Testing Carbon-Input Feasibility in RothC Using Paired Soil Resampling over a 20-Year Interval in a Semi-Arid Steppe

Long-term soil organic carbon (SOC) monitoring provides a rare opportunity to test the performance of process-based models against real data. We evaluated RothC using 20 georeferenced soil profiles sampled in 2004 and 2024 in the semi-arid steppe of Central Kazakhstan. We used the 2004 SOC stocks for equilibrium initialization, whereas independently measured 2024 stocks were used for endpoint evaluation. A baseline-conditioned, endpoint-uncalibrated forward simulation (S1) was driven by profile-specific climate, NPP-scaled plant-C inputs, vegetation cover, and reconstructed management; a constrained inverse analysis (S2) estimated the non-negative effective C-input multiplier required to reproduce the observed endpoint, and a zero-input simulation (S3) defined the lower feasibility boundary. S1 preserved the broad between-profile variation in absolute 2024 SOC stocks (R2 = 0.692), but agreement for the observed 2004–2024 SOC change was negligible (R2 < 0.001; Lin’s CCC = 0.002). The direction of SOC change was reproduced at 9 of the 20 profiles, with an RMSE of 12.49 Mg C ha−1 and a mean bias of −4.41 Mg C ha−1. We obtained physically admissible inverse solutions for 17 profiles, with Mrequired ranging from 0.42 to 4.62 (mean = 2.04; median = 1.96). Profiles 295, 299, and 313 remained below the zero-input boundary under all management-timing scenarios. Together, these results show that adjusting plant-C input can reconcile modeled and observed SOC at most profiles. However, no non-negative adjustment of plant-C input could reproduce some observed endpoints. These cases indicate that other processes or sources of uncertainty should be considered.