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Simulating the spatio-temporal dynamics of inundation is key to  understanding the role of wetlands under past and future climate  change. Earlier modelling studies have mostly relied on fixed  prescribed peatland maps and inundation time series of limited  temporal coverage. Here, we describe and assess the the Dynamical Peatland Model Based onTOPMODEL (DYPTOP), which predicts the extent of inundation based on a computationally  efficient TOPMODEL implementation. This approach rests on an  empirical, grid-cell-specific relationship between the mean soil  water balance and the flooded area. DYPTOP combines the simulated  inundation extent and its temporal persistency with criteria for the  ecosystem water balance and the modelled peatland-specific soil  carbon balance to predict the global distribution of  peatlands. We apply DYPTOP in combination with the LPX-Bern  DGVM and benchmark the global-scale distribution, extent, and  seasonality of inundation against satellite data. DYPTOP  successfully predicts the spatial distribution and extent of  wetlands and major boreal and tropical peatland complexes and  reveals the governing limitations to peatland occurrence across the  globe. Peatlands covering large boreal lowlands are reproduced only  when accounting for a positive feedback induced by the enhanced mean  soil water holding capacity in peatland-dominated regions. DYPTOP is  designed to minimize input data requirements, optimizes  computational efficiency and allows for a modular adoption in Earth  system models

DYPTOP: a cost-efficient TOPMODEL implementation to simulate sub-grid spatio-temporal dynamics of global wetlands and peatlands