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The sampled reaches are associated with different elevations throughout the watershed. I will map the distribution here and color code points by which river they belong to.
```{r temperature1, eval = TRUE}
library(ggplot2)
reaches %>%
ggplot(aes(y = elevation_m, x = temp_rank, color = river_name)) +
geom_point() +
theme_minimal() +
labs(fill = 'Total Upstream Drainage Area (sqKm)',
y = 'Elevation (m)',
x = 'Temperature (m)',
color = 'River') +
theme(legend.position = "bottom")
```
As expected, the temperature rank for the sampled reaches tends to be higher in lower elevations. This would be helpful if I was trying to understand how temperature changes throughout a river as elevation decreases and rivers gain more tributaries.