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The hydrology of wetland‐dominated landscapes is often controlled by a fill‐and‐spill mechanism, whereby surface depressions retain water and release it once a deficit is filled. The response of these systems to precipitation/snowmelt events is influenced by the local storage deficit and connectivity between storage features. To estimate runoff generated from a heterogeneous wetland complex, a closed‐form analytical upscaled probabilistic model is developed. The mathematical solution requires information on the distribution of initial deficits and wetland local contributing areas, which may be estimated via a combination of spatial analysis and field observation. The model is used to explore the influence of spatial heterogeneity of wetland properties including deficit depth, local contributing area, and cascade depth (the number of wetlands in‐series within a cascade) on runoff response. It is also used to clarify “gatekeeper” storage features role at large scales and for systems with shallow wetland cascade depths. The proposed solution is shown to be a generalization of the well‐known Probability Distributed Model and Xinanjiang runoff models, augmented to include information about local contributing areas and wetlands connectivity. The closed form probabilistic mathematical solution is verified by comparing results with Monte Carlo simulations. The proposed runoff model has been implemented in Raven, a hydrologic model, to test the method performance in lumped runoff simulation of wetland‐dominated basins influenced by fill‐and‐spill hydrology. This study can contribute to our understanding of wetland characteristics distribution on landscape hydrology, and compensate for insufficiently resolved elevation data in flat terrains where threshold criteria are hard to estimate.

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