Modification of the RothC model to simulate soil C mineralization of exogenous organic matter

Abstract

Abstract. The development of soil organic C (SOC) models capable of producing accurate predictions for the long-term decomposition of exogenous organic matter (EOM) in soils is important for the effective management of organic amendments. However, reliable C modeling in amended soils requires specific optimization of current C models to take into account the high variability in EOM origin and properties. The aim of this work was to improve the prediction of C mineralization rates in amended soils by modifying the RothC model to encompass a better description of EOM quality. The standard RothC model, involving C input to the soil only as decomposable (DPM) or resistant (RPM) organic material, was modified by introducing additional pools of decomposable (DEOM), resistant (REOM) and humified (HEOM) EOM. The partitioning factors and decomposition rates of the additional EOM pools were estimated by model fitting to the respiratory curves of amended soils. For this task, 30 EOMs from 8 contrasting groups (compost, anaerobic digestates, sewage sludge, agro-industrial waste, crop residues, bioenergy by-products, animal residues and meat and bone meals) were added to 10 soils and incubated under different conditions. The modified RothC model was fitted to C mineralization curves in amended soils with great accuracy (mean correlation coefficient 0.995). In contrast to the standard model, the EOM-optimized RothC was able to better accommodate the large variability in EOM source and composition, as indicated by the decrease in the root mean square error of the simulations for different EOMs (from 29.9 to 3.7 % and 20.0 to 2.5 % for soils amended with bioethanol residue and household waste compost, respectively). The average decomposition rates for DEOM and REOM pools were 89 and 0.4 yr−1, higher than the standard model coefficients for DPM (10 yr−1) and RPM (0.3 yr−1). The results indicate that the explicit treatment of EOM heterogeneity enhances the model ability to describe amendment decomposition under laboratory conditions and provides useful information to improve C modeling on the effects of different EOM on C dynamics in agricultural soils. Future research will involve the validation of the modified model with field data and its application in the long-term simulation of SOC patterns in amended soil at regional scales under climate change.

Sensitivity analysis of C and N modules in biogeochemical crop and grassland models following manure addition to soil

“…Most decay constants of manure pools were comparable to those reported for APSIM (Mohanty et al, ), a modified version of RothC (Mondini et al, ), MOTOR (implementing a model similar to RothC) (Whitmore, ), NCSOIL (Noirot‐Cosson et al, ), CN‐SIM (Cavalli & Bechini, and ; Petersen et al, ) and the model of Henriksen et al (). Indeed, MRT of ML varied from 4 to 9 days for crop residues and animal manures.…”

“…To overcome this limitation, alternative methods can be used to define manure pools kinetically. They assign C and N contents to model pools that optimize the simulation of experimental dynamics (Gillis & Price, ; Mondini et al, ; Noirot‐Cosson et al, ; Petersen et al, ) and assume implicitly that fast‐ and slow‐decay pools are chemically heterogeneous mixtures of molecules.…”

“…Indeed, MRT of ML varied from 4 to 9 days for crop residues and animal manures. The range for MR was wider, and the MRT values were as small as 20 days in APSIM and MOTOR and as large as 1.1–2.7 years for the modified RothC (Mondini et al, ) and NCSOIL (Noirot‐Cosson et al, ). Models also differed in the turnover of MVR: those similar to MOD4 (Henriksen et al, ; Petersen et al, ) and MOD3 (Mondini et al, ) adopted an MRT of 3–50 years, whereas studies using APSIM (Mohanty et al, ; Probert et al, ) used a smaller value (105 days), in accordance with the results of MOD2.…”

Multi‐objective calibration of RothC using measured carbon stocks and auxiliary data of a long‐term experiment in Switzerland

“…Here we found that combining SOC data from plots under different management practices, but with the same soil type, did not alleviate the equifinality issues (Figures and S6, Supporting Information). It was possible to characterize only the composition of FYM (DPM_RATIO ~ 1), confirming that more work could be done to develop a general parameterization of exogenous organic matter from different sources (Mondini et al, ). The humified organic matter pool, KHUM, as already reported by Luo et al (), and the IOM pool (Figures and S5, Supporting Information) were the most important in terms of model sensitivity, with some interaction between these two parameters.…”

“…The DPM/RPM ratio value of 1.44 for crop and grassland was retained as in the original RothC model. The organic amendments are defined in terms of DPM, RPM and HUM, and their composition is usually more variable than the plant litter (Mondini et al, ). In this study, the composition of farmyard manure was calculated from two calibrated parameters, DPM_RATIO and HUM_factor, according to the following equations: …”