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you can only calculate terrain flattening if you calibrated to beta0.
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maximum likelihood is not suitable for radar data because the data is not distributed equally (vh is generally lower than vv), random forest works better. For both cases, conversion to dB is helpful because it changes the histogram [please see the examples here and here]. If you want to include image textures, random forest is necessary because it is based on thresholds and not of clusters. If you don’t want to include textures, please have a look at these comments on feature space here.
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Please have a look at the difference between Sigma0 and Gamma0 here. As these refer to topographically induced radiometric distortions (and water bodies are usually flat), it barely makes a difference. Calculate a scatter plot between Sigma0 and Gamma0 to see where they are different.