I have data on 5 agriculture fields over the same period of time. At some point, there is a sudden change in behavior for all 5 time series, which correspond to the harvest of the field. My task is to implement a methodology to determine the date at which the field was harvested and provide prediction intervals. Here is what it looks like plot. Here is the correlation matrix.
As you can see, it's not obvious from visual inspection as there are several peaks and ups and downs . It's important to say that I don't know what the values in the time series correspond to.
I have though of some methods like max(sum over all TS of the derivatives at each point), or using first and second derivative etc. But I want to know if there is a more systematic way or method? And how to provide prediction intervals.
I know that there are a lot of packages in R to work with Time series (see here but I have to use python for this problem. Thanks!