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Evapotranspiration-Based Irrigation for Agriculture: Sources of Evapotranspiration Data for Irrigation Scheduling in Florida

Isaya Kisekka, Kati W. Migliaccio, Michael D. Dukes, Bruce Schaffer, Jonathan H. Crane, Kelly Morgan, Haimanote K. Bayabil, and Sandra M. Guzman

This article is part of a series on ET-based irrigation scheduling for agriculture. The rest of the series can be found at https://edis.ifas.ufl.edu/topic_series_ET-based_irrigation_scheduling_for_agriculture.

Introduction

The first step to using evapotranspiration (ET) for irrigation scheduling is to estimate reference ET (ETo). This document lists some of the public sources of ETo in Florida.

Evapotranspiration: Basic Concepts

ET is the process through which water is lost to the atmosphere from the soil by evaporation and from plants by transpiration. ET of a specific crop (also referred to as "crop ET" or "actual ET") is affected by several factors including weather, the crop under consideration, its management, and environmental variables (Table 1). The more information available about factors affecting ET, the more accurate the ET prediction will be. Generally, ET is not directly measured but estimated using mathematical or empirical models that have been developed over time and selected site-specific factors listed in Table 1. More information on basic ET concepts can be found in EDIS document ABE 343, Evapotranspiration: Potential or Reference (https://edis.ifas.ufl.edu/ae256).

Crop ET (ETc) is calculated using Equation 1 by multiplying ETo by the crop coefficient (Kc). ETo refers to ET from a well-watered hypothetical grass surface of known characteristics (height of 4.72 in, surface resistance of 70 sec 3.2ft-1, and an albedo of 0.23) (Irmak and Haman 2017). It expresses the evaporative demand of the atmosphere at a given location from a well-watered reference grass that is fully shading the ground.

Etc = ETo x Kc

Equation 1. Formula used to calculate ETc for a specific crop based on reference ET and crop coefficient.

Reference ET can be calculated using different equations. The different mathematical equations used for ETo estimation are based on different concepts, and the variables (inputs) to include depend on the equation selected. ETo may be determined using a complex equation (i.e., Penman-Monteith) or simpler equations (i.e., Hargreaves). It is important to know which radiation or temperature-based method to use in the calculation of ETo because some equations are more accurate than others depending on the location where they are applied (Table 2). Basic information on how to estimate ETo can be found in EDIS document AE446, Smart Irrigation Controllers: Operation of Evapotranspiration-Based Controllers (https://edis.ifas.ufl.edu/ae446).

The Kc component of Equation 1 integrates the crop characteristics (e.g., crop height, the fraction of net radiation absorbed at the land surface, canopy resistance, and evaporation from bare soil surface) into the ETc estimation equation to account for the difference in transpiration from the actual crop compared to that from the reference grass. Typical Kc values for some Florida crops can be found in EDIS document AE456, Evapotranspiration-Based Irrigation for Agriculture: Crop Coefficients of Some Commercial Crops in Florida (https://edis.ifas.ufl.edu/ae456). General information on estimating crop water requirements for irrigation from ETc can be found in EDIS document AE457, Evapotranspiration-Based Irrigation Scheduling for Agriculture (https://edis.ifas.ufl.edu/ae457).

Sources of ETo Data for Implementing ET-Based Irrigation Scheduling in Florida

Two types of ETo data can be used in ET-based irrigation scheduling: historical ETo and real-time ETo. Historical ETo should represent long-term daily, monthly, or seasonal ETo averages for a long record of data that includes yearly and 10-year variations. Real-time ETo used to schedule irrigation is updated daily, which provides an advantage over the historical ETo-based approach because it accounts for daily variations in weather conditions. Florida growers can easily obtain real-time ETo and monthly average ETo data from the Florida Automated Weather Network (FAWN) website at http://fawn.ifas.ufl.edu/, where ETo is estimated using the University of Florida Institute of Food and Agricultural Sciences (UF/IFAS) (1984) modified Penman equation. Daily, average daily, and historic monthly ETo can be obtained from the FAWN database for numerous locations throughout Florida using the following steps:

  • Go to http://fawn.ifas.ufl.edu/.
  • Click Tools on the top menu.
  • Click Evapotranspiration (ET) menu under Irrigation.
  • A table with daily ETo for the past 7 calendar days and the 7-day average ETo for each of the FAWN weather station sites will appear. A graph with the past 14 days' ETo for selected FAWN sites is also available.

Historical data for FAWN stations can also be obtained from FAWN by clicking on the Data Access menu tab and selecting Report Generator. Historical data can be 15-minute observation; or hourly, daily, or monthly averages.

Actual ET data in Florida can be obtained from the United States Geological Survey (USGS). Data can be accessed by following the steps below.

  • Go to https://www.usgs.gov/centers/car-fl-water/science/evapotranspiration-and-carbon-flux.
  • Click Learn more link under Evapotranspiration Network to view a map of monitoring stations and site names with numbers.
  • Click on the Site number of the station closest to you. This will take you to the USGS NWIS Web Interface.
  • From the list of available parameters, select Evapotranspiration (Mean).
  • Choose Output format.
  • Enter the Begin date and End date.
  • Daily ET data are then presented in your choice of output format.

Of the two public sources of ET data, data from USGS have the greatest quality control in estimating actual ET over the different land covers where USGS has ET monitoring stations; however, the available data are limited to only a 10-year period (1995–2005) at some sites. FAWN has a wider coverage of weather stations and a more continuous period of record.

Summary

Obtaining ETo or actual ET values from the above public weather data sources will improve the estimation of crop water requirements, which are key to implementing crop-specific ET-based irrigation schedules. For ETo estimation using radiation- or temperature-based methods, always select the method most suitable for your area from Table 2.

References

Dukes, M. D., M. L. Shedd, and S. L. Davis. 2019. Smart Irrigation Controllers: Operation of Evapotranspiration-Based Controllers. AE446. Gainesville: University of Florida Institute of Food and Agricultural Sciences. https://edis.ifas.ufl.edu/ae446

Irmak, S., and D. Z. Haman. 2017. Evapotranspiration: Potential or Reference? ABE343. Gainesville: University of Florida Institute of Food and Agricultural Sciences. https://edis.ifas.ufl.edu/ae256

Jacobs, J. M., and S. R. Satti. 2001. Evaluation of Reference Evapotranspiration Methodologies and AFSIRS Crop Water Use Simulation. Final Report. Palatka, FL: St. Johns River Water Management District. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.629.9639&rep=rep1&type=pdf

Kisekka, I., K. W. Migliaccio, M. D. Dukes, J. H. Crane, B. Schaffer, S. M. Guzman, and H. K. Bayabil. 2019. Evapotranspiration-Based Irrigation for Agriculture: Crop Coefficients of Some Commercial Crops in Florida. AE456. Gainesville: University of Florida Institute of Food and Agricultural Sciences. https://edis.ifas.ufl.edu/ae456

Kisekka, I., K. W. Migliaccio, M. D. Dukes, B. Schaffer, J. H. Crane, H. K. Bayabil, and S. M. Guzman. 2019. Evapotranspiration-Based Irrigation Scheduling for Agriculture. AE457. Gainesville: University of Florida Institute of Food and Agricultural Sciences. https://edis.ifas.ufl.edu/ae457

Table 1. 

Factors that influence ET.

Factors That Influence ET

Examples

Weather parameters

Solar radiation

Air temperature

Relative humidity

Wind speed

Crop factors

Crop type

Variety

Stage of development

 

Management

Soil water management

Pest control

Poor soil management

Plant density

Environmental

Soil salinity

Impenetrable soil layers

  
Table 2. 

Examples of simpler radiation-based equations that can be used to estimate ETo for different locations in Florida.

Geographical Location

Radiation-Based Methods

Southeast Florida1

Turc (1961)

Priestley-Taylor

SFWMD-SM3

Northeast and north-central Florida2

Turc (1961)

Hargreaves4

SFWMD5

Note: These simpler radiation-based ETo estimation equations should only be used when complete weather data sets are not available to evaluate the American Society of Civil Engineers-Environmental and Water Resources Institute (ASCE-EWRI) standardized ETo estimation equation.

1 Methods selected are based on a comparison of ETo estimation equations in southeast Florida (Miami-Dade and Broward Counties) by Kisekka et al. (2009) (unpublished).

2 Methods selected are based on a comparison of ETo estimation equations in northeast and north-central Florida (Jacksonville, Gainesville, and Daytona Beach) by Jacobs and Satti (2001).

3 South Florida Water Management District (SFWMD)-Simple Method.

4 Jacobs and Satti (2001) classified Hargreaves et al. (1985) as a radiation-based method.

5 Modified Blaney-Criddle with SFWMD crop coefficients.

 

Publication #AE455

Release Date:March 27th, 2020

Reviewed At:April 13th, 2023

Related Experts

Crane, Jonathan H.

Specialist/SSA/RSA

University of Florida

Schaffer, Bruce

Specialist/SSA/RSA

University of Florida

Dukes, Michael D.

Specialist/SSA/RSA

University of Florida

Migliaccio, Kati White

Specialist/SSA/RSA

University of Florida

Bayabil, Haimanote

Specialist/SSA/RSA

University of Florida

Guzman, Sandra M.

Specialist/SSA/RSA

University of Florida

Morgan, Kelly T.

Specialist/SSA/RSA

University of Florida

Fact Sheet

About this Publication

This document is AE455, one of a series of the Department of Agricultural and Biological Engineering, UF/IFAS Extension. Original publication date January 2010. Revised February 2013 and January 2020. Visit the EDIS website at https://edis.ifas.ufl.edu for the currently supported version of this publication.

About the Authors

Isaya Kisekka, graduate student, Department of Agricultural and Biological Engineering, UF/IFAS Tropical Research and Education Center; Kati W. Migliaccio, professor, Department of Agricultural and Biological Engineering; Michael D. Dukes, professor, Department of Agricultural and Biological Engineering; Bruce Schaffer, professor, Department of Horticultural Sciences, UF/IFAS TREC; Jonathan H. Crane, professor, Department of Horticultural Sciences, UF/IFAS TREC; Kelly Morgan, professor, Department of Soil, Water, and Ecosystem Sciences, UF/IFAS Southwest Florida REC; Haimanote K. Bayabil, assistant professor, Department of Agricultural and Biological Engineering, UF/IFAS TREC; and Sandra M. Guzman, assistant professor, UF/IFAS Indian River REC; UF/IFAS Extension, Gainesville, FL 32611.

Contacts

  • Haimanote Bayabil