---
title: "💧 ETo Calculation Based on FAO-56 Penman-Monteith"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{💧 ETo Calculation Based on FAO-56 Penman-Monteith}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

## 🚀 Reference Evapotranspiration (ETo) Estimation

This article demonstrates how to use the BrazilMet package to compute reference evapotranspiration (ETo) based on the FAO-56 Penman-Monteith method, using weather data from INMET automatic stations.

## 📦 Load the package

```{r}
library(BrazilMet)
```

## 🌍 View available INMET stations

Before downloading data, you can check the available weather stations with:

```{r}
see_stations_info()
```

## ⬇️ Download daily weather data

Let’s download daily meteorological data for station A001 between January 2023 and December 2024:

```{r download, eval = FALSE}
df <- download_AWS_INMET_daily(
  stations   = c("A001"),
  start_date = "2023-01-01",
  end_date   = "2024-12-31"
)
```

The resulting data frame includes temperature, solar radiation, wind speed, humidity, and atmospheric pressure.

To keep this article reproducible without depending on the INMET server, the data downloaded with the call above are bundled with the package and loaded here:

```{r load-data}
df <- readRDS(system.file("extdata", "A001_daily_2023_2024.rds", package = "BrazilMet"))
```

## 🧠 Calculate daily ETo using FAO-56

Station data have occasional sensor failures, and any missing input makes ETo `NA` on that day. `fill_gaps()` fills gaps of up to three days by linear interpolation and flags the filled values in `*_filled` columns:

```{r gap-fill}
df <- fill_gaps(df, max_gap = 3)
```

Now we use the daily_eto_FAO56() function to estimate daily ETo values:

```{r}
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
)
```

## 📊 Plotting ETo results

Below is a basic line plot of daily ETo:

```{r plot-eto-ggplot, fig.width = 10, fig.height = 4}

library(ggplot2)

# Ensure date column is in Date format
df$date <- as.Date(df$date)

ggplot(df, aes(x = date, y = eto)) +
  geom_line(color = "darkblue", linewidth = 1) +
  labs(
    title = "Reference Evapotranspiration (FAO-56)",
    x = "Date",
    y = "ETo (mm/day)"
  ) +
  theme_minimal(base_size = 14) +
  theme(
    plot.title = element_text(hjust = 0.5),
    panel.grid.minor = element_blank()
  )

```

## ✅ 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.


## 🔗 Useful links

https://github.com/FilgueirasR/BrazilMet