Evaluation of FAO-56 Procedures for Estimating Reference Evapotranspiration Using Missing Climatic Data for a Brazilian Tropical Savanna

Abstract

The Brazilian savanna (Cerrado) has been heavily impacted by agricultural activities over the last four to five decades, and reliable estimates of reference evapotranspiration (ETo) are needed for water resource management and irrigation agriculture. The Penman–Monteith (PM) is one of the most accepted models for ETo estimation, but it requires many inputs that are not commonly available. Therefore, assessing the FAO guidelines to compute ETo when meteorological data are missing could lead to a better understanding of which variables are critically important for reliable estimates of ETo and how climatic variables are related to water requirements and atmospheric demands. In this study, ETo was computed for a grass-dominated part of the Cerrado from April 2010 to August 2019. We tested 12 different scenarios considering radiation, relative humidity, and/or wind speed as missing climatic data using guidelines given by the FAO. Our results presented that wind speed and actual vapor pressure do not affect ETo estimates as much as the other climatic variables; therefore, in the Cerrado’s conditions, wind speed and relative humidity measurements are less required than temperature and radiation data. When radiation data were missing, the computed ETo was overestimated compared to the benchmark. FAO procedures to estimate the net radiation presented good results during the wet season; however, during the dry season, their results were overestimated because the method could not estimate negative Rn. Our results indicate that radiation data have the highest impact on ETo for our study area and presumably for regions with similar climatic conditions. In addition, those FAO procedures for estimating radiation are not suitable when radiation data are missing.

Assessing the Effects of Surface Conditions on Potential Evapotranspiration in a Humid Subtropical Region of China

“…The impacts of environmental variables on ET p showed both similarity and difference across time scales. Namely, ET p was negatively correlated with P, RH, and SWC and positively with other variables at the annual scale, which has been found consistent across studies (Chu et al, 2017;Jerin et al, 2021;Valle Júnior et al, 2021). However, when it comes to seasons, ET p is most sensitive to environmental changes in summer and least sensitive in winter indicated by the regression slopes.…”

A New Methodology for Reference Evapotranspiration Prediction and Uncertainty Analysis under Climate Change Conditions Based on Machine Learning, Multi Criteria Decision Making and Monte Carlo Methods

“…In recent years, instead of using ETo data measured at meteorological stations [24], the FAO-56 PM method has been used to estimate ETo [36,37]. The present study implemented the FAO-56 PM method to estimate the ETo from meteorological data.…”

PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru

“…Although TerraClimate and ERA5-Land provide a better spatial resolution, biases in solar radiation could be presented. This is crucial because solar radiation errors have the highest impact on the estimated ET o 8 , 9 , 19 . A recent study proved that satellite-based solar radiation estimates are more accurate than ERA5-Land solar radiation outputs, implying a more accurate ET o by using the satellite-based estimation 83 .…”