PCA Analysis of Soil Quality Indicators in Relation to Soil Erodibility.

Soil quality indices based on soil characteristics can be used as indicators of sustainable soil management. Principal component analysis (PCA) technique which can generate relationships among many correlated variables into a few principal components (PCs) was used to identify dominant soil characteristics in relation to soil erodibility in watersheds of submontane soils of 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 PCs. These five PCs namely soil hydraulic factor, density factor, structural factor, sand factor and cation factor, explained 86 per cent variability in data. These PCs also explained 51, 88 and 93 % variability under natural rainfall conditions and 86, 73 and 77 % variability under simulated rainfall conditions in relation to runoff, soil loss and soil erodibility, respectively. Soil structural characteristics mainly mean weight diameter can be considered as dynamic soil quality indicator and can be used to monitor temporal and spatial changes in soil quality.