Video streaming on the Internet is increasingly using Dynamic Adaptive Streaming over HTTP (DASH), in which the video is converted into various quality levels and divided into two-second segments. A client can then adjust its video quality over time by choosing to download the appropriate quality level for a given segment using standard HTTP. Scalable Video Coding (SVC) is a promising enhancement to the DASH protocol. With SVC, segments are divided into subset bitstream blocks. At playback, blocks received for a given segment are combined to additively increase the current quality. Unlike traditional DASH, which downloads segments serially, this encoding creates a large space of possible ways to download a video; for example, if given a variable download rate, when should the client try to maximize the current segment's video quality, and when should it instead play it safe and ensure a minimum level of quality for future segments? In this work, we examine the impact of SVC on the client's quality selection policy, with the goal of maximizing a performance metric quantifying user satisfaction. We use acombination of analysis, dynamic programming, and simulation to show that, in many cases, a client should use a diagonal quality selection policy, balancing both of the aforementioned concerns, and that the slope of the best policy flattens out as the variation in download rateincreases.