COS 98-3
A process-based lake biogeochemical model for improving prediction of carbon dynamics in arctic lakes

Thursday, August 13, 2015: 8:40 AM
318, Baltimore Convention Center
Zeli Tan, Department of Earth, Atmospheric, and Planetary Sciences, Purdue University, West Lafayette, IN
Qianlai Zhuang, Department of Agronomy, Purdue University, West Lafayette, IN
Katey Walter Anthony, Water and Environmental Research Center, University of Alaska Fairbanks, Fairbanks, AK

The transport of terrigenous carbon to aquatic ecosystems can offset the role of terrestrial ecosystems as a net sink of atmospheric carbon. In arctic, the outcome of this migration could be complex. When CH4 and CO2 emissions from aquatic lakes and rivers are fueled by labile carbon release from thawed permafrost, lake productivity and sedimentation are also stimulated by nutrient release from organic matter degradation and terrestrial carbon deposition. Here we report the development of a state-of-the-art process-based lake biogeochemical model that simulates the dynamics of POC, DOC and DIC in yedoma and non-yedoma, thaw and non-thaw arctic lakes. The microbial and photochemical degradation of autochthonous and allochthonous DOM, the photosynthesis and respiration of two phytoplankton function groups (picoplankton and microplankton), the sedimentation of dead phytoplankton, and the aerobic respiration and methanogenesis in sediments were modeled. The change of carbon cycle due to the variations of ice layers, sediment thaw bulb and water mixing was also modeled. The growth of phytoplankton is parameterized as a function of light, temperature and dissolved phosphorus. 


This presentation will focus on our development and validation of this process-based lake biogeochemical model. Model sensitivity to a group of biogeochemical parameters including phytoplankton growth and metabolic loss rates, the maximum and minimum chlorophyll to carbon ratios of phytoplankton, the phosphorus and temperature limitation coefficients and DOM turnover rate in sediments was analyzed using a variance-based method. Key parameters were calibrated using a Monte Carlo based Bayesian approach. The model was validated by comparing with observational data of CO2 and CH4 emissions and dissolved O2 from four yedoma lakes in Alaska and Siberia and one non-yedoma non-thermokarst lake in Alaska. Our model simulations indicated that, due to thermokarst erosion and terrestrial OM deposition, the elevation of lake productivity, sedimentation and CO2 and CH4 outgassing can coexist at arctic lakes under warming conditions.