In this work, we provide a methodology to analyze optimal adaptation policies for scalable video delivery in mobile environments. Typically, download policies for adaptive video are tuned to very specific system settings. The aim of this work is not to propose a new policy, but instead to understand how the optimal policy changes according to the operating environment and the system characteristics of a mobile video client. Armed with this insight, we can design or adapt policies for SVC adaptive video delivery for a broader range of settings. Using a semi-Markov decision process (SMDP), we find optimal video retrieval policies for a single user, subject to different limits on buffer capacity and different wireless environments. We apply a decision tree classifier to the output of the SMDP to derive simple approximate policies for 55 scenarios and use these to derive high-level rules on the relationship between optimal download policy and the underlying channel settings. For example, we show that the optimal policy is more conservative in slowly varying channels, and becomes more greedy in fast changing channels, and that instantaneous channel state is relevant to the decision-making process only in a setting with a very limited buffer capacity and slow-varying channel.