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Understanding Critical Zone Evolution through Predicting the Three‐Dimensional Soil Chemical Properties of a Small Forested Catchment
Author(s) -
Shepard Christopher,
Schaap Marcel G.,
Chorover Jon,
Rasmussen Craig
Publication year - 2018
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj2018.03.0119
Subject(s) - soil science , geology , soil horizon , environmental science , soil map , soil morphology , hydrology (agriculture) , soil water , soil classification , geotechnical engineering
Core Ideas Used step function to predict three‐dimensional (3D) soil property distributions. 3D soil property distribution influenced by lithology and topography. Profile reconstructions and digital soil mapping informed critical zone evolution. Understanding critical zone evolution and function requires an accurate assessment of the distributions of its soil physical and chemical properties. Two‐dimensional (2D) digital soil mapping (DSM) provides a general understanding of soil characteristics across landscapes, but lacks the ability to predict soil properties with depth. Soil depth functions enable the reconstruction of soil properties with depth, potentially extending traditional DSM techniques to three dimensions (3D). We predicted the three‐dimensional soil chemical and physical properties of a small forested subcatchment of the Catalina‐Jemez Critical Zone Observatory using a combination of profile depth functions and traditional DSM techniques. The step function was used to reconstruct selected soil chemical and physical properties with depth for 24 described soil profiles. We compensated for uneven sampling depths by standardizing the profiles from 0.0 to 1.0, and splitting them into five equal standardized depth layers. Using available environmental covariates, step‐wise regressions were used to predict soil properties across the catchment. R 2 values for the predictive functions ranged from 0.20 to 0.97 ( p = 0.21 to <0.0001). Calcium and magnesium preferentially accumulated in channel drainages compared to potassium or sodium; this pattern corresponded with accumulation of clay in channel drainages. Parent material and sediment redistribution, driven by colluvial movement and hydrological flowpaths, were the main controls on the 3D soil chemical properties of the catchment. Combining depth functions with traditional DSM will provide more accurate assessments of soil spatial patterns across landscapes and with depth.