River water input from upstream areas into the Cuvette Centrale peatland complex detected via SMOS data assimilation

In this research, we applied our recently developed tropical peatland-specific module PEATCLSMTrop,Nat in a land surface modeling and assimilation scheme that uses L-band brightness temperature (Tb) data from the Soil Moisture and Ocean Salinity (SMOS) satellite mission. Despite the dense vegetation cover in tropical peatlands, preliminary results showed that the data assimilation improved the water level estimates at 4 evaluation sites over model-only simulations, with mean correlation coefficients of 0.46 for the model-only and 0.63 for the data assimilation estimates, and mean anomaly correlation coefficients of 0.02 for the model-only and 0.26 for the data assimilation estimates. To gain insight into the large-scale hydrology of the Cuvette Centrale peatland complex, we analyzed data assimilation diagnostics and found temporally autocorrelated positive and negative total water storage (tws) increments (=tws correction introduced via data assimilation) over periods of up to four months over the Cuvette Centrale peatlands. This is indicative of a temporarily suboptimal assimilation system, due to a shortcoming in the LSM. Since PEATCLSMTrop,Nat does not simulate lateral water input and the positive autocorrelated periods of tws increments coincide with anomalies in river stages measured upstream, it suggests that lateral water input (=flooding) from upstream mineral areas into the peatlands of the Cuvette Centrale is an important but unmodelled process in its hydrology. This means that land use change and a climate change-induced precipitation reduction in upstream mineral areas will influence the local hydrology of the Cuvette Centrale peatland complex, making it even more vulnerable to external disturbances.