AUTHOR=Jadalla Faroug A. H. , Oluwasemire Kolapo O. , Elmobarak Abd Elmagid A. , Zein Mohammed A. M. Mohammed 
  
TITLE=Spatial prediction of soil organic carbon stocks in Sudanese clay soils using regression kriging
  
JOURNAL=Spanish Journal of Soil Science
  
VOLUME=Volume 16 - 2026
  
YEAR=2026
  
URL=https://www.frontierspartnerships.org/journals/spanish-journal-of-soil-science/articles/10.3389/sjss.2026.16733
  
DOI=10.3389/sjss.2026.16733
  
ISSN=2253-6574
  
ABSTRACT=Soil organic carbon (SOC) stocks are a critical component of terrestrial carbon pools, influencing soil quality, agricultural productivity, and climate change mitigation. This study aimed to map and improve spatial estimation of SOC stocks in Sudan’s Blue Nile clay soils using regression kriging (RK). The model integrated 554 spatially unique soil profiles with nine environmental covariates: precipitation, temperature, relative humidity, normalized difference vegetation index (NDVI), land use/cover, bare soil index (BSI), digital elevation model (DEM), LS-factor, and aspect. Spectral indices were derived from Landsat 9 imagery (April 2024), while climate and terrain data were obtained from CHIRPS/WorldClim and SRTM (30 m). RK performance was robust, with spatial cross-validation R2 = 0.72, RMSE = 8.4 Mg C ha−1 (29% of mean observed stock), and mean bias = −0.8 Mg C ha−1. Predicted SOC stocks (0–30 cm) ranged from 12.4 to 51.2 Mg C ha−1 (mean 28.6 Mg C ha−1). NDVI, clay content, and topographic wetness index were the most influential predictors. Agricultural lands exhibited the highest stocks (51.2 Mg C ha−1), while bare lands had the lowest (14.2 Mg C ha−1). This study (1) applies spatially explicit validation for SOC mapping in Sudan’s Blue Nile region, (2) harmonizes legacy and contemporary soil data using equivalent soil mass correction, and (3) provides high-resolution SOC maps for climate-resilient agricultural planning. Findings support soil carbon management and climate mitigation in semi-arid regions.