In situ surface shear strength as affected by soil characteristics and land use in calcareous soils of central Iran

• Cohesion (c) and internal friction angle (φ) depended on texture/structure & gravel
• Positive correlation was obtained between c and fine clay content.
• The NDVI is an important factor indirectly explaining variability of c and φ.
• Highest clay content and c, and lowest sand content and φ belong to dryland farming.
• Prediction of in situ shear strength using soil properties + NDVI is recommended.

Soil surface shear strength is an important input parameter in the process-based soil erosion models, but its direct measurement at the watershed scale is difficult, time-consuming and costly. This study was conducted to predict in situ shear strength of the soil surface using multiple-linear regression (MLR). The land use impact on the surface shear strength was examined as well. A direct shear box was constructed to measure in situ shear strength (cohesion, c and angle of internal friction, φ) of the soil surface in the Semirom region located in Isfahan province, central Iran. The shear device consisted of a circular shear box (with 10 cm internal diameter and height of 1 cm), an S-shaped load cell for measuring horizontal (shear) stress and an electric motor for applying the shear stress. The normal stress acting on the failure surface was adjusted by adding weights on the shear box. Soil surface shear strength was determined using the shear box at 100 locations under three land use systems of grassland, irrigated farming and dryland farming. Soil particle size distribution (clay, silt, sand and fine clay), organic matter content (OM), carbonate content, bulk density and gravel content were determined as predictors of the surface shear strength. Normalized difference vegetation index (NDVI) was also calculated using satellite images. The MLR was employed to predict the shear strength (i.e. c and φ) using two groups of input variables: i) easily-available soil properties (pedotransfer functions, PTFs) and ii) easily-available soil properties and NDVI (soil spatial prediction functions, SSPFs). A strong negative correlation (r = − 0.72, p < 0.001) was found between c and φ in the studied area. Positive correlation (r = 0.41, p < 0.001) was obtained between c and fine clay content. The c was negatively correlated (r = − 0.31, p < 0.01; r = − 0.37, p < 0.001) with sand and gravel contents, respectively. A significant positive correlation (r = 0.47, p < 0.001) was observed between φ and gravel content, indicating the roughness effect of coarse particles on frictional shear strength. The results also showed that NDVI is an important factor indirectly explaining the variability of both c and φ in the studied soils. The land use effect on the soil properties was investigated using the LSD0.05 test. The means of φ somehow follow the variation of gravel content among the land uses; the highest means of clay and fine clay contents and c, and the lowest means of sand and gravel contents and φ were observed in dryland farming. The c has the same trend as did clay content; irrigated farming with the highest mean of sand content and lowest mean of clay content had the lowest mean of c. The c means were significantly different between irrigated farming and dryland farming. Prediction models of in situ shear strength derived using both soil properties and NDVI as predictors (SSPFs) were more accurate than those derived using only soil properties (PTFs).