@jrkrideau is right—a little data will attract more specific answers.
Here's a framework to approach R.
Every R problem can be thought of with advantage as the interaction of three objects— an existing object, x , a desired object,y , and a function, f, that will return a value of y given x as an argument. In other words, school algebra— f(x) = y. Any of the objects can be composites.
Here, you have two csv files to start. That's x. y is an object (everything in R is an object) that contains two variables, plot and days_flooded.
f is composed of several functions.
You can use readr::read_csv to bring x into two data frames, DF1 and DF2. DF1 has two variables, plot and base_elevation and DF2 hasplot, elevationanddate_measured`. (Or whatever you want to name the objects.)
The two data frames need to be combined, which can be done using one of the join functions in {dplyr} yielding plot, base_elevation, elevation, date_measured and elevation. For each date_mentioned, create a new variable, based on whether elevation > base_elevations. Then it's a matter of doing the date arithmetic on date_measured.