Published in Land, the study, “Assessing and Modelling Soil Organic Carbon Dynamics in a Mining Spill Restoration Area from 1998”, investigates the Guadiamar Green Corridor in Seville, Spain. The area provides a particularly interesting case for long-term soil monitoring, having undergone extensive ecological restoration following the Aznalcóllar mining spill in 1998.
Combining different sources of information
Reliable measurement of changes in soil organic carbon is essential for understanding the effectiveness of land restoration and assessing the potential contribution of soils to climate change mitigation. However, repeated field sampling over long periods can be costly and difficult, while soil conditions can vary considerably even across relatively small areas.
The researchers therefore investigated whether different sources of environmental information could complement field observations.
Using the RothC soil carbon model, the study tested several scenarios in which locally measured input data were progressively replaced by alternative sources. These included satellite-derived vegetation indicators, climate reanalysis and remote sensing products, as well as global soil datasets.
This approach allowed the researchers to examine not only how soil carbon evolved during the restoration period, but also how the choice of input data influences the reliability of SOC modelling.
What did the study find?
The modelling successfully reproduced the general direction of the observed decline in surface-layer soil organic carbon, although most scenarios did not fully reproduce the magnitude of the changes measured in the field.
Importantly, the results show that model performance can be particularly sensitive to variables such as initial SOC levels, clay content and evapotranspiration.
The study also highlights the potential of open-access and satellite-derived environmental datasets. These resources can provide useful information when local measurements are unavailable or incomplete, but they cannot simply be treated as direct substitutes for field data. Their suitability depends on how accurately they represent local soil and environmental conditions.
Why does this matter for MRV4SOC?
These findings connect directly with one of the central challenges addressed by MRV4SOC: how to make soil organic carbon monitoring more robust, scalable and applicable across different European contexts.
Accurate Monitoring, Reporting and Verification (MRV) systems need to bring together different sources of evidence. Field measurements remain essential, but modelling, Earth Observation and other environmental datasets can help extend the spatial and temporal coverage of SOC assessments.
The research demonstrates both the opportunities and limitations of integrating these different data sources. In particular, it reinforces the importance of local validation and appropriate model calibration when alternative datasets are used to fill information gaps.
By testing these approaches in a landscape with more than two decades of restoration history, the study contributes valuable evidence towards the development of more flexible and reliable methodologies for monitoring changes in soil carbon.
From local observations to scalable SOC monitoring
Developing effective approaches for SOC monitoring requires finding the right balance between accuracy, data availability, cost and scalability.
Research such as this helps identify where remote sensing, modelling and open environmental data can strengthen conventional soil monitoring and, equally importantly, where local observations remain indispensable.
These insights contribute to MRV4SOC’s wider ambition to advance reliable and harmonised approaches for soil carbon MRV, supporting better assessment of soil carbon dynamics and the implementation of effective soil management and climate mitigation strategies.
Publication: Assessing and Modelling Soil Organic Carbon Dynamics in a Mining Spill Restoration Area from 1998
Authors: Javier Bravo-García, Juan Mariano Camarillo-Naranjo, Francisco José Blanco-Velázquez and María Anaya-Romero
Journal: Land, 2026, 15(8), 1367
Read the full open-access publication:
https://www.mdpi.com/2073-445X/15/8/1367