Improving process-based modeling of CO2 and CH4 exchange from managed wetlands in the Sacramento-San Joaquin River Delta

Background/Question/Methods

Under California’s Cap-and-Trade program, companies are looking to invest in land-use practices that will reduce greenhouse gas (GHG) emissions. The Sacramento-San Joaquin River Delta is a drained cultivated peatland system and a large source of CO₂. To slow soil subsidence and reduce CO₂ emissions, there is growing interest in converting drained peatlands to wetlands. However, wetlands are large sources of CH₄ that could offset CO₂-based GHG reductions. The goal of our research is to provide accurate measurements and model predictions of the changes in GHG budgets that occur when drained peatlands are restored to wetland conditions. We have installed a network of eddy covariance towers across multiple land use types in the Delta and have been measuring CO₂ and CH₄ ecosystem exchange for multiple years. In order to upscale these measurements we are using a data assimilation approach to parameterize and validate a new process-based biogeochemical model: the Peatland Arrhenius Michaelis-Menten (PAMM) model. 

Results/Conclusions

To predict gross primary productivity (GPP), we employ a simple light use efficiency model which can explain 90% of the observed variation in GPP in a mature wetland. To predict ecosystem respiration (R_eco) we employ two Michaelis-Menten (MM) equations paired with Arrhenius equations to describe temperature-sensitive soil carbon pools: recently-fixed photosynthetic carbon and soil organic matter. By modeling both GPP and R_eco, the PAMM model accurately simulates half-hourly net ecosystem exchange of CO₂ (NEE) in a mature wetland (r²=0.85). To predict CH₄ exchange, we simulate methanogenesis using two MM equations paired with Arrhenius equations, where most methane is derived from recently-fixed carbon. We also simulate methane oxidation using one MM equation, with methane as the only substrate. As the wetlands in the Delta are densely vegetated, only plant-mediated and hydrodynamic transport of CH₄ are modeled, ignoring ebullition. By modeling CH₄ production, oxidation, and transport, the PAMM model accurately simulates daily ecosystem exchange of CH₄ in a mature wetland (r²=0.62). A second year of data were used to validate the model and found the model to accurately predict both annual CO₂ (observed = -495g C m^-2 yr^-1; modeled = -450 ±51g C m^-2 yr^-1) and CH₄ exchange (observed = 27g C m^-2 yr^-1; modeled = 31 ±2g C m^-2 yr^-1). Our work advances biogeochemical modeling in managed peatland systems and aids the development of a GHG protocol that can be employed under California’s Cap and Trade program.