Agoro Carbon Alliance’s Modeling Work Under Independent Review
Agoro Carbon Alliance is currently undergoing an independent assessment of two model validation reports to ensure they meet Verra Standards’ pasture and rangeland modeling requirements.
These reports have already passed an initial review by independent modeling experts, who described them as “outstanding” and “high quality.”
Commitment to Scientific Rigor
Before finalizing the reports, Agoro Carbon’s modeling team, led by Senior Data Scientist Dr. Xiuying (Susan) Wang, took extra steps to ensure scientific transparency and integrity. Their efforts are further supported by a peer-reviewed research article published in the journal Environmental Modelling and Software.
This article introduces the DayCent-CUTE tool (auto-Calibration, sensitivity, and Uncertainty analysis ToolSet), which features a user-friendly interface. The tool streamlines the calibration process for the DayCent model, making it more efficient and adaptable for both single-site and multi-site research—essential for national-scale carbon programs.
“This article represents our contribution to the scientific research community, showcasing our work in carbon modeling” said Dr. Wang.
Expertise Behind the Work
Dr. Wang brings over 20 years of experience in environmental modeling and previously contributed to key models like APEX and EPIC during her time at Texas A&M University’s Blackland Research Center. Her collaboration with Texas A&M, USDA-ARS researchers, and DayCent experts reflects Agoro Carbon’s deep commitment to scientific excellence.
Why This Matters
This research highlights the importance of accurately quantifying soil organic carbon (SOC) stock changes – especially in carbon credit markets where the effects of conservation practices must be measured precisely.
When using models informed by diverse, peer-reviewed datasets, it’s essential that those models correctly represent how management practices influence carbon sequestration. That level of precision is vital for ensuring the credibility of carbon credit outcomes.
Results That Meet the Standard
Agoro Carbon’s submitted validation reports demonstrate strong model performance in line with Verra’s VMD0053 guidelines for agricultural land management. Specifically:
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Over 90% of model predictions fell within observed measurement ranges.
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Model biases were lower than the accepted measurement uncertainty.
These results affirm that Agoro Carbon’s modeling work is not only scientifically rigorous but also fit for purpose in supporting carbon credit programs.
