Selection of soil physical quality indicators in relation to soil erodibility
Manmohan J. Singh, K. L. Khera, Priyabrata Santra
Abstract
Manmohan J. Singh, K. L. Khera, Priyabrata Santra
Abstract
Soil quality indices based on soil characteristics can be used to assess the sustainability of soil and to assist in soil management decisions. Principal component analysis (PCA) technique was used to identify dominant soil characteristics in relation to soil erodibility in watersheds of submontane Punjab (India). Soil physical and chemical characteristics were evaluated for four locations with four land uses at each location whereas runoff, soil loss and soil erodibility were determined at two locations under natural rainfall conditions and at four locations under simulated rainfall conditions. PCA was performed on 22 physical and chemical soil characteristics, which grouped these soil characteristics into five distinct principal components (PCs). These five PCs namely soil hydraulic factor, density factor, structural factor, sand factor and cation factor, explained 86% variability in data. These PCs also explained 86, 96 and 93% variability under natural rainfall conditions and 75, 76 and 77% variability under simulated rainfall conditions in relation to runoff, soil loss and soil erodibility, respectively. Soil total organic carbon content can be considered as dynamic soil physical quality indicator and can be used to monitor temporal and spatial changes in soil quality.
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Soil quality indices based on soil characteristics can be used to assess the sustainability of soil and to assist in soil management decisions. Principal component analysis (PCA) technique was used to identify dominant soil characteristics in relation to soil erodibility in watersheds of submontane Punjab (India). Soil physical and chemical characteristics were evaluated for four locations with four land uses at each location whereas runoff, soil loss and soil erodibility were determined at two locations under natural rainfall conditions and at four locations under simulated rainfall conditions. PCA was performed on 22 physical and chemical soil characteristics, which grouped these soil characteristics into five distinct principal components (PCs). These five PCs namely soil hydraulic factor, density factor, structural factor, sand factor and cation factor, explained 86% variability in data. These PCs also explained 86, 96 and 93% variability under natural rainfall conditions and 75, 76 and 77% variability under simulated rainfall conditions in relation to runoff, soil loss and soil erodibility, respectively. Soil total organic carbon content can be considered as dynamic soil physical quality indicator and can be used to monitor temporal and spatial changes in soil quality.
Key concepts: Environmental science, Soil science, Soil quality, Pedotransfer function, Surface runoff, Soil carbon, Spatial variability, Hydrology (agriculture)