Mapping the three-dimensional variation of soil salinity in a rice-paddy soil

Abstract

Soil salinity is widespread in a variety of environments, and land managers need to map its severity and extent both laterally and vertically. In this research we explore the inversion of apparent electrical conductivity (ECa) measured with an EM38 using a linear model and Tikhonov regularization to model electrical conductivity (σ) profiles in a saline paddy field in the Yangtze delta of China. The modelled σ matched closely the directly measured bulk electrical conductivity (σb) in the topsoil within our calibration field. Discrepancies were greatest between 0.4 and 0.8m, below which they converged again, and were judged small enough to map soil salinity. Equivalent ECa data, recorded in an adjacent field, was similarly inverted with the modelled σ analysed geostatistically. In this regard, the σ data at 10 depths were treated as 10 correlated variates, and experimental auto-and cross-variograms were computed by the method of moments from them. A linear model of coregionalization fitted well, and it was used to cokrige σ on 5m×5m blocks on a fine grid. The kriging errors, computed as the square roots of the cokriging variances, were typically about 5% of the kriged estimates. Estimates of σ were then converted into the universal standard of soil salinity measurement (i.e. electrical conductivity of a saturated soil paste extract — ECe). The results indicate that an irregularly shaped patch of strongly saline topsoil (i.e. 8–12dSm−1) and subsoil salinity (i.e. >16dSm−1) at the southern end of the field was consistent with a yield reduction of some 33%; and as compared with the weakly saline conditions evident at the northern end of the field (e.g. topsoil ECe 2–4dSm−1) where yield was much larger. We conclude that the approach has merit and might be useful in providing a baseline set of data and a method that can used to monitor and evaluate the management of salinity.