Procarbon-Soil—Procs: A Dynamic Soil Carbon Model for Improved Model-Data Compatibility in Carbon Farming

Abstract

Carbon farming trading schemes (CFTS) are emerging as a nature-based solution to contribute to the mitigation of climate change by capturing carbon from the atmosphere and storing it in the plant-soil system as soil organic carbon (SOC). Increasing SOC for CFTS requires improved soil management practices, monitoring through soil sampling measurements, and ex-ante economic evaluation. The implication is that SOC needs to be quantified reliably, i.e., compatible with the soil measurements data for validation and certification under CFTS. Multicompartmental SOC dynamic models (mSCDM) have been widely proposed for assessing spatial and temporal trajectories of SOC stocks. However, the overly complex structure of mSCDM means they are prone to overparameterization and overfitting, and poor performance with unseen data, thus, not appropriate for CFTS. The present paper addresses this gap by describing the development of the ProCarbon-Soil (PROCS) model, designed explicitly for CTFS in the new context of data-model fusion.PROCS holds the same fundamental biophysical principles of the most applied SCDM and has the advantage of improving adherence to empirical data by shortening the soil-plant system’s state variables to the total carbon stocks and decomposability and to allow reducing the number of parameters needed.

Keywords: soil organic carbon, Carbon market, dynamic modelling, carbon turnover, ordinary differential equations, carbon quality models