Correlated features to the dependent variable don't improve the accuracy of a Random Forest regression model
It could be that the other features that you are using as input are already enough to give accurate predictions. Thus including the two binary features does not improve the model accuracy. Id estimate variable importance to see how important the two binary features are relevant to overall predictions.
My model aims to predict radio listening in hours (on a given day at a given time for 1 specific radio station. Each row of my training set represents 1 hour blocks for each day of the year and has a little under 30,000 records going back 3.5 years. My features include parametric information such as date, station, day of week, start time as well as weather information. 
Recently I added 2 binary features which I expected would help the accuracy of the model but they don't. They are whether a station is running a contest at a given time (contests help to pull more audiences) and if the station is playing Christmas music or not (X-Mas music tends to also pull audiences). When I run a Pearson correlation of all my features vs. my dependent variable (amount of listening hours), these 2 features are in the top 4 of the most correlated features (0.16 for X-Mas music and 0.20 for contests) with the highest correlated feature sitting at 0.31. When there is a contest listening hours tend to double and when X_mas music is playing, hours tend to increase by about 50%. Interestingly, my predictions are also proportionately higher when these 2 features are True (1's).
The way I know that these features are not adding predictive value is that when I remove them from my dataset to train the model and make predictions, the model accuracy does not improve. I am measuring Mean Absolute Error, MSE and R2 to evaluate the model performance.
Any ideas as to why important features to the dependant variable, not very correlated with other features, are not helping to reduce errors?
I am running a RF with 100 trees. The issue is there if I only run a single tree as well.