Comparison of Penman–Monteith and Priestley‐Taylor Evapotranspiration Methods for Crop Modeling in Oklahoma

Potential evapotranspiration (PET) is a key variable simulated by most crop simulation models using a variety of approaches. The objective of this study was to compare Priestley-Taylor (PT) and FAO-56 Penman–Monteith (FAO-56 PM) PET methods when simulating crop evapotranspiration (ET), yield, and aboveground biomass in Oklahoma. The study used data from 87 weather stations across nine climate divisions to simulate maize, sorghum, soybean, and wheat crop growth and development in Oklahoma for 1998 to 2017. Our results show that seasonal crop ET estimated by PT was lower than FAO-56 PM in most climate divisions and crops with average difference ranging from –10 to –1% for rainfed and from –21 to –1% for irrigated simulations. Differences in ET were greater for winter wheat than for maize, sorghum, and soybean. Additionally, differences in ET between methods were smaller in humid regions than in arid regions. Analysis of simulated rainfed yield and biomass showed higher values with PT for all crops except in the most humid climate divisions. However, under full irrigation, the yield differences between PT and FAO-56 PM were very low and ranged between 0–2% for all crops. In conclusion, this study confirmed that PT estimation of ET could be significantly different from FAO-56 PM especially in the arid and semiarid regions and during the winter under rainfed conditions. However, the differences in ET estimation did not affect yield and biomass simulation under full irrigation because the impact of soil water balance on the crop growth simulation was removed.

[1]  C. Priestley,et al.  On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters , 1972 .

[2]  William A. Jury,et al.  Use of Deterministic and Empirical Models to Predict Potential Evapotranspiration in an Advective Environment1 , 1980 .

[3]  C. H. Batchelor,et al.  A comparison of the Priestley-Taylor and Penman methods for estimating reference crop evapotranspiration in tropical countries , 1983 .

[4]  George H. Hargreaves,et al.  Reference Crop Evapotranspiration from Temperature , 1985 .

[5]  Antonio R. Pereira,et al.  Analysis of the Priestley-Taylor parameter , 1992 .

[6]  Devendra M. Amatya,et al.  Comparison of methods for estimating REF-ET , 1995 .

[7]  B. Itier,et al.  Operational limits to the Priestley-Taylor formula , 1996, Irrigation Science.

[8]  L. S. Pereira,et al.  Crop evapotranspiration : guidelines for computing crop water requirements , 1998 .

[9]  Martin Smith,et al.  The application of climatic data for planning and management of sustainable rainfed and irrigated crop production , 2000 .

[10]  Pradeep Kashyap,et al.  Evaluation of evapotranspiration estimation methods and development of crop-coefficients for potato crop in a sub-humid region , 2001 .

[11]  Petra Döll,et al.  Global modeling of irrigation water requirements , 2002 .

[12]  J. Eitzingera,et al.  Sensitivity of different evapotranspiration calculation methods in different crop-weather models , 2002 .

[13]  Suat Irmak,et al.  Daily Grass and Alfalfa-Reference Evapotranspiration Estimates and Alfalfa-to-Grass Evapotranspiration Ratios in Florida , 2003 .

[14]  James W. Jones,et al.  The DSSAT cropping system model , 2003 .

[15]  Edzer J. Pebesma,et al.  Multivariable geostatistics in S: the gstat package , 2004, Comput. Geosci..

[16]  James W. Jones,et al.  Testing and Improving Evapotranspiration and Soil Water Balance of the DSSAT Crop Models , 2004 .

[17]  J. Cavero,et al.  Comparing Penman-Monteith and Priestley-Taylor approaches as reference-evapotranspiration inputs for modeling maize water-use under Mediterranean conditions , 2004 .

[18]  Antonio Roberto Pereira,et al.  The Priestley–Taylor parameter and the decoupling factor for estimating reference evapotranspiration , 2004 .

[19]  Lin Erda,et al.  Performance of the Priestley–Taylor equation in the semiarid climate of North China , 2005 .

[20]  R. E. Yoder,et al.  Evaluation Of Methods For Estimating Daily Reference Crop Evapotranspiration At A Site In The Humid Southeast United States , 2005 .

[21]  G. Hoogenboom,et al.  Comparison of Priestley-Taylor and FAO-56 Penman-Monteith for Daily Reference Evapotranspiration Estimation in Georgia , 2007 .

[22]  Sutherland,et al.  Statewide Monitoring of the Mesoscale Environment: A Technical Update on the Oklahoma Mesonet , 2007 .

[23]  Kenneth J. Boote,et al.  Improving the CERES-Maize Model Ability to Simulate Water Deficit Impact on Maize Production and Yield Components , 2008 .

[24]  Andreas Schumann,et al.  Global irrigation water demand: Variability and uncertainties arising from agricultural and climate data sets , 2008 .

[25]  Jennifer M. Jacobs,et al.  A comparison of models for estimating potential evapotranspiration for Florida land cover types , 2009 .

[26]  R. McPherson,et al.  On the Economic Nature of Crop Production Decisions Using the Oklahoma Mesonet , 2010 .

[27]  S. Greene,et al.  Wind Climatology, Climate Change, and Wind Energy , 2010 .

[28]  Terry J. Gillespie,et al.  Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada , 2010 .

[29]  Milan Gocic,et al.  Comparison of some empirical equations for estimating daily reference evapotranspiration , 2010 .

[30]  Bradley G. Illston,et al.  New Soil Property Database Improves Oklahoma Mesonet Soil Moisture Estimates , 2013 .

[31]  J. Nagy,et al.  Comparison of Several Methods for Calculation of Reference Evapotranspiration , 2013 .

[32]  Luis S. Pereira,et al.  Partitioning evapotranspiration, yield prediction and economic returns of maize under various irrigation management strategies , 2014 .

[33]  Comparison of methods for estimating reference evapotranspiration in two locations of Espirito Santo. , 2014 .

[34]  J. S. Greene,et al.  Climate Change Impacts on Oklahoma Wind Resources: Potential Energy Output Changes , 2015 .

[35]  Fulu Tao,et al.  Prediction of Evapotranspiration and Yields of Maize: An Inter-comparison among 29 Maize Models , 2016 .

[36]  Edzer Pebesma,et al.  Spatio-Temporal Interpolation using gstat , 2016, R J..

[37]  Kelly R. Thorp,et al.  Implementing Standardized Reference Evapotranspiration and Dual Crop Coefficient Approach in the DSSAT Cropping System Model , 2017 .

[38]  Kendall C. DeJonge,et al.  Water productivity of maize in the US high plains , 2017, Irrigation Science.

[39]  H. F. Blaney,et al.  Determining Water Requirements in Irrigated Areas From Climatological and Irrigation Data , 2017 .

[40]  Prasanna H. Gowda,et al.  Evaluation of water-limited cropping systems in a semi-arid climate using DSSAT-CSM , 2017 .