Besides the "normal" challenge of obtaining adequate intake rates in a patchy and dangerous world, shorebirds foraging in intertidal habitats face additional environmental hurdles. The tide forces them to commute between a roosting site and feeding grounds, twice a day. Moreover, because intertidal food patches are not all available at the same time, shorebirds should follow itineraries along the best patches available at a given time. Finally, shorebirds need additional energy stores in order to survive unpredictable periods of bad weather, during which food patches are covered by extreme tides. In order to model such tide-specific decisions, we applied stochastic dynamic programming in a spatially explicit context. Two assumptions were varied, leading to four models. First, birds had either perfect (ideal) or no (non-ideal) information about the intake rate at each site. Second, traveling between sites was either for free or incurred time and energy costs (non-free). Predictions were generated for three aspects of foraging: area use, foraging routines, and energy stores. In general, non-ideal foragers should feed most intensely and should maintain low energy stores. If traveling for such birds is free, they should feed at a random site; otherwise, they should feed close to their roost. Ideal foragers should concentrate their feeding around low tide (especially when free) and should maintain larger energy stores (especially when non-free). If traveling for such birds is free, they should feed at the site offering the highest intake rate; otherwise, they should trade off travel costs and intake rate. Models were parameterized for Red Knots (Calidris canutus) living in the Dutch Wadden Sea in late summer, an area for which detailed, spatially explicit data on prey densities and tidal heights are available. Observations of radio-marked knots (area use) and unmarked knots (foraging routines, energy stores) showed the closest match with the ideal/non-free model. We conclude that knots make state-dependent decisions by trading off starvation against foraging-associated risks, including predation. Presumably, knots share public information about resource quality that enables them to behave in a more or less ideal manner. We suggest that our modeling approach may be applicable in other systems where resources fluctuate in space and time.