation of Rn and on estimated ETo and ETr was investigated in winter November-March and summer May-September months. To analyze the influence of clouds on the impact of Rn models, relative shortwave radiation Rrs was used as a means to express the cloudiness of the days as: 0 Rrs0.35 for completely cloudy days; 0.35 Rrs0.70 for partially cloudy days; and 0.70 Rrs1.0 for clear sky days. The performances of Rn 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 Rn on estimated ETo and ETr was related to the methods used to calculate atmospheric emissivity rather than methods used to calculate clear sky solar radiation Rso or cloud adjustment factor f. Rn models that used average air temperature to compute 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 Rso, f, and , there were significant seasonal variations in performances of models that calculated as a function of actual vapor pressure of the air ea. 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 as a function of ea performed better under completely cloudy days than on other days, more so at Clay Center. Methods used to calculate have a significant impact on the Rn 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 Rn relative to the ASCE-EWRI Rn method in subhumid and semiarid climates similar to Clay Center, Neb. and Davis, Calif.

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