🚀 Design ETo calculation estimation
This article shows a quick example of how to download INMET station data and estimate reference evapotranspiration (ETo) using FAO-56, followed by the calculation of the design ETo.
🌍 View available INMET stations
Before downloading data, you can check the available weather stations with:
see_stations_info()
#> # A tibble: 564 × 8
#> station_municipality uf situation_operation latitude_degrees
#> <chr> <chr> <chr> <dbl>
#> 1 Abrolhos BA breakdown -18.0
#> 2 Acarau CE breakdown -3.12
#> 3 Afonso Claudio ES operating -20.1
#> 4 Agua Boa MT operating -14.0
#> 5 Agua Clara MS operating -20.4
#> 6 Aguas Emendadas DF operating -15.6
#> 7 Aguas Vermelhas MG operating -15.8
#> 8 Aimores MG operating -19.5
#> 9 Alegre ES operating -20.8
#> 10 Alegrete RS operating -29.7
#> # ℹ 554 more rows
#> # ℹ 4 more variables: longitude_degrees <dbl>, altitude_m <dbl>,
#> # operation_start_date <dttm>, station_code <chr>⬇️ Download daily weather data
Let’s download daily meteorological data for one stations between January 2000 until March 2025:
df <- BrazilMet::download_AWS_INMET_daily(stations = "A001",
start_date = "2000-01-01",
end_date = "2025-03-31")
#> Downloading data for: 2000
#> Downloading data for: 2001
#> Downloading data for: 2002
#> Downloading data for: 2003
#> Downloading data for: 2004
#> Downloading data for: 2005
#> Downloading data for: 2006
#> Downloading data for: 2007
#> Downloading data for: 2008
#> Downloading data for: 2009
#> Downloading data for: 2010
#> Downloading data for: 2011
#> Downloading data for: 2012
#> Downloading data for: 2013
#> Downloading data for: 2014
#> Downloading data for: 2015
#> Downloading data for: 2016
#> Downloading data for: 2017
#> Downloading data for: 2018
#> Downloading data for: 2019
#> Downloading data for: 2020
#> Downloading data for: 2021
#> Downloading data for: 2022
#> Downloading data for: 2023
#> Downloading data for: 2024
#> Downloading data for: 2025The resulting data frame includes temperature, solar radiation, wind speed, humidity, and atmospheric pressure
🧠 Calculate daily ETo using FAO-56
Now we use the daily_eto_FAO56() function to estimate daily ETo values:
df$eto <- daily_eto_FAO56(
lat = df$latitude_degrees,
tmin = df$tair_min_c,
tmax = df$tair_max_c,
tmean = df$tair_mean_c,
Rs = df$sr_mj_m2,
u2 = df$ws_2_m_s,
Patm = df$patm_mb,
RH_max = df$rh_max_porc,
RH_min = df$rh_min_porc,
z = df$altitude_m,
date = df$date
)💧 Design ETo calculation
And after the ETo calculation, we use the design_eto() function to estimate the design ETo for irrigation project purpose:
eto_design <- BrazilMet::design_eto(eto_daily_data = df, percentile = .80)📝 Printing the design ETo based on an 80% probability of occurrence
Below is a basic line plot of daily ETo:
print(eto_design)
#> design_eto
#> 1 5.672264✅ Summary
The BrazilMet package allows you to download official INMET weather data and compute ETo using the FAO-56 method in a reproducible and efficient way. This is essential for irrigation planning, crop modeling, and climate-based decision support.