Advancing tropical peatland hydrology in the Noah-MP land surface model

Tropical peatlands, which cover 13–15% of the global peatland area, play a vital role in the global carbon storage, yet their key hydrological processes influencing carbon dynamics are not well accounted for in most land surface models. The Cuvette Centrale wetland of the Congo Basin is the world’s largest continuous tropical peatland area, which is governed by a complex hydrology. It is partly driven by river-peatland interactions and a spatially variable bimodal annual precipitation pattern across the Congo Basin, as well as by an unknown influence of deeper groundwater on the phreatic water levels (WL) in the peatlands. Accurate estimation of water and carbon dynamics for peatlands necessitates advancements in land surface models by incorporating peatland-specific modules to simulate key hydrological processes. In this study, we enhance the Noah-Multiparameterization (Noah-MP) land surface model to incorporate peatland hydrological processes, by including peat soil hydraulic parameters, microtopographic integration, and new runoff and evapotranspiration schemes. The peatland-specific scheme and the default TOPMODEL scheme of Noah-MP (further called “reference”) are applied across the Cuvette Centrale domain using two different meteorological forcing datasets, MERRA-2 and MERRA-2 with CHIRPS precipitation. The simulations were evaluated using in-situ WL observations and terrestrial water storage anomaly (TWSA) observations from the GRACE and GRACE-FO missions. Preliminary evaluation with in-situ WL observations shows overall improvement for peatland-specific simulations compared to the reference. Especially for the experiment with CHIRPS precipitation, which generally showed the better skill metrics, the new peatland scheme shows 5.79% increase in correlation and 86% reduction in RMSE compared to the reference driven by the same forcing. The terrestrial water storage anomalies simulated by the peatland-specific model in conjunction with altimetry-based river water storage estimates, also show an increased anomaly correlation with GRACE mascon-derived water storage anomalies. By more realistically representing the peatland hydrology, this work lays the groundwork for improved predictions of tropical peatland carbon–water interactions, with future scope for coupling with a river-routing model to better understand the peatland-river interactions for the Congo peatlands.