Modeling Thickness of Soil- Surface Layer Using Topographic Attributes of Landscape in Rimeleh Catchment, Lorestan Province
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Article Type:
Research/Original Article (دارای رتبه معتبر)
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.
Language:
Persian
Published:
Iranian Journal of Soil Research, Volume:33 Issue: 3, 2019
Pages:
315 to 323
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