Identification of soil erosion‑susceptible areas using fuzzy logic and hydrological indices aided by mineralogical-granulometric analysis in lower Subansiri basin, Assam, India

Abstract

Soil erosion is one of the critical environmental issues in many places globally. It is significantly affecting in the lower Subansiri Basin of Assam, India, to environmental degradation, reduced soil quality, and declining agricultural productivity while exacerbating climate change vulnerability. This study identifies erosion-prone areas in the lower Subansiri basin, using a hybrid methodology combining fuzzy logic modeling with hydrological indices analysis, supported by mineralogical and granulometric assessments. Key factors influencing soil erosion, including rainfall, aspect, topographic variables, land use/land cover (LULC), normalized difference vegetation index (NDVI), and slope, were analysed in this study. Sediment composition and distribution patterns were further examined using X-Ray Diffraction (XRD) and grain size analysis. The results reveal that the north and northwest regions of the basin are most susceptible to erosion, with approximately 80% of the soil being sandy. Dominant minerals identified include quartz, montmorillonite, illite, calcite, and plagioclase feldspar albite. The erosion vulnerability map highlights five classes: low (11%), moderate (5%), high (20%), very high (26%), and severe (37%). These findings emphasize the need for targeted management and mitigation strategies in high-risk zones to address soil erosion effectively. This study offers valuable insights for sustainable land-use planning and soil conservation in the lower Subansiri Basin, promoting environmental resilience and agricultural sustainability.