Modeling Thickness of Soil- Surface Layer Using Topographic Attributes of Landscape in Rimeleh Catchment, Lorestan Province

Document Type : Research Paper

Authors

1 Research Lecture, Soil and Water Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Khorramabad, Iran

2 Professor of Soil Sciences Department, Gorgan University of Agricultural Sciences and Natural Resources

3 Assistant Professor of Soil Sciences Department, Gorgan University of Agricultural Sciences and Natural Resources

4 Assistant Professor of Soil and Water Research Institute, Agricultural Research, Education and Extension Organization

Abstract

Distinguishing soil surface horizon and its thickness is possible through soil survey and drilling. This requires budget, time, and skilled persons; therefore, using predicting methods as a solution for simple determination of soil characteristics has gained much importance in recent years. This work considers employing stepwise multiple linear regression statistical approach in order to propose a suitable model to predicate soil surface horizon thickness (SSHT) from topographic attributes according to establishment of soil and landscape characteristics relationships. To fulfill the goals of this study, data of primary and secondary topographic features of the Rimeleh sub-catchment located in Lorestan Province of Iran were derived from a Digital Elevation Model (DEM) and, the SSHT data yielded from soil surveys at 191 sampling points distributed in the study area in a systematically randomized manner. The SPSS 19 package was used to clarify statistical characteristics of gathered SSHT topographic data and test the fitted model considerations. The fitted model for the gathered data was Athick = 39.596 – 0.012E – 0.152S + 0.008AS.  The determination coefficient of the model was computed as 0.54. It is clear that the model fitted to the data has highly significant negative correlation with slope percent (S) and elevation (E) (P≤0.01) and a significant positive correlation with aspect (AS) (P≤0.05). Our investigation demonstrated that the fitted model to the scatter plot of observed data values versus predicted values has a determination coefficient of 0.54, which indicates the explanatory power of the model. Other topographic attributes affected the SSHT but their effects were not significant statistically. Therefore, they were not included in the model.

Keywords

References

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Iranian Journal of Soil Research
Volume 33, Issue 3
December 2019
Pages 415-423

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