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ARS Home » Plains Area » Lubbock, Texas » Cropping Systems Research Laboratory » Wind Erosion and Water Conservation Research » Research » Publications at this Location » Publication #337745

Research Project: Managing and Modeling Deficit Irrigation and Limited Rainfall for Crop Production in Semi-Arid Regions

Location: Wind Erosion and Water Conservation Research

Title: Calculation of evapotranspiration: Recursive and explicit methods

Author
item Lascano, Robert
item Goebel, Tim

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 2/13/2017
Publication Date: 5/26/2017
Citation: Lascano, R.J., Goebel, T.S. 2017. Calculation of evapotranspiration: Recursive and explicit methods. [abstract]. 2017 UCOWR/NIWR Annual Conference Water in a Changing Environment. June 13-15, 2017, Fort Collins, Colorado. Abstract No.001.

Interpretive Summary:

Technical Abstract: Crop yield is proportional to crop evapotranspiration (ETc) and it is important to calculate ETc correctly. Methods to calculate ETc have combined empirical and theoretical approaches. The combination method was used to calculate potential ETp. It is a combination method because it combined the energy balance and an aerodynamic formula to calculate ETp and thus eliminated the surface temperature (Ts) from the equations. This method led to the Penman-Monteith (PM) equation to estimate ETc and is used by FAO and ASCE. The procedure is to multiply a reference crop ET (ETsz) by a crop coefficient (Kc) and both use the PM equation and are an Explicit Combination Method (ECM). Assumptions made with the ECM regarding the temperature and the humidity of the evaporating surface are not necessary when using a Recursive Combination Method (RCM), which solves ETsz by finding the temperature and humidity of the evaporating surface by iteration satisfying the energy balance. Calculated values of ETsz obtained with RCM are by preferable as they are physically correct and give the “true” temperature of the crop. To illustrate differences in calculated values of ETsz for a short grass (ETos) obtained with ECM and RCM, we used a 45-d from Lubbock, TX using 3 methods: M1) ETos calculated using RCM and a canopy resistance (rc) = 35 s/m: M2) ETos calculated using ECM and the recommended value of rc = 70 s/m, which corresponds to a short grass and; M3) ETos using RCM and using the input values recommended by FAO and ASCE. Results showed that M3 yielded the largest values of ETos. The smallest values of ETos were calculated with M2, which underestimated cumulative ETos by 7% compared to RCM. However, when the input parameters used in M2 were used with a RCM cumulative ETos was overestimated by 29% compared to RCM. In many cases, M2 yielded the correct value of ETos but for wrong reasons, and thus the 7% discrepancy obtained between them is deceptive. Results suggested that the rc value of 70 s/m used by ECM is perhaps too large. In summary, results showed that a RCM of ET is easily implemented and uses the same weather input data as ECM. From a physical point of view values of ET obtained with RCM are correct as they are derived from a solution that satisfies the energy balance.