https://essopenarchive.org/doi/full/10.22541/essoar.176227291.17261695/v1
Authors: Zahra Ghahremani, David P Huber, Arash Modaresi Rad, Michael J Johnson, Jennifer Pierce
04 November 2025
Abstract
Soil inorganic carbon (SIC) is critical for carbon sequestration, infiltration, and climate modeling, yet its formation and distribution remain poorly understood. This study introduces a high-resolution (30m) SIC map of CONUS in a Google Earth Engine app. Using climate and land surface data and leveraging machine learning (ML) models, we enhance predictions and reduce uncertainty in unsampled areas. Our SIC RFR achieved an RMSE of 15 kg/m2, and the multi-class classifier had an accuracy of 0.56. Our model estimates that CONUS soils store 77 ± 1.8 Pg of SIC in the top 1 m, a significant increase over prior inventories. Our findings distinguish between two key occurrences: lithogenic carbonates persisting in humid regions and pedogenic carbonates, which characteristically form in arid soils. Soil pH is the strongest predictor of calcareous soil formation, while precipitation, with a threshold of 1700 mm/year, emerges as the primary driver.
Source: ESS Open Archive