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ARS Home » Plains Area » Bushland, Texas » Conservation and Production Research Laboratory » Soil and Water Management Research » Research » Publications at this Location » Publication #144320

Title: PREDICTING DAILY NET RADIATION USING MINIMUM CLIMATOLOGICAL DATA

Author
item IRMAK, S - UNIV. OF FLORIDA
item IRMAK, A - UNIV. OF FLORIDA
item JONES, J - UNIV. OF FLORIDA
item Howell, Terry
item JACOBS, J - UNIV. OF FLORIDA
item ALLEN, R - UNIV. OF IDAHO
item HOOGENBOOM, G - UNIV. OF GEORGIA

Submitted to: Journal of Irrigation and Drainage Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 3/25/2003
Publication Date: 8/1/2003
Citation: IRMAK, S., IRMAK, A., JONES, J.W., HOWELL, T.A., JACOBS, J.M., ALLEN, R.G., HOOGENBOOM, G. PREDICTING DAILY NET RADIATION USING MINIMUM CLIMATOLOGICAL DATA. JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING. 2003. V. 129(4). p. 256-269.

Interpretive Summary: Net radiation (Rn) represents the net balance of short-wave radiation received and reflected and incident and emitted long-wave radiation. It is an important parameter in computing crop water use and is often a tedious and error prone process. This paper evaluated two proposed simpler procedures and evaluated them against the current accepted world standard Rn estimation procedure. The predicted Rn values using the simpler procedures for a day were in close agreement to the more complex estimation procedures. It was concluded that both of the proposed equations are simple, reliable, and practical to predict daily Rn. The significant advantage of the these equations are that they can be used to predict daily Rn with a reasonable precision when measured solar radiation data are not available. This is a significant improvement and contribution for engineers, agronomists, climatologists, and others when working with National Weather Service climatological data sets that only record Tmax and Tmin on a regular basis.

Technical Abstract: Net radiation (Rn) is a key variable for computing reference evapotranspiration and is a driving force in many other physical and biological processes. The procedures outlined in the Food and Agriculture Organization Irrigation and Drainage Paper No. 56 for predicting daily Rn have been widely used. The objectives of this study were to develop two alternative equations to reduce the input data requirements and computation intensity of the FAO 56 Rn procedures to predict daily Rn and to evaluate the performance of these equations in the humid regions of south-east and two arid regions in the U.S. Two equations were developed-- the first equation [measured Rs-based (Rs-M)] required measured maximum and minimum air temperatures (Tmax and Tmin), measured solar radiation (Rs), and inverse relative distance from Earth to Sun (dr) while the second equation [predicted Rs-based (Rs-P)] required Tmax, Tmin, mean relative humidity (RHmean), and predicted Rs. The performance of both equations was evaluated in different locations including humid and arid, and coastal and inland regions (Gainesville, FL; Miami, FL; Tampa, FL; Tifton, GA; Watkinsville, GA; Mobile, AL; Logan, UT; and Bushland, TX). The daily Rn values predicted by the Rs-M equation were in close agreement with those obtained from the FAO 56 Rn in all locations and for all years evaluated. The performance of the Rs-P equation was quite good when compared with the measured Rn in Gainesville, Watkinsville, Logan, and Bushland locations and provided similar or better daily Rn predictions than the FAO 56 Rn procedures. The Rs-P equation was able to explain at least 79% of the variability in Rn predictions using only Tmax, Tmin, and RH data for all locations.