Spatial Variability of Soil Erodibility at the Rhirane Catchment Using Geostatistical Analysis

Author:

Othmani Ouafa1ORCID,Khanchoul Kamel1,Boubehziz Sana1,Bouguerra Hamza2ORCID,Benslama Abderraouf34,Navarro-Pedreño Jose4ORCID

Affiliation:

1. Soil and Sustainable Development Laboratory, Department of Biology, Badji Mokhtar University-Annaba, Annaba 23000, Algeria

2. Water Resources and Sustainable Development Laboratory, Department of Geology, Faculty of Earth Sciences, Badji Mokhtar-Annaba University, P.O. Box 12, Annaba 23000, Algeria

3. Laboratoire de Valorisation et Conservation des Écosystèmes Arides (LVCEA), University of Ghardaïa, Ghardaïa 47000, Algeria

4. Department of Agrochemistry and Environment, University Miguel Hernández of Elche, 03202 Elche, Spain

Abstract

Soil erodibility is one of the most crucial factors used to estimate soil erosion by applying modeling techniques. Soil data from soil maps are commonly used to create maps of soil erodibility for soil conservation planning. This study analyzed the spatial variability of soil erodibility by using a digital elevation model (DTM) and surface soil sample data at the Rhirane catchment (Algeria). A total of 132 soil samples were collected of up to 20 cm in depth. The spatial distributions of the K-value and soil physical properties (permeability, organic matter, and texture) were used to elaborate ordinary Kriging interpolation maps. Results showed that mean values of soil organic matter content were statistically different between Chromic Cambisols (M = 3.4%) vs. Calcic Cambisols (M = 2.2%). The analysis of variance of the organic matter provided a tool for identifying significant differences when comparing means between the soil types. The soil granulometry is mainly composed of silt and fine sand. The soil erodibility showed values varying between 0.012 and 0.077 with an average of 0.034, which was greater in soils with calcic horizons. Statistical evaluation by using Pearson’s correlation revealed positive correlations between erodibility and silt (0.63%), and negative correlations with sand (−0.16%), clay (−0.56%), organic matter (−0.32%), permeability (−0.41%), soil structure (−0.40%), and the soil stability index (−0.26%). The variability analysis of the K-factor showed moderate spatial dependency with the soil erodibility map indicating moderate to highly erodible risk in cropland and sparse grassland land uses. Overall, the study provides scientific support for soil conservation management and appropriate agricultural food practices for food supply.

Funder

Ministry of Higher Education and Algerian Scientific Research

Publisher

MDPI AG

Subject

Earth-Surface Processes,Soil Science

Reference46 articles.

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4. Tilligkeit, J.K. (2012). The Spatial Distribution of K-Factor Values Across a Topo Sequence and a Soil Survey Map Unit. Unpublished. [Master’s Thesis, The Faculty of California Polytechnic State University].

5. Estimation of Soil Erodibility Factor in Rusle Equation for Euphrates River Watershed Using Gis;Int. J. Geomate,2018

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