Prediction the soil erodibility and sediments load using soil attributes

Abstract

Soil erodibility (K factor) is the most important tool for estimation the erosion. The aim of this study was to estimate the soil erodibility in Sanganeh area located in Naderi Kalat, Khorasan Razavi Province of northeastern Iran. The sediments load collected during the 17 rainfall events were measured at the end of 12 plots during 2009-2012. The K factor was calculated according to the USLE for each plot and rainfall event. The relationships between K factor and measured sediments load with soil attributes were studied. The results showed that calcium carbonate, SAR (sodium absorption ratio), silt, clay contents, and SI (structural stability index) were the most effective soil attributes for estimating the sediments load and OM (organic matter), sand, SI and calcium carbonate, silt, clay contents, and SI for K factor. The results of stepwise regression equations showed that the precision of regression equation derived from PCA for estimating the K factor and sediments load were more than ones derived from correlation test. According to the results of this research, it’s recommended that PCA be applied for determination the effective soil attributes for estimating the K factor in USLE and sediments load in studied area.

Keywords

• Soil erodibility, soil erosion, sediment

References

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