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Simulations of the spatiotemporal dynamics of wetlands arekey to understanding the role of wetland biogeochemistry under past andfuture climate. Hydrologic inundation models, such as the TOPography-basedhydrological model (TOPMODEL), are based on a fundamental parameter known asthe compound topographic index (CTI) and offer a computationally cost-efficient approach to simulate wetlanddynamics at global scales. However, there remains a large discrepancy in theimplementations of TOPMODEL in land-surface models (LSMs) and thus theirperformance against observations. This study describes new improvements toTOPMODEL implementation and estimates of global wetland dynamics using theLPJ-wsl (Lund–Potsdam–Jena Wald Schnee und Landschaft version) Dynamic Global Vegetation Model(DGVM) and quantifies uncertainties by comparing three digital elevationmodel (DEM) products (HYDRO1k, GMTED, and HydroSHEDS) at different spatialresolution and accuracy on simulated inundation dynamics. In addition, wefound that calibrating TOPMODEL with a benchmark wetland data set can help tosuccessfully delineate the seasonal and interannual variation of wetlands,as well as improve the spatial distribution of wetlands to be consistentwith inventories. The HydroSHEDS DEM, using a river-basin scheme foraggregating the CTI, shows the best accuracy for capturing the spatiotemporaldynamics of wetlands among the three DEM products. The estimate of global wetland potential/maximum is  ∼ 10.3 Mkm2 (106 km2), with a mean annual maximum of  ∼ 5.17 Mkm2 for1980–2010. When integrated with wetland methane emission submodule, theuncertainty of global annual CH4 emissions from topography inputs isestimated to be 29.0 Tg yr−1. This study demonstrates thefeasibility of TOPMODEL to capture spatial heterogeneity of inundation at alarge scale and highlights the significance of correcting maximum wetlandextent to improve modeling of interannual variations in wetland area. Itadditionally highlights the importance of an adequate investigation oftopographic indices for simulating global wetlands and shows the opportunityto converge wetland estimates across LSMs by identifying the uncertaintyassociated with existing wetland products

Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties