| 25 Feb 2026
Challenges in Soil Carbon Modelling and Measurement: A Decade of Experimental Data vs. RothC Simulations in an Organic Olive Grove
Abstract. Modelling the persistence of soil organic carbon (SOC) is currently recognised as a key approach to enhance our understanding of its potential contribution to climate change mitigation. Despite its value, SOC modelling is challenged by soil heterogeneity and the limited availability of reliable data for model calibration and validation, often resulting in discrepancies between simulated and measured SOC dynamics. This study employs a modified version of the RothC model, adapted for amended soils, to simulate soil C dynamics under an 11-year experiment in an organic olive grove. The experiment evaluated four treatments of soil amendment: Compost, Biochar, a Mixture of both, and a control soil without amendment. By comparing the SOC data simulated by the RothC model with experimental field-sampling data, we assessed the model’s accuracy in estimating SOC accumulation and stability in the soil. Both field measurements and RothC simulations consistently identified biochar as the most effective amendment for soil carbon accumulation over the 11-year period, followed by the Mixture and Compost treatments. Estimated soil carbon sequestration rates ranged from 1.67 to 2.66 Mg C ha⁻¹ yr⁻¹ based on field measurements and from 2.88 to 5.30 Mg C ha⁻¹ yr⁻¹ according to model simulations. However, treatment-dependent discrepancies were observed between modelled and field-based SOC stocks. While Compost and Mixture showed close agreement, Biochar exhibited the largest mismatch, likely due to its intrinsic properties that complicate field quantification and are not fully represented in current SOC models, posing challenges for monitoring and verification within carbon accounting frameworks.
General comment
This interesting and well-structured manuscript is about the challenge of matching soil carbon modelling results with soil carbon measurements of a field experiment with organic amendments (biochar, compost). Specifically, it compares soil carbon dynamics that were modelled with a modified version of the RothC model with measurements from an 11-year old field experiment on an olive grove. The authors found a large mismatch for the biochar treatment, and an acceptable match for the compost treatment. The manuscript is well written and covers many important aspects. Thus, it has the potential to be an important contribution to the discussion around using SOC models for MRV systems in carbon accounting frameworks.
However, I see one larger issue that is not discussed well enough at the moment: The biochar treatment included a massive addition of C of up to 13.46 Mg C ha-1 per application (L.114). This does not seem to be reflected well in the measured SOC over time (Fig. 4). In the biochar facet of Fig. 4, we basically see a step from the first measurement (that is, the mean SOC from the control plot only) to the second measurement (that is, the first real measurement from the biochar plots), and no change afterwards anymore, even though there were four additional biochar application events over that time. In my view, this shows two issues: (1) It could be possible that the treatment plots are not comparable to the control plots. This needs to be checked and, ideally, the initial SOC of each plot needs to be shown in the corresponding figure instead of using the mean SOC from the control plot for all treatment plots. And (2) surprisingly, there is almost no biochar-induced C increase detectable. In the discussion, the authors attribute this to the “randomness associated with manual soil sampling” (L. 405), but this seems to apply only to the biochar treatment but not the compost treatment and therefore, cannot tell the whole story. Could this also be a result of the outlier exclusion (L.135), where potentially those measurements with large local amounts of biochar-C were excluded? Do the authors have any recommendations how to improve future field experiments and sampling? The fact that this massive biochar application does not result in significant SOC increases is a surprising and interesting finding that needs more discussion (after thorough checks of potential errors) before the manuscript can be considered for publication.
Specific comments
L92: Please clarify for which treatment and time this organic C content applies. Or is it the average from all measurements?
L135: Please add how many samples were classified as outliers (number and % of all samples). Could this lead to exclusion of samples with large local amounts of biochar-C? Please consider showing all data in the supplement.
L147: How large was the short-term variability? Did this also affect the earlier measurements?
L202: Please specify whether the amount of irrigated water was considered in the simulations, e.g. as precipitation. In case it was not considered, it needs to be added in the simulations.
L206: Please clarify how the plant residues were handled prior to the experiment and during the experiment: Is this annual C input only belowground C input (roots and exudates) due to removal of aboveground biomass (branches, leaves are removed), or is it also woody biomass input (branches and leaves decompose directly in the soil)? Did the residue management change with the beginning of the experiment or during the experiment (e.g., branches were left on the ground and are now removed in order to convert them as compost/biochar)?
L.210: Please consider to add the distance of the weather station to the experimental field.
L240: Please consider to add the amount of irrigated water to this figure, to cover the whole effect on soil moisture.
L241: “Bars represent standard deviation.” This is incorrect for the upper panel: Bars show the precipitation; standard deviation is not shown in upper panel.
Figure 3: The resolution is not sufficient; Please consider to submit as vector graphic if possible.
L274: Are there also measurements of the initial SOC of the treatment plots?
L292: Which means that the assumption of the SOC being in equilibrium was not valid. Please clarify in the Material and Methods section how the land has been used before the implementation of the experiment and prior to the establishment of the orchard). Land-use changes can have a long legacy effect on SOC of more than 100 years (e.g., Emde et al. 2024).
L318: Please specify for which model the statistics are given: RothC or the regression line. Please include your approach for the regression line in the Material & Methods section.
L322: It is not clear to me how the control SOC change was included in this estimate. If we want to know the treatment effect, the control SOC trend needs to be substracted from the treatment SOC trend (baseline== control trend), but I think this was not done here. Please clarify this accordingly.
L325: Does this mean that the compost was more stable than the biochar?
L355: There are also studies which claim that RothC does not represent the soil moisture conditions in semi-arid conditions well - please refer to Farina et al. 2013 for more information.
L364: The assumption of both the SOC and C input from the olive grove being in equilibrium is not valid.
L379: Please consider to add the biochar content in parentheses, e.g. (5%).
L390: Please clarify what other "routine agricultural practices" could increase the "background carbon inputs".
L401-409: Please elaborate a bit more on how biochar field experiments should be sampled to fully capture the SOC increase. How could the study design and sampling design be improved in the future? Now it is not clear enough how to reduce the error, and everything between 100% model error and 100% sampling error seems possible. Can you give a tendency, what needs to be done to find out whether the biochar was really not as stable as we thought, or whether the sampling approach needs to be changed? How should biochar research proceed in the future?
L463: Do you think these output pathways could be of relevance in this specific study? Please elaborate a bit more on potential losses via erosion.
Technical corrections
L92: Remove the % sign after the pH value.
L219: Abbreviation not yet defined.
L283: Move the definition to the first mentioning of the abbreviation.