3d digital mapping of soil cation exchange capacity in dorud, lorestan province

there is an increasing demand for reliable large-scale soil datato meet the requirements of models for planning of land-usesystems, characterization of soil pollution, and prediction ofland degradation. cation exchangecapacity (cec) is among the most important soil propertiesthat are required in soil databases. this paper applied a novel method for whole-soil profile predictions of cec (to 1 m) across dorudlocated in lorestanprovince. at present research, we combined equal-area spline depth functions with digital soil mapping techniques to predict the vertical and lateral variations of cec across the study area where limited soil information exists (103 soil profiles). to model the relationship between cec and environmental factors (i.e. representative soil forming factors), derived from a digital elevation model and landsat imagery, a regression tree was applied. results indicated that some auxiliary data had more influence on the prediction model (i.e. b3 and modified catchment area). our results also confirmed the regression tree model predicted target variable at the five specific depths with coefficient of determination of 0.84, 0.84, 0.84, 0.66, 0.27 and root mean square of 1.75, 1.84, 1.84, 2.11, and 2.16, respectively. results showed a reasonable r2 in first four depths ranged from 0.66 to 0.84; while, it decreases to 0.27 in the last depth. our results also confirmed that the regression tree as a predictive model, digital soil mappingtechniqueand equal area splinesare powerful tools to predict lateral and vertical variation of cec.