Accepting/refusing high rainfall measurement
As you have multiple nearby gauge stations. I would suggest to compute a multiple linear regression that would allow you to estimate the rain in one station using the data from the others.

Then, compute the historical standard  deviation of the measurements in that station relative to the prediction using the linear regression model.

With this, you can filter data errors by rejecting all points that deviate more than X standard deviations from the prediction based on nearby stations. You have to define your threshold X based on experience, and by looking at the data. It will depend in the quality of the correlation between the precipitation in the different stations, so no universal value can be defined.