Vapor pressure deficit calculations and their effect on the combination equation

• Published in: Agricultural and forest meteorology Vol. 49; no. 1; pp. 55 - 80
• Main Authors: Sadler, E.John, Evans, Dean E.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 1989; Oxford Elsevier; New York, NY
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agronomy. Soil science and plant productions; AIR TEMPERATURE; Biological and medical sciences; EVAPOTRANSPIRACION; EVAPOTRANSPIRATION; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Generalities, techniques; Generalities. Techniques. Climatology. Meteorology. Climatic models of plant production; MODELE; MODELOS; RADIACIONES; RADIATION; RADIATIONS; TEMPERATURA DEL AIRE; TEMPERATURE DE L'AIR; VENT; VIENTO; WINDS; Bioclimatology; Potential evapotranspiration; Sensitivity analysis; Methodology; Vapor pressure; Linear regression; Humidity; Error correction; Computing; Mathematical model; Computer aid
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/0168-1923(89)90062-2

Of the several models used to calculate potential evapotranspiration (PET), many researchers use the combination method because of its theoretical basis. This model can be affected by random errors in the input parameters (net radiation, air temperature, wind speed, and daily average vapor pressure deficit, ▿) and sensitivity analyses have described the impact of these errors. However, a more subtle non-random error may be introduced in PET estimates by changing the form by which the ▿ term is specified. At least 12 different ways to present ▿ have been published; the primary differences among them are the measured humidity parameter and the algebra used to compute ▿. The effect of all applicable published computational methods on monthly and seasonal PET values for a range of locations differing in evaporative demand was examined in this study. Related methods of computing ▿ resulted in little difference between PET values. The range of summer PET means obtained from the extreme methods was 8–17% of the best estimate method over all locations. Although this range approximates the expected accuracy of the combination method, it must be stressed that the net effect of the systematic and random errors may constitute a bias and, therefore, should be evaluated as such. Apparently innocuous computational differences can significantly affect PET results and, therefore, degrade confidence in the resulting values.