Dynamics of global wetlands by TOPMODEL

Dynamics of global wetlands are closely linked to biodiversity conservation, hydrology, and greenhouse gas emissions. However, long-term time series of global wetland products are still lacking. Using a TOPMODEL-based diagnostic model, we produced an ensemble of 28 gridded maps of monthly global/regional wetland extent products at 0.25° × 0.25° spatial resolution based on four observation-based wetland products and seven reanalysis soil moisture (SM) data sets for the period going from 1980 to 2017. The parameters of the model are calibrated on grid-scale against four observation-based wetland products including the dynamic Global Inundation Estimation from Multiple Satellites version 2 (GIEMS-2; Prigent et al., 2019), the static Regularly Flooded Wetland map (RFW; Tootchi et al., 2019), the dynamic Surface Water Microwave Product Series (SWAMPS; Schroeder et al., 2015; Poulter et al., 2017), and the static wetland area from Gumbricht et al. (2017) limited to the tropics (G2017). Overall, our products can capture the spatial distributions, seasonal cycles, and interannual variabilities of observed wetland extent well, and also show a good agreement with independent terrestrial water storage (TWS) estimates derived from the Gravity Recovery and Climate Experiment (GRACE) satellites (Tapley et al., 2004; Wouters et al., 2014). The dispersion of the 28 spatio-temporal datasets shows the large uncertainties in the estimation of global absolute wetland extent, which result from uncertainties in SM data, the choice of observed wetland data sets and calibration methods, as well as limitations of TOPMODEL. The simulated mean annual maximum global wetland area calibrated by GIEMS-2, RFW, and SWAMPS fluctuates within a range of 3.8–4.8 Mkm2, 3.8–4.9 Mkm2, and 4.8–5.7 Mkm2 respectively. The long temporal coverage beyond the era of satellite datasets, the global coverage and the opportunity to provide real time update from ongoing SM data make these products helpful for various applications such as analyzing the wetland-related methane emission.