Advancing Land Surface Modeling and Satellite Data Assimilation over Tropical Peatlands

Water storage dynamics exert a first order control on the functioning of tropical peatland ecosystems. During the last decades, many regions had their peat-specific hydrology either disrupted by drainage or altered due to climate change effects. As a consequence, tropical peatlands turned from long-term carbon sinks into global hotspots of wildfires and greenhouse gas emissions affecting regional to global economies, environments and human health. Better estimates of peat moisture and water table depth are urgently needed to establish more sustainable management of tropical peatlands.

This research will address this need by developing a novel global-scale land surface modeling and satellite data assimilation framework for tropical peatlands. The research will leverage the operational data assimilation algorithm of the Level 4 Soil Moisture Active Passive (SMAP) satellite mission and will realize two crucial advancements: (i) a detailed modeling of tropical peatland hydrology including anthropogenic drainage and dynamical land cover and vegetation input; and (ii) an enhanced radiative transfer modeling with a correction for open water along coastal areas, and for dense vegetation layers. The novel estimates of water storage will be evaluated with a field dataset of unprecedented coverage and by experts of new water management regulations. The asset of the novel peat moisture for fire management will be demonstrated through its use in an operational fire danger rating system.