Regional-Scale Soil Salinity Assessment Using Anocova Modeling Techniques.

Directed soil sampling based on geospatial measurements of apparent soil electrical conductivity (EC_a) is a potential means of characterizing the spatial variability of any soil property that influences EC_a including soil salinity, water content, texture, bulk density, organic matter, and cation exchange capacity.  Multi‑field EC_a survey data often exhibit abrupt changes in magnitude across field boundaries that complicate the calibration of EC_a to soil salinity (i.e., EC_e, electrical conductivity of the saturation extract) over large spatial extents.  The primary objective of this study is to evaluate three regression techniques for calibrating EC_a to EC_e over spatial scales ranging from a few thousand to a hundred thousand hectares, where EC_a was measured using electromagnetic induction equipment.  The regression techniques include analysis of covariance (ANOCOVA), field specific regression (FSR), and common coefficient regression (CCR).  An evaluation was made by comparing jack‑knifed mean square prediction errors (MSPE) of EC_e for two case studies: 2400 ha of the Broadview Water District in California’s San Joaquin Valley and roughly 100,000 ha of the west side of Kittson County in the Red River Valley of Minnesota. The ANOCOVA model outperformed the FSR and CCR regression models on a prediction accuracy basis with the smallest MSPE estimates for depth predictions of soil salinity. The implication of this evaluation is that once ANOCOVA models for each depth are established for a representative set of fields within a regional‑scale study area, then the slope coefficients can be used at all future fields, thereby significantly reducing the need for ground‑truth soil samples at future fields, which substantially reduces labor and cost. Land resource managers, producers, agriculture consultants, extension specialists, and Natural Resource Conservation Service field staff are the beneficiaries of regional‑scale maps of soil salinity.