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Salinity and sodicity problems are ubiquitous in dryland and irrigated systems, and research into possible amendments to remediate soils in these systems is needed. This study was conducted to investigate the effects of organic and inorganic amendments on spring wheat (Triticum aestivum UG99) yield and salts redistribution within the profile of a repacked saline–sodic silt loam soil (ECe = 12.9 dS m−1, exchangeable sodium percent (ESP) = 17.6% for control). The experimental design for greenhouse study was completely random with two factors (amendment and leaching fraction, LF). The amendments included biochar (2%) [B], biochar + manure (2%) [BM], zeolite modified with CaCl2 (2%) [ZC], super absorbent (1%) [SA], and a control (no amendment) considering two levels of LF (15 and 30%). All amendments, except ZC, decreased soil bulk density and electrical conductivity, and increased soil pH and water content at field capacity after 2 pore volumes leaching. There was positive effect (p + and Mg2+ concentration in straw, while K+ concentration increased; resulting in reductions in the Na+/K+ ratio. In general, the study showed that B, BM and SA are suitable amendments for increasing yield by improving soil conditions and reducing salts and Na+ accumulation in plants.

Atterberg consistency limits (liquid limit, LL; plastic limit, PL; shrinkage limit, SL) and indices (plasticity index, PI; friability index, FI) are useful indicators of soil mechanical behaviour. This study was conducted to evaluate the use of soil and environmental data for predicting Atterberg limits or indices using artificial neural network (ANN) models at the watershed scale in western Iran. The LL, PL, SL, PI, FI, particle size distribution, organic matter (OM) and calcium carbonate equivalent (CCE) were measured in soil samples collected from 113 locations. Three sets of readily available properties were employed as inputs. The first of these data sets or models consisted of soil properties. The second included topographic attributes and normalized difference vegetation index (NDVI), and the third was a combination of soil, topographic attributes and NDVI. Developed ANN models could explain a majority of the variability (62–94%) in Atterberg limits and indices. Greatest and poorest performances were attributed to the third and first models, respectively. No significant efficacy difference was observed between the second and third models. Therefore, the second data set with its readily available environmental variables is suggested for use in predicting Atterberg limits and indices at the regional scale. Sensitivity analysis showed that NDVI, OM, clay content, CCE and topographic attributes (wetness index, elevation, plan curvature and slope) could explain much of the variance associated with Atterberg limits and indices at the watershed scale in western Iran.

This study was conducted to investigate the impact of land use (dryland farming, grassland and irrigated farming) on bulk density, (ρb) and relative bulk density (ρb-rel), and to study the relationships between ρb and ρb-rel, respectively, and soil organic matter content (OM) and soil texture at 100 locations in calcareous soils of central Iran. The ρb–rel was expressed as the ratio of ρb to a reference bulk density, ρbef. By considering ρb-ref an inherent soil property that is dependent on soil texture but not on OM, the combined effects of OM due to land use and compaction (due to agricultural machinery) on the degree of compactness could be explored. Multiple linear regression was used to derive pedotransfer functions for predicting ρb and ρb-rel. It was found that ρb-rel is strongly affected by OM, and a strong correlation was obtained between ρb-rel and the ratio of OM to clay content. The predictive performance of the multiple regression models was poorest for irrigated farming, which might be explained by intensive soil disturbance by tillage in irrigated farming. The main effect of land use was on OM, and consequently, the degree of compactness was mainly controlled by OM. The greatest OM and least ρb-rel were measured in irrigated farming. Dryland farming had the least OM and the greatest ρb-rel.