USLE/RUSLE K-factors allocated through a linear mixed model for Uruguayan soils

Q2 Agricultural and Biological Sciences
A. Beretta-Blanco, L. Carrasco-Letelier
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引用次数: 9

Abstract

Soil erosion by rainfall is a process that demands management, both for the prevention of excessive soil erosion and for the protection of the quality of freshwater bodies. Erosion coefficients (K-factors) of the universal soil loss equation (USLE)/revised USLE (RUSLE) model were assigned to 99 mapped Uruguayan soil types at 1:1,000,000 scale. This work developed a linear mixed model (LMM) with 79 soils with assigned K-factors, in which the following variables were considered: soil taxonomy, chemical composition, and parent material. The developed LMM had an R2=0.86, in which the soil taxonomy (p<0.0001), parent material (p=0.0174), clay (p=0.0005) and sand (p=0.017) contents had significant statistical effects. The prediction capacity of this model was assessed with 10 soils not previously used in development of the LMM with assigned K-factors. The prediction assessment had an R2=0.84 and a mean error of 9.08% of the mean K-factor value. The LMM developed was used for the allocation of K-factors to soils mapped at a 1:20,000-resolution. Thus, the use of LMM increased the soil area with assigned K-factors from 111,822 km2 (at a scale of 1:1,000,000) to 174,132 km2 (1:20,000).
USLE/RUSLE k因子通过乌拉圭土壤的线性混合模型分配
降雨造成的土壤侵蚀是一个需要管理的过程,既要防止土壤过度侵蚀,又要保护淡水水体的质量。将通用土壤流失方程(USLE)/修正USLE (RUSLE)模型的侵蚀系数(k因子)按1:10万比例尺分配给99个绘制的乌拉圭土壤类型。本工作建立了一个线性混合模型(LMM),其中79种土壤具有指定的k因子,其中考虑了以下变量:土壤分类、化学成分和母质。发达LMM的R2=0.86,其中土壤分类(p<0.0001)、母质(p=0.0174)、粘土(p=0.0005)和砂(p=0.017)含量具有显著的统计学影响。该模型的预测能力用10种土壤进行了评估,这些土壤以前没有用于开发具有指定k因子的LMM。预测评价的R2=0.84,平均误差为k因子平均值的9.08%。开发的LMM用于按1:20 000分辨率对土壤进行k因子分配。因此,LMM的使用使分配k因子的土壤面积从111,822 km2(1:10,000)增加到174,132 km2(1:20 000)。
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来源期刊
Ciencia E Investigacion Agraria
Ciencia E Investigacion Agraria 农林科学-农业综合
CiteScore
1.40
自引率
0.00%
发文量
0
审稿时长
6-12 weeks
期刊介绍: The subject matter that is considered to be appropriate for publication in International Journal of Agriculture and Natural Resources (formerly Ciencia e Investigación Agraria) is all new scientific and technological research in agriculture, animal production, forestry, natural resources and other related fields.
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