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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #408097
Research Project: Contributions of Climate, Soils, Species Diversity, and Management to Sustainable Crop, Grassland, and Livestock Production Systems

Location: Grassland Soil and Water Research Laboratory

Title: Version 1.2.0 - pyfao56: FAO-56 evapotranspiration in Python

Author
item Thorp, Kelly
item Brekel, Joshua
item DeJonge, Kendall

Submitted to: SoftwareX
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 9/3/2023
Publication Date: 9/16/2023
Citation: Thorp, K.R., Brekel, J.J., DeJonge, K.C. 2023. Version 1.2.0 - pyfao56: FAO-56 evapotranspiration in Python. SoftwareX. 24. Article 101518. https://doi.org/10.1016/j.softx.2023.101518.
DOI: https://doi.org/10.1016/j.softx.2023.101518

Interpretive Summary: The seminal publication of FAO-56 described standardized methods to estimate crop water use or evapotranspiration (ET), which is a critical aspect of irrigation management, water rights in many Western states, and large-scale studies of hydrology. In the first release of the "pyfao56" software, the FAO-56 methodology was programmed using the modern open-source Python programming environment. The current pyfao56 release (version 1.2.0) adds considerable functionality to the original software and previous releases, including enhanced weather forecasts, incorporating measured soil water data, adding visualization tools, and updating file header information. The pyfao56 software serves as a useful tool or framework for users of ET-based irrigation scheduling, which includes agronomists, crop consultants, irrigators, and agricultural water researchers.

Technical Abstract: 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) enhancing the “forecast” module which obtains seven-day weather forecasts from the National Weather Service (NWS), 2) incorporating measured soil water content profiles to estimate soil water depletion in the dynamic and maximum root zones, 3) adding visualization tools that plot measured and simulated soil water depletion and ET versus time, 4) updating the format of standard file headers to include timestamps, simulation options, and user defined metadata, and 5) incorporating minor improvements to the functionality of the core pyfao56 modules. These updates arose from efforts to incorporate pyfao56 into a computational workflow for maize irrigation scheduling research at the Limited Irrigation Research Farm (LIRF) in Greeley, Colorado during the 2023 growing season.