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

IF 2.9 Q2 SOIL SCIENCE
Ouafa Othmani, K. Khanchoul, Sana Boubehziz, H. Bouguerra, Abderraouf Benslama, J. Navarro-Pedreño
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引用次数: 1

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.
基于地统计分析的莱茵河流域土壤可蚀性空间变异
土壤可蚀性是利用模型技术估算土壤侵蚀的最重要因素之一。来自土壤图的土壤数据通常用于创建土壤可蚀性图,用于土壤保持规划。利用数字高程模型(DTM)和表层土壤样本数据,分析了阿尔及利亚莱茵河流域土壤可蚀性的空间变异性。共采集了132个深度为20 cm的土壤样品。利用k值的空间分布和土壤物理性质(渗透率、有机质和质地)绘制普通Kriging插值图。结果表明,铬色cambisol (M = 3.4%)与钙色cambisol (M = 2.2%)土壤有机质含量平均值差异有统计学意义。有机质的方差分析提供了一种工具,可以在比较土壤类型之间的方法时识别出显著差异。土壤粒度主要由粉砂和细砂组成。土壤可蚀性在0.012 ~ 0.077之间变化,平均为0.034,含钙层土壤可蚀性较大。Pearson相关分析表明,土壤可蚀性与粉砂(0.63%)呈正相关,与砂(- 0.16%)、粘土(- 0.56%)、有机质(- 0.32%)、渗透性(- 0.41%)、土壤结构(- 0.40%)、土壤稳定性指数(- 0.26%)呈负相关。土壤可蚀性图显示,土壤可蚀性具有中等至高度的可蚀性风险。总体而言,本研究为土壤保持管理和粮食供应的适宜农业粮食做法提供了科学支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Soil Systems
Soil Systems Earth and Planetary Sciences-Earth-Surface Processes
CiteScore
5.30
自引率
5.70%
发文量
80
审稿时长
11 weeks
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