We develop a stochastic-dynamic model of technology adoption that imposes fewer restrictions on behavior than do previous studies of similar decision problems. Like these previous studies, our model is forward-looking and can be used to demonstrate the additional "hurdle rate" that must be met before adoption will take place when the future state of the world is uncertain. Unlike these previous studies, our approach does not impose the untenable assumptions that investment in a new technology is irreversible or that technologies have unlimited useful lifetimes. Rather, we address the more reasonable situation of costly reversibility and limited lifetimes. Our solution method utilizes Bellman's equation and standard dynamic programming techniques. Similar methods have been used previously to examine irreversible investment and adoption problems, but to our knowledge no application to costly reversible adoption has yet to appear in the literature. Our behavioral simulations, calibrated for irrigated cotton farming in California's San Joaquin Valley, demonstrate that the more restrictive approach can produce significant model prediction errors and can overlook important features of the adoption problem when decisions are reversible and technologies eventually become obsolete. Policy implications are discussed.