“Version 1.3.0 pyfao56: FAO-56 evapotranspiration in Python”
Kelly R. Thorp,
Kendall C. DeJonge,
Tyler Pokoski,
Dinesh Gulati,
Meetpal Kukal,
Fared Farag,
Ahmed Hashem,
Gabrial Erismann,
Tamara Baumgartner,
Annelie Holzkaemper
Affiliations
Kelly R. Thorp
USDA-ARS, Grassland Soil and Water Research Laboratory, 808 E Blackland Rd., Temple 76502, TX, United States; Corresponding author.
Kendall C. DeJonge
USDA-ARS, Water Management and Systems Research Unit, 2150 Centre Ave., Bldg. D Ste. 320, Fort Collins 80526, Colorado, United States
Tyler Pokoski
USDA-ARS, Water Management and Systems Research Unit, 2150 Centre Ave., Bldg. D Ste. 320, Fort Collins 80526, Colorado, United States
Dinesh Gulati
Department of Agricultural and Biological Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States
Meetpal Kukal
Department of Agricultural and Biological Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States; Department of Soil and Water Systems, University of Idaho, Boise, Idaho, United States
Fared Farag
Department of Computer Science, Arkansas State University, Jonesboro, Arkansas, United States
Ahmed Hashem
Natural Resources Consulting Engineers, Fort Collins, Colorado, United States; Agricultural Engineering Department, Suez Canal University, Ismailia, Egypt
Gabrial Erismann
Agroscope, Agroecology and Environment, Reckenholzstr. 191, CH-8046 Zurich, Switzerland
Tamara Baumgartner
Agroscope, Agroecology and Environment, Reckenholzstr. 191, CH-8046 Zurich, Switzerland
Annelie Holzkaemper
Agroscope, Agroecology and Environment, Reckenholzstr. 191, CH-8046 Zurich, Switzerland
The pyfao56 software package is a Python-based implementation of the standardized evapotranspiration (ET) methodologies described in Irrigation and Drainage paper No. 56 of the Food and Agriculture Organization of the United Nations, commonly known as FAO-56. This update improved pyfao56 by 1) adding an optional surface runoff methodology, 2) adding an extensive algorithm for automating the computation of irrigation schedules, 3) considering irrigation losses due to irrigation system inefficiencies, 4) adding an optional method to compute the transpiration reduction coefficient (Ks) based on the curvilinear approach from AquaCrop, 5) incorporating a module for computing 15 goodness-of-fit statistics between simulated and measured data, and 6) computing a cumulative seasonal water balance summary. Most of these updates arose from user requests to add new features or options, and the collaborations demonstrated the value of community-based development for rapid improvement and generalization of scientific software.
