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In this study, we present a stochastic landscape modeling approach that has the power to transfer and integrate existing information on vegetation dynamics and hydrological processes from the small scale to the landscape scale. To include microscale processes like ecohydrological feedback mechanisms and spatial exchange like surface water flow, we derive transition probabilities from a fine-scale simulation model. We applied two versions of the landscape model, one that includes and one that disregards spatial exchange of water to the situation of a sustainably used research farm and communally used and degraded rangeland in semiarid Namibia. Our simulation experiments show that including spatial exchange of overland flow among vegetation patches into our model is a precondition to reproduce vegetation dynamics, composition, and productivity, as well as hydrological processes at the landscape scale. In the model version that includes spatial exchange of water, biomass production at light grazing intensities increases 2.24-fold compared to the model without overland flow. In contrast, overgrazing destabilizes positive feedbacks through vegetation and hydrology and decreases the number of hydrological sinks in the model with overland flow. The buffer capacity of these hydrological sinks disappears and runoff increases. Here, both models predicted runoff losses from the system and artificial droughts occurring even in years with good precipitation. Overall, our study reveals that a thorough understanding of overland flow is an important precondition for improving the management of semiarid and arid rangelands with distinct topography.