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Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques

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Abstract

Soil degradation associated with soil erosion and land use is a critical problem in Iran and there is little or insufficient scientific information in assessing soil quality indicator. In this study, factor analysis (FA) and discriminant analysis (DA) were used to identify the most sensitive indicators of soil quality for evaluating land use and soil erosion within the Hiv catchment in Iran and subsequently compare soil quality assessment using expert opinion based on soil surface factors (SSF) form of Bureau of Land Management (BLM) method. Therefore, 19 soil physical, chemical, and biochemical properties were measured from 56 different sampling sites covering three land use/soil erosion categories (rangeland/surface erosion, orchard/surface erosion, and rangeland/stream bank erosion). FA identified four factors that explained for 82 % of the variation in soil properties. Three factors showed significant differences among the three land use/soil erosion categories. The results indicated that based upon backward-mode DA, dehydrogenase, silt, and manganese allowed more than 80 % of the samples to be correctly assigned to their land use and erosional status. Canonical scores of discriminant functions were significantly correlated to the six soil surface indices derived of BLM method. Stepwise linear regression revealed that soil surface indices: soil movement, surface litter, pedestalling, and sum of SSF were also positively related to the dehydrogenase and silt. This suggests that dehydrogenase and silt are most sensitive to land use and soil erosion.

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Acknowledgments

This project was funded by a grant from the research council of Shahid Beheshti University, Tehran, Iran.

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  1. Department of Physical Geography, Faculty of Earth Sciences, Shahid Beheshti University, 1983963113, Tehran, Iran

    Kazem Nosrati

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  1. Kazem Nosrati
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Nosrati, K. Assessing soil quality indicator under different land use and soil erosion using multivariate statistical techniques. Environ Monit Assess 185, 2895–2907 (2013). https://doi.org/10.1007/s10661-012-2758-y

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  • DOI: https://doi.org/10.1007/s10661-012-2758-y

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