Identification of soil erosion‑susceptible areas using fuzzy logic and sediment transport index aided by mineralogical-granulometric analysis in Subansiri basin, Assam, India

Abstract

Erosion poses a significant challenge along the river Subansiri in Assam, India impacting river banks and sediment breakdown. This paper presents a comprehensive study on the identification of soil erosion-susceptible areas in the Subansiri Basin using fuzzy logic modeling and sediment transport index (STI) analysis with emphasis on X-Ray Diffraction (XRD) and grain size analysis. The soil erosion map's overall findings showed that the areas it covered were vulnerable to erosion in severe, very high, high, moderate, and low levels. Slope gradients and flow accumulation were used to calculate the STI on the Raster Calculator in ArcGIS. The Sediment Transport Index ranges from 0 to 2770. This study also aims to elucidate the mineral composition and grain size distributions of sediments sourced from the Subansiri river in Assam. Examination of 12 soil samples facilitated the assessment of their mineral composition and size distribution. Sieve analysis unveiled that a predominant 80% of the soil along the Subansiri river constitutes sand, with lesser percentages attributed to silt and clay, following USDA primary classification guidelines. Utilizing XRD methodology, the major crystalline minerals identified in these sands encompassed Quartz, Montmorillonite, Illite, Calcite, and Plagioclase Feldspar Albite. Skewness and kurtosis is also studied to determine the shape and distribution of the soil samples and the values range from 0.25 to 0.70 signifying a fine skewed to very fine skewed and from − 1.16 to -1.93 showing a very platykurtic distribution. Thus, for a thorough investigation of soil erosion, this research provides a novel hybrid methodology that integrates fuzzy logic, STI, XRD and grain size analysis.