Role of hydrological parameters in the uncertainty in modeled soil organic carbon using a coupled water-carbon cycle model

Soil organic carbon is the largest carbon pool in the terrestrial biosphere. Large uncertainties exist in the numerical simulations of soil organic carbon due to inaccuracies in their mathematical descriptions of hydrological processes. In this study, the upper limit of uncertainty in modeled soil organic carbon that is induced by hydrological parameter errors, which may stem from measurement or experiential errors, is estimated in China under four different arid and humid conditions. The study was conducted using a conditional nonlinear optimal perturbation related to parameters (CNOP-P) approach and a model of the coupled water-carbon cycle (the Lund Potsdam-Jena Wetland Hydrology and Methane Dynamic Global Vegetation Model, LPJ-WHyMe). Uncertainties in hydrological processes resulted in the largest error (2.73 kg C m(-2) yr(-1), 20.2%) in the modeled soil organic carbon in the arid and semiarid regions of northern China, with errors of 1.20 kg C m(-2) yr(-1) (6.1%) in northeastern China, 0.45 kg C m(-2) yr(-1) (3.3%) in southern China, and -1.71 kg C m(-2) yr(-1) (13.7%) in the semihumid region of northern China. By analyzing the three components of soil organic carbon, the fast soil carbon pool was found to be the main cause of the uncertainties in modeled soil organic carbon in the four regions of China. Moreover, belowground litter was another cause of the uncertainties in the modeled soil organic carbon in northeastern China and in the semihumid region of northern China. Additional results indicated that the simulation and prediction abilities of soil organic carbon could be improved by reducing parameter errors in hydrological processes through observations or targeted observations. The parameter sensitivity test showed that the benefits to modeling soil organic carbon were similar when reducing the errors in the sensitive hydrological parameter subset, compared to the benefits of reducing the errors in all the hydrological parameters.